merge
diff --git a/.hgtags b/.hgtags
index 0830aaf..0414826 100644
--- a/.hgtags
+++ b/.hgtags
@@ -95,3 +95,4 @@
c860feaa348d663e598986894ee4680480577e15 v3.2.2rc1
137e45f15c0bd262c9ad4c032d97425bc0589456 v3.2.2
7085403daf439adb3f9e70ef13f6bedb1c447376 v3.2.3rc1
+f1a9a6505731714f0e157453ff850e3b71615c45 v3.3.0a1
diff --git a/Doc/c-api/buffer.rst b/Doc/c-api/buffer.rst
index 2d19992..d636935 100644
--- a/Doc/c-api/buffer.rst
+++ b/Doc/c-api/buffer.rst
@@ -81,17 +81,23 @@
around a buffer is needed, a :ref:`memoryview <memoryview-objects>` object
can be created.
+For short instructions how to write an exporting object, see
+:ref:`Buffer Object Structures <buffer-structs>`. For obtaining
+a buffer, see :c:func:`PyObject_GetBuffer`.
.. c:type:: Py_buffer
.. c:member:: void \*obj
- A new reference to the exporting object or *NULL*. The reference is owned
- by the consumer and automatically decremented and set to *NULL* by
- :c:func:`PyBuffer_Release`.
+ A new reference to the exporting object. The reference is owned by
+ the consumer and automatically decremented and set to *NULL* by
+ :c:func:`PyBuffer_Release`. The field is the equivalent of the return
+ value of any standard C-API function.
- For temporary buffers that are wrapped by :c:func:`PyMemoryView_FromBuffer`
- this field must be *NULL*.
+ As a special case, for *temporary* buffers that are wrapped by
+ :c:func:`PyMemoryView_FromBuffer` or :c:func:`PyBuffer_FillInfo`
+ this field is *NULL*. In general, exporting objects MUST NOT
+ use this scheme.
.. c:member:: void \*buf
@@ -423,7 +429,9 @@
return -1.
On success, fill in *view*, set :c:member:`view->obj` to a new reference
- to *exporter* and return 0.
+ to *exporter* and return 0. In the case of chained buffer providers
+ that redirect requests to a single object, :c:member:`view->obj` MAY
+ refer to this object instead of *exporter* (See :ref:`Buffer Object Structures <buffer-structs>`).
Successful calls to :c:func:`PyObject_GetBuffer` must be paired with calls
to :c:func:`PyBuffer_Release`, similar to :c:func:`malloc` and :c:func:`free`.
diff --git a/Doc/c-api/typeobj.rst b/Doc/c-api/typeobj.rst
index b15d927..ea1a0ad 100644
--- a/Doc/c-api/typeobj.rst
+++ b/Doc/c-api/typeobj.rst
@@ -1213,18 +1213,29 @@
int (PyObject *exporter, Py_buffer *view, int flags);
Handle a request to *exporter* to fill in *view* as specified by *flags*.
- A standard implementation of this function will take these steps:
+ Except for point (3), an implementation of this function MUST take these
+ steps:
- - Check if the request can be met. If not, raise :c:data:`PyExc_BufferError`,
- set :c:data:`view->obj` to *NULL* and return -1.
+ (1) Check if the request can be met. If not, raise :c:data:`PyExc_BufferError`,
+ set :c:data:`view->obj` to *NULL* and return -1.
- - Fill in the requested fields.
+ (2) Fill in the requested fields.
- - Increment an internal counter for the number of exports.
+ (3) Increment an internal counter for the number of exports.
- - Set :c:data:`view->obj` to *exporter* and increment :c:data:`view->obj`.
+ (4) Set :c:data:`view->obj` to *exporter* and increment :c:data:`view->obj`.
- - Return 0.
+ (5) Return 0.
+
+ If *exporter* is part of a chain or tree of buffer providers, two main
+ schemes can be used:
+
+ * Re-export: Each member of the tree acts as the exporting object and
+ sets :c:data:`view->obj` to a new reference to itself.
+
+ * Redirect: The buffer request is redirected to the root object of the
+ tree. Here, :c:data:`view->obj` will be a new reference to the root
+ object.
The individual fields of *view* are described in section
:ref:`Buffer structure <buffer-structure>`, the rules how an exporter
@@ -1233,8 +1244,9 @@
All memory pointed to in the :c:type:`Py_buffer` structure belongs to
the exporter and must remain valid until there are no consumers left.
- :c:member:`~Py_buffer.shape`, :c:member:`~Py_buffer.strides`,
- :c:member:`~Py_buffer.suboffsets` and :c:member:`~Py_buffer.internal`
+ :c:member:`~Py_buffer.format`, :c:member:`~Py_buffer.shape`,
+ :c:member:`~Py_buffer.strides`, :c:member:`~Py_buffer.suboffsets`
+ and :c:member:`~Py_buffer.internal`
are read-only for the consumer.
:c:func:`PyBuffer_FillInfo` provides an easy way of exposing a simple
@@ -1250,21 +1262,23 @@
void (PyObject *exporter, Py_buffer *view);
Handle a request to release the resources of the buffer. If no resources
- need to be released, this field may be *NULL*. A standard implementation
- of this function will take these steps:
+ need to be released, :c:member:`PyBufferProcs.bf_releasebuffer` may be
+ *NULL*. Otherwise, a standard implementation of this function will take
+ these optional steps:
- - Decrement an internal counter for the number of exports.
+ (1) Decrement an internal counter for the number of exports.
- - If the counter is 0, free all memory associated with *view*.
+ (2) If the counter is 0, free all memory associated with *view*.
The exporter MUST use the :c:member:`~Py_buffer.internal` field to keep
- track of buffer-specific resources (if present). This field is guaranteed
- to remain constant, while a consumer MAY pass a copy of the original buffer
- as the *view* argument.
+ track of buffer-specific resources. This field is guaranteed to remain
+ constant, while a consumer MAY pass a copy of the original buffer as the
+ *view* argument.
This function MUST NOT decrement :c:data:`view->obj`, since that is
- done automatically in :c:func:`PyBuffer_Release`.
+ done automatically in :c:func:`PyBuffer_Release` (this scheme is
+ useful for breaking reference cycles).
:c:func:`PyBuffer_Release` is the interface for the consumer that
diff --git a/Doc/howto/advocacy.rst b/Doc/howto/advocacy.rst
index e67e201..2969d26 100644
--- a/Doc/howto/advocacy.rst
+++ b/Doc/howto/advocacy.rst
@@ -264,8 +264,7 @@
**What are the restrictions on Python's use?**
-They're practically nonexistent. Consult the :file:`Misc/COPYRIGHT` file in the
-source distribution, or the section :ref:`history-and-license` for the full
+They're practically nonexistent. Consult :ref:`history-and-license` for the full
language, but it boils down to three conditions:
* You have to leave the copyright notice on the software; if you don't include
diff --git a/Doc/howto/cporting.rst b/Doc/howto/cporting.rst
index 98db9dd..bea2153 100644
--- a/Doc/howto/cporting.rst
+++ b/Doc/howto/cporting.rst
@@ -261,8 +261,8 @@
copy as you see fit.)
You can find :file:`capsulethunk.h` in the Python source distribution
-in the :file:`Doc/includes` directory. We also include it here for
-your reference; here is :file:`capsulethunk.h`:
+as :source:`Doc/includes/capsulethunk.h`. We also include it here for
+your convenience:
.. literalinclude:: ../includes/capsulethunk.h
diff --git a/Doc/howto/regex.rst b/Doc/howto/regex.rst
index 07a8b56..3ac03ca 100644
--- a/Doc/howto/regex.rst
+++ b/Doc/howto/regex.rst
@@ -360,7 +360,7 @@
You can learn about this by interactively experimenting with the :mod:`re`
module. If you have :mod:`tkinter` available, you may also want to look at
-:file:`Tools/demo/redemo.py`, a demonstration program included with the
+:source:`Tools/demo/redemo.py`, a demonstration program included with the
Python distribution. It allows you to enter REs and strings, and displays
whether the RE matches or fails. :file:`redemo.py` can be quite useful when
trying to debug a complicated RE. Phil Schwartz's `Kodos
@@ -495,7 +495,7 @@
the same ones in several locations, then it might be worthwhile to collect all
the definitions in one place, in a section of code that compiles all the REs
ahead of time. To take an example from the standard library, here's an extract
-from the now deprecated :file:`xmllib.py`::
+from the now-defunct Python 2 standard :mod:`xmllib` module::
ref = re.compile( ... )
entityref = re.compile( ... )
diff --git a/Doc/library/copyreg.rst b/Doc/library/copyreg.rst
index a2d316e..41061e5 100644
--- a/Doc/library/copyreg.rst
+++ b/Doc/library/copyreg.rst
@@ -32,6 +32,8 @@
returned by *function* at pickling time. :exc:`TypeError` will be raised if
*object* is a class or *constructor* is not callable.
- See the :mod:`pickle` module for more details on the interface expected of
- *function* and *constructor*.
-
+ See the :mod:`pickle` module for more details on the interface
+ expected of *function* and *constructor*. Note that the
+ :attr:`~pickle.Pickler.dispatch_table` attribute of a pickler
+ object or subclass of :class:`pickle.Pickler` can also be used for
+ declaring reduction functions.
diff --git a/Doc/library/markup.rst b/Doc/library/markup.rst
index 49794ef..1b4cca5 100644
--- a/Doc/library/markup.rst
+++ b/Doc/library/markup.rst
@@ -23,7 +23,7 @@
html.rst
html.parser.rst
html.entities.rst
- pyexpat.rst
+ xml.etree.elementtree.rst
xml.dom.rst
xml.dom.minidom.rst
xml.dom.pulldom.rst
@@ -31,4 +31,4 @@
xml.sax.handler.rst
xml.sax.utils.rst
xml.sax.reader.rst
- xml.etree.elementtree.rst
+ pyexpat.rst
diff --git a/Doc/library/multiprocessing.rst b/Doc/library/multiprocessing.rst
index 5019eff..d8e1d92 100644
--- a/Doc/library/multiprocessing.rst
+++ b/Doc/library/multiprocessing.rst
@@ -415,13 +415,14 @@
A numeric handle of a system object which will become "ready" when
the process ends.
+ You can use this value if you want to wait on several events at
+ once using :func:`multiprocessing.connection.wait`. Otherwise
+ calling :meth:`join()` is simpler.
+
On Windows, this is an OS handle usable with the ``WaitForSingleObject``
and ``WaitForMultipleObjects`` family of API calls. On Unix, this is
a file descriptor usable with primitives from the :mod:`select` module.
- You can use this value if you want to wait on several events at once.
- Otherwise calling :meth:`join()` is simpler.
-
.. versionadded:: 3.3
.. method:: terminate()
@@ -785,6 +786,9 @@
*timeout* is a number then this specifies the maximum time in seconds to
block. If *timeout* is ``None`` then an infinite timeout is used.
+ Note that multiple connection objects may be polled at once by
+ using :func:`multiprocessing.connection.wait`.
+
.. method:: send_bytes(buffer[, offset[, size]])
Send byte data from an object supporting the buffer interface as a
@@ -1779,8 +1783,9 @@
However, the :mod:`multiprocessing.connection` module allows some extra
flexibility. It basically gives a high level message oriented API for dealing
-with sockets or Windows named pipes, and also has support for *digest
-authentication* using the :mod:`hmac` module.
+with sockets or Windows named pipes. It also has support for *digest
+authentication* using the :mod:`hmac` module, and for polling
+multiple connections at the same time.
.. function:: deliver_challenge(connection, authkey)
@@ -1878,6 +1883,38 @@
The address from which the last accepted connection came. If this is
unavailable then it is ``None``.
+.. function:: wait(object_list, timeout=None)
+
+ Wait till an object in *object_list* is ready. Returns the list of
+ those objects in *object_list* which are ready. If *timeout* is a
+ float then the call blocks for at most that many seconds. If
+ *timeout* is ``None`` then it will block for an unlimited period.
+
+ For both Unix and Windows, an object can appear in *object_list* if
+ it is
+
+ * a readable :class:`~multiprocessing.Connection` object;
+ * a connected and readable :class:`socket.socket` object; or
+ * the :attr:`~multiprocessing.Process.sentinel` attribute of a
+ :class:`~multiprocessing.Process` object.
+
+ A connection or socket object is ready when there is data available
+ to be read from it, or the other end has been closed.
+
+ **Unix**: ``wait(object_list, timeout)`` almost equivalent
+ ``select.select(object_list, [], [], timeout)``. The difference is
+ that, if :func:`select.select` is interrupted by a signal, it can
+ raise :exc:`OSError` with an error number of ``EINTR``, whereas
+ :func:`wait` will not.
+
+ **Windows**: An item in *object_list* must either be an integer
+ handle which is waitable (according to the definition used by the
+ documentation of the Win32 function ``WaitForMultipleObjects()``)
+ or it can be an object with a :meth:`fileno` method which returns a
+ socket handle or pipe handle. (Note that pipe handles and socket
+ handles are **not** waitable handles.)
+
+ .. versionadded:: 3.3
The module defines two exceptions:
@@ -1929,6 +1966,41 @@
conn.close()
+The following code uses :func:`~multiprocessing.connection.wait` to
+wait for messages from multiple processes at once::
+
+ import time, random
+ from multiprocessing import Process, Pipe, current_process
+ from multiprocessing.connection import wait
+
+ def foo(w):
+ for i in range(10):
+ w.send((i, current_process().name))
+ w.close()
+
+ if __name__ == '__main__':
+ readers = []
+
+ for i in range(4):
+ r, w = Pipe(duplex=False)
+ readers.append(r)
+ p = Process(target=foo, args=(w,))
+ p.start()
+ # We close the writable end of the pipe now to be sure that
+ # p is the only process which owns a handle for it. This
+ # ensures that when p closes its handle for the writable end,
+ # wait() will promptly report the readable end as being ready.
+ w.close()
+
+ while readers:
+ for r in wait(readers):
+ try:
+ msg = r.recv()
+ except EOFError:
+ readers.remove(r)
+ else:
+ print(msg)
+
.. _multiprocessing-address-formats:
diff --git a/Doc/library/packaging.database.rst b/Doc/library/packaging.database.rst
index aaa2cb9..9d750f0 100644
--- a/Doc/library/packaging.database.rst
+++ b/Doc/library/packaging.database.rst
@@ -15,6 +15,11 @@
Most functions also provide an extra argument ``use_egg_info`` to take legacy
distributions into account.
+For the purpose of this module, "installed" means that the distribution's
+:file:`.dist-info`, :file:`.egg-info` or :file:`egg` directory or file is found
+on :data:`sys.path`. For example, if the parent directory of a
+:file:`dist-info` directory is added to :envvar:`PYTHONPATH`, then it will be
+available in the database.
Classes representing installed distributions
--------------------------------------------
@@ -128,7 +133,7 @@
for the first installed distribution matching *name*. Egg distributions are
considered only if *use_egg_info* is true; if both a dist-info and an egg
file are found, the dist-info prevails. The directories to be searched are
- given in *paths*, which defaults to :data:`sys.path`. Return ``None`` if no
+ given in *paths*, which defaults to :data:`sys.path`. Returns ``None`` if no
matching distribution is found.
.. FIXME param should be named use_egg
@@ -200,20 +205,23 @@
Examples
--------
-Print all information about a distribution
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Printing all information about a distribution
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-Given a path to a ``.dist-info`` distribution, we shall print out all
+Given the name of an installed distribution, we shall print out all
information that can be obtained using functions provided in this module::
import sys
import packaging.database
- path = input()
- # first create the Distribution instance
try:
- dist = packaging.database.Distribution(path)
- except FileNotFoundError:
+ name = sys.argv[1]
+ except ValueError:
+ sys.exit('Not enough arguments')
+
+ # first create the Distribution instance
+ dist = packaging.database.Distribution(path)
+ if dist is None:
sys.exit('No such distribution')
print('Information about %r' % dist.name)
@@ -244,7 +252,7 @@
.. code-block:: sh
- $ echo /tmp/choxie/choxie-2.0.0.9.dist-info | python3 print_info.py
+ python print_info.py choxie
we get the following output:
@@ -299,10 +307,23 @@
* It was installed as a dependency
-Find out obsoleted distributions
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Getting metadata about a distribution
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-Now, we take tackle a different problem, we are interested in finding out
+Sometimes you're not interested about the packaging information contained in a
+full :class:`Distribution` object but just want to do something with its
+:attr:`~Distribution.metadata`::
+
+ >>> from packaging.database import get_distribution
+ >>> info = get_distribution('chocolate').metadata
+ >>> info['Keywords']
+ ['cooking', 'happiness']
+
+
+Finding out obsoleted distributions
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Now, we tackle a different problem, we are interested in finding out
which distributions have been obsoleted. This can be easily done as follows::
import packaging.database
diff --git a/Doc/library/pickle.rst b/Doc/library/pickle.rst
index bf0a72e..1b85bfa 100644
--- a/Doc/library/pickle.rst
+++ b/Doc/library/pickle.rst
@@ -285,6 +285,29 @@
See :ref:`pickle-persistent` for details and examples of uses.
+ .. attribute:: dispatch_table
+
+ A pickler object's dispatch table is a registry of *reduction
+ functions* of the kind which can be declared using
+ :func:`copyreg.pickle`. It is a mapping whose keys are classes
+ and whose values are reduction functions. A reduction function
+ takes a single argument of the associated class and should
+ conform to the same interface as a :meth:`~object.__reduce__`
+ method.
+
+ By default, a pickler object will not have a
+ :attr:`dispatch_table` attribute, and it will instead use the
+ global dispatch table managed by the :mod:`copyreg` module.
+ However, to customize the pickling for a specific pickler object
+ one can set the :attr:`dispatch_table` attribute to a dict-like
+ object. Alternatively, if a subclass of :class:`Pickler` has a
+ :attr:`dispatch_table` attribute then this will be used as the
+ default dispatch table for instances of that class.
+
+ See :ref:`pickle-dispatch` for usage examples.
+
+ .. versionadded:: 3.3
+
.. attribute:: fast
Deprecated. Enable fast mode if set to a true value. The fast mode
@@ -575,6 +598,44 @@
.. literalinclude:: ../includes/dbpickle.py
+.. _pickle-dispatch:
+
+Dispatch Tables
+^^^^^^^^^^^^^^^
+
+If one wants to customize pickling of some classes without disturbing
+any other code which depends on pickling, then one can create a
+pickler with a private dispatch table.
+
+The global dispatch table managed by the :mod:`copyreg` module is
+available as :data:`copyreg.dispatch_table`. Therefore, one may
+choose to use a modified copy of :data:`copyreg.dispatch_table` as a
+private dispatch table.
+
+For example ::
+
+ f = io.BytesIO()
+ p = pickle.Pickler(f)
+ p.dispatch_table = copyreg.dispatch_table.copy()
+ p.dispatch_table[SomeClass] = reduce_SomeClass
+
+creates an instance of :class:`pickle.Pickler` with a private dispatch
+table which handles the ``SomeClass`` class specially. Alternatively,
+the code ::
+
+ class MyPickler(pickle.Pickler):
+ dispatch_table = copyreg.dispatch_table.copy()
+ dispatch_table[SomeClass] = reduce_SomeClass
+ f = io.BytesIO()
+ p = MyPickler(f)
+
+does the same, but all instances of ``MyPickler`` will by default
+share the same dispatch table. The equivalent code using the
+:mod:`copyreg` module is ::
+
+ copyreg.pickle(SomeClass, reduce_SomeClass)
+ f = io.BytesIO()
+ p = pickle.Pickler(f)
.. _pickle-state:
diff --git a/Doc/library/signal.rst b/Doc/library/signal.rst
index 4fc3fd6..04afd9e 100644
--- a/Doc/library/signal.rst
+++ b/Doc/library/signal.rst
@@ -369,12 +369,11 @@
.. versionadded:: 3.3
-.. function:: sigtimedwait(sigset, (timeout_sec, timeout_nsec))
+.. function:: sigtimedwait(sigset, timeout)
- Like :func:`sigtimedwait`, but takes a tuple of ``(seconds, nanoseconds)``
- as an additional argument specifying a timeout. If both *timeout_sec* and
- *timeout_nsec* are specified as :const:`0`, a poll is performed. Returns
- :const:`None` if a timeout occurs.
+ Like :func:`sigwaitinfo`, but takes an additional *timeout* argument
+ specifying a timeout. If *timeout* is specified as :const:`0`, a poll is
+ performed. Returns :const:`None` if a timeout occurs.
Availability: Unix (see the man page :manpage:`sigtimedwait(2)` for further
information).
diff --git a/Doc/library/socket.rst b/Doc/library/socket.rst
index 8cc5a7e..69fa378 100644
--- a/Doc/library/socket.rst
+++ b/Doc/library/socket.rst
@@ -1311,7 +1311,7 @@
import struct
- # CAN frame packing/unpacking (see `struct can_frame` in <linux/can.h>)
+ # CAN frame packing/unpacking (see 'struct can_frame' in <linux/can.h>)
can_frame_fmt = "=IB3x8s"
can_frame_size = struct.calcsize(can_frame_fmt)
@@ -1326,7 +1326,7 @@
return (can_id, can_dlc, data[:can_dlc])
- # create a raw socket and bind it to the `vcan0` interface
+ # create a raw socket and bind it to the 'vcan0' interface
s = socket.socket(socket.AF_CAN, socket.SOCK_RAW, socket.CAN_RAW)
s.bind(('vcan0',))
diff --git a/Doc/library/sys.rst b/Doc/library/sys.rst
index da87be7..96450c5 100644
--- a/Doc/library/sys.rst
+++ b/Doc/library/sys.rst
@@ -770,7 +770,7 @@
independent Python files are installed; by default, this is the string
``'/usr/local'``. This can be set at build time with the ``--prefix``
argument to the :program:`configure` script. The main collection of Python
- library modules is installed in the directory :file:`{prefix}/lib/python{X.Y}``
+ library modules is installed in the directory :file:`{prefix}/lib/python{X.Y}`
while the platform independent header files (all except :file:`pyconfig.h`) are
stored in :file:`{prefix}/include/python{X.Y}`, where *X.Y* is the version
number of Python, for example ``3.2``.
diff --git a/Doc/library/xml.dom.minidom.rst b/Doc/library/xml.dom.minidom.rst
index ab5476d..ae286b0 100644
--- a/Doc/library/xml.dom.minidom.rst
+++ b/Doc/library/xml.dom.minidom.rst
@@ -15,6 +15,14 @@
Model interface. It is intended to be simpler than the full DOM and also
significantly smaller.
+.. note::
+
+ The :mod:`xml.dom.minidom` module provides an implementation of the W3C-DOM,
+ with an API similar to that in other programming languages. Users who are
+ unfamiliar with the W3C-DOM interface or who would like to write less code
+ for processing XML files should consider using the
+ :mod:`xml.etree.ElementTree` module instead.
+
DOM applications typically start by parsing some XML into a DOM. With
:mod:`xml.dom.minidom`, this is done through the parse functions::
diff --git a/Doc/license.rst b/Doc/license.rst
index 6f63ed4..9d6ef24 100644
--- a/Doc/license.rst
+++ b/Doc/license.rst
@@ -118,7 +118,7 @@
+----------------+--------------+------------+------------+-----------------+
| 3.2.2 | 3.2.1 | 2011 | PSF | yes |
+----------------+--------------+------------+------------+-----------------+
-| 3.3 | 3.2 | 2012 | PSF | yes |
+| 3.3.0 | 3.2 | 2012 | PSF | yes |
+----------------+--------------+------------+------------+-----------------+
.. note::
diff --git a/Doc/reference/lexical_analysis.rst b/Doc/reference/lexical_analysis.rst
index 65f8ffd..c94a47f 100644
--- a/Doc/reference/lexical_analysis.rst
+++ b/Doc/reference/lexical_analysis.rst
@@ -401,7 +401,7 @@
.. productionlist::
stringliteral: [`stringprefix`](`shortstring` | `longstring`)
- stringprefix: "r" | "R"
+ stringprefix: "r" | "u" | "ur" | "R" | "U" | "UR" | "Ur" | "uR"
shortstring: "'" `shortstringitem`* "'" | '"' `shortstringitem`* '"'
longstring: "'''" `longstringitem`* "'''" | '"""' `longstringitem`* '"""'
shortstringitem: `shortstringchar` | `stringescapeseq`
@@ -441,6 +441,9 @@
may only contain ASCII characters; bytes with a numeric value of 128 or greater
must be expressed with escapes.
+As of Python 3.3 it is possible again to prefix unicode strings with a
+``u`` prefix to simplify maintenance of dual 2.x and 3.x codebases.
+
Both string and bytes literals may optionally be prefixed with a letter ``'r'``
or ``'R'``; such strings are called :dfn:`raw strings` and treat backslashes as
literal characters. As a result, in string literals, ``'\U'`` and ``'\u'``
@@ -450,6 +453,11 @@
The ``'rb'`` prefix of raw bytes literals has been added as a synonym
of ``'br'``.
+ .. versionadded:: 3.3
+ Support for the unicode legacy literal (``u'value'``) and other
+ versions were reintroduced to simplify the maintenance of dual
+ Python 2.x and 3.x codebases. See :pep:`414` for more information.
+
In triple-quoted strings, unescaped newlines and quotes are allowed (and are
retained), except that three unescaped quotes in a row terminate the string. (A
"quote" is the character used to open the string, i.e. either ``'`` or ``"``.)
diff --git a/Doc/tools/sphinxext/pyspecific.py b/Doc/tools/sphinxext/pyspecific.py
index d928cfd..f359530 100644
--- a/Doc/tools/sphinxext/pyspecific.py
+++ b/Doc/tools/sphinxext/pyspecific.py
@@ -5,7 +5,7 @@
Sphinx extension with Python doc-specific markup.
- :copyright: 2008, 2009, 2010 by Georg Brandl.
+ :copyright: 2008, 2009, 2010, 2011, 2012 by Georg Brandl.
:license: Python license.
"""
@@ -201,11 +201,12 @@
document.append(doctree.ids[labelid])
destination = StringOutput(encoding='utf-8')
writer.write(document, destination)
- self.topics[label] = str(writer.output)
+ self.topics[label] = writer.output.encode('utf-8')
def finish(self):
f = open(path.join(self.outdir, 'topics.py'), 'w')
try:
+ f.write('# -*- coding: utf-8 -*-\n')
f.write('# Autogenerated by Sphinx on %s\n' % asctime())
f.write('topics = ' + pformat(self.topics) + '\n')
finally:
diff --git a/Doc/tools/sphinxext/susp-ignored.csv b/Doc/tools/sphinxext/susp-ignored.csv
index 18a16d7..a3d8d0b 100644
--- a/Doc/tools/sphinxext/susp-ignored.csv
+++ b/Doc/tools/sphinxext/susp-ignored.csv
@@ -1,16 +1,24 @@
c-api/arg,,:ref,"PyArg_ParseTuple(args, ""O|O:ref"", &object, &callback)"
c-api/list,,:high,list[low:high]
c-api/list,,:high,list[low:high] = itemlist
+c-api/sequence,,:i2,del o[i1:i2]
c-api/sequence,,:i2,o[i1:i2]
c-api/sequence,,:i2,o[i1:i2] = v
-c-api/sequence,,:i2,del o[i1:i2]
c-api/unicode,,:end,str[start:end]
+c-api/unicode,,:start,unicode[start:start+length]
+distutils/examples,267,`,This is the description of the ``foobar`` package.
distutils/setupscript,,::,
extending/embedding,,:numargs,"if(!PyArg_ParseTuple(args, "":numargs""))"
-extending/extending,,:set,"if (PyArg_ParseTuple(args, ""O:set_callback"", &temp)) {"
extending/extending,,:myfunction,"PyArg_ParseTuple(args, ""D:myfunction"", &c);"
+extending/extending,,:set,"if (PyArg_ParseTuple(args, ""O:set_callback"", &temp)) {"
extending/newtypes,,:call,"if (!PyArg_ParseTuple(args, ""sss:call"", &arg1, &arg2, &arg3)) {"
extending/windows,,:initspam,/export:initspam
+faq/programming,,:chr,">=4.0) or 1+f(xc,yc,x*x-y*y+xc,2.0*x*y+yc,k-1,f):f(xc,yc,x,y,k,f):chr("
+faq/programming,,::,for x in sequence[::-1]:
+faq/programming,,:reduce,"print((lambda Ru,Ro,Iu,Io,IM,Sx,Sy:reduce(lambda x,y:x+y,map(lambda y,"
+faq/programming,,:reduce,"Sx=Sx,Sy=Sy:reduce(lambda x,y:x+y,map(lambda x,xc=Ru,yc=yc,Ru=Ru,Ro=Ro,"
+faq/windows,229,:EOF,@setlocal enableextensions & python -x %~f0 %* & goto :EOF
+faq/windows,393,:REG,.py :REG_SZ: c:\<path to python>\python.exe -u %s %s
howto/cporting,,:add,"if (!PyArg_ParseTuple(args, ""ii:add_ints"", &one, &two))"
howto/cporting,,:encode,"if (!PyArg_ParseTuple(args, ""O:encode_object"", &myobj))"
howto/cporting,,:say,"if (!PyArg_ParseTuple(args, ""U:say_hello"", &name))"
@@ -22,19 +30,53 @@
howto/curses,,:red,"They are: 0:black, 1:red, 2:green, 3:yellow, 4:blue, 5:magenta, 6:cyan, and"
howto/curses,,:white,"7:white."
howto/curses,,:yellow,"They are: 0:black, 1:red, 2:green, 3:yellow, 4:blue, 5:magenta, 6:cyan, and"
+howto/logging,,:And,"WARNING:And this, too"
+howto/logging,,:And,"WARNING:root:And this, too"
+howto/logging,,:Doing,INFO:root:Doing something
+howto/logging,,:Finished,INFO:root:Finished
+howto/logging,,:logger,severity:logger name:message
+howto/logging,,:Look,WARNING:root:Look before you leap!
+howto/logging,,:message,severity:logger name:message
+howto/logging,,:root,DEBUG:root:This message should go to the log file
+howto/logging,,:root,INFO:root:Doing something
+howto/logging,,:root,INFO:root:Finished
+howto/logging,,:root,INFO:root:So should this
+howto/logging,,:root,INFO:root:Started
+howto/logging,,:root,"WARNING:root:And this, too"
+howto/logging,,:root,WARNING:root:Look before you leap!
+howto/logging,,:root,WARNING:root:Watch out!
+howto/logging,,:So,INFO:root:So should this
+howto/logging,,:So,INFO:So should this
+howto/logging,,:Started,INFO:root:Started
+howto/logging,,:This,DEBUG:root:This message should go to the log file
+howto/logging,,:This,DEBUG:This message should appear on the console
+howto/logging,,:Watch,WARNING:root:Watch out!
+howto/pyporting,75,::,# make sure to use :: Python *and* :: Python :: 3 so
+howto/pyporting,75,::,"'Programming Language :: Python',"
+howto/pyporting,75,::,'Programming Language :: Python :: 3'
howto/regex,,::,
howto/regex,,:foo,(?:foo)
howto/urllib2,,:example,"for example ""joe@password:example.com"""
howto/webservers,,.. image:,.. image:: http.png
library/audioop,,:ipos,"# factor = audioop.findfactor(in_test[ipos*2:ipos*2+len(out_test)],"
+library/bisect,32,:hi,all(val >= x for val in a[i:hi])
+library/bisect,42,:hi,all(val > x for val in a[i:hi])
+library/configparser,,:home,my_dir: ${Common:home_dir}/twosheds
+library/configparser,,:option,${section:option}
+library/configparser,,:path,python_dir: ${Frameworks:path}/Python/Versions/${Frameworks:Python}
+library/configparser,,:Python,python_dir: ${Frameworks:path}/Python/Versions/${Frameworks:Python}
+library/configparser,,`,# Set the optional `raw` argument of get() to True if you wish to disable
+library/configparser,,:system,path: ${Common:system_dir}/Library/Frameworks/
+library/configparser,,`,# The optional `fallback` argument can be used to provide a fallback value
+library/configparser,,`,# The optional `vars` argument is a dict with members that will take
library/datetime,,:MM,
library/datetime,,:SS,
library/decimal,,:optional,"trailneg:optional trailing minus indicator"
library/difflib,,:ahi,a[alo:ahi]
library/difflib,,:bhi,b[blo:bhi]
+library/difflib,,:i1,
library/difflib,,:i2,
library/difflib,,:j2,
-library/difflib,,:i1,
library/dis,,:TOS,
library/dis,,`,TOS = `TOS`
library/doctest,,`,``factorial`` from the ``example`` module:
@@ -44,96 +86,164 @@
library/functions,,:stop,"a[start:stop, i]"
library/functions,,:stop,a[start:stop:step]
library/hotshot,,:lineno,"ncalls tottime percall cumtime percall filename:lineno(function)"
+library/http.client,52,:port,host:port
library/httplib,,:port,host:port
library/imaplib,,:MM,"""DD-Mmm-YYYY HH:MM:SS"
library/imaplib,,:SS,"""DD-Mmm-YYYY HH:MM:SS"
-library/itertools,,:stop,elements from seq[start:stop:step]
library/itertools,,:step,elements from seq[start:stop:step]
+library/itertools,,:stop,elements from seq[start:stop:step]
library/linecache,,:sys,"sys:x:3:3:sys:/dev:/bin/sh"
library/logging,,:And,
+library/logging,,:Doing,INFO:root:Doing something
+library/logging,,:Finished,INFO:root:Finished
+library/logging,,:logger,severity:logger name:message
+library/logging,,:Look,WARNING:root:Look before you leap!
+library/logging,,:message,severity:logger name:message
library/logging,,:package1,
library/logging,,:package2,
-library/logging,,:root,
-library/logging,,:This,
library/logging,,:port,host:port
+library/logging,,:root,
+library/logging,,:So,INFO:root:So should this
+library/logging,,:So,INFO:So should this
+library/logging,,:Started,INFO:root:Started
+library/logging,,:This,
+library/logging,,:Watch,WARNING:root:Watch out!
+library/logging.handlers,,:port,host:port
library/mmap,,:i2,obj[i1:i2]
-library/multiprocessing,,:queue,">>> QueueManager.register('get_queue', callable=lambda:queue)"
-library/multiprocessing,,`,">>> l._callmethod('__getitem__', (20,)) # equiv to `l[20]`"
-library/multiprocessing,,`,">>> l._callmethod('__getslice__', (2, 7)) # equiv to `l[2:7]`"
-library/multiprocessing,,`,# `BaseManager`.
-library/multiprocessing,,`,# `Pool.imap()` (which will save on the amount of code needed anyway).
+library/multiprocessing,,`,# Add more tasks using `put()`
library/multiprocessing,,`,# A test file for the `multiprocessing` package
library/multiprocessing,,`,# A test of `multiprocessing.Pool` class
-library/multiprocessing,,`,# Add more tasks using `put()`
+library/multiprocessing,,`,# `BaseManager`.
+library/multiprocessing,,`,`Cluster` is a subclass of `SyncManager` so it allows creation of
library/multiprocessing,,`,# create server for a `HostManager` object
library/multiprocessing,,`,# Depends on `multiprocessing` package -- tested with `processing-0.60`
+library/multiprocessing,,`,`hostname` gives the name of the host. If hostname is not
library/multiprocessing,,`,# in the original order then consider using `Pool.map()` or
+library/multiprocessing,,`,">>> l._callmethod('__getitem__', (20,)) # equiv to `l[20]`"
+library/multiprocessing,,`,">>> l._callmethod('__getslice__', (2, 7)) # equiv to `l[2:7]`"
library/multiprocessing,,`,# Not sure if we should synchronize access to `socket.accept()` method by
library/multiprocessing,,`,# object. (We import `multiprocessing.reduction` to enable this pickling.)
+library/multiprocessing,,`,# `Pool.imap()` (which will save on the amount of code needed anyway).
+library/multiprocessing,,:queue,">>> QueueManager.register('get_queue', callable=lambda:queue)"
library/multiprocessing,,`,# register the Foo class; make `f()` and `g()` accessible via proxy
library/multiprocessing,,`,# register the Foo class; make `g()` and `_h()` accessible via proxy
library/multiprocessing,,`,# register the generator function baz; use `GeneratorProxy` to make proxies
-library/multiprocessing,,`,`Cluster` is a subclass of `SyncManager` so it allows creation of
-library/multiprocessing,,`,`hostname` gives the name of the host. If hostname is not
library/multiprocessing,,`,`slots` is used to specify the number of slots for processes on
+library/nntplib,,:bytes,:bytes
+library/nntplib,,:bytes,"['xref', 'from', ':lines', ':bytes', 'references', 'date', 'message-id', 'subject']"
+library/nntplib,,:lines,:lines
+library/nntplib,,:lines,"['xref', 'from', ':lines', ':bytes', 'references', 'date', 'message-id', 'subject']"
library/optparse,,:len,"del parser.rargs[:len(value)]"
library/os.path,,:foo,c:foo
library/parser,,`,"""Make a function that raises an argument to the exponent `exp`."""
+library/pdb,,:lineno,filename:lineno
+library/pdb,,:lineno,[filename:lineno | bpnumber [bpnumber ...]]
+library/pickle,,:memory,"conn = sqlite3.connect("":memory:"")"
library/posix,,`,"CFLAGS=""`getconf LFS_CFLAGS`"" OPT=""-g -O2 $CFLAGS"""
-library/profile,,:lineno,ncalls tottime percall cumtime percall filename:lineno(function)
+library/pprint,209,::,"'classifiers': ['Development Status :: 4 - Beta',"
+library/pprint,209,::,"'Intended Audience :: Developers',"
+library/pprint,209,::,"'License :: OSI Approved :: MIT License',"
+library/pprint,209,::,"'Natural Language :: English',"
+library/pprint,209,::,"'Operating System :: OS Independent',"
+library/pprint,209,::,"'Programming Language :: Python',"
+library/pprint,209,::,"'Programming Language :: Python :: 2',"
+library/pprint,209,::,"'Programming Language :: Python :: 2.6',"
+library/pprint,209,::,"'Programming Language :: Python :: 2.7',"
+library/pprint,209,::,"'Topic :: Software Development :: Libraries',"
+library/pprint,209,::,"'Topic :: Software Development :: Libraries :: Python Modules'],"
library/profile,,:lineno,filename:lineno(function)
+library/profile,,:lineno,ncalls tottime percall cumtime percall filename:lineno(function)
+library/profile,,:lineno,"(sort by filename:lineno),"
library/pyexpat,,:elem1,<py:elem1 />
library/pyexpat,,:py,"xmlns:py = ""http://www.python.org/ns/"">"
library/repr,,`,"return `obj`"
library/smtplib,,:port,"as well as a regular host:port server."
+library/smtplib,,:port,method must support that as well as a regular host:port
+library/socket,,::,"(10, 1, 6, '', ('2001:888:2000:d::a2', 80, 0, 0))]"
library/socket,,::,'5aef:2b::8'
-library/sqlite3,,:memory,
+library/socket,,:can,"return (can_id, can_dlc, data[:can_dlc])"
+library/socket,,:len,fds.fromstring(cmsg_data[:len(cmsg_data) - (len(cmsg_data) % fds.itemsize)])
+library/sqlite3,,:age,"cur.execute(""select * from people where name_last=:who and age=:age"", {""who"": who, ""age"": age})"
library/sqlite3,,:age,"select name_last, age from people where name_last=:who and age=:age"
-library/sqlite3,,:who,"select name_last, age from people where name_last=:who and age=:age"
-library/ssl,,:My,"Organization Name (eg, company) [Internet Widgits Pty Ltd]:My Organization, Inc."
+library/sqlite3,,:memory,
+library/sqlite3,,:who,"cur.execute(""select * from people where name_last=:who and age=:age"", {""who"": who, ""age"": age})"
library/ssl,,:My,"Organizational Unit Name (eg, section) []:My Group"
+library/ssl,,:My,"Organization Name (eg, company) [Internet Widgits Pty Ltd]:My Organization, Inc."
library/ssl,,:myserver,"Common Name (eg, YOUR name) []:myserver.mygroup.myorganization.com"
library/ssl,,:MyState,State or Province Name (full name) [Some-State]:MyState
library/ssl,,:ops,Email Address []:ops@myserver.mygroup.myorganization.com
library/ssl,,:Some,"Locality Name (eg, city) []:Some City"
library/ssl,,:US,Country Name (2 letter code) [AU]:US
+library/stdtypes,,::,>>> a[::-1].tolist()
+library/stdtypes,,::,>>> a[::2].tolist()
+library/stdtypes,,:end,s[start:end]
+library/stdtypes,,::,>>> hash(v[::-2]) == hash(b'abcefg'[::-2])
library/stdtypes,,:len,s[len(s):len(s)]
-library/stdtypes,,:len,s[len(s):len(s)]
+library/stdtypes,,::,>>> y = m[::2]
library/string,,:end,s[start:end]
-library/string,,:end,s[start:end]
-library/subprocess,,`,"output=`mycmd myarg`"
library/subprocess,,`,"output=`dmesg | grep hda`"
+library/subprocess,,`,"output=`mycmd myarg`"
+library/tarfile,,:bz2,
library/tarfile,,:compression,filemode[:compression]
library/tarfile,,:gz,
-library/tarfile,,:bz2,
+library/tarfile,,:xz,'a:xz'
+library/tarfile,,:xz,'r:xz'
+library/tarfile,,:xz,'w:xz'
library/time,,:mm,
library/time,,:ss,
library/turtle,,::,Example::
-library/urllib,,:port,:port
library/urllib2,,:password,"""joe:password@python.org"""
+library/urllib,,:port,:port
+library/urllib.request,,:close,Connection:close
+library/urllib.request,,:lang,"xmlns=""http://www.w3.org/1999/xhtml"" xml:lang=""en"" lang=""en"">\n\n<head>\n"
+library/urllib.request,,:password,"""joe:password@python.org"""
library/uuid,,:uuid,urn:uuid:12345678-1234-5678-1234-567812345678
-library/xmlrpclib,,:pass,http://user:pass@host:port/path
-library/xmlrpclib,,:pass,user:pass
-library/xmlrpclib,,:port,http://user:pass@host:port/path
+library/xmlrpc.client,,:pass,http://user:pass@host:port/path
+library/xmlrpc.client,,:pass,user:pass
+library/xmlrpc.client,,:port,http://user:pass@host:port/path
+license,,`,"``Software''), to deal in the Software without restriction, including"
+license,,`,"THE SOFTWARE IS PROVIDED ``AS IS'', WITHOUT WARRANTY OF ANY KIND,"
+license,,`,* THIS SOFTWARE IS PROVIDED BY ERIC YOUNG ``AS IS'' AND
+license,,`,THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND
+license,,`,* THIS SOFTWARE IS PROVIDED BY THE OpenSSL PROJECT ``AS IS'' AND ANY
license,,`,THIS SOFTWARE IS PROVIDED BY THE PROJECT AND CONTRIBUTORS ``AS IS'' AND
license,,:zooko,mailto:zooko@zooko.com
-license,,`,THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND
-reference/datamodel,,:step,a[i:j:step]
+packaging/examples,,`,This is the description of the ``foobar`` project.
+packaging/setupcfg,,::,Development Status :: 3 - Alpha
+packaging/setupcfg,,::,License :: OSI Approved :: Mozilla Public License 1.1 (MPL 1.1)
+packaging/setupscript,,::,"'Development Status :: 4 - Beta',"
+packaging/setupscript,,::,"'Environment :: Console',"
+packaging/setupscript,,::,"'Environment :: Web Environment',"
+packaging/setupscript,,::,"'Intended Audience :: Developers',"
+packaging/setupscript,,::,"'Intended Audience :: End Users/Desktop',"
+packaging/setupscript,,::,"'Intended Audience :: System Administrators',"
+packaging/setupscript,,::,"'License :: OSI Approved :: Python Software Foundation License',"
+packaging/setupscript,,::,"'Operating System :: MacOS :: MacOS X',"
+packaging/setupscript,,::,"'Operating System :: Microsoft :: Windows',"
+packaging/setupscript,,::,"'Operating System :: POSIX',"
+packaging/setupscript,,::,"'Programming Language :: Python',"
+packaging/setupscript,,::,"'Topic :: Communications :: Email',"
+packaging/setupscript,,::,"'Topic :: Office/Business',"
+packaging/setupscript,,::,"'Topic :: Software Development :: Bug Tracking',"
+packaging/tutorial,,::,1) License :: OSI Approved :: GNU General Public License (GPL)
+packaging/tutorial,,::,2) License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
+packaging/tutorial,,::,classifier = Development Status :: 3 - Alpha
+packaging/tutorial,,::,License :: OSI Approved :: GNU General Public License (GPL)
+packaging/tutorial,,::,Type the number of the license you wish to use or ? to try again:: 1
reference/datamodel,,:max,
-reference/expressions,,:index,x[index:index]
+reference/datamodel,,:step,a[i:j:step]
reference/expressions,,:datum,{key:datum...}
reference/expressions,,`,`expressions...`
+reference/expressions,,:index,x[index:index]
reference/grammar,,:output,#diagram:output
reference/grammar,,:rules,#diagram:rules
-reference/grammar,,:token,#diagram:token
reference/grammar,,`,'`' testlist1 '`'
-reference/lexical_analysis,,:fileencoding,# vim:fileencoding=<encoding-name>
+reference/grammar,,:token,#diagram:token
reference/lexical_analysis,,`,", : . ` = ;"
-tutorial/datastructures,,:value,key:value pairs within the braces adds initial key:value pairs
+reference/lexical_analysis,,`,$ ? `
+reference/lexical_analysis,,:fileencoding,# vim:fileencoding=<encoding-name>
tutorial/datastructures,,:value,It is also possible to delete a key:value
-tutorial/stdlib2,,:start,"fields = struct.unpack('<IIIHH', data[start:start+16])"
-tutorial/stdlib2,,:start,extra = data[start:start+extra_size]
-tutorial/stdlib2,,:start,filename = data[start:start+filenamesize]
+tutorial/datastructures,,:value,key:value pairs within the braces adds initial key:value pairs
tutorial/stdlib2,,:config,"logging.warning('Warning:config file %s not found', 'server.conf')"
tutorial/stdlib2,,:config,WARNING:root:Warning:config file server.conf not found
tutorial/stdlib2,,:Critical,CRITICAL:root:Critical error -- shutting down
@@ -141,15 +251,16 @@
tutorial/stdlib2,,:root,CRITICAL:root:Critical error -- shutting down
tutorial/stdlib2,,:root,ERROR:root:Error occurred
tutorial/stdlib2,,:root,WARNING:root:Warning:config file server.conf not found
+tutorial/stdlib2,,:start,extra = data[start:start+extra_size]
+tutorial/stdlib2,,:start,"fields = struct.unpack('<IIIHH', data[start:start+16])"
+tutorial/stdlib2,,:start,filename = data[start:start+filenamesize]
tutorial/stdlib2,,:Warning,WARNING:root:Warning:config file server.conf not found
-using/cmdline,,:line,file:line: category: message
using/cmdline,,:category,action:message:category:module:line
+using/cmdline,,:errorhandler,:errorhandler
using/cmdline,,:line,action:message:category:module:line
+using/cmdline,,:line,file:line: category: message
using/cmdline,,:message,action:message:category:module:line
using/cmdline,,:module,action:message:category:module:line
-using/cmdline,,:errorhandler,:errorhandler
-using/windows,162,`,`` this fixes syntax highlighting errors in some editors due to the \\\\ hackery
-using/windows,170,`,``
whatsnew/2.0,418,:len,
whatsnew/2.3,,::,
whatsnew/2.3,,:config,
@@ -163,135 +274,26 @@
whatsnew/2.5,,:memory,:memory:
whatsnew/2.5,,:step,[start:stop:step]
whatsnew/2.5,,:stop,[start:stop:step]
-distutils/examples,267,`,This is the description of the ``foobar`` package.
-faq/programming,,:reduce,"print((lambda Ru,Ro,Iu,Io,IM,Sx,Sy:reduce(lambda x,y:x+y,map(lambda y,"
-faq/programming,,:reduce,"Sx=Sx,Sy=Sy:reduce(lambda x,y:x+y,map(lambda x,xc=Ru,yc=yc,Ru=Ru,Ro=Ro,"
-faq/programming,,:chr,">=4.0) or 1+f(xc,yc,x*x-y*y+xc,2.0*x*y+yc,k-1,f):f(xc,yc,x,y,k,f):chr("
-faq/programming,,::,for x in sequence[::-1]:
-faq/windows,229,:EOF,@setlocal enableextensions & python -x %~f0 %* & goto :EOF
-faq/windows,393,:REG,.py :REG_SZ: c:\<path to python>\python.exe -u %s %s
-library/bisect,32,:hi,all(val >= x for val in a[i:hi])
-library/bisect,42,:hi,all(val > x for val in a[i:hi])
-library/http.client,52,:port,host:port
-library/nntplib,,:bytes,:bytes
-library/nntplib,,:lines,:lines
-library/nntplib,,:lines,"['xref', 'from', ':lines', ':bytes', 'references', 'date', 'message-id', 'subject']"
-library/nntplib,,:bytes,"['xref', 'from', ':lines', ':bytes', 'references', 'date', 'message-id', 'subject']"
-library/pickle,,:memory,"conn = sqlite3.connect("":memory:"")"
-library/profile,,:lineno,"(sort by filename:lineno),"
-library/socket,,::,"(10, 1, 6, '', ('2001:888:2000:d::a2', 80, 0, 0))]"
-library/stdtypes,,:end,s[start:end]
-library/stdtypes,,:end,s[start:end]
-library/urllib.request,,:close,Connection:close
-library/urllib.request,,:password,"""joe:password@python.org"""
-library/urllib.request,,:lang,"xmlns=""http://www.w3.org/1999/xhtml"" xml:lang=""en"" lang=""en"">\n\n<head>\n"
-library/xmlrpc.client,103,:pass,http://user:pass@host:port/path
-library/xmlrpc.client,103,:port,http://user:pass@host:port/path
-library/xmlrpc.client,103,:pass,user:pass
-license,,`,* THIS SOFTWARE IS PROVIDED BY THE OpenSSL PROJECT ``AS IS'' AND ANY
-license,,`,* THIS SOFTWARE IS PROVIDED BY ERIC YOUNG ``AS IS'' AND
-license,,`,"``Software''), to deal in the Software without restriction, including"
-license,,`,"THE SOFTWARE IS PROVIDED ``AS IS'', WITHOUT WARRANTY OF ANY KIND,"
-reference/lexical_analysis,704,`,$ ? `
-whatsnew/2.7,735,:Sunday,'2009:4:Sunday'
-whatsnew/2.7,862,::,"export PYTHONWARNINGS=all,error:::Cookie:0"
-whatsnew/2.7,862,:Cookie,"export PYTHONWARNINGS=all,error:::Cookie:0"
-whatsnew/2.7,1619,::,>>> urlparse.urlparse('http://[1080::8:800:200C:417A]/foo')
whatsnew/2.7,1619,::,"ParseResult(scheme='http', netloc='[1080::8:800:200C:417A]',"
-library/configparser,,`,# Set the optional `raw` argument of get() to True if you wish to disable
-library/configparser,,`,# The optional `vars` argument is a dict with members that will take
-library/configparser,,`,# The optional `fallback` argument can be used to provide a fallback value
-library/configparser,,:option,${section:option}
-library/configparser,,:system,path: ${Common:system_dir}/Library/Frameworks/
-library/configparser,,:home,my_dir: ${Common:home_dir}/twosheds
-library/configparser,,:path,python_dir: ${Frameworks:path}/Python/Versions/${Frameworks:Python}
-library/configparser,,:Python,python_dir: ${Frameworks:path}/Python/Versions/${Frameworks:Python}
-library/pdb,,:lineno,[filename:lineno | bpnumber [bpnumber ...]]
-library/pdb,,:lineno,filename:lineno
-library/logging,,:Watch,WARNING:root:Watch out!
-library/logging,,:So,INFO:root:So should this
-library/logging,,:Started,INFO:root:Started
-library/logging,,:Doing,INFO:root:Doing something
-library/logging,,:Finished,INFO:root:Finished
-library/logging,,:Look,WARNING:root:Look before you leap!
-library/logging,,:So,INFO:So should this
-library/logging,,:logger,severity:logger name:message
-library/logging,,:message,severity:logger name:message
-whatsnew/3.2,,:directory,... ${buildout:directory}/downloads/dist
-whatsnew/3.2,,:location,... zope9-location = ${zope9:location}
-whatsnew/3.2,,:prefix,... zope-conf = ${custom:prefix}/etc/zope.conf
-howto/logging,,:root,WARNING:root:Watch out!
-howto/logging,,:Watch,WARNING:root:Watch out!
-howto/logging,,:root,DEBUG:root:This message should go to the log file
-howto/logging,,:This,DEBUG:root:This message should go to the log file
-howto/logging,,:root,INFO:root:So should this
-howto/logging,,:So,INFO:root:So should this
-howto/logging,,:root,"WARNING:root:And this, too"
-howto/logging,,:And,"WARNING:root:And this, too"
-howto/logging,,:root,INFO:root:Started
-howto/logging,,:Started,INFO:root:Started
-howto/logging,,:root,INFO:root:Doing something
-howto/logging,,:Doing,INFO:root:Doing something
-howto/logging,,:root,INFO:root:Finished
-howto/logging,,:Finished,INFO:root:Finished
-howto/logging,,:root,WARNING:root:Look before you leap!
-howto/logging,,:Look,WARNING:root:Look before you leap!
-howto/logging,,:This,DEBUG:This message should appear on the console
-howto/logging,,:So,INFO:So should this
-howto/logging,,:And,"WARNING:And this, too"
-howto/logging,,:logger,severity:logger name:message
-howto/logging,,:message,severity:logger name:message
-library/logging.handlers,,:port,host:port
-library/imaplib,116,:MM,"""DD-Mmm-YYYY HH:MM:SS"
-library/imaplib,116,:SS,"""DD-Mmm-YYYY HH:MM:SS"
-whatsnew/3.2,,::,"$ export PYTHONWARNINGS='ignore::RuntimeWarning::,once::UnicodeWarning::'"
-howto/pyporting,75,::,# make sure to use :: Python *and* :: Python :: 3 so
-howto/pyporting,75,::,"'Programming Language :: Python',"
-howto/pyporting,75,::,'Programming Language :: Python :: 3'
-whatsnew/3.2,,:gz,">>> with tarfile.open(name='myarchive.tar.gz', mode='w:gz') as tf:"
-whatsnew/3.2,,:directory,${buildout:directory}/downloads/dist
-whatsnew/3.2,,:location,zope9-location = ${zope9:location}
-whatsnew/3.2,,:prefix,zope-conf = ${custom:prefix}/etc/zope.conf
-whatsnew/3.2,,:beef,>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/')
-whatsnew/3.2,,:cafe,>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/')
-whatsnew/3.2,,:affe,>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/')
-whatsnew/3.2,,:deaf,>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/')
-whatsnew/3.2,,:feed,>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/')
-whatsnew/3.2,,:beef,"netloc='[dead:beef:cafe:5417:affe:8FA3:deaf:feed]',"
-whatsnew/3.2,,:cafe,"netloc='[dead:beef:cafe:5417:affe:8FA3:deaf:feed]',"
+whatsnew/2.7,1619,::,>>> urlparse.urlparse('http://[1080::8:800:200C:417A]/foo')
+whatsnew/2.7,735,:Sunday,'2009:4:Sunday'
+whatsnew/2.7,862,:Cookie,"export PYTHONWARNINGS=all,error:::Cookie:0"
+whatsnew/2.7,862,::,"export PYTHONWARNINGS=all,error:::Cookie:0"
whatsnew/3.2,,:affe,"netloc='[dead:beef:cafe:5417:affe:8FA3:deaf:feed]',"
+whatsnew/3.2,,:affe,>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/')
+whatsnew/3.2,,:beef,"netloc='[dead:beef:cafe:5417:affe:8FA3:deaf:feed]',"
+whatsnew/3.2,,:beef,>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/')
+whatsnew/3.2,,:cafe,"netloc='[dead:beef:cafe:5417:affe:8FA3:deaf:feed]',"
+whatsnew/3.2,,:cafe,>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/')
whatsnew/3.2,,:deaf,"netloc='[dead:beef:cafe:5417:affe:8FA3:deaf:feed]',"
+whatsnew/3.2,,:deaf,>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/')
+whatsnew/3.2,,:directory,... ${buildout:directory}/downloads/dist
+whatsnew/3.2,,:directory,${buildout:directory}/downloads/dist
+whatsnew/3.2,,::,"$ export PYTHONWARNINGS='ignore::RuntimeWarning::,once::UnicodeWarning::'"
whatsnew/3.2,,:feed,"netloc='[dead:beef:cafe:5417:affe:8FA3:deaf:feed]',"
-library/pprint,209,::,"'classifiers': ['Development Status :: 4 - Beta',"
-library/pprint,209,::,"'Intended Audience :: Developers',"
-library/pprint,209,::,"'License :: OSI Approved :: MIT License',"
-library/pprint,209,::,"'Natural Language :: English',"
-library/pprint,209,::,"'Operating System :: OS Independent',"
-library/pprint,209,::,"'Programming Language :: Python',"
-library/pprint,209,::,"'Programming Language :: Python :: 2',"
-library/pprint,209,::,"'Programming Language :: Python :: 2.6',"
-library/pprint,209,::,"'Programming Language :: Python :: 2.7',"
-library/pprint,209,::,"'Topic :: Software Development :: Libraries',"
-library/pprint,209,::,"'Topic :: Software Development :: Libraries :: Python Modules'],"
-packaging/examples,,`,This is the description of the ``foobar`` project.
-packaging/setupcfg,,::,Development Status :: 3 - Alpha
-packaging/setupcfg,,::,License :: OSI Approved :: Mozilla Public License 1.1 (MPL 1.1)
-packaging/setupscript,,::,"'Development Status :: 4 - Beta',"
-packaging/setupscript,,::,"'Environment :: Console',"
-packaging/setupscript,,::,"'Environment :: Web Environment',"
-packaging/setupscript,,::,"'Intended Audience :: End Users/Desktop',"
-packaging/setupscript,,::,"'Intended Audience :: Developers',"
-packaging/setupscript,,::,"'Intended Audience :: System Administrators',"
-packaging/setupscript,,::,"'License :: OSI Approved :: Python Software Foundation License',"
-packaging/setupscript,,::,"'Operating System :: MacOS :: MacOS X',"
-packaging/setupscript,,::,"'Operating System :: Microsoft :: Windows',"
-packaging/setupscript,,::,"'Operating System :: POSIX',"
-packaging/setupscript,,::,"'Programming Language :: Python',"
-packaging/setupscript,,::,"'Topic :: Communications :: Email',"
-packaging/setupscript,,::,"'Topic :: Office/Business',"
-packaging/setupscript,,::,"'Topic :: Software Development :: Bug Tracking',"
-packaging/tutorial,,::,1) License :: OSI Approved :: GNU General Public License (GPL)
-packaging/tutorial,,::,2) License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
-packaging/tutorial,,::,Type the number of the license you wish to use or ? to try again:: 1
-packaging/tutorial,,::,classifier = Development Status :: 3 - Alpha
-packaging/tutorial,,::,License :: OSI Approved :: GNU General Public License (GPL)
+whatsnew/3.2,,:feed,>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/')
+whatsnew/3.2,,:gz,">>> with tarfile.open(name='myarchive.tar.gz', mode='w:gz') as tf:"
+whatsnew/3.2,,:location,... zope9-location = ${zope9:location}
+whatsnew/3.2,,:location,zope9-location = ${zope9:location}
+whatsnew/3.2,,:prefix,... zope-conf = ${custom:prefix}/etc/zope.conf
+whatsnew/3.2,,:prefix,zope-conf = ${custom:prefix}/etc/zope.conf
diff --git a/Doc/whatsnew/3.3.rst b/Doc/whatsnew/3.3.rst
index 7799ade..23048c5 100644
--- a/Doc/whatsnew/3.3.rst
+++ b/Doc/whatsnew/3.3.rst
@@ -49,6 +49,8 @@
This article explains the new features in Python 3.3, compared to 3.2.
+.. pep-3118-update:
+
PEP 3118: New memoryview implementation and buffer protocol documentation
=========================================================================
@@ -85,7 +87,9 @@
* Multi-dimensional comparisons are supported for any array type.
* All array types are hashable if the exporting object is hashable
- and the view is read-only.
+ and the view is read-only. (Contributed by Antoine Pitrou in
+ :issue:`13411`)
+
* Arbitrary slicing of any 1-D arrays type is supported. For example, it
is now possible to reverse a memoryview in O(1) by using a negative step.
@@ -167,19 +171,16 @@
* non-BMP strings (``U+10000-U+10FFFF``) use 4 bytes per codepoint.
-The net effect is that for most applications, memory usage of string storage
-should decrease significantly - especially compared to former wide unicode
-builds - as, in many cases, strings will be pure ASCII even in international
-contexts (because many strings store non-human language data, such as XML
-fragments, HTTP headers, JSON-encoded data, etc.). We also hope that it
-will, for the same reasons, increase CPU cache efficiency on non-trivial
-applications.
-
-.. The memory usage of Python 3.3 is two to three times smaller than Python 3.2,
- and a little bit better than Python 2.7, on a `Django benchmark
- <http://mail.python.org/pipermail/python-dev/2011-September/113714.html>`_.
- XXX The result should be moved in the PEP and a link to the PEP should
- be added here.
+The net effect is that for most applications, memory usage of string
+storage should decrease significantly - especially compared to former
+wide unicode builds - as, in many cases, strings will be pure ASCII
+even in international contexts (because many strings store non-human
+language data, such as XML fragments, HTTP headers, JSON-encoded data,
+etc.). We also hope that it will, for the same reasons, increase CPU
+cache efficiency on non-trivial applications. The memory usage of
+Python 3.3 is two to three times smaller than Python 3.2, and a little
+bit better than Python 2.7, on a Django benchmark (see the PEP for
+details).
PEP 3151: Reworking the OS and IO exception hierarchy
@@ -261,9 +262,56 @@
containing 'yield' to be factored out and placed in another generator.
Additionally, the subgenerator is allowed to return with a value, and the
value is made available to the delegating generator.
+
While designed primarily for use in delegating to a subgenerator, the ``yield
from`` expression actually allows delegation to arbitrary subiterators.
+For simple iterators, ``yield from iterable`` is essentially just a shortened
+form of ``for item in iterable: yield item``::
+
+ >>> def g(x):
+ ... yield from range(x, 0, -1)
+ ... yield from range(x)
+ ...
+ >>> list(g(5))
+ [5, 4, 3, 2, 1, 0, 1, 2, 3, 4]
+
+However, unlike an ordinary loop, ``yield from`` allows subgenerators to
+receive sent and thrown values directly from the calling scope, and
+return a final value to the outer generator::
+
+ >>> def accumulate(start=0):
+ ... tally = start
+ ... while 1:
+ ... next = yield
+ ... if next is None:
+ ... return tally
+ ... tally += next
+ ...
+ >>> def gather_tallies(tallies, start=0):
+ ... while 1:
+ ... tally = yield from accumulate()
+ ... tallies.append(tally)
+ ...
+ >>> tallies = []
+ >>> acc = gather_tallies(tallies)
+ >>> next(acc) # Ensure the accumulator is ready to accept values
+ >>> for i in range(10):
+ ... acc.send(i)
+ ...
+ >>> acc.send(None) # Finish the first tally
+ >>> for i in range(5):
+ ... acc.send(i)
+ ...
+ >>> acc.send(None) # Finish the second tally
+ >>> tallies
+ [45, 10]
+
+The main principle driving this change is to allow even generators that are
+designed to be used with the ``send`` and ``throw`` methods to be split into
+multiple subgenerators as easily as a single large function can be split into
+multiple subfunctions.
+
(Implementation by Greg Ewing, integrated into 3.3 by Renaud Blanch, Ryan
Kelly and Nick Coghlan, documentation by Zbigniew Jędrzejewski-Szmek and
Nick Coghlan)
@@ -330,6 +378,21 @@
KeyError('x',)
+PEP 414: Explicit Unicode literals
+======================================
+
+:pep:`414` - Explicit Unicode literals
+ PEP written by Armin Ronacher.
+
+To ease the transition from Python 2 for Unicode aware Python applications
+that make heavy use of Unicode literals, Python 3.3 once again supports the
+"``u``" prefix for string literals. This prefix has no semantic significance
+in Python 3, it is provided solely to reduce the number of purely mechanical
+changes in migrating to Python 3, making it easier for developers to focus on
+the more significant semantic changes (such as the stricter default
+separation of binary and text data).
+
+
PEP 3155: Qualified name for classes and functions
==================================================
@@ -411,10 +474,6 @@
(:issue:`12170`)
-* Memoryview objects are now hashable when the underlying object is hashable.
-
- (Contributed by Antoine Pitrou in :issue:`13411`)
-
New and Improved Modules
========================
diff --git a/Include/abstract.h b/Include/abstract.h
index abb996f..3a99c4e 100644
--- a/Include/abstract.h
+++ b/Include/abstract.h
@@ -1026,7 +1026,7 @@
PyAPI_FUNC(PyObject *) PySequence_Fast(PyObject *o, const char* m);
/*
- Returns the sequence, o, as a tuple, unless it's already a
+ Returns the sequence, o, as a list, unless it's already a
tuple or list. Use PySequence_Fast_GET_ITEM to access the
members of this list, and PySequence_Fast_GET_SIZE to get its length.
diff --git a/Include/patchlevel.h b/Include/patchlevel.h
index 4996e8e..e247875 100644
--- a/Include/patchlevel.h
+++ b/Include/patchlevel.h
@@ -20,10 +20,10 @@
#define PY_MINOR_VERSION 3
#define PY_MICRO_VERSION 0
#define PY_RELEASE_LEVEL PY_RELEASE_LEVEL_ALPHA
-#define PY_RELEASE_SERIAL 0
+#define PY_RELEASE_SERIAL 1
/* Version as a string */
-#define PY_VERSION "3.3.0a0"
+#define PY_VERSION "3.3.0a1+"
/*--end constants--*/
/* Version as a single 4-byte hex number, e.g. 0x010502B2 == 1.5.2b2.
diff --git a/Include/pytime.h b/Include/pytime.h
index d707bdb..2ea64c9 100644
--- a/Include/pytime.h
+++ b/Include/pytime.h
@@ -3,6 +3,7 @@
#define Py_PYTIME_H
#include "pyconfig.h" /* include for defines */
+#include "object.h"
/**************************************************************************
Symbols and macros to supply platform-independent interfaces to time related
@@ -37,6 +38,16 @@
((tv_end.tv_sec - tv_start.tv_sec) + \
(tv_end.tv_usec - tv_start.tv_usec) * 0.000001)
+#ifndef Py_LIMITED_API
+/* Convert a number of seconds, int or float, to a timespec structure.
+ nsec is always in the range [0; 999999999]. For example, -1.2 is converted
+ to (-2, 800000000). */
+PyAPI_FUNC(int) _PyTime_ObjectToTimespec(
+ PyObject *obj,
+ time_t *sec,
+ long *nsec);
+#endif
+
/* Dummy to force linking. */
PyAPI_FUNC(void) _PyTime_Init(void);
diff --git a/Include/unicodeobject.h b/Include/unicodeobject.h
index 465d87b..8f74995 100644
--- a/Include/unicodeobject.h
+++ b/Include/unicodeobject.h
@@ -499,17 +499,14 @@
do { \
switch ((kind)) { \
case PyUnicode_1BYTE_KIND: { \
- assert(value <= 0xff); \
((Py_UCS1 *)(data))[(index)] = (Py_UCS1)(value); \
break; \
} \
case PyUnicode_2BYTE_KIND: { \
- assert(value <= 0xffff); \
((Py_UCS2 *)(data))[(index)] = (Py_UCS2)(value); \
break; \
} \
default: { \
- assert(value <= 0x10ffff); \
assert((kind) == PyUnicode_4BYTE_KIND); \
((Py_UCS4 *)(data))[(index)] = (Py_UCS4)(value); \
} \
diff --git a/LICENSE b/LICENSE
index 349cbbf..235b568 100644
--- a/LICENSE
+++ b/LICENSE
@@ -73,7 +73,7 @@
3.2 3.1 2011 PSF yes
3.2.1 3.2 2011 PSF yes
3.2.2 3.2.1 2011 PSF yes
- 3.3 3.2 2012 PSF yes
+ 3.3.0 3.2 2012 PSF yes
Footnotes:
diff --git a/Lib/_weakrefset.py b/Lib/_weakrefset.py
index f34aa86..6a98b88 100644
--- a/Lib/_weakrefset.py
+++ b/Lib/_weakrefset.py
@@ -114,36 +114,21 @@
def update(self, other):
if self._pending_removals:
self._commit_removals()
- if isinstance(other, self.__class__):
- self.data.update(other.data)
- else:
- for element in other:
- self.add(element)
+ for element in other:
+ self.add(element)
def __ior__(self, other):
self.update(other)
return self
- # Helper functions for simple delegating methods.
- def _apply(self, other, method):
- if not isinstance(other, self.__class__):
- other = self.__class__(other)
- newdata = method(other.data)
- newset = self.__class__()
- newset.data = newdata
- return newset
-
def difference(self, other):
- return self._apply(other, self.data.difference)
+ newset = self.copy()
+ newset.difference_update(other)
+ return newset
__sub__ = difference
def difference_update(self, other):
- if self._pending_removals:
- self._commit_removals()
- if self is other:
- self.data.clear()
- else:
- self.data.difference_update(ref(item) for item in other)
+ self.__isub__(other)
def __isub__(self, other):
if self._pending_removals:
self._commit_removals()
@@ -154,13 +139,11 @@
return self
def intersection(self, other):
- return self._apply(other, self.data.intersection)
+ return self.__class__(item for item in other if item in self)
__and__ = intersection
def intersection_update(self, other):
- if self._pending_removals:
- self._commit_removals()
- self.data.intersection_update(ref(item) for item in other)
+ self.__iand__(other)
def __iand__(self, other):
if self._pending_removals:
self._commit_removals()
@@ -169,17 +152,17 @@
def issubset(self, other):
return self.data.issubset(ref(item) for item in other)
- __lt__ = issubset
+ __le__ = issubset
- def __le__(self, other):
- return self.data <= set(ref(item) for item in other)
+ def __lt__(self, other):
+ return self.data < set(ref(item) for item in other)
def issuperset(self, other):
return self.data.issuperset(ref(item) for item in other)
- __gt__ = issuperset
+ __ge__ = issuperset
- def __ge__(self, other):
- return self.data >= set(ref(item) for item in other)
+ def __gt__(self, other):
+ return self.data > set(ref(item) for item in other)
def __eq__(self, other):
if not isinstance(other, self.__class__):
@@ -187,27 +170,24 @@
return self.data == set(ref(item) for item in other)
def symmetric_difference(self, other):
- return self._apply(other, self.data.symmetric_difference)
+ newset = self.copy()
+ newset.symmetric_difference_update(other)
+ return newset
__xor__ = symmetric_difference
def symmetric_difference_update(self, other):
- if self._pending_removals:
- self._commit_removals()
- if self is other:
- self.data.clear()
- else:
- self.data.symmetric_difference_update(ref(item) for item in other)
+ self.__ixor__(other)
def __ixor__(self, other):
if self._pending_removals:
self._commit_removals()
if self is other:
self.data.clear()
else:
- self.data.symmetric_difference_update(ref(item) for item in other)
+ self.data.symmetric_difference_update(ref(item, self._remove) for item in other)
return self
def union(self, other):
- return self._apply(other, self.data.union)
+ return self.__class__(e for s in (self, other) for e in s)
__or__ = union
def isdisjoint(self, other):
diff --git a/Lib/concurrent/futures/process.py b/Lib/concurrent/futures/process.py
index 7f31ec2..04238a7 100644
--- a/Lib/concurrent/futures/process.py
+++ b/Lib/concurrent/futures/process.py
@@ -50,7 +50,8 @@
from concurrent.futures import _base
import queue
import multiprocessing
-from multiprocessing.queues import SimpleQueue, SentinelReady, Full
+from multiprocessing.queues import SimpleQueue, Full
+from multiprocessing.connection import wait
import threading
import weakref
@@ -212,6 +213,8 @@
for p in processes.values():
p.join()
+ reader = result_queue._reader
+
while True:
_add_call_item_to_queue(pending_work_items,
work_ids_queue,
@@ -219,9 +222,10 @@
sentinels = [p.sentinel for p in processes.values()]
assert sentinels
- try:
- result_item = result_queue.get(sentinels=sentinels)
- except SentinelReady:
+ ready = wait([reader] + sentinels)
+ if reader in ready:
+ result_item = reader.recv()
+ else:
# Mark the process pool broken so that submits fail right now.
executor = executor_reference()
if executor is not None:
diff --git a/Lib/distutils/__init__.py b/Lib/distutils/__init__.py
index f883916..8b4261a 100644
--- a/Lib/distutils/__init__.py
+++ b/Lib/distutils/__init__.py
@@ -13,5 +13,5 @@
# Updated automatically by the Python release process.
#
#--start constants--
-__version__ = "3.3a0"
+__version__ = "3.3.0a1"
#--end constants--
diff --git a/Lib/distutils/command/bdist_msi.py b/Lib/distutils/command/bdist_msi.py
index b3cfe9c..fde0f63 100644
--- a/Lib/distutils/command/bdist_msi.py
+++ b/Lib/distutils/command/bdist_msi.py
@@ -260,7 +260,7 @@
self.db.Commit()
if hasattr(self.distribution, 'dist_files'):
- tup = 'bdist_msi', self.target_version or 'any', fullname
+ tup = 'bdist_msi', self.target_version or 'any', installer_name
self.distribution.dist_files.append(tup)
if not self.keep_temp:
diff --git a/Lib/distutils/tests/test_bdist_msi.py b/Lib/distutils/tests/test_bdist_msi.py
index 9308c79..e599461 100644
--- a/Lib/distutils/tests/test_bdist_msi.py
+++ b/Lib/distutils/tests/test_bdist_msi.py
@@ -1,12 +1,12 @@
"""Tests for distutils.command.bdist_msi."""
-import unittest
+import os
import sys
-
+import unittest
from test.support import run_unittest
-
from distutils.tests import support
-@unittest.skipUnless(sys.platform=="win32", "These tests are only for win32")
+
+@unittest.skipUnless(sys.platform == 'win32', 'these tests require Windows')
class BDistMSITestCase(support.TempdirManager,
support.LoggingSilencer,
unittest.TestCase):
@@ -14,9 +14,18 @@
def test_minimal(self):
# minimal test XXX need more tests
from distutils.command.bdist_msi import bdist_msi
- pkg_pth, dist = self.create_dist()
+ project_dir, dist = self.create_dist()
cmd = bdist_msi(dist)
cmd.ensure_finalized()
+ cmd.run()
+
+ bdists = os.listdir(os.path.join(project_dir, 'dist'))
+ self.assertEqual(bdists, ['foo-0.1.msi'])
+
+ # bug #13719: upload ignores bdist_msi files
+ self.assertEqual(dist.dist_files,
+ [('bdist_msi', 'any', 'dist/foo-0.1.msi')])
+
def test_suite():
return unittest.makeSuite(BDistMSITestCase)
diff --git a/Lib/idlelib/idlever.py b/Lib/idlelib/idlever.py
index 5e9afb1..76b8bb8 100644
--- a/Lib/idlelib/idlever.py
+++ b/Lib/idlelib/idlever.py
@@ -1 +1 @@
-IDLE_VERSION = "3.3a0"
+IDLE_VERSION = "3.3.0a1"
diff --git a/Lib/multiprocessing/connection.py b/Lib/multiprocessing/connection.py
index 8807618..ca0c973 100644
--- a/Lib/multiprocessing/connection.py
+++ b/Lib/multiprocessing/connection.py
@@ -32,7 +32,7 @@
# SUCH DAMAGE.
#
-__all__ = [ 'Client', 'Listener', 'Pipe' ]
+__all__ = [ 'Client', 'Listener', 'Pipe', 'wait' ]
import io
import os
@@ -58,8 +58,6 @@
raise
win32 = None
-_select = _eintr_retry(select.select)
-
#
#
#
@@ -122,15 +120,6 @@
else:
raise ValueError('address type of %r unrecognized' % address)
-
-class SentinelReady(Exception):
- """
- Raised when a sentinel is ready when polling.
- """
- def __init__(self, *args):
- Exception.__init__(self, *args)
- self.sentinels = args[0]
-
#
# Connection classes
#
@@ -268,11 +257,11 @@
(offset + size) // itemsize])
return size
- def recv(self, sentinels=None):
+ def recv(self):
"""Receive a (picklable) object"""
self._check_closed()
self._check_readable()
- buf = self._recv_bytes(sentinels=sentinels)
+ buf = self._recv_bytes()
return pickle.loads(buf.getbuffer())
def poll(self, timeout=0.0):
@@ -290,85 +279,80 @@
Overlapped I/O is used, so the handles must have been created
with FILE_FLAG_OVERLAPPED.
"""
- _buffered = b''
+ _got_empty_message = False
def _close(self, _CloseHandle=win32.CloseHandle):
_CloseHandle(self._handle)
def _send_bytes(self, buf):
- overlapped = win32.WriteFile(self._handle, buf, overlapped=True)
- nwritten, complete = overlapped.GetOverlappedResult(True)
- assert complete
+ ov, err = win32.WriteFile(self._handle, buf, overlapped=True)
+ try:
+ if err == win32.ERROR_IO_PENDING:
+ waitres = win32.WaitForMultipleObjects(
+ [ov.event], False, INFINITE)
+ assert waitres == WAIT_OBJECT_0
+ except:
+ ov.cancel()
+ raise
+ finally:
+ nwritten, err = ov.GetOverlappedResult(True)
+ assert err == 0
assert nwritten == len(buf)
- def _recv_bytes(self, maxsize=None, sentinels=()):
- if sentinels:
- self._poll(-1.0, sentinels)
- buf = io.BytesIO()
- firstchunk = self._buffered
- if firstchunk:
- lenfirstchunk = len(firstchunk)
- buf.write(firstchunk)
- self._buffered = b''
+ def _recv_bytes(self, maxsize=None):
+ if self._got_empty_message:
+ self._got_empty_message = False
+ return io.BytesIO()
else:
- # A reasonable size for the first chunk transfer
- bufsize = 128
- if maxsize is not None and maxsize < bufsize:
- bufsize = maxsize
+ bsize = 128 if maxsize is None else min(maxsize, 128)
try:
- overlapped = win32.ReadFile(self._handle, bufsize, overlapped=True)
- lenfirstchunk, complete = overlapped.GetOverlappedResult(True)
- firstchunk = overlapped.getbuffer()
- assert lenfirstchunk == len(firstchunk)
+ ov, err = win32.ReadFile(self._handle, bsize,
+ overlapped=True)
+ try:
+ if err == win32.ERROR_IO_PENDING:
+ waitres = win32.WaitForMultipleObjects(
+ [ov.event], False, INFINITE)
+ assert waitres == WAIT_OBJECT_0
+ except:
+ ov.cancel()
+ raise
+ finally:
+ nread, err = ov.GetOverlappedResult(True)
+ if err == 0:
+ f = io.BytesIO()
+ f.write(ov.getbuffer())
+ return f
+ elif err == win32.ERROR_MORE_DATA:
+ return self._get_more_data(ov, maxsize)
except IOError as e:
if e.winerror == win32.ERROR_BROKEN_PIPE:
raise EOFError
- raise
- buf.write(firstchunk)
- if complete:
- return buf
- navail, nleft = win32.PeekNamedPipe(self._handle)
- if maxsize is not None and lenfirstchunk + nleft > maxsize:
- return None
- if nleft > 0:
- overlapped = win32.ReadFile(self._handle, nleft, overlapped=True)
- res, complete = overlapped.GetOverlappedResult(True)
- assert res == nleft
- assert complete
- buf.write(overlapped.getbuffer())
- return buf
+ else:
+ raise
+ raise RuntimeError("shouldn't get here; expected KeyboardInterrupt")
- def _poll(self, timeout, sentinels=()):
- # Fast non-blocking path
- navail, nleft = win32.PeekNamedPipe(self._handle)
- if navail > 0:
+ def _poll(self, timeout):
+ if (self._got_empty_message or
+ win32.PeekNamedPipe(self._handle)[0] != 0):
return True
- elif timeout == 0.0:
- return False
- # Blocking: use overlapped I/O
- if timeout < 0.0:
- timeout = INFINITE
- else:
- timeout = int(timeout * 1000 + 0.5)
- overlapped = win32.ReadFile(self._handle, 1, overlapped=True)
- try:
- handles = [overlapped.event]
- handles += sentinels
- res = win32.WaitForMultipleObjects(handles, False, timeout)
- finally:
- # Always cancel overlapped I/O in the same thread
- # (because CancelIoEx() appears only in Vista)
- overlapped.cancel()
- if res == WAIT_TIMEOUT:
- return False
- idx = res - WAIT_OBJECT_0
- if idx == 0:
- # I/O was successful, store received data
- overlapped.GetOverlappedResult(True)
- self._buffered += overlapped.getbuffer()
- return True
- assert 0 < idx < len(handles)
- raise SentinelReady([handles[idx]])
+ if timeout < 0:
+ timeout = None
+ return bool(wait([self], timeout))
+
+ def _get_more_data(self, ov, maxsize):
+ buf = ov.getbuffer()
+ f = io.BytesIO()
+ f.write(buf)
+ left = win32.PeekNamedPipe(self._handle)[1]
+ assert left > 0
+ if maxsize is not None and len(buf) + left > maxsize:
+ self._bad_message_length()
+ ov, err = win32.ReadFile(self._handle, left, overlapped=True)
+ rbytes, err = ov.GetOverlappedResult(True)
+ assert err == 0
+ assert rbytes == left
+ f.write(ov.getbuffer())
+ return f
class Connection(_ConnectionBase):
@@ -397,17 +381,11 @@
break
buf = buf[n:]
- def _recv(self, size, sentinels=(), read=_read):
+ def _recv(self, size, read=_read):
buf = io.BytesIO()
handle = self._handle
- if sentinels:
- handles = [handle] + sentinels
remaining = size
while remaining > 0:
- if sentinels:
- r = _select(handles, [], [])[0]
- if handle not in r:
- raise SentinelReady(r)
chunk = read(handle, remaining)
n = len(chunk)
if n == 0:
@@ -428,17 +406,17 @@
if n > 0:
self._send(buf)
- def _recv_bytes(self, maxsize=None, sentinels=()):
- buf = self._recv(4, sentinels)
+ def _recv_bytes(self, maxsize=None):
+ buf = self._recv(4)
size, = struct.unpack("!i", buf.getvalue())
if maxsize is not None and size > maxsize:
return None
- return self._recv(size, sentinels)
+ return self._recv(size)
def _poll(self, timeout):
if timeout < 0.0:
timeout = None
- r = _select([self._handle], [], [], timeout)[0]
+ r = wait([self._handle], timeout)
return bool(r)
@@ -559,7 +537,8 @@
)
overlapped = win32.ConnectNamedPipe(h1, overlapped=True)
- overlapped.GetOverlappedResult(True)
+ _, err = overlapped.GetOverlappedResult(True)
+ assert err == 0
c1 = PipeConnection(h1, writable=duplex)
c2 = PipeConnection(h2, readable=duplex)
@@ -633,39 +612,40 @@
'''
def __init__(self, address, backlog=None):
self._address = address
- handle = win32.CreateNamedPipe(
- address, win32.PIPE_ACCESS_DUPLEX |
- win32.FILE_FLAG_FIRST_PIPE_INSTANCE,
- win32.PIPE_TYPE_MESSAGE | win32.PIPE_READMODE_MESSAGE |
- win32.PIPE_WAIT,
- win32.PIPE_UNLIMITED_INSTANCES, BUFSIZE, BUFSIZE,
- win32.NMPWAIT_WAIT_FOREVER, win32.NULL
- )
- self._handle_queue = [handle]
+ self._handle_queue = [self._new_handle(first=True)]
+
self._last_accepted = None
-
sub_debug('listener created with address=%r', self._address)
-
self.close = Finalize(
self, PipeListener._finalize_pipe_listener,
args=(self._handle_queue, self._address), exitpriority=0
)
- def accept(self):
- newhandle = win32.CreateNamedPipe(
- self._address, win32.PIPE_ACCESS_DUPLEX,
+ def _new_handle(self, first=False):
+ flags = win32.PIPE_ACCESS_DUPLEX | win32.FILE_FLAG_OVERLAPPED
+ if first:
+ flags |= win32.FILE_FLAG_FIRST_PIPE_INSTANCE
+ return win32.CreateNamedPipe(
+ self._address, flags,
win32.PIPE_TYPE_MESSAGE | win32.PIPE_READMODE_MESSAGE |
win32.PIPE_WAIT,
win32.PIPE_UNLIMITED_INSTANCES, BUFSIZE, BUFSIZE,
win32.NMPWAIT_WAIT_FOREVER, win32.NULL
)
- self._handle_queue.append(newhandle)
+
+ def accept(self):
+ self._handle_queue.append(self._new_handle())
handle = self._handle_queue.pop(0)
+ ov = win32.ConnectNamedPipe(handle, overlapped=True)
try:
- win32.ConnectNamedPipe(handle, win32.NULL)
- except WindowsError as e:
- if e.winerror != win32.ERROR_PIPE_CONNECTED:
- raise
+ res = win32.WaitForMultipleObjects([ov.event], False, INFINITE)
+ except:
+ ov.cancel()
+ win32.CloseHandle(handle)
+ raise
+ finally:
+ _, err = ov.GetOverlappedResult(True)
+ assert err == 0
return PipeConnection(handle)
@staticmethod
@@ -684,7 +664,8 @@
win32.WaitNamedPipe(address, 1000)
h = win32.CreateFile(
address, win32.GENERIC_READ | win32.GENERIC_WRITE,
- 0, win32.NULL, win32.OPEN_EXISTING, 0, win32.NULL
+ 0, win32.NULL, win32.OPEN_EXISTING,
+ win32.FILE_FLAG_OVERLAPPED, win32.NULL
)
except WindowsError as e:
if e.winerror not in (win32.ERROR_SEM_TIMEOUT,
@@ -773,6 +754,125 @@
import xmlrpc.client as xmlrpclib
return ConnectionWrapper(Client(*args, **kwds), _xml_dumps, _xml_loads)
+#
+# Wait
+#
+
+if sys.platform == 'win32':
+
+ def _exhaustive_wait(handles, timeout):
+ # Return ALL handles which are currently signalled. (Only
+ # returning the first signalled might create starvation issues.)
+ L = list(handles)
+ ready = []
+ while L:
+ res = win32.WaitForMultipleObjects(L, False, timeout)
+ if res == WAIT_TIMEOUT:
+ break
+ elif WAIT_OBJECT_0 <= res < WAIT_OBJECT_0 + len(L):
+ res -= WAIT_OBJECT_0
+ elif WAIT_ABANDONED_0 <= res < WAIT_ABANDONED_0 + len(L):
+ res -= WAIT_ABANDONED_0
+ else:
+ raise RuntimeError('Should not get here')
+ ready.append(L[res])
+ L = L[res+1:]
+ timeout = 0
+ return ready
+
+ _ready_errors = {win32.ERROR_BROKEN_PIPE, win32.ERROR_NETNAME_DELETED}
+
+ def wait(object_list, timeout=None):
+ '''
+ Wait till an object in object_list is ready/readable.
+
+ Returns list of those objects in object_list which are ready/readable.
+ '''
+ if timeout is None:
+ timeout = INFINITE
+ elif timeout < 0:
+ timeout = 0
+ else:
+ timeout = int(timeout * 1000 + 0.5)
+
+ object_list = list(object_list)
+ waithandle_to_obj = {}
+ ov_list = []
+ ready_objects = set()
+ ready_handles = set()
+
+ try:
+ for o in object_list:
+ try:
+ fileno = getattr(o, 'fileno')
+ except AttributeError:
+ waithandle_to_obj[o.__index__()] = o
+ else:
+ # start an overlapped read of length zero
+ try:
+ ov, err = win32.ReadFile(fileno(), 0, True)
+ except OSError as e:
+ err = e.winerror
+ if err not in _ready_errors:
+ raise
+ if err == win32.ERROR_IO_PENDING:
+ ov_list.append(ov)
+ waithandle_to_obj[ov.event] = o
+ else:
+ # If o.fileno() is an overlapped pipe handle and
+ # err == 0 then there is a zero length message
+ # in the pipe, but it HAS NOT been consumed.
+ ready_objects.add(o)
+ timeout = 0
+
+ ready_handles = _exhaustive_wait(waithandle_to_obj.keys(), timeout)
+ finally:
+ # request that overlapped reads stop
+ for ov in ov_list:
+ ov.cancel()
+
+ # wait for all overlapped reads to stop
+ for ov in ov_list:
+ try:
+ _, err = ov.GetOverlappedResult(True)
+ except OSError as e:
+ err = e.winerror
+ if err not in _ready_errors:
+ raise
+ if err != win32.ERROR_OPERATION_ABORTED:
+ o = waithandle_to_obj[ov.event]
+ ready_objects.add(o)
+ if err == 0:
+ # If o.fileno() is an overlapped pipe handle then
+ # a zero length message HAS been consumed.
+ if hasattr(o, '_got_empty_message'):
+ o._got_empty_message = True
+
+ ready_objects.update(waithandle_to_obj[h] for h in ready_handles)
+ return [o for o in object_list if o in ready_objects]
+
+else:
+
+ def wait(object_list, timeout=None):
+ '''
+ Wait till an object in object_list is ready/readable.
+
+ Returns list of those objects in object_list which are ready/readable.
+ '''
+ if timeout is not None:
+ if timeout <= 0:
+ return select.select(object_list, [], [], 0)[0]
+ else:
+ deadline = time.time() + timeout
+ while True:
+ try:
+ return select.select(object_list, [], [], timeout)[0]
+ except OSError as e:
+ if e.errno != errno.EINTR:
+ raise
+ if timeout is not None:
+ timeout = deadline - time.time()
+
# Late import because of circular import
from multiprocessing.forking import duplicate, close
diff --git a/Lib/multiprocessing/queues.py b/Lib/multiprocessing/queues.py
index c4f9cda..262fd85 100644
--- a/Lib/multiprocessing/queues.py
+++ b/Lib/multiprocessing/queues.py
@@ -44,7 +44,7 @@
from queue import Empty, Full
import _multiprocessing
-from multiprocessing.connection import Pipe, SentinelReady
+from multiprocessing.connection import Pipe
from multiprocessing.synchronize import Lock, BoundedSemaphore, Semaphore, Condition
from multiprocessing.util import debug, info, Finalize, register_after_fork
from multiprocessing.forking import assert_spawning
@@ -360,6 +360,7 @@
def __init__(self):
self._reader, self._writer = Pipe(duplex=False)
self._rlock = Lock()
+ self._poll = self._reader.poll
if sys.platform == 'win32':
self._wlock = None
else:
@@ -367,7 +368,7 @@
self._make_methods()
def empty(self):
- return not self._reader.poll()
+ return not self._poll()
def __getstate__(self):
assert_spawning(self)
@@ -380,10 +381,10 @@
def _make_methods(self):
recv = self._reader.recv
racquire, rrelease = self._rlock.acquire, self._rlock.release
- def get(*, sentinels=None):
+ def get():
racquire()
try:
- return recv(sentinels)
+ return recv()
finally:
rrelease()
self.get = get
diff --git a/Lib/packaging/command/bdist_msi.py b/Lib/packaging/command/bdist_msi.py
index 995eec5..ad1edef 100644
--- a/Lib/packaging/command/bdist_msi.py
+++ b/Lib/packaging/command/bdist_msi.py
@@ -261,7 +261,7 @@
self.db.Commit()
if hasattr(self.distribution, 'dist_files'):
- tup = 'bdist_msi', self.target_version or 'any', fullname
+ tup = 'bdist_msi', self.target_version or 'any', installer_name
self.distribution.dist_files.append(tup)
if not self.keep_temp:
diff --git a/Lib/packaging/database.py b/Lib/packaging/database.py
index b2fcb97..e028dc5 100644
--- a/Lib/packaging/database.py
+++ b/Lib/packaging/database.py
@@ -19,6 +19,7 @@
'get_distributions', 'get_distribution', 'get_file_users',
'provides_distribution', 'obsoletes_distribution',
'enable_cache', 'disable_cache', 'clear_cache',
+ # XXX these functions' names look like get_file_users but are not related
'get_file_path', 'get_file']
diff --git a/Lib/packaging/tests/test_command_bdist_msi.py b/Lib/packaging/tests/test_command_bdist_msi.py
index fded962..25973ef 100644
--- a/Lib/packaging/tests/test_command_bdist_msi.py
+++ b/Lib/packaging/tests/test_command_bdist_msi.py
@@ -1,20 +1,29 @@
"""Tests for distutils.command.bdist_msi."""
+import os
import sys
from packaging.tests import unittest, support
+@unittest.skipUnless(sys.platform == 'win32', 'these tests require Windows')
class BDistMSITestCase(support.TempdirManager,
support.LoggingCatcher,
unittest.TestCase):
- @unittest.skipUnless(sys.platform == "win32", "runs only on win32")
def test_minimal(self):
# minimal test XXX need more tests
from packaging.command.bdist_msi import bdist_msi
- pkg_pth, dist = self.create_dist()
+ project_dir, dist = self.create_dist()
cmd = bdist_msi(dist)
cmd.ensure_finalized()
+ cmd.run()
+
+ bdists = os.listdir(os.path.join(project_dir, 'dist'))
+ self.assertEqual(bdists, ['foo-0.1.msi'])
+
+ # bug #13719: upload ignores bdist_msi files
+ self.assertEqual(dist.dist_files,
+ [('bdist_msi', 'any', 'dist/foo-0.1.msi')])
def test_suite():
diff --git a/Lib/pickle.py b/Lib/pickle.py
index c01a6af..20b3646 100644
--- a/Lib/pickle.py
+++ b/Lib/pickle.py
@@ -297,8 +297,8 @@
f(self, obj) # Call unbound method with explicit self
return
- # Check copyreg.dispatch_table
- reduce = dispatch_table.get(t)
+ # Check private dispatch table if any, or else copyreg.dispatch_table
+ reduce = getattr(self, 'dispatch_table', dispatch_table).get(t)
if reduce:
rv = reduce(obj)
else:
diff --git a/Lib/pydoc_data/topics.py b/Lib/pydoc_data/topics.py
index 7edc551..92e045e 100644
--- a/Lib/pydoc_data/topics.py
+++ b/Lib/pydoc_data/topics.py
@@ -1,30 +1,31 @@
-# Autogenerated by Sphinx on Thu Apr 28 07:53:12 2011
+# -*- coding: utf-8 -*-
+# Autogenerated by Sphinx on Sun Mar 4 16:11:27 2012
topics = {'assert': '\nThe ``assert`` statement\n************************\n\nAssert statements are a convenient way to insert debugging assertions\ninto a program:\n\n assert_stmt ::= "assert" expression ["," expression]\n\nThe simple form, ``assert expression``, is equivalent to\n\n if __debug__:\n if not expression: raise AssertionError\n\nThe extended form, ``assert expression1, expression2``, is equivalent\nto\n\n if __debug__:\n if not expression1: raise AssertionError(expression2)\n\nThese equivalences assume that ``__debug__`` and ``AssertionError``\nrefer to the built-in variables with those names. In the current\nimplementation, the built-in variable ``__debug__`` is ``True`` under\nnormal circumstances, ``False`` when optimization is requested\n(command line option -O). The current code generator emits no code\nfor an assert statement when optimization is requested at compile\ntime. Note that it is unnecessary to include the source code for the\nexpression that failed in the error message; it will be displayed as\npart of the stack trace.\n\nAssignments to ``__debug__`` are illegal. The value for the built-in\nvariable is determined when the interpreter starts.\n',
'assignment': '\nAssignment statements\n*********************\n\nAssignment statements are used to (re)bind names to values and to\nmodify attributes or items of mutable objects:\n\n assignment_stmt ::= (target_list "=")+ (expression_list | yield_expression)\n target_list ::= target ("," target)* [","]\n target ::= identifier\n | "(" target_list ")"\n | "[" target_list "]"\n | attributeref\n | subscription\n | slicing\n | "*" target\n\n(See section *Primaries* for the syntax definitions for the last three\nsymbols.)\n\nAn assignment statement evaluates the expression list (remember that\nthis can be a single expression or a comma-separated list, the latter\nyielding a tuple) and assigns the single resulting object to each of\nthe target lists, from left to right.\n\nAssignment is defined recursively depending on the form of the target\n(list). When a target is part of a mutable object (an attribute\nreference, subscription or slicing), the mutable object must\nultimately perform the assignment and decide about its validity, and\nmay raise an exception if the assignment is unacceptable. The rules\nobserved by various types and the exceptions raised are given with the\ndefinition of the object types (see section *The standard type\nhierarchy*).\n\nAssignment of an object to a target list, optionally enclosed in\nparentheses or square brackets, is recursively defined as follows.\n\n* If the target list is a single target: The object is assigned to\n that target.\n\n* If the target list is a comma-separated list of targets: The object\n must be an iterable with the same number of items as there are\n targets in the target list, and the items are assigned, from left to\n right, to the corresponding targets.\n\n * If the target list contains one target prefixed with an asterisk,\n called a "starred" target: The object must be a sequence with at\n least as many items as there are targets in the target list, minus\n one. The first items of the sequence are assigned, from left to\n right, to the targets before the starred target. The final items\n of the sequence are assigned to the targets after the starred\n target. A list of the remaining items in the sequence is then\n assigned to the starred target (the list can be empty).\n\n * Else: The object must be a sequence with the same number of items\n as there are targets in the target list, and the items are\n assigned, from left to right, to the corresponding targets.\n\nAssignment of an object to a single target is recursively defined as\nfollows.\n\n* If the target is an identifier (name):\n\n * If the name does not occur in a ``global`` or ``nonlocal``\n statement in the current code block: the name is bound to the\n object in the current local namespace.\n\n * Otherwise: the name is bound to the object in the global namespace\n or the outer namespace determined by ``nonlocal``, respectively.\n\n The name is rebound if it was already bound. This may cause the\n reference count for the object previously bound to the name to reach\n zero, causing the object to be deallocated and its destructor (if it\n has one) to be called.\n\n* If the target is a target list enclosed in parentheses or in square\n brackets: The object must be an iterable with the same number of\n items as there are targets in the target list, and its items are\n assigned, from left to right, to the corresponding targets.\n\n* If the target is an attribute reference: The primary expression in\n the reference is evaluated. It should yield an object with\n assignable attributes; if this is not the case, ``TypeError`` is\n raised. That object is then asked to assign the assigned object to\n the given attribute; if it cannot perform the assignment, it raises\n an exception (usually but not necessarily ``AttributeError``).\n\n Note: If the object is a class instance and the attribute reference\n occurs on both sides of the assignment operator, the RHS expression,\n ``a.x`` can access either an instance attribute or (if no instance\n attribute exists) a class attribute. The LHS target ``a.x`` is\n always set as an instance attribute, creating it if necessary.\n Thus, the two occurrences of ``a.x`` do not necessarily refer to the\n same attribute: if the RHS expression refers to a class attribute,\n the LHS creates a new instance attribute as the target of the\n assignment:\n\n class Cls:\n x = 3 # class variable\n inst = Cls()\n inst.x = inst.x + 1 # writes inst.x as 4 leaving Cls.x as 3\n\n This description does not necessarily apply to descriptor\n attributes, such as properties created with ``property()``.\n\n* If the target is a subscription: The primary expression in the\n reference is evaluated. It should yield either a mutable sequence\n object (such as a list) or a mapping object (such as a dictionary).\n Next, the subscript expression is evaluated.\n\n If the primary is a mutable sequence object (such as a list), the\n subscript must yield an integer. If it is negative, the sequence\'s\n length is added to it. The resulting value must be a nonnegative\n integer less than the sequence\'s length, and the sequence is asked\n to assign the assigned object to its item with that index. If the\n index is out of range, ``IndexError`` is raised (assignment to a\n subscripted sequence cannot add new items to a list).\n\n If the primary is a mapping object (such as a dictionary), the\n subscript must have a type compatible with the mapping\'s key type,\n and the mapping is then asked to create a key/datum pair which maps\n the subscript to the assigned object. This can either replace an\n existing key/value pair with the same key value, or insert a new\n key/value pair (if no key with the same value existed).\n\n For user-defined objects, the ``__setitem__()`` method is called\n with appropriate arguments.\n\n* If the target is a slicing: The primary expression in the reference\n is evaluated. It should yield a mutable sequence object (such as a\n list). The assigned object should be a sequence object of the same\n type. Next, the lower and upper bound expressions are evaluated,\n insofar they are present; defaults are zero and the sequence\'s\n length. The bounds should evaluate to integers. If either bound is\n negative, the sequence\'s length is added to it. The resulting\n bounds are clipped to lie between zero and the sequence\'s length,\n inclusive. Finally, the sequence object is asked to replace the\n slice with the items of the assigned sequence. The length of the\n slice may be different from the length of the assigned sequence,\n thus changing the length of the target sequence, if the object\n allows it.\n\n**CPython implementation detail:** In the current implementation, the\nsyntax for targets is taken to be the same as for expressions, and\ninvalid syntax is rejected during the code generation phase, causing\nless detailed error messages.\n\nWARNING: Although the definition of assignment implies that overlaps\nbetween the left-hand side and the right-hand side are \'safe\' (for\nexample ``a, b = b, a`` swaps two variables), overlaps *within* the\ncollection of assigned-to variables are not safe! For instance, the\nfollowing program prints ``[0, 2]``:\n\n x = [0, 1]\n i = 0\n i, x[i] = 1, 2\n print(x)\n\nSee also:\n\n **PEP 3132** - Extended Iterable Unpacking\n The specification for the ``*target`` feature.\n\n\nAugmented assignment statements\n===============================\n\nAugmented assignment is the combination, in a single statement, of a\nbinary operation and an assignment statement:\n\n augmented_assignment_stmt ::= augtarget augop (expression_list | yield_expression)\n augtarget ::= identifier | attributeref | subscription | slicing\n augop ::= "+=" | "-=" | "*=" | "/=" | "//=" | "%=" | "**="\n | ">>=" | "<<=" | "&=" | "^=" | "|="\n\n(See section *Primaries* for the syntax definitions for the last three\nsymbols.)\n\nAn augmented assignment evaluates the target (which, unlike normal\nassignment statements, cannot be an unpacking) and the expression\nlist, performs the binary operation specific to the type of assignment\non the two operands, and assigns the result to the original target.\nThe target is only evaluated once.\n\nAn augmented assignment expression like ``x += 1`` can be rewritten as\n``x = x + 1`` to achieve a similar, but not exactly equal effect. In\nthe augmented version, ``x`` is only evaluated once. Also, when\npossible, the actual operation is performed *in-place*, meaning that\nrather than creating a new object and assigning that to the target,\nthe old object is modified instead.\n\nWith the exception of assigning to tuples and multiple targets in a\nsingle statement, the assignment done by augmented assignment\nstatements is handled the same way as normal assignments. Similarly,\nwith the exception of the possible *in-place* behavior, the binary\noperation performed by augmented assignment is the same as the normal\nbinary operations.\n\nFor targets which are attribute references, the same *caveat about\nclass and instance attributes* applies as for regular assignments.\n',
'atom-identifiers': '\nIdentifiers (Names)\n*******************\n\nAn identifier occurring as an atom is a name. See section\n*Identifiers and keywords* for lexical definition and section *Naming\nand binding* for documentation of naming and binding.\n\nWhen the name is bound to an object, evaluation of the atom yields\nthat object. When a name is not bound, an attempt to evaluate it\nraises a ``NameError`` exception.\n\n**Private name mangling:** When an identifier that textually occurs in\na class definition begins with two or more underscore characters and\ndoes not end in two or more underscores, it is considered a *private\nname* of that class. Private names are transformed to a longer form\nbefore code is generated for them. The transformation inserts the\nclass name in front of the name, with leading underscores removed, and\na single underscore inserted in front of the class name. For example,\nthe identifier ``__spam`` occurring in a class named ``Ham`` will be\ntransformed to ``_Ham__spam``. This transformation is independent of\nthe syntactical context in which the identifier is used. If the\ntransformed name is extremely long (longer than 255 characters),\nimplementation defined truncation may happen. If the class name\nconsists only of underscores, no transformation is done.\n',
- 'atom-literals': "\nLiterals\n********\n\nPython supports string and bytes literals and various numeric\nliterals:\n\n literal ::= stringliteral | bytesliteral\n | integer | floatnumber | imagnumber\n\nEvaluation of a literal yields an object of the given type (string,\nbytes, integer, floating point number, complex number) with the given\nvalue. The value may be approximated in the case of floating point\nand imaginary (complex) literals. See section *Literals* for details.\n\nWith the exception of bytes literals, these all correspond to\nimmutable data types, and hence the object's identity is less\nimportant than its value. Multiple evaluations of literals with the\nsame value (either the same occurrence in the program text or a\ndifferent occurrence) may obtain the same object or a different object\nwith the same value.\n",
- 'attribute-access': '\nCustomizing attribute access\n****************************\n\nThe following methods can be defined to customize the meaning of\nattribute access (use of, assignment to, or deletion of ``x.name``)\nfor class instances.\n\nobject.__getattr__(self, name)\n\n Called when an attribute lookup has not found the attribute in the\n usual places (i.e. it is not an instance attribute nor is it found\n in the class tree for ``self``). ``name`` is the attribute name.\n This method should return the (computed) attribute value or raise\n an ``AttributeError`` exception.\n\n Note that if the attribute is found through the normal mechanism,\n ``__getattr__()`` is not called. (This is an intentional asymmetry\n between ``__getattr__()`` and ``__setattr__()``.) This is done both\n for efficiency reasons and because otherwise ``__getattr__()``\n would have no way to access other attributes of the instance. Note\n that at least for instance variables, you can fake total control by\n not inserting any values in the instance attribute dictionary (but\n instead inserting them in another object). See the\n ``__getattribute__()`` method below for a way to actually get total\n control over attribute access.\n\nobject.__getattribute__(self, name)\n\n Called unconditionally to implement attribute accesses for\n instances of the class. If the class also defines\n ``__getattr__()``, the latter will not be called unless\n ``__getattribute__()`` either calls it explicitly or raises an\n ``AttributeError``. This method should return the (computed)\n attribute value or raise an ``AttributeError`` exception. In order\n to avoid infinite recursion in this method, its implementation\n should always call the base class method with the same name to\n access any attributes it needs, for example,\n ``object.__getattribute__(self, name)``.\n\n Note: This method may still be bypassed when looking up special methods\n as the result of implicit invocation via language syntax or\n built-in functions. See *Special method lookup*.\n\nobject.__setattr__(self, name, value)\n\n Called when an attribute assignment is attempted. This is called\n instead of the normal mechanism (i.e. store the value in the\n instance dictionary). *name* is the attribute name, *value* is the\n value to be assigned to it.\n\n If ``__setattr__()`` wants to assign to an instance attribute, it\n should call the base class method with the same name, for example,\n ``object.__setattr__(self, name, value)``.\n\nobject.__delattr__(self, name)\n\n Like ``__setattr__()`` but for attribute deletion instead of\n assignment. This should only be implemented if ``del obj.name`` is\n meaningful for the object.\n\nobject.__dir__(self)\n\n Called when ``dir()`` is called on the object. A list must be\n returned.\n\n\nImplementing Descriptors\n========================\n\nThe following methods only apply when an instance of the class\ncontaining the method (a so-called *descriptor* class) appears in an\n*owner* class (the descriptor must be in either the owner\'s class\ndictionary or in the class dictionary for one of its parents). In the\nexamples below, "the attribute" refers to the attribute whose name is\nthe key of the property in the owner class\' ``__dict__``.\n\nobject.__get__(self, instance, owner)\n\n Called to get the attribute of the owner class (class attribute\n access) or of an instance of that class (instance attribute\n access). *owner* is always the owner class, while *instance* is the\n instance that the attribute was accessed through, or ``None`` when\n the attribute is accessed through the *owner*. This method should\n return the (computed) attribute value or raise an\n ``AttributeError`` exception.\n\nobject.__set__(self, instance, value)\n\n Called to set the attribute on an instance *instance* of the owner\n class to a new value, *value*.\n\nobject.__delete__(self, instance)\n\n Called to delete the attribute on an instance *instance* of the\n owner class.\n\n\nInvoking Descriptors\n====================\n\nIn general, a descriptor is an object attribute with "binding\nbehavior", one whose attribute access has been overridden by methods\nin the descriptor protocol: ``__get__()``, ``__set__()``, and\n``__delete__()``. If any of those methods are defined for an object,\nit is said to be a descriptor.\n\nThe default behavior for attribute access is to get, set, or delete\nthe attribute from an object\'s dictionary. For instance, ``a.x`` has a\nlookup chain starting with ``a.__dict__[\'x\']``, then\n``type(a).__dict__[\'x\']``, and continuing through the base classes of\n``type(a)`` excluding metaclasses.\n\nHowever, if the looked-up value is an object defining one of the\ndescriptor methods, then Python may override the default behavior and\ninvoke the descriptor method instead. Where this occurs in the\nprecedence chain depends on which descriptor methods were defined and\nhow they were called.\n\nThe starting point for descriptor invocation is a binding, ``a.x``.\nHow the arguments are assembled depends on ``a``:\n\nDirect Call\n The simplest and least common call is when user code directly\n invokes a descriptor method: ``x.__get__(a)``.\n\nInstance Binding\n If binding to an object instance, ``a.x`` is transformed into the\n call: ``type(a).__dict__[\'x\'].__get__(a, type(a))``.\n\nClass Binding\n If binding to a class, ``A.x`` is transformed into the call:\n ``A.__dict__[\'x\'].__get__(None, A)``.\n\nSuper Binding\n If ``a`` is an instance of ``super``, then the binding ``super(B,\n obj).m()`` searches ``obj.__class__.__mro__`` for the base class\n ``A`` immediately preceding ``B`` and then invokes the descriptor\n with the call: ``A.__dict__[\'m\'].__get__(obj, obj.__class__)``.\n\nFor instance bindings, the precedence of descriptor invocation depends\non the which descriptor methods are defined. A descriptor can define\nany combination of ``__get__()``, ``__set__()`` and ``__delete__()``.\nIf it does not define ``__get__()``, then accessing the attribute will\nreturn the descriptor object itself unless there is a value in the\nobject\'s instance dictionary. If the descriptor defines ``__set__()``\nand/or ``__delete__()``, it is a data descriptor; if it defines\nneither, it is a non-data descriptor. Normally, data descriptors\ndefine both ``__get__()`` and ``__set__()``, while non-data\ndescriptors have just the ``__get__()`` method. Data descriptors with\n``__set__()`` and ``__get__()`` defined always override a redefinition\nin an instance dictionary. In contrast, non-data descriptors can be\noverridden by instances.\n\nPython methods (including ``staticmethod()`` and ``classmethod()``)\nare implemented as non-data descriptors. Accordingly, instances can\nredefine and override methods. This allows individual instances to\nacquire behaviors that differ from other instances of the same class.\n\nThe ``property()`` function is implemented as a data descriptor.\nAccordingly, instances cannot override the behavior of a property.\n\n\n__slots__\n=========\n\nBy default, instances of classes have a dictionary for attribute\nstorage. This wastes space for objects having very few instance\nvariables. The space consumption can become acute when creating large\nnumbers of instances.\n\nThe default can be overridden by defining *__slots__* in a class\ndefinition. The *__slots__* declaration takes a sequence of instance\nvariables and reserves just enough space in each instance to hold a\nvalue for each variable. Space is saved because *__dict__* is not\ncreated for each instance.\n\nobject.__slots__\n\n This class variable can be assigned a string, iterable, or sequence\n of strings with variable names used by instances. If defined in a\n class, *__slots__* reserves space for the declared variables and\n prevents the automatic creation of *__dict__* and *__weakref__* for\n each instance.\n\n\nNotes on using *__slots__*\n--------------------------\n\n* When inheriting from a class without *__slots__*, the *__dict__*\n attribute of that class will always be accessible, so a *__slots__*\n definition in the subclass is meaningless.\n\n* Without a *__dict__* variable, instances cannot be assigned new\n variables not listed in the *__slots__* definition. Attempts to\n assign to an unlisted variable name raises ``AttributeError``. If\n dynamic assignment of new variables is desired, then add\n ``\'__dict__\'`` to the sequence of strings in the *__slots__*\n declaration.\n\n* Without a *__weakref__* variable for each instance, classes defining\n *__slots__* do not support weak references to its instances. If weak\n reference support is needed, then add ``\'__weakref__\'`` to the\n sequence of strings in the *__slots__* declaration.\n\n* *__slots__* are implemented at the class level by creating\n descriptors (*Implementing Descriptors*) for each variable name. As\n a result, class attributes cannot be used to set default values for\n instance variables defined by *__slots__*; otherwise, the class\n attribute would overwrite the descriptor assignment.\n\n* The action of a *__slots__* declaration is limited to the class\n where it is defined. As a result, subclasses will have a *__dict__*\n unless they also define *__slots__* (which must only contain names\n of any *additional* slots).\n\n* If a class defines a slot also defined in a base class, the instance\n variable defined by the base class slot is inaccessible (except by\n retrieving its descriptor directly from the base class). This\n renders the meaning of the program undefined. In the future, a\n check may be added to prevent this.\n\n* Nonempty *__slots__* does not work for classes derived from\n "variable-length" built-in types such as ``int``, ``str`` and\n ``tuple``.\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings may\n also be used; however, in the future, special meaning may be\n assigned to the values corresponding to each key.\n\n* *__class__* assignment works only if both classes have the same\n *__slots__*.\n',
+ 'atom-literals': "\nLiterals\n********\n\nPython supports string and bytes literals and various numeric\nliterals:\n\n literal ::= stringliteral | bytesliteral\n | integer | floatnumber | imagnumber\n\nEvaluation of a literal yields an object of the given type (string,\nbytes, integer, floating point number, complex number) with the given\nvalue. The value may be approximated in the case of floating point\nand imaginary (complex) literals. See section *Literals* for details.\n\nAll literals correspond to immutable data types, and hence the\nobject's identity is less important than its value. Multiple\nevaluations of literals with the same value (either the same\noccurrence in the program text or a different occurrence) may obtain\nthe same object or a different object with the same value.\n",
+ 'attribute-access': '\nCustomizing attribute access\n****************************\n\nThe following methods can be defined to customize the meaning of\nattribute access (use of, assignment to, or deletion of ``x.name``)\nfor class instances.\n\nobject.__getattr__(self, name)\n\n Called when an attribute lookup has not found the attribute in the\n usual places (i.e. it is not an instance attribute nor is it found\n in the class tree for ``self``). ``name`` is the attribute name.\n This method should return the (computed) attribute value or raise\n an ``AttributeError`` exception.\n\n Note that if the attribute is found through the normal mechanism,\n ``__getattr__()`` is not called. (This is an intentional asymmetry\n between ``__getattr__()`` and ``__setattr__()``.) This is done both\n for efficiency reasons and because otherwise ``__getattr__()``\n would have no way to access other attributes of the instance. Note\n that at least for instance variables, you can fake total control by\n not inserting any values in the instance attribute dictionary (but\n instead inserting them in another object). See the\n ``__getattribute__()`` method below for a way to actually get total\n control over attribute access.\n\nobject.__getattribute__(self, name)\n\n Called unconditionally to implement attribute accesses for\n instances of the class. If the class also defines\n ``__getattr__()``, the latter will not be called unless\n ``__getattribute__()`` either calls it explicitly or raises an\n ``AttributeError``. This method should return the (computed)\n attribute value or raise an ``AttributeError`` exception. In order\n to avoid infinite recursion in this method, its implementation\n should always call the base class method with the same name to\n access any attributes it needs, for example,\n ``object.__getattribute__(self, name)``.\n\n Note: This method may still be bypassed when looking up special methods\n as the result of implicit invocation via language syntax or\n built-in functions. See *Special method lookup*.\n\nobject.__setattr__(self, name, value)\n\n Called when an attribute assignment is attempted. This is called\n instead of the normal mechanism (i.e. store the value in the\n instance dictionary). *name* is the attribute name, *value* is the\n value to be assigned to it.\n\n If ``__setattr__()`` wants to assign to an instance attribute, it\n should call the base class method with the same name, for example,\n ``object.__setattr__(self, name, value)``.\n\nobject.__delattr__(self, name)\n\n Like ``__setattr__()`` but for attribute deletion instead of\n assignment. This should only be implemented if ``del obj.name`` is\n meaningful for the object.\n\nobject.__dir__(self)\n\n Called when ``dir()`` is called on the object. A sequence must be\n returned. ``dir()`` converts the returned sequence to a list and\n sorts it.\n\n\nImplementing Descriptors\n========================\n\nThe following methods only apply when an instance of the class\ncontaining the method (a so-called *descriptor* class) appears in an\n*owner* class (the descriptor must be in either the owner\'s class\ndictionary or in the class dictionary for one of its parents). In the\nexamples below, "the attribute" refers to the attribute whose name is\nthe key of the property in the owner class\' ``__dict__``.\n\nobject.__get__(self, instance, owner)\n\n Called to get the attribute of the owner class (class attribute\n access) or of an instance of that class (instance attribute\n access). *owner* is always the owner class, while *instance* is the\n instance that the attribute was accessed through, or ``None`` when\n the attribute is accessed through the *owner*. This method should\n return the (computed) attribute value or raise an\n ``AttributeError`` exception.\n\nobject.__set__(self, instance, value)\n\n Called to set the attribute on an instance *instance* of the owner\n class to a new value, *value*.\n\nobject.__delete__(self, instance)\n\n Called to delete the attribute on an instance *instance* of the\n owner class.\n\n\nInvoking Descriptors\n====================\n\nIn general, a descriptor is an object attribute with "binding\nbehavior", one whose attribute access has been overridden by methods\nin the descriptor protocol: ``__get__()``, ``__set__()``, and\n``__delete__()``. If any of those methods are defined for an object,\nit is said to be a descriptor.\n\nThe default behavior for attribute access is to get, set, or delete\nthe attribute from an object\'s dictionary. For instance, ``a.x`` has a\nlookup chain starting with ``a.__dict__[\'x\']``, then\n``type(a).__dict__[\'x\']``, and continuing through the base classes of\n``type(a)`` excluding metaclasses.\n\nHowever, if the looked-up value is an object defining one of the\ndescriptor methods, then Python may override the default behavior and\ninvoke the descriptor method instead. Where this occurs in the\nprecedence chain depends on which descriptor methods were defined and\nhow they were called.\n\nThe starting point for descriptor invocation is a binding, ``a.x``.\nHow the arguments are assembled depends on ``a``:\n\nDirect Call\n The simplest and least common call is when user code directly\n invokes a descriptor method: ``x.__get__(a)``.\n\nInstance Binding\n If binding to an object instance, ``a.x`` is transformed into the\n call: ``type(a).__dict__[\'x\'].__get__(a, type(a))``.\n\nClass Binding\n If binding to a class, ``A.x`` is transformed into the call:\n ``A.__dict__[\'x\'].__get__(None, A)``.\n\nSuper Binding\n If ``a`` is an instance of ``super``, then the binding ``super(B,\n obj).m()`` searches ``obj.__class__.__mro__`` for the base class\n ``A`` immediately preceding ``B`` and then invokes the descriptor\n with the call: ``A.__dict__[\'m\'].__get__(obj, obj.__class__)``.\n\nFor instance bindings, the precedence of descriptor invocation depends\non the which descriptor methods are defined. A descriptor can define\nany combination of ``__get__()``, ``__set__()`` and ``__delete__()``.\nIf it does not define ``__get__()``, then accessing the attribute will\nreturn the descriptor object itself unless there is a value in the\nobject\'s instance dictionary. If the descriptor defines ``__set__()``\nand/or ``__delete__()``, it is a data descriptor; if it defines\nneither, it is a non-data descriptor. Normally, data descriptors\ndefine both ``__get__()`` and ``__set__()``, while non-data\ndescriptors have just the ``__get__()`` method. Data descriptors with\n``__set__()`` and ``__get__()`` defined always override a redefinition\nin an instance dictionary. In contrast, non-data descriptors can be\noverridden by instances.\n\nPython methods (including ``staticmethod()`` and ``classmethod()``)\nare implemented as non-data descriptors. Accordingly, instances can\nredefine and override methods. This allows individual instances to\nacquire behaviors that differ from other instances of the same class.\n\nThe ``property()`` function is implemented as a data descriptor.\nAccordingly, instances cannot override the behavior of a property.\n\n\n__slots__\n=========\n\nBy default, instances of classes have a dictionary for attribute\nstorage. This wastes space for objects having very few instance\nvariables. The space consumption can become acute when creating large\nnumbers of instances.\n\nThe default can be overridden by defining *__slots__* in a class\ndefinition. The *__slots__* declaration takes a sequence of instance\nvariables and reserves just enough space in each instance to hold a\nvalue for each variable. Space is saved because *__dict__* is not\ncreated for each instance.\n\nobject.__slots__\n\n This class variable can be assigned a string, iterable, or sequence\n of strings with variable names used by instances. If defined in a\n class, *__slots__* reserves space for the declared variables and\n prevents the automatic creation of *__dict__* and *__weakref__* for\n each instance.\n\n\nNotes on using *__slots__*\n--------------------------\n\n* When inheriting from a class without *__slots__*, the *__dict__*\n attribute of that class will always be accessible, so a *__slots__*\n definition in the subclass is meaningless.\n\n* Without a *__dict__* variable, instances cannot be assigned new\n variables not listed in the *__slots__* definition. Attempts to\n assign to an unlisted variable name raises ``AttributeError``. If\n dynamic assignment of new variables is desired, then add\n ``\'__dict__\'`` to the sequence of strings in the *__slots__*\n declaration.\n\n* Without a *__weakref__* variable for each instance, classes defining\n *__slots__* do not support weak references to its instances. If weak\n reference support is needed, then add ``\'__weakref__\'`` to the\n sequence of strings in the *__slots__* declaration.\n\n* *__slots__* are implemented at the class level by creating\n descriptors (*Implementing Descriptors*) for each variable name. As\n a result, class attributes cannot be used to set default values for\n instance variables defined by *__slots__*; otherwise, the class\n attribute would overwrite the descriptor assignment.\n\n* The action of a *__slots__* declaration is limited to the class\n where it is defined. As a result, subclasses will have a *__dict__*\n unless they also define *__slots__* (which must only contain names\n of any *additional* slots).\n\n* If a class defines a slot also defined in a base class, the instance\n variable defined by the base class slot is inaccessible (except by\n retrieving its descriptor directly from the base class). This\n renders the meaning of the program undefined. In the future, a\n check may be added to prevent this.\n\n* Nonempty *__slots__* does not work for classes derived from\n "variable-length" built-in types such as ``int``, ``str`` and\n ``tuple``.\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings may\n also be used; however, in the future, special meaning may be\n assigned to the values corresponding to each key.\n\n* *__class__* assignment works only if both classes have the same\n *__slots__*.\n',
'attribute-references': '\nAttribute references\n********************\n\nAn attribute reference is a primary followed by a period and a name:\n\n attributeref ::= primary "." identifier\n\nThe primary must evaluate to an object of a type that supports\nattribute references, which most objects do. This object is then\nasked to produce the attribute whose name is the identifier (which can\nbe customized by overriding the ``__getattr__()`` method). If this\nattribute is not available, the exception ``AttributeError`` is\nraised. Otherwise, the type and value of the object produced is\ndetermined by the object. Multiple evaluations of the same attribute\nreference may yield different objects.\n',
'augassign': '\nAugmented assignment statements\n*******************************\n\nAugmented assignment is the combination, in a single statement, of a\nbinary operation and an assignment statement:\n\n augmented_assignment_stmt ::= augtarget augop (expression_list | yield_expression)\n augtarget ::= identifier | attributeref | subscription | slicing\n augop ::= "+=" | "-=" | "*=" | "/=" | "//=" | "%=" | "**="\n | ">>=" | "<<=" | "&=" | "^=" | "|="\n\n(See section *Primaries* for the syntax definitions for the last three\nsymbols.)\n\nAn augmented assignment evaluates the target (which, unlike normal\nassignment statements, cannot be an unpacking) and the expression\nlist, performs the binary operation specific to the type of assignment\non the two operands, and assigns the result to the original target.\nThe target is only evaluated once.\n\nAn augmented assignment expression like ``x += 1`` can be rewritten as\n``x = x + 1`` to achieve a similar, but not exactly equal effect. In\nthe augmented version, ``x`` is only evaluated once. Also, when\npossible, the actual operation is performed *in-place*, meaning that\nrather than creating a new object and assigning that to the target,\nthe old object is modified instead.\n\nWith the exception of assigning to tuples and multiple targets in a\nsingle statement, the assignment done by augmented assignment\nstatements is handled the same way as normal assignments. Similarly,\nwith the exception of the possible *in-place* behavior, the binary\noperation performed by augmented assignment is the same as the normal\nbinary operations.\n\nFor targets which are attribute references, the same *caveat about\nclass and instance attributes* applies as for regular assignments.\n',
'binary': '\nBinary arithmetic operations\n****************************\n\nThe binary arithmetic operations have the conventional priority\nlevels. Note that some of these operations also apply to certain non-\nnumeric types. Apart from the power operator, there are only two\nlevels, one for multiplicative operators and one for additive\noperators:\n\n m_expr ::= u_expr | m_expr "*" u_expr | m_expr "//" u_expr | m_expr "/" u_expr\n | m_expr "%" u_expr\n a_expr ::= m_expr | a_expr "+" m_expr | a_expr "-" m_expr\n\nThe ``*`` (multiplication) operator yields the product of its\narguments. The arguments must either both be numbers, or one argument\nmust be an integer and the other must be a sequence. In the former\ncase, the numbers are converted to a common type and then multiplied\ntogether. In the latter case, sequence repetition is performed; a\nnegative repetition factor yields an empty sequence.\n\nThe ``/`` (division) and ``//`` (floor division) operators yield the\nquotient of their arguments. The numeric arguments are first\nconverted to a common type. Integer division yields a float, while\nfloor division of integers results in an integer; the result is that\nof mathematical division with the \'floor\' function applied to the\nresult. Division by zero raises the ``ZeroDivisionError`` exception.\n\nThe ``%`` (modulo) operator yields the remainder from the division of\nthe first argument by the second. The numeric arguments are first\nconverted to a common type. A zero right argument raises the\n``ZeroDivisionError`` exception. The arguments may be floating point\nnumbers, e.g., ``3.14%0.7`` equals ``0.34`` (since ``3.14`` equals\n``4*0.7 + 0.34``.) The modulo operator always yields a result with\nthe same sign as its second operand (or zero); the absolute value of\nthe result is strictly smaller than the absolute value of the second\noperand [1].\n\nThe floor division and modulo operators are connected by the following\nidentity: ``x == (x//y)*y + (x%y)``. Floor division and modulo are\nalso connected with the built-in function ``divmod()``: ``divmod(x, y)\n== (x//y, x%y)``. [2].\n\nIn addition to performing the modulo operation on numbers, the ``%``\noperator is also overloaded by string objects to perform old-style\nstring formatting (also known as interpolation). The syntax for\nstring formatting is described in the Python Library Reference,\nsection *Old String Formatting Operations*.\n\nThe floor division operator, the modulo operator, and the ``divmod()``\nfunction are not defined for complex numbers. Instead, convert to a\nfloating point number using the ``abs()`` function if appropriate.\n\nThe ``+`` (addition) operator yields the sum of its arguments. The\narguments must either both be numbers or both sequences of the same\ntype. In the former case, the numbers are converted to a common type\nand then added together. In the latter case, the sequences are\nconcatenated.\n\nThe ``-`` (subtraction) operator yields the difference of its\narguments. The numeric arguments are first converted to a common\ntype.\n',
'bitwise': '\nBinary bitwise operations\n*************************\n\nEach of the three bitwise operations has a different priority level:\n\n and_expr ::= shift_expr | and_expr "&" shift_expr\n xor_expr ::= and_expr | xor_expr "^" and_expr\n or_expr ::= xor_expr | or_expr "|" xor_expr\n\nThe ``&`` operator yields the bitwise AND of its arguments, which must\nbe integers.\n\nThe ``^`` operator yields the bitwise XOR (exclusive OR) of its\narguments, which must be integers.\n\nThe ``|`` operator yields the bitwise (inclusive) OR of its arguments,\nwhich must be integers.\n',
'bltin-code-objects': '\nCode Objects\n************\n\nCode objects are used by the implementation to represent "pseudo-\ncompiled" executable Python code such as a function body. They differ\nfrom function objects because they don\'t contain a reference to their\nglobal execution environment. Code objects are returned by the built-\nin ``compile()`` function and can be extracted from function objects\nthrough their ``__code__`` attribute. See also the ``code`` module.\n\nA code object can be executed or evaluated by passing it (instead of a\nsource string) to the ``exec()`` or ``eval()`` built-in functions.\n\nSee *The standard type hierarchy* for more information.\n',
- 'bltin-ellipsis-object': '\nThe Ellipsis Object\n*******************\n\nThis object is commonly used by slicing (see *Slicings*). It supports\nno special operations. There is exactly one ellipsis object, named\n``Ellipsis`` (a built-in name).\n\nIt is written as ``Ellipsis`` or ``...``.\n',
- 'bltin-null-object': "\nThe Null Object\n***************\n\nThis object is returned by functions that don't explicitly return a\nvalue. It supports no special operations. There is exactly one null\nobject, named ``None`` (a built-in name).\n\nIt is written as ``None``.\n",
+ 'bltin-ellipsis-object': '\nThe Ellipsis Object\n*******************\n\nThis object is commonly used by slicing (see *Slicings*), but may also\nbe used in other situations where a sentinel value other than ``None``\nis needed. It supports no special operations. There is exactly one\nellipsis object, named ``Ellipsis`` (a built-in name).\n``type(Ellipsis)()`` produces the ``Ellipsis`` singleton.\n\nIt is written as ``Ellipsis`` or ``...``.\n',
+ 'bltin-null-object': "\nThe Null Object\n***************\n\nThis object is returned by functions that don't explicitly return a\nvalue. It supports no special operations. There is exactly one null\nobject, named ``None`` (a built-in name). ``type(None)()`` produces\nthe same singleton.\n\nIt is written as ``None``.\n",
'bltin-type-objects': "\nType Objects\n************\n\nType objects represent the various object types. An object's type is\naccessed by the built-in function ``type()``. There are no special\noperations on types. The standard module ``types`` defines names for\nall standard built-in types.\n\nTypes are written like this: ``<class 'int'>``.\n",
'booleans': '\nBoolean operations\n******************\n\n or_test ::= and_test | or_test "or" and_test\n and_test ::= not_test | and_test "and" not_test\n not_test ::= comparison | "not" not_test\n\nIn the context of Boolean operations, and also when expressions are\nused by control flow statements, the following values are interpreted\nas false: ``False``, ``None``, numeric zero of all types, and empty\nstrings and containers (including strings, tuples, lists,\ndictionaries, sets and frozensets). All other values are interpreted\nas true. User-defined objects can customize their truth value by\nproviding a ``__bool__()`` method.\n\nThe operator ``not`` yields ``True`` if its argument is false,\n``False`` otherwise.\n\nThe expression ``x and y`` first evaluates *x*; if *x* is false, its\nvalue is returned; otherwise, *y* is evaluated and the resulting value\nis returned.\n\nThe expression ``x or y`` first evaluates *x*; if *x* is true, its\nvalue is returned; otherwise, *y* is evaluated and the resulting value\nis returned.\n\n(Note that neither ``and`` nor ``or`` restrict the value and type they\nreturn to ``False`` and ``True``, but rather return the last evaluated\nargument. This is sometimes useful, e.g., if ``s`` is a string that\nshould be replaced by a default value if it is empty, the expression\n``s or \'foo\'`` yields the desired value. Because ``not`` has to\ninvent a value anyway, it does not bother to return a value of the\nsame type as its argument, so e.g., ``not \'foo\'`` yields ``False``,\nnot ``\'\'``.)\n',
'break': '\nThe ``break`` statement\n***********************\n\n break_stmt ::= "break"\n\n``break`` may only occur syntactically nested in a ``for`` or\n``while`` loop, but not nested in a function or class definition\nwithin that loop.\n\nIt terminates the nearest enclosing loop, skipping the optional\n``else`` clause if the loop has one.\n\nIf a ``for`` loop is terminated by ``break``, the loop control target\nkeeps its current value.\n\nWhen ``break`` passes control out of a ``try`` statement with a\n``finally`` clause, that ``finally`` clause is executed before really\nleaving the loop.\n',
'callable-types': '\nEmulating callable objects\n**************************\n\nobject.__call__(self[, args...])\n\n Called when the instance is "called" as a function; if this method\n is defined, ``x(arg1, arg2, ...)`` is a shorthand for\n ``x.__call__(arg1, arg2, ...)``.\n',
- 'calls': '\nCalls\n*****\n\nA call calls a callable object (e.g., a function) with a possibly\nempty series of arguments:\n\n call ::= primary "(" [argument_list [","] | comprehension] ")"\n argument_list ::= positional_arguments ["," keyword_arguments]\n ["," "*" expression] ["," keyword_arguments]\n ["," "**" expression]\n | keyword_arguments ["," "*" expression]\n ["," keyword_arguments] ["," "**" expression]\n | "*" expression ["," keyword_arguments] ["," "**" expression]\n | "**" expression\n positional_arguments ::= expression ("," expression)*\n keyword_arguments ::= keyword_item ("," keyword_item)*\n keyword_item ::= identifier "=" expression\n\nA trailing comma may be present after the positional and keyword\narguments but does not affect the semantics.\n\nThe primary must evaluate to a callable object (user-defined\nfunctions, built-in functions, methods of built-in objects, class\nobjects, methods of class instances, and all objects having a\n``__call__()`` method are callable). All argument expressions are\nevaluated before the call is attempted. Please refer to section\n*Function definitions* for the syntax of formal parameter lists.\n\nIf keyword arguments are present, they are first converted to\npositional arguments, as follows. First, a list of unfilled slots is\ncreated for the formal parameters. If there are N positional\narguments, they are placed in the first N slots. Next, for each\nkeyword argument, the identifier is used to determine the\ncorresponding slot (if the identifier is the same as the first formal\nparameter name, the first slot is used, and so on). If the slot is\nalready filled, a ``TypeError`` exception is raised. Otherwise, the\nvalue of the argument is placed in the slot, filling it (even if the\nexpression is ``None``, it fills the slot). When all arguments have\nbeen processed, the slots that are still unfilled are filled with the\ncorresponding default value from the function definition. (Default\nvalues are calculated, once, when the function is defined; thus, a\nmutable object such as a list or dictionary used as default value will\nbe shared by all calls that don\'t specify an argument value for the\ncorresponding slot; this should usually be avoided.) If there are any\nunfilled slots for which no default value is specified, a\n``TypeError`` exception is raised. Otherwise, the list of filled\nslots is used as the argument list for the call.\n\n**CPython implementation detail:** An implementation may provide\nbuilt-in functions whose positional parameters do not have names, even\nif they are \'named\' for the purpose of documentation, and which\ntherefore cannot be supplied by keyword. In CPython, this is the case\nfor functions implemented in C that use ``PyArg_ParseTuple()`` to\nparse their arguments.\n\nIf there are more positional arguments than there are formal parameter\nslots, a ``TypeError`` exception is raised, unless a formal parameter\nusing the syntax ``*identifier`` is present; in this case, that formal\nparameter receives a tuple containing the excess positional arguments\n(or an empty tuple if there were no excess positional arguments).\n\nIf any keyword argument does not correspond to a formal parameter\nname, a ``TypeError`` exception is raised, unless a formal parameter\nusing the syntax ``**identifier`` is present; in this case, that\nformal parameter receives a dictionary containing the excess keyword\narguments (using the keywords as keys and the argument values as\ncorresponding values), or a (new) empty dictionary if there were no\nexcess keyword arguments.\n\nIf the syntax ``*expression`` appears in the function call,\n``expression`` must evaluate to a sequence. Elements from this\nsequence are treated as if they were additional positional arguments;\nif there are positional arguments *x1*,..., *xN*, and ``expression``\nevaluates to a sequence *y1*, ..., *yM*, this is equivalent to a call\nwith M+N positional arguments *x1*, ..., *xN*, *y1*, ..., *yM*.\n\nA consequence of this is that although the ``*expression`` syntax may\nappear *after* some keyword arguments, it is processed *before* the\nkeyword arguments (and the ``**expression`` argument, if any -- see\nbelow). So:\n\n >>> def f(a, b):\n ... print(a, b)\n ...\n >>> f(b=1, *(2,))\n 2 1\n >>> f(a=1, *(2,))\n Traceback (most recent call last):\n File "<stdin>", line 1, in ?\n TypeError: f() got multiple values for keyword argument \'a\'\n >>> f(1, *(2,))\n 1 2\n\nIt is unusual for both keyword arguments and the ``*expression``\nsyntax to be used in the same call, so in practice this confusion does\nnot arise.\n\nIf the syntax ``**expression`` appears in the function call,\n``expression`` must evaluate to a mapping, the contents of which are\ntreated as additional keyword arguments. In the case of a keyword\nappearing in both ``expression`` and as an explicit keyword argument,\na ``TypeError`` exception is raised.\n\nFormal parameters using the syntax ``*identifier`` or ``**identifier``\ncannot be used as positional argument slots or as keyword argument\nnames.\n\nA call always returns some value, possibly ``None``, unless it raises\nan exception. How this value is computed depends on the type of the\ncallable object.\n\nIf it is---\n\na user-defined function:\n The code block for the function is executed, passing it the\n argument list. The first thing the code block will do is bind the\n formal parameters to the arguments; this is described in section\n *Function definitions*. When the code block executes a ``return``\n statement, this specifies the return value of the function call.\n\na built-in function or method:\n The result is up to the interpreter; see *Built-in Functions* for\n the descriptions of built-in functions and methods.\n\na class object:\n A new instance of that class is returned.\n\na class instance method:\n The corresponding user-defined function is called, with an argument\n list that is one longer than the argument list of the call: the\n instance becomes the first argument.\n\na class instance:\n The class must define a ``__call__()`` method; the effect is then\n the same as if that method was called.\n',
- 'class': '\nClass definitions\n*****************\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= [decorators] "class" classname [inheritance] ":" suite\n inheritance ::= "(" [argument_list [","] | comprehension] ")"\n classname ::= identifier\n\nA class definition is an executable statement. The inheritance list\nusually gives a list of base classes (see *Customizing class creation*\nfor more advanced uses), so each item in the list should evaluate to a\nclass object which allows subclassing. Classes without an inheritance\nlist inherit, by default, from the base class ``object``; hence,\n\n class Foo:\n pass\n\nis equivalent to\n\n class Foo(object):\n pass\n\nThe class\'s suite is then executed in a new execution frame (see\n*Naming and binding*), using a newly created local namespace and the\noriginal global namespace. (Usually, the suite contains mostly\nfunction definitions.) When the class\'s suite finishes execution, its\nexecution frame is discarded but its local namespace is saved. [4] A\nclass object is then created using the inheritance list for the base\nclasses and the saved local namespace for the attribute dictionary.\nThe class name is bound to this class object in the original local\nnamespace.\n\nClass creation can be customized heavily using *metaclasses*.\n\nClasses can also be decorated: just like when decorating functions,\n\n @f1(arg)\n @f2\n class Foo: pass\n\nis equivalent to\n\n class Foo: pass\n Foo = f1(arg)(f2(Foo))\n\nThe evaluation rules for the decorator expressions are the same as for\nfunction decorators. The result must be a class object, which is then\nbound to the class name.\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass attributes; they are shared by instances. Instance attributes\ncan be set in a method with ``self.name = value``. Both class and\ninstance attributes are accessible through the notation\n"``self.name``", and an instance attribute hides a class attribute\nwith the same name when accessed in this way. Class attributes can be\nused as defaults for instance attributes, but using mutable values\nthere can lead to unexpected results. *Descriptors* can be used to\ncreate instance variables with different implementation details.\n\nSee also:\n\n **PEP 3115** - Metaclasses in Python 3 **PEP 3129** - Class\n Decorators\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack only if there\n is no ``finally`` clause that negates the exception.\n\n[2] Currently, control "flows off the end" except in the case of an\n exception or the execution of a ``return``, ``continue``, or\n ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n body is transformed into the function\'s ``__doc__`` attribute and\n therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n body is transformed into the namespace\'s ``__doc__`` item and\n therefore the class\'s *docstring*.\n',
+ 'calls': '\nCalls\n*****\n\nA call calls a callable object (e.g., a function) with a possibly\nempty series of arguments:\n\n call ::= primary "(" [argument_list [","] | comprehension] ")"\n argument_list ::= positional_arguments ["," keyword_arguments]\n ["," "*" expression] ["," keyword_arguments]\n ["," "**" expression]\n | keyword_arguments ["," "*" expression]\n ["," keyword_arguments] ["," "**" expression]\n | "*" expression ["," keyword_arguments] ["," "**" expression]\n | "**" expression\n positional_arguments ::= expression ("," expression)*\n keyword_arguments ::= keyword_item ("," keyword_item)*\n keyword_item ::= identifier "=" expression\n\nA trailing comma may be present after the positional and keyword\narguments but does not affect the semantics.\n\nThe primary must evaluate to a callable object (user-defined\nfunctions, built-in functions, methods of built-in objects, class\nobjects, methods of class instances, and all objects having a\n``__call__()`` method are callable). All argument expressions are\nevaluated before the call is attempted. Please refer to section\n*Function definitions* for the syntax of formal parameter lists.\n\nIf keyword arguments are present, they are first converted to\npositional arguments, as follows. First, a list of unfilled slots is\ncreated for the formal parameters. If there are N positional\narguments, they are placed in the first N slots. Next, for each\nkeyword argument, the identifier is used to determine the\ncorresponding slot (if the identifier is the same as the first formal\nparameter name, the first slot is used, and so on). If the slot is\nalready filled, a ``TypeError`` exception is raised. Otherwise, the\nvalue of the argument is placed in the slot, filling it (even if the\nexpression is ``None``, it fills the slot). When all arguments have\nbeen processed, the slots that are still unfilled are filled with the\ncorresponding default value from the function definition. (Default\nvalues are calculated, once, when the function is defined; thus, a\nmutable object such as a list or dictionary used as default value will\nbe shared by all calls that don\'t specify an argument value for the\ncorresponding slot; this should usually be avoided.) If there are any\nunfilled slots for which no default value is specified, a\n``TypeError`` exception is raised. Otherwise, the list of filled\nslots is used as the argument list for the call.\n\n**CPython implementation detail:** An implementation may provide\nbuilt-in functions whose positional parameters do not have names, even\nif they are \'named\' for the purpose of documentation, and which\ntherefore cannot be supplied by keyword. In CPython, this is the case\nfor functions implemented in C that use ``PyArg_ParseTuple()`` to\nparse their arguments.\n\nIf there are more positional arguments than there are formal parameter\nslots, a ``TypeError`` exception is raised, unless a formal parameter\nusing the syntax ``*identifier`` is present; in this case, that formal\nparameter receives a tuple containing the excess positional arguments\n(or an empty tuple if there were no excess positional arguments).\n\nIf any keyword argument does not correspond to a formal parameter\nname, a ``TypeError`` exception is raised, unless a formal parameter\nusing the syntax ``**identifier`` is present; in this case, that\nformal parameter receives a dictionary containing the excess keyword\narguments (using the keywords as keys and the argument values as\ncorresponding values), or a (new) empty dictionary if there were no\nexcess keyword arguments.\n\nIf the syntax ``*expression`` appears in the function call,\n``expression`` must evaluate to an iterable. Elements from this\niterable are treated as if they were additional positional arguments;\nif there are positional arguments *x1*, ..., *xN*, and ``expression``\nevaluates to a sequence *y1*, ..., *yM*, this is equivalent to a call\nwith M+N positional arguments *x1*, ..., *xN*, *y1*, ..., *yM*.\n\nA consequence of this is that although the ``*expression`` syntax may\nappear *after* some keyword arguments, it is processed *before* the\nkeyword arguments (and the ``**expression`` argument, if any -- see\nbelow). So:\n\n >>> def f(a, b):\n ... print(a, b)\n ...\n >>> f(b=1, *(2,))\n 2 1\n >>> f(a=1, *(2,))\n Traceback (most recent call last):\n File "<stdin>", line 1, in ?\n TypeError: f() got multiple values for keyword argument \'a\'\n >>> f(1, *(2,))\n 1 2\n\nIt is unusual for both keyword arguments and the ``*expression``\nsyntax to be used in the same call, so in practice this confusion does\nnot arise.\n\nIf the syntax ``**expression`` appears in the function call,\n``expression`` must evaluate to a mapping, the contents of which are\ntreated as additional keyword arguments. In the case of a keyword\nappearing in both ``expression`` and as an explicit keyword argument,\na ``TypeError`` exception is raised.\n\nFormal parameters using the syntax ``*identifier`` or ``**identifier``\ncannot be used as positional argument slots or as keyword argument\nnames.\n\nA call always returns some value, possibly ``None``, unless it raises\nan exception. How this value is computed depends on the type of the\ncallable object.\n\nIf it is---\n\na user-defined function:\n The code block for the function is executed, passing it the\n argument list. The first thing the code block will do is bind the\n formal parameters to the arguments; this is described in section\n *Function definitions*. When the code block executes a ``return``\n statement, this specifies the return value of the function call.\n\na built-in function or method:\n The result is up to the interpreter; see *Built-in Functions* for\n the descriptions of built-in functions and methods.\n\na class object:\n A new instance of that class is returned.\n\na class instance method:\n The corresponding user-defined function is called, with an argument\n list that is one longer than the argument list of the call: the\n instance becomes the first argument.\n\na class instance:\n The class must define a ``__call__()`` method; the effect is then\n the same as if that method was called.\n',
+ 'class': '\nClass definitions\n*****************\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= [decorators] "class" classname [inheritance] ":" suite\n inheritance ::= "(" [parameter_list] ")"\n classname ::= identifier\n\nA class definition is an executable statement. The inheritance list\nusually gives a list of base classes (see *Customizing class creation*\nfor more advanced uses), so each item in the list should evaluate to a\nclass object which allows subclassing. Classes without an inheritance\nlist inherit, by default, from the base class ``object``; hence,\n\n class Foo:\n pass\n\nis equivalent to\n\n class Foo(object):\n pass\n\nThe class\'s suite is then executed in a new execution frame (see\n*Naming and binding*), using a newly created local namespace and the\noriginal global namespace. (Usually, the suite contains mostly\nfunction definitions.) When the class\'s suite finishes execution, its\nexecution frame is discarded but its local namespace is saved. [4] A\nclass object is then created using the inheritance list for the base\nclasses and the saved local namespace for the attribute dictionary.\nThe class name is bound to this class object in the original local\nnamespace.\n\nClass creation can be customized heavily using *metaclasses*.\n\nClasses can also be decorated: just like when decorating functions,\n\n @f1(arg)\n @f2\n class Foo: pass\n\nis equivalent to\n\n class Foo: pass\n Foo = f1(arg)(f2(Foo))\n\nThe evaluation rules for the decorator expressions are the same as for\nfunction decorators. The result must be a class object, which is then\nbound to the class name.\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass attributes; they are shared by instances. Instance attributes\ncan be set in a method with ``self.name = value``. Both class and\ninstance attributes are accessible through the notation\n"``self.name``", and an instance attribute hides a class attribute\nwith the same name when accessed in this way. Class attributes can be\nused as defaults for instance attributes, but using mutable values\nthere can lead to unexpected results. *Descriptors* can be used to\ncreate instance variables with different implementation details.\n\nSee also:\n\n **PEP 3115** - Metaclasses in Python 3 **PEP 3129** - Class\n Decorators\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack unless there\n is a ``finally`` clause which happens to raise another exception.\n That new exception causes the old one to be lost.\n\n[2] Currently, control "flows off the end" except in the case of an\n exception or the execution of a ``return``, ``continue``, or\n ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n body is transformed into the function\'s ``__doc__`` attribute and\n therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n body is transformed into the namespace\'s ``__doc__`` item and\n therefore the class\'s *docstring*.\n',
'comparisons': '\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation. Also unlike C, expressions like ``a < b < c`` have the\ninterpretation that is conventional in mathematics:\n\n comparison ::= or_expr ( comp_operator or_expr )*\n comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "!="\n | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: ``True`` or ``False``.\n\nComparisons can be chained arbitrarily, e.g., ``x < y <= z`` is\nequivalent to ``x < y and y <= z``, except that ``y`` is evaluated\nonly once (but in both cases ``z`` is not evaluated at all when ``x <\ny`` is found to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y\nopN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,\nexcept that each expression is evaluated at most once.\n\nNote that ``a op1 b op2 c`` doesn\'t imply any kind of comparison\nbetween *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal\n(though perhaps not pretty).\n\nThe operators ``<``, ``>``, ``==``, ``>=``, ``<=``, and ``!=`` compare\nthe values of two objects. The objects need not have the same type.\nIf both are numbers, they are converted to a common type. Otherwise,\nthe ``==`` and ``!=`` operators *always* consider objects of different\ntypes to be unequal, while the ``<``, ``>``, ``>=`` and ``<=``\noperators raise a ``TypeError`` when comparing objects of different\ntypes that do not implement these operators for the given pair of\ntypes. You can control comparison behavior of objects of non-built-in\ntypes by defining rich comparison methods like ``__gt__()``, described\nin section *Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values ``float(\'NaN\')`` and ``Decimal(\'NaN\')`` are special. The\n are identical to themselves, ``x is x`` but are not equal to\n themselves, ``x != x``. Additionally, comparing any value to a\n not-a-number value will return ``False``. For example, both ``3 <\n float(\'NaN\')`` and ``float(\'NaN\') < 3`` will return ``False``.\n\n* Bytes objects are compared lexicographically using the numeric\n values of their elements.\n\n* Strings are compared lexicographically using the numeric equivalents\n (the result of the built-in function ``ord()``) of their characters.\n [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison of\n corresponding elements. This means that to compare equal, each\n element must compare equal and the two sequences must be of the same\n type and have the same length.\n\n If not equal, the sequences are ordered the same as their first\n differing elements. For example, ``[1,2,x] <= [1,2,y]`` has the\n same value as ``x <= y``. If the corresponding element does not\n exist, the shorter sequence is ordered first (for example, ``[1,2] <\n [1,2,3]``).\n\n* Mappings (dictionaries) compare equal if and only if they have the\n same ``(key, value)`` pairs. Order comparisons ``(\'<\', \'<=\', \'>=\',\n \'>\')`` raise ``TypeError``.\n\n* Sets and frozensets define comparison operators to mean subset and\n superset tests. Those relations do not define total orderings (the\n two sets ``{1,2}`` and {2,3} are not equal, nor subsets of one\n another, nor supersets of one another). Accordingly, sets are not\n appropriate arguments for functions which depend on total ordering.\n For example, ``min()``, ``max()``, and ``sorted()`` produce\n undefined results given a list of sets as inputs.\n\n* Most other objects of built-in types compare unequal unless they are\n the same object; the choice whether one object is considered smaller\n or larger than another one is made arbitrarily but consistently\n within one execution of a program.\n\nComparison of objects of the differing types depends on whether either\nof the types provide explicit support for the comparison. Most\nnumeric types can be compared with one another, but comparisons of\n``float`` and ``Decimal`` are not supported to avoid the inevitable\nconfusion arising from representation issues such as ``float(\'1.1\')``\nbeing inexactly represented and therefore not exactly equal to\n``Decimal(\'1.1\')`` which is. When cross-type comparison is not\nsupported, the comparison method returns ``NotImplemented``. This can\ncreate the illusion of non-transitivity between supported cross-type\ncomparisons and unsupported comparisons. For example, ``Decimal(2) ==\n2`` and ``2 == float(2)`` but ``Decimal(2) != float(2)``.\n\nThe operators ``in`` and ``not in`` test for membership. ``x in s``\nevaluates to true if *x* is a member of *s*, and false otherwise. ``x\nnot in s`` returns the negation of ``x in s``. All built-in sequences\nand set types support this as well as dictionary, for which ``in``\ntests whether a the dictionary has a given key. For container types\nsuch as list, tuple, set, frozenset, dict, or collections.deque, the\nexpression ``x in y`` is equivalent to ``any(x is e or x == e for e in\ny)``.\n\nFor the string and bytes types, ``x in y`` is true if and only if *x*\nis a substring of *y*. An equivalent test is ``y.find(x) != -1``.\nEmpty strings are always considered to be a substring of any other\nstring, so ``"" in "abc"`` will return ``True``.\n\nFor user-defined classes which define the ``__contains__()`` method,\n``x in y`` is true if and only if ``y.__contains__(x)`` is true.\n\nFor user-defined classes which do not define ``__contains__()`` but do\ndefine ``__iter__()``, ``x in y`` is true if some value ``z`` with ``x\n== z`` is produced while iterating over ``y``. If an exception is\nraised during the iteration, it is as if ``in`` raised that exception.\n\nLastly, the old-style iteration protocol is tried: if a class defines\n``__getitem__()``, ``x in y`` is true if and only if there is a non-\nnegative integer index *i* such that ``x == y[i]``, and all lower\ninteger indices do not raise ``IndexError`` exception. (If any other\nexception is raised, it is as if ``in`` raised that exception).\n\nThe operator ``not in`` is defined to have the inverse true value of\n``in``.\n\nThe operators ``is`` and ``is not`` test for object identity: ``x is\ny`` is true if and only if *x* and *y* are the same object. ``x is\nnot y`` yields the inverse truth value. [4]\n',
- 'compound': '\nCompound statements\n*******************\n\nCompound statements contain (groups of) other statements; they affect\nor control the execution of those other statements in some way. In\ngeneral, compound statements span multiple lines, although in simple\nincarnations a whole compound statement may be contained in one line.\n\nThe ``if``, ``while`` and ``for`` statements implement traditional\ncontrol flow constructs. ``try`` specifies exception handlers and/or\ncleanup code for a group of statements, while the ``with`` statement\nallows the execution of initialization and finalization code around a\nblock of code. Function and class definitions are also syntactically\ncompound statements.\n\nCompound statements consist of one or more \'clauses.\' A clause\nconsists of a header and a \'suite.\' The clause headers of a\nparticular compound statement are all at the same indentation level.\nEach clause header begins with a uniquely identifying keyword and ends\nwith a colon. A suite is a group of statements controlled by a\nclause. A suite can be one or more semicolon-separated simple\nstatements on the same line as the header, following the header\'s\ncolon, or it can be one or more indented statements on subsequent\nlines. Only the latter form of suite can contain nested compound\nstatements; the following is illegal, mostly because it wouldn\'t be\nclear to which ``if`` clause a following ``else`` clause would belong:\n\n if test1: if test2: print(x)\n\nAlso note that the semicolon binds tighter than the colon in this\ncontext, so that in the following example, either all or none of the\n``print()`` calls are executed:\n\n if x < y < z: print(x); print(y); print(z)\n\nSummarizing:\n\n compound_stmt ::= if_stmt\n | while_stmt\n | for_stmt\n | try_stmt\n | with_stmt\n | funcdef\n | classdef\n suite ::= stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT\n statement ::= stmt_list NEWLINE | compound_stmt\n stmt_list ::= simple_stmt (";" simple_stmt)* [";"]\n\nNote that statements always end in a ``NEWLINE`` possibly followed by\na ``DEDENT``. Also note that optional continuation clauses always\nbegin with a keyword that cannot start a statement, thus there are no\nambiguities (the \'dangling ``else``\' problem is solved in Python by\nrequiring nested ``if`` statements to be indented).\n\nThe formatting of the grammar rules in the following sections places\neach clause on a separate line for clarity.\n\n\nThe ``if`` statement\n====================\n\nThe ``if`` statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n\n\nThe ``while`` statement\n=======================\n\nThe ``while`` statement is used for repeated execution as long as an\nexpression is true:\n\n while_stmt ::= "while" expression ":" suite\n ["else" ":" suite]\n\nThis repeatedly tests the expression and, if it is true, executes the\nfirst suite; if the expression is false (which may be the first time\nit is tested) the suite of the ``else`` clause, if present, is\nexecuted and the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ngoes back to testing the expression.\n\n\nThe ``for`` statement\n=====================\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" expression_list ":" suite\n ["else" ":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject. An iterator is created for the result of the\n``expression_list``. The suite is then executed once for each item\nprovided by the iterator, in the order of ascending indices. Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments (see *Assignment statements*), and then the suite is\nexecuted. When the items are exhausted (which is immediately when the\nsequence is empty or an iterator raises a ``StopIteration``\nexception), the suite in the ``else`` clause, if present, is executed,\nand the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ncontinues with the next item, or with the ``else`` clause if there was\nno next item.\n\nThe suite may assign to the variable(s) in the target list; this does\nnot affect the next item assigned to it.\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, it will not have been assigned to at all\nby the loop. Hint: the built-in function ``range()`` returns an\niterator of integers suitable to emulate the effect of Pascal\'s ``for\ni := a to b do``; e.g., ``list(range(3))`` returns the list ``[0, 1,\n2]``.\n\nNote: There is a subtlety when the sequence is being modified by the loop\n (this can only occur for mutable sequences, i.e. lists). An\n internal counter is used to keep track of which item is used next,\n and this is incremented on each iteration. When this counter has\n reached the length of the sequence the loop terminates. This means\n that if the suite deletes the current (or a previous) item from the\n sequence, the next item will be skipped (since it gets the index of\n the current item which has already been treated). Likewise, if the\n suite inserts an item in the sequence before the current item, the\n current item will be treated again the next time through the loop.\n This can lead to nasty bugs that can be avoided by making a\n temporary copy using a slice of the whole sequence, e.g.,\n\n for x in a[:]:\n if x < 0: a.remove(x)\n\n\nThe ``try`` statement\n=====================\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n try_stmt ::= try1_stmt | try2_stmt\n try1_stmt ::= "try" ":" suite\n ("except" [expression ["as" target]] ":" suite)+\n ["else" ":" suite]\n ["finally" ":" suite]\n try2_stmt ::= "try" ":" suite\n "finally" ":" suite\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started. This search inspects the except\nclauses in turn until one is found that matches the exception. An\nexpression-less except clause, if present, must be last; it matches\nany exception. For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception. An object is\ncompatible with an exception if it is the class or a base class of the\nexception object or a tuple containing an item compatible with the\nexception.\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified after the ``as`` keyword in that except clause,\nif present, and the except clause\'s suite is executed. All except\nclauses must have an executable block. When the end of this block is\nreached, execution continues normally after the entire try statement.\n(This means that if two nested handlers exist for the same exception,\nand the exception occurs in the try clause of the inner handler, the\nouter handler will not handle the exception.)\n\nWhen an exception has been assigned using ``as target``, it is cleared\nat the end of the except clause. This is as if\n\n except E as N:\n foo\n\nwas translated to\n\n except E as N:\n try:\n foo\n finally:\n del N\n\nThis means the exception must be assigned to a different name to be\nable to refer to it after the except clause. Exceptions are cleared\nbecause with the traceback attached to them, they form a reference\ncycle with the stack frame, keeping all locals in that frame alive\nuntil the next garbage collection occurs.\n\nBefore an except clause\'s suite is executed, details about the\nexception are stored in the ``sys`` module and can be access via\n``sys.exc_info()``. ``sys.exc_info()`` returns a 3-tuple consisting of\nthe exception class, the exception instance and a traceback object\n(see section *The standard type hierarchy*) identifying the point in\nthe program where the exception occurred. ``sys.exc_info()`` values\nare restored to their previous values (before the call) when returning\nfrom a function that handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler. The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses. If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted. If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the saved\nexception is lost. The exception information is not available to the\nprogram during execution of the ``finally`` clause.\n\nWhen a ``return``, ``break`` or ``continue`` statement is executed in\nthe ``try`` suite of a ``try``...``finally`` statement, the\n``finally`` clause is also executed \'on the way out.\' A ``continue``\nstatement is illegal in the ``finally`` clause. (The reason is a\nproblem with the current implementation --- this restriction may be\nlifted in the future).\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n\n\nThe ``with`` statement\n======================\n\nThe ``with`` statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common\n``try``...``except``...``finally`` usage patterns to be encapsulated\nfor convenient reuse.\n\n with_stmt ::= "with" with_item ("," with_item)* ":" suite\n with_item ::= expression ["as" target]\n\nThe execution of the ``with`` statement with one "item" proceeds as\nfollows:\n\n1. The context expression (the expression given in the ``with_item``)\n is evaluated to obtain a context manager.\n\n2. The context manager\'s ``__exit__()`` is loaded for later use.\n\n3. The context manager\'s ``__enter__()`` method is invoked.\n\n4. If a target was included in the ``with`` statement, the return\n value from ``__enter__()`` is assigned to it.\n\n Note: The ``with`` statement guarantees that if the ``__enter__()``\n method returns without an error, then ``__exit__()`` will always\n be called. Thus, if an error occurs during the assignment to the\n target list, it will be treated the same as an error occurring\n within the suite would be. See step 6 below.\n\n5. The suite is executed.\n\n6. The context manager\'s ``__exit__()`` method is invoked. If an\n exception caused the suite to be exited, its type, value, and\n traceback are passed as arguments to ``__exit__()``. Otherwise,\n three ``None`` arguments are supplied.\n\n If the suite was exited due to an exception, and the return value\n from the ``__exit__()`` method was false, the exception is\n reraised. If the return value was true, the exception is\n suppressed, and execution continues with the statement following\n the ``with`` statement.\n\n If the suite was exited for any reason other than an exception, the\n return value from ``__exit__()`` is ignored, and execution proceeds\n at the normal location for the kind of exit that was taken.\n\nWith more than one item, the context managers are processed as if\nmultiple ``with`` statements were nested:\n\n with A() as a, B() as b:\n suite\n\nis equivalent to\n\n with A() as a:\n with B() as b:\n suite\n\nChanged in version 3.1: Support for multiple context expressions.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n\n\nFunction definitions\n====================\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n funcdef ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n ( "*" [parameter] ("," defparameter)*\n [, "**" parameter]\n | "**" parameter\n | defparameter [","] )\n parameter ::= identifier [":" expression]\n defparameter ::= parameter ["=" expression]\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more parameters have the form *parameter* ``=``\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding argument may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted. If a parameter has a default value, all following\nparameters up until the "``*``" must also have a default value ---\nthis is a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.** This means that the expression is evaluated once, when\nthe function is defined, and that that same "pre-computed" value is\nused for each call. This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended. A way around this is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple. If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary. Parameters after "``*``" or "``*identifier``" are\nkeyword-only parameters and may only be passed used keyword arguments.\n\nParameters may have annotations of the form "``: expression``"\nfollowing the parameter name. Any parameter may have an annotation\neven those of the form ``*identifier`` or ``**identifier``. Functions\nmay have "return" annotation of the form "``-> expression``" after the\nparameter list. These annotations can be any valid Python expression\nand are evaluated when the function definition is executed.\nAnnotations may be evaluated in a different order than they appear in\nthe source code. The presence of annotations does not change the\nsemantics of a function. The annotation values are available as\nvalues of a dictionary keyed by the parameters\' names in the\n``__annotations__`` attribute of the function object.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda forms,\ndescribed in section *Lambdas*. Note that the lambda form is merely a\nshorthand for a simplified function definition; a function defined in\na "``def``" statement can be passed around or assigned to another name\njust like a function defined by a lambda form. The "``def``" form is\nactually more powerful since it allows the execution of multiple\nstatements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A "``def``"\nform executed inside a function definition defines a local function\nthat can be returned or passed around. Free variables used in the\nnested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n\n\nClass definitions\n=================\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= [decorators] "class" classname [inheritance] ":" suite\n inheritance ::= "(" [argument_list [","] | comprehension] ")"\n classname ::= identifier\n\nA class definition is an executable statement. The inheritance list\nusually gives a list of base classes (see *Customizing class creation*\nfor more advanced uses), so each item in the list should evaluate to a\nclass object which allows subclassing. Classes without an inheritance\nlist inherit, by default, from the base class ``object``; hence,\n\n class Foo:\n pass\n\nis equivalent to\n\n class Foo(object):\n pass\n\nThe class\'s suite is then executed in a new execution frame (see\n*Naming and binding*), using a newly created local namespace and the\noriginal global namespace. (Usually, the suite contains mostly\nfunction definitions.) When the class\'s suite finishes execution, its\nexecution frame is discarded but its local namespace is saved. [4] A\nclass object is then created using the inheritance list for the base\nclasses and the saved local namespace for the attribute dictionary.\nThe class name is bound to this class object in the original local\nnamespace.\n\nClass creation can be customized heavily using *metaclasses*.\n\nClasses can also be decorated: just like when decorating functions,\n\n @f1(arg)\n @f2\n class Foo: pass\n\nis equivalent to\n\n class Foo: pass\n Foo = f1(arg)(f2(Foo))\n\nThe evaluation rules for the decorator expressions are the same as for\nfunction decorators. The result must be a class object, which is then\nbound to the class name.\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass attributes; they are shared by instances. Instance attributes\ncan be set in a method with ``self.name = value``. Both class and\ninstance attributes are accessible through the notation\n"``self.name``", and an instance attribute hides a class attribute\nwith the same name when accessed in this way. Class attributes can be\nused as defaults for instance attributes, but using mutable values\nthere can lead to unexpected results. *Descriptors* can be used to\ncreate instance variables with different implementation details.\n\nSee also:\n\n **PEP 3115** - Metaclasses in Python 3 **PEP 3129** - Class\n Decorators\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack only if there\n is no ``finally`` clause that negates the exception.\n\n[2] Currently, control "flows off the end" except in the case of an\n exception or the execution of a ``return``, ``continue``, or\n ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n body is transformed into the function\'s ``__doc__`` attribute and\n therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n body is transformed into the namespace\'s ``__doc__`` item and\n therefore the class\'s *docstring*.\n',
+ 'compound': '\nCompound statements\n*******************\n\nCompound statements contain (groups of) other statements; they affect\nor control the execution of those other statements in some way. In\ngeneral, compound statements span multiple lines, although in simple\nincarnations a whole compound statement may be contained in one line.\n\nThe ``if``, ``while`` and ``for`` statements implement traditional\ncontrol flow constructs. ``try`` specifies exception handlers and/or\ncleanup code for a group of statements, while the ``with`` statement\nallows the execution of initialization and finalization code around a\nblock of code. Function and class definitions are also syntactically\ncompound statements.\n\nCompound statements consist of one or more \'clauses.\' A clause\nconsists of a header and a \'suite.\' The clause headers of a\nparticular compound statement are all at the same indentation level.\nEach clause header begins with a uniquely identifying keyword and ends\nwith a colon. A suite is a group of statements controlled by a\nclause. A suite can be one or more semicolon-separated simple\nstatements on the same line as the header, following the header\'s\ncolon, or it can be one or more indented statements on subsequent\nlines. Only the latter form of suite can contain nested compound\nstatements; the following is illegal, mostly because it wouldn\'t be\nclear to which ``if`` clause a following ``else`` clause would belong:\n\n if test1: if test2: print(x)\n\nAlso note that the semicolon binds tighter than the colon in this\ncontext, so that in the following example, either all or none of the\n``print()`` calls are executed:\n\n if x < y < z: print(x); print(y); print(z)\n\nSummarizing:\n\n compound_stmt ::= if_stmt\n | while_stmt\n | for_stmt\n | try_stmt\n | with_stmt\n | funcdef\n | classdef\n suite ::= stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT\n statement ::= stmt_list NEWLINE | compound_stmt\n stmt_list ::= simple_stmt (";" simple_stmt)* [";"]\n\nNote that statements always end in a ``NEWLINE`` possibly followed by\na ``DEDENT``. Also note that optional continuation clauses always\nbegin with a keyword that cannot start a statement, thus there are no\nambiguities (the \'dangling ``else``\' problem is solved in Python by\nrequiring nested ``if`` statements to be indented).\n\nThe formatting of the grammar rules in the following sections places\neach clause on a separate line for clarity.\n\n\nThe ``if`` statement\n====================\n\nThe ``if`` statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n\n\nThe ``while`` statement\n=======================\n\nThe ``while`` statement is used for repeated execution as long as an\nexpression is true:\n\n while_stmt ::= "while" expression ":" suite\n ["else" ":" suite]\n\nThis repeatedly tests the expression and, if it is true, executes the\nfirst suite; if the expression is false (which may be the first time\nit is tested) the suite of the ``else`` clause, if present, is\nexecuted and the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ngoes back to testing the expression.\n\n\nThe ``for`` statement\n=====================\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" expression_list ":" suite\n ["else" ":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject. An iterator is created for the result of the\n``expression_list``. The suite is then executed once for each item\nprovided by the iterator, in the order of ascending indices. Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments (see *Assignment statements*), and then the suite is\nexecuted. When the items are exhausted (which is immediately when the\nsequence is empty or an iterator raises a ``StopIteration``\nexception), the suite in the ``else`` clause, if present, is executed,\nand the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ncontinues with the next item, or with the ``else`` clause if there was\nno next item.\n\nThe suite may assign to the variable(s) in the target list; this does\nnot affect the next item assigned to it.\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, it will not have been assigned to at all\nby the loop. Hint: the built-in function ``range()`` returns an\niterator of integers suitable to emulate the effect of Pascal\'s ``for\ni := a to b do``; e.g., ``list(range(3))`` returns the list ``[0, 1,\n2]``.\n\nNote: There is a subtlety when the sequence is being modified by the loop\n (this can only occur for mutable sequences, i.e. lists). An\n internal counter is used to keep track of which item is used next,\n and this is incremented on each iteration. When this counter has\n reached the length of the sequence the loop terminates. This means\n that if the suite deletes the current (or a previous) item from the\n sequence, the next item will be skipped (since it gets the index of\n the current item which has already been treated). Likewise, if the\n suite inserts an item in the sequence before the current item, the\n current item will be treated again the next time through the loop.\n This can lead to nasty bugs that can be avoided by making a\n temporary copy using a slice of the whole sequence, e.g.,\n\n for x in a[:]:\n if x < 0: a.remove(x)\n\n\nThe ``try`` statement\n=====================\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n try_stmt ::= try1_stmt | try2_stmt\n try1_stmt ::= "try" ":" suite\n ("except" [expression ["as" target]] ":" suite)+\n ["else" ":" suite]\n ["finally" ":" suite]\n try2_stmt ::= "try" ":" suite\n "finally" ":" suite\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started. This search inspects the except\nclauses in turn until one is found that matches the exception. An\nexpression-less except clause, if present, must be last; it matches\nany exception. For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception. An object is\ncompatible with an exception if it is the class or a base class of the\nexception object or a tuple containing an item compatible with the\nexception.\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified after the ``as`` keyword in that except clause,\nif present, and the except clause\'s suite is executed. All except\nclauses must have an executable block. When the end of this block is\nreached, execution continues normally after the entire try statement.\n(This means that if two nested handlers exist for the same exception,\nand the exception occurs in the try clause of the inner handler, the\nouter handler will not handle the exception.)\n\nWhen an exception has been assigned using ``as target``, it is cleared\nat the end of the except clause. This is as if\n\n except E as N:\n foo\n\nwas translated to\n\n except E as N:\n try:\n foo\n finally:\n del N\n\nThis means the exception must be assigned to a different name to be\nable to refer to it after the except clause. Exceptions are cleared\nbecause with the traceback attached to them, they form a reference\ncycle with the stack frame, keeping all locals in that frame alive\nuntil the next garbage collection occurs.\n\nBefore an except clause\'s suite is executed, details about the\nexception are stored in the ``sys`` module and can be access via\n``sys.exc_info()``. ``sys.exc_info()`` returns a 3-tuple consisting of\nthe exception class, the exception instance and a traceback object\n(see section *The standard type hierarchy*) identifying the point in\nthe program where the exception occurred. ``sys.exc_info()`` values\nare restored to their previous values (before the call) when returning\nfrom a function that handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler. The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses. If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted. If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the saved\nexception is set as the context of the new exception. The exception\ninformation is not available to the program during execution of the\n``finally`` clause.\n\nWhen a ``return``, ``break`` or ``continue`` statement is executed in\nthe ``try`` suite of a ``try``...``finally`` statement, the\n``finally`` clause is also executed \'on the way out.\' A ``continue``\nstatement is illegal in the ``finally`` clause. (The reason is a\nproblem with the current implementation --- this restriction may be\nlifted in the future).\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n\n\nThe ``with`` statement\n======================\n\nThe ``with`` statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common\n``try``...``except``...``finally`` usage patterns to be encapsulated\nfor convenient reuse.\n\n with_stmt ::= "with" with_item ("," with_item)* ":" suite\n with_item ::= expression ["as" target]\n\nThe execution of the ``with`` statement with one "item" proceeds as\nfollows:\n\n1. The context expression (the expression given in the ``with_item``)\n is evaluated to obtain a context manager.\n\n2. The context manager\'s ``__exit__()`` is loaded for later use.\n\n3. The context manager\'s ``__enter__()`` method is invoked.\n\n4. If a target was included in the ``with`` statement, the return\n value from ``__enter__()`` is assigned to it.\n\n Note: The ``with`` statement guarantees that if the ``__enter__()``\n method returns without an error, then ``__exit__()`` will always\n be called. Thus, if an error occurs during the assignment to the\n target list, it will be treated the same as an error occurring\n within the suite would be. See step 6 below.\n\n5. The suite is executed.\n\n6. The context manager\'s ``__exit__()`` method is invoked. If an\n exception caused the suite to be exited, its type, value, and\n traceback are passed as arguments to ``__exit__()``. Otherwise,\n three ``None`` arguments are supplied.\n\n If the suite was exited due to an exception, and the return value\n from the ``__exit__()`` method was false, the exception is\n reraised. If the return value was true, the exception is\n suppressed, and execution continues with the statement following\n the ``with`` statement.\n\n If the suite was exited for any reason other than an exception, the\n return value from ``__exit__()`` is ignored, and execution proceeds\n at the normal location for the kind of exit that was taken.\n\nWith more than one item, the context managers are processed as if\nmultiple ``with`` statements were nested:\n\n with A() as a, B() as b:\n suite\n\nis equivalent to\n\n with A() as a:\n with B() as b:\n suite\n\nChanged in version 3.1: Support for multiple context expressions.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n\n\nFunction definitions\n====================\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n funcdef ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [parameter_list [","]] ")"] NEWLINE\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n ( "*" [parameter] ("," defparameter)*\n [, "**" parameter]\n | "**" parameter\n | defparameter [","] )\n parameter ::= identifier [":" expression]\n defparameter ::= parameter ["=" expression]\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more parameters have the form *parameter* ``=``\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding argument may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted. If a parameter has a default value, all following\nparameters up until the "``*``" must also have a default value ---\nthis is a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.** This means that the expression is evaluated once, when\nthe function is defined, and that the same "pre-computed" value is\nused for each call. This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended. A way around this is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple. If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary. Parameters after "``*``" or "``*identifier``" are\nkeyword-only parameters and may only be passed used keyword arguments.\n\nParameters may have annotations of the form "``: expression``"\nfollowing the parameter name. Any parameter may have an annotation\neven those of the form ``*identifier`` or ``**identifier``. Functions\nmay have "return" annotation of the form "``-> expression``" after the\nparameter list. These annotations can be any valid Python expression\nand are evaluated when the function definition is executed.\nAnnotations may be evaluated in a different order than they appear in\nthe source code. The presence of annotations does not change the\nsemantics of a function. The annotation values are available as\nvalues of a dictionary keyed by the parameters\' names in the\n``__annotations__`` attribute of the function object.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda forms,\ndescribed in section *Lambdas*. Note that the lambda form is merely a\nshorthand for a simplified function definition; a function defined in\na "``def``" statement can be passed around or assigned to another name\njust like a function defined by a lambda form. The "``def``" form is\nactually more powerful since it allows the execution of multiple\nstatements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A "``def``"\nform executed inside a function definition defines a local function\nthat can be returned or passed around. Free variables used in the\nnested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n\n\nClass definitions\n=================\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= [decorators] "class" classname [inheritance] ":" suite\n inheritance ::= "(" [parameter_list] ")"\n classname ::= identifier\n\nA class definition is an executable statement. The inheritance list\nusually gives a list of base classes (see *Customizing class creation*\nfor more advanced uses), so each item in the list should evaluate to a\nclass object which allows subclassing. Classes without an inheritance\nlist inherit, by default, from the base class ``object``; hence,\n\n class Foo:\n pass\n\nis equivalent to\n\n class Foo(object):\n pass\n\nThe class\'s suite is then executed in a new execution frame (see\n*Naming and binding*), using a newly created local namespace and the\noriginal global namespace. (Usually, the suite contains mostly\nfunction definitions.) When the class\'s suite finishes execution, its\nexecution frame is discarded but its local namespace is saved. [4] A\nclass object is then created using the inheritance list for the base\nclasses and the saved local namespace for the attribute dictionary.\nThe class name is bound to this class object in the original local\nnamespace.\n\nClass creation can be customized heavily using *metaclasses*.\n\nClasses can also be decorated: just like when decorating functions,\n\n @f1(arg)\n @f2\n class Foo: pass\n\nis equivalent to\n\n class Foo: pass\n Foo = f1(arg)(f2(Foo))\n\nThe evaluation rules for the decorator expressions are the same as for\nfunction decorators. The result must be a class object, which is then\nbound to the class name.\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass attributes; they are shared by instances. Instance attributes\ncan be set in a method with ``self.name = value``. Both class and\ninstance attributes are accessible through the notation\n"``self.name``", and an instance attribute hides a class attribute\nwith the same name when accessed in this way. Class attributes can be\nused as defaults for instance attributes, but using mutable values\nthere can lead to unexpected results. *Descriptors* can be used to\ncreate instance variables with different implementation details.\n\nSee also:\n\n **PEP 3115** - Metaclasses in Python 3 **PEP 3129** - Class\n Decorators\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack unless there\n is a ``finally`` clause which happens to raise another exception.\n That new exception causes the old one to be lost.\n\n[2] Currently, control "flows off the end" except in the case of an\n exception or the execution of a ``return``, ``continue``, or\n ``break`` statement.\n\n[3] A string literal appearing as the first statement in the function\n body is transformed into the function\'s ``__doc__`` attribute and\n therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n body is transformed into the namespace\'s ``__doc__`` item and\n therefore the class\'s *docstring*.\n',
'context-managers': '\nWith Statement Context Managers\n*******************************\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a ``with`` statement. The context\nmanager handles the entry into, and the exit from, the desired runtime\ncontext for the execution of the block of code. Context managers are\nnormally invoked using the ``with`` statement (described in section\n*The with statement*), but can also be used by directly invoking their\nmethods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n Enter the runtime context related to this object. The ``with``\n statement will bind this method\'s return value to the target(s)\n specified in the ``as`` clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n Exit the runtime context related to this object. The parameters\n describe the exception that caused the context to be exited. If the\n context was exited without an exception, all three arguments will\n be ``None``.\n\n If an exception is supplied, and the method wishes to suppress the\n exception (i.e., prevent it from being propagated), it should\n return a true value. Otherwise, the exception will be processed\n normally upon exit from this method.\n\n Note that ``__exit__()`` methods should not reraise the passed-in\n exception; this is the caller\'s responsibility.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n',
'continue': '\nThe ``continue`` statement\n**************************\n\n continue_stmt ::= "continue"\n\n``continue`` may only occur syntactically nested in a ``for`` or\n``while`` loop, but not nested in a function or class definition or\n``finally`` clause within that loop. It continues with the next cycle\nof the nearest enclosing loop.\n\nWhen ``continue`` passes control out of a ``try`` statement with a\n``finally`` clause, that ``finally`` clause is executed before really\nstarting the next loop cycle.\n',
'conversions': '\nArithmetic conversions\n**********************\n\nWhen a description of an arithmetic operator below uses the phrase\n"the numeric arguments are converted to a common type," this means\nthat the operator implementation for built-in types works that way:\n\n* If either argument is a complex number, the other is converted to\n complex;\n\n* otherwise, if either argument is a floating point number, the other\n is converted to floating point;\n\n* otherwise, both must be integers and no conversion is necessary.\n\nSome additional rules apply for certain operators (e.g., a string left\nargument to the \'%\' operator). Extensions must define their own\nconversion behavior.\n',
- 'customization': '\nBasic customization\n*******************\n\nobject.__new__(cls[, ...])\n\n Called to create a new instance of class *cls*. ``__new__()`` is a\n static method (special-cased so you need not declare it as such)\n that takes the class of which an instance was requested as its\n first argument. The remaining arguments are those passed to the\n object constructor expression (the call to the class). The return\n value of ``__new__()`` should be the new object instance (usually\n an instance of *cls*).\n\n Typical implementations create a new instance of the class by\n invoking the superclass\'s ``__new__()`` method using\n ``super(currentclass, cls).__new__(cls[, ...])`` with appropriate\n arguments and then modifying the newly-created instance as\n necessary before returning it.\n\n If ``__new__()`` returns an instance of *cls*, then the new\n instance\'s ``__init__()`` method will be invoked like\n ``__init__(self[, ...])``, where *self* is the new instance and the\n remaining arguments are the same as were passed to ``__new__()``.\n\n If ``__new__()`` does not return an instance of *cls*, then the new\n instance\'s ``__init__()`` method will not be invoked.\n\n ``__new__()`` is intended mainly to allow subclasses of immutable\n types (like int, str, or tuple) to customize instance creation. It\n is also commonly overridden in custom metaclasses in order to\n customize class creation.\n\nobject.__init__(self[, ...])\n\n Called when the instance is created. The arguments are those\n passed to the class constructor expression. If a base class has an\n ``__init__()`` method, the derived class\'s ``__init__()`` method,\n if any, must explicitly call it to ensure proper initialization of\n the base class part of the instance; for example:\n ``BaseClass.__init__(self, [args...])``. As a special constraint\n on constructors, no value may be returned; doing so will cause a\n ``TypeError`` to be raised at runtime.\n\nobject.__del__(self)\n\n Called when the instance is about to be destroyed. This is also\n called a destructor. If a base class has a ``__del__()`` method,\n the derived class\'s ``__del__()`` method, if any, must explicitly\n call it to ensure proper deletion of the base class part of the\n instance. Note that it is possible (though not recommended!) for\n the ``__del__()`` method to postpone destruction of the instance by\n creating a new reference to it. It may then be called at a later\n time when this new reference is deleted. It is not guaranteed that\n ``__del__()`` methods are called for objects that still exist when\n the interpreter exits.\n\n Note: ``del x`` doesn\'t directly call ``x.__del__()`` --- the former\n decrements the reference count for ``x`` by one, and the latter\n is only called when ``x``\'s reference count reaches zero. Some\n common situations that may prevent the reference count of an\n object from going to zero include: circular references between\n objects (e.g., a doubly-linked list or a tree data structure with\n parent and child pointers); a reference to the object on the\n stack frame of a function that caught an exception (the traceback\n stored in ``sys.exc_info()[2]`` keeps the stack frame alive); or\n a reference to the object on the stack frame that raised an\n unhandled exception in interactive mode (the traceback stored in\n ``sys.last_traceback`` keeps the stack frame alive). The first\n situation can only be remedied by explicitly breaking the cycles;\n the latter two situations can be resolved by storing ``None`` in\n ``sys.last_traceback``. Circular references which are garbage are\n detected when the option cycle detector is enabled (it\'s on by\n default), but can only be cleaned up if there are no Python-\n level ``__del__()`` methods involved. Refer to the documentation\n for the ``gc`` module for more information about how\n ``__del__()`` methods are handled by the cycle detector,\n particularly the description of the ``garbage`` value.\n\n Warning: Due to the precarious circumstances under which ``__del__()``\n methods are invoked, exceptions that occur during their execution\n are ignored, and a warning is printed to ``sys.stderr`` instead.\n Also, when ``__del__()`` is invoked in response to a module being\n deleted (e.g., when execution of the program is done), other\n globals referenced by the ``__del__()`` method may already have\n been deleted or in the process of being torn down (e.g. the\n import machinery shutting down). For this reason, ``__del__()``\n methods should do the absolute minimum needed to maintain\n external invariants. Starting with version 1.5, Python\n guarantees that globals whose name begins with a single\n underscore are deleted from their module before other globals are\n deleted; if no other references to such globals exist, this may\n help in assuring that imported modules are still available at the\n time when the ``__del__()`` method is called.\n\nobject.__repr__(self)\n\n Called by the ``repr()`` built-in function to compute the\n "official" string representation of an object. If at all possible,\n this should look like a valid Python expression that could be used\n to recreate an object with the same value (given an appropriate\n environment). If this is not possible, a string of the form\n ``<...some useful description...>`` should be returned. The return\n value must be a string object. If a class defines ``__repr__()``\n but not ``__str__()``, then ``__repr__()`` is also used when an\n "informal" string representation of instances of that class is\n required.\n\n This is typically used for debugging, so it is important that the\n representation is information-rich and unambiguous.\n\nobject.__str__(self)\n\n Called by the ``str()`` built-in function and by the ``print()``\n function to compute the "informal" string representation of an\n object. This differs from ``__repr__()`` in that it does not have\n to be a valid Python expression: a more convenient or concise\n representation may be used instead. The return value must be a\n string object.\n\nobject.__format__(self, format_spec)\n\n Called by the ``format()`` built-in function (and by extension, the\n ``format()`` method of class ``str``) to produce a "formatted"\n string representation of an object. The ``format_spec`` argument is\n a string that contains a description of the formatting options\n desired. The interpretation of the ``format_spec`` argument is up\n to the type implementing ``__format__()``, however most classes\n will either delegate formatting to one of the built-in types, or\n use a similar formatting option syntax.\n\n See *Format Specification Mini-Language* for a description of the\n standard formatting syntax.\n\n The return value must be a string object.\n\nobject.__lt__(self, other)\nobject.__le__(self, other)\nobject.__eq__(self, other)\nobject.__ne__(self, other)\nobject.__gt__(self, other)\nobject.__ge__(self, other)\n\n These are the so-called "rich comparison" methods. The\n correspondence between operator symbols and method names is as\n follows: ``x<y`` calls ``x.__lt__(y)``, ``x<=y`` calls\n ``x.__le__(y)``, ``x==y`` calls ``x.__eq__(y)``, ``x!=y`` calls\n ``x.__ne__(y)``, ``x>y`` calls ``x.__gt__(y)``, and ``x>=y`` calls\n ``x.__ge__(y)``.\n\n A rich comparison method may return the singleton\n ``NotImplemented`` if it does not implement the operation for a\n given pair of arguments. By convention, ``False`` and ``True`` are\n returned for a successful comparison. However, these methods can\n return any value, so if the comparison operator is used in a\n Boolean context (e.g., in the condition of an ``if`` statement),\n Python will call ``bool()`` on the value to determine if the result\n is true or false.\n\n There are no implied relationships among the comparison operators.\n The truth of ``x==y`` does not imply that ``x!=y`` is false.\n Accordingly, when defining ``__eq__()``, one should also define\n ``__ne__()`` so that the operators will behave as expected. See\n the paragraph on ``__hash__()`` for some important notes on\n creating *hashable* objects which support custom comparison\n operations and are usable as dictionary keys.\n\n There are no swapped-argument versions of these methods (to be used\n when the left argument does not support the operation but the right\n argument does); rather, ``__lt__()`` and ``__gt__()`` are each\n other\'s reflection, ``__le__()`` and ``__ge__()`` are each other\'s\n reflection, and ``__eq__()`` and ``__ne__()`` are their own\n reflection.\n\n Arguments to rich comparison methods are never coerced.\n\n To automatically generate ordering operations from a single root\n operation, see ``functools.total_ordering()``.\n\nobject.__hash__(self)\n\n Called by built-in function ``hash()`` and for operations on\n members of hashed collections including ``set``, ``frozenset``, and\n ``dict``. ``__hash__()`` should return an integer. The only\n required property is that objects which compare equal have the same\n hash value; it is advised to somehow mix together (e.g. using\n exclusive or) the hash values for the components of the object that\n also play a part in comparison of objects.\n\n If a class does not define an ``__eq__()`` method it should not\n define a ``__hash__()`` operation either; if it defines\n ``__eq__()`` but not ``__hash__()``, its instances will not be\n usable as items in hashable collections. If a class defines\n mutable objects and implements an ``__eq__()`` method, it should\n not implement ``__hash__()``, since the implementation of hashable\n collections requires that a key\'s hash value is immutable (if the\n object\'s hash value changes, it will be in the wrong hash bucket).\n\n User-defined classes have ``__eq__()`` and ``__hash__()`` methods\n by default; with them, all objects compare unequal (except with\n themselves) and ``x.__hash__()`` returns ``id(x)``.\n\n Classes which inherit a ``__hash__()`` method from a parent class\n but change the meaning of ``__eq__()`` such that the hash value\n returned is no longer appropriate (e.g. by switching to a value-\n based concept of equality instead of the default identity based\n equality) can explicitly flag themselves as being unhashable by\n setting ``__hash__ = None`` in the class definition. Doing so means\n that not only will instances of the class raise an appropriate\n ``TypeError`` when a program attempts to retrieve their hash value,\n but they will also be correctly identified as unhashable when\n checking ``isinstance(obj, collections.Hashable)`` (unlike classes\n which define their own ``__hash__()`` to explicitly raise\n ``TypeError``).\n\n If a class that overrides ``__eq__()`` needs to retain the\n implementation of ``__hash__()`` from a parent class, the\n interpreter must be told this explicitly by setting ``__hash__ =\n <ParentClass>.__hash__``. Otherwise the inheritance of\n ``__hash__()`` will be blocked, just as if ``__hash__`` had been\n explicitly set to ``None``.\n\nobject.__bool__(self)\n\n Called to implement truth value testing and the built-in operation\n ``bool()``; should return ``False`` or ``True``. When this method\n is not defined, ``__len__()`` is called, if it is defined, and the\n object is considered true if its result is nonzero. If a class\n defines neither ``__len__()`` nor ``__bool__()``, all its instances\n are considered true.\n',
+ 'customization': '\nBasic customization\n*******************\n\nobject.__new__(cls[, ...])\n\n Called to create a new instance of class *cls*. ``__new__()`` is a\n static method (special-cased so you need not declare it as such)\n that takes the class of which an instance was requested as its\n first argument. The remaining arguments are those passed to the\n object constructor expression (the call to the class). The return\n value of ``__new__()`` should be the new object instance (usually\n an instance of *cls*).\n\n Typical implementations create a new instance of the class by\n invoking the superclass\'s ``__new__()`` method using\n ``super(currentclass, cls).__new__(cls[, ...])`` with appropriate\n arguments and then modifying the newly-created instance as\n necessary before returning it.\n\n If ``__new__()`` returns an instance of *cls*, then the new\n instance\'s ``__init__()`` method will be invoked like\n ``__init__(self[, ...])``, where *self* is the new instance and the\n remaining arguments are the same as were passed to ``__new__()``.\n\n If ``__new__()`` does not return an instance of *cls*, then the new\n instance\'s ``__init__()`` method will not be invoked.\n\n ``__new__()`` is intended mainly to allow subclasses of immutable\n types (like int, str, or tuple) to customize instance creation. It\n is also commonly overridden in custom metaclasses in order to\n customize class creation.\n\nobject.__init__(self[, ...])\n\n Called when the instance is created. The arguments are those\n passed to the class constructor expression. If a base class has an\n ``__init__()`` method, the derived class\'s ``__init__()`` method,\n if any, must explicitly call it to ensure proper initialization of\n the base class part of the instance; for example:\n ``BaseClass.__init__(self, [args...])``. As a special constraint\n on constructors, no value may be returned; doing so will cause a\n ``TypeError`` to be raised at runtime.\n\nobject.__del__(self)\n\n Called when the instance is about to be destroyed. This is also\n called a destructor. If a base class has a ``__del__()`` method,\n the derived class\'s ``__del__()`` method, if any, must explicitly\n call it to ensure proper deletion of the base class part of the\n instance. Note that it is possible (though not recommended!) for\n the ``__del__()`` method to postpone destruction of the instance by\n creating a new reference to it. It may then be called at a later\n time when this new reference is deleted. It is not guaranteed that\n ``__del__()`` methods are called for objects that still exist when\n the interpreter exits.\n\n Note: ``del x`` doesn\'t directly call ``x.__del__()`` --- the former\n decrements the reference count for ``x`` by one, and the latter\n is only called when ``x``\'s reference count reaches zero. Some\n common situations that may prevent the reference count of an\n object from going to zero include: circular references between\n objects (e.g., a doubly-linked list or a tree data structure with\n parent and child pointers); a reference to the object on the\n stack frame of a function that caught an exception (the traceback\n stored in ``sys.exc_info()[2]`` keeps the stack frame alive); or\n a reference to the object on the stack frame that raised an\n unhandled exception in interactive mode (the traceback stored in\n ``sys.last_traceback`` keeps the stack frame alive). The first\n situation can only be remedied by explicitly breaking the cycles;\n the latter two situations can be resolved by storing ``None`` in\n ``sys.last_traceback``. Circular references which are garbage are\n detected when the option cycle detector is enabled (it\'s on by\n default), but can only be cleaned up if there are no Python-\n level ``__del__()`` methods involved. Refer to the documentation\n for the ``gc`` module for more information about how\n ``__del__()`` methods are handled by the cycle detector,\n particularly the description of the ``garbage`` value.\n\n Warning: Due to the precarious circumstances under which ``__del__()``\n methods are invoked, exceptions that occur during their execution\n are ignored, and a warning is printed to ``sys.stderr`` instead.\n Also, when ``__del__()`` is invoked in response to a module being\n deleted (e.g., when execution of the program is done), other\n globals referenced by the ``__del__()`` method may already have\n been deleted or in the process of being torn down (e.g. the\n import machinery shutting down). For this reason, ``__del__()``\n methods should do the absolute minimum needed to maintain\n external invariants. Starting with version 1.5, Python\n guarantees that globals whose name begins with a single\n underscore are deleted from their module before other globals are\n deleted; if no other references to such globals exist, this may\n help in assuring that imported modules are still available at the\n time when the ``__del__()`` method is called.\n\nobject.__repr__(self)\n\n Called by the ``repr()`` built-in function to compute the\n "official" string representation of an object. If at all possible,\n this should look like a valid Python expression that could be used\n to recreate an object with the same value (given an appropriate\n environment). If this is not possible, a string of the form\n ``<...some useful description...>`` should be returned. The return\n value must be a string object. If a class defines ``__repr__()``\n but not ``__str__()``, then ``__repr__()`` is also used when an\n "informal" string representation of instances of that class is\n required.\n\n This is typically used for debugging, so it is important that the\n representation is information-rich and unambiguous.\n\nobject.__str__(self)\n\n Called by the ``str()`` built-in function and by the ``print()``\n function to compute the "informal" string representation of an\n object. This differs from ``__repr__()`` in that it does not have\n to be a valid Python expression: a more convenient or concise\n representation may be used instead. The return value must be a\n string object.\n\nobject.__bytes__(self)\n\n Called by ``bytes()`` to compute a byte-string representation of an\n object. This should return a ``bytes`` object.\n\nobject.__format__(self, format_spec)\n\n Called by the ``format()`` built-in function (and by extension, the\n ``format()`` method of class ``str``) to produce a "formatted"\n string representation of an object. The ``format_spec`` argument is\n a string that contains a description of the formatting options\n desired. The interpretation of the ``format_spec`` argument is up\n to the type implementing ``__format__()``, however most classes\n will either delegate formatting to one of the built-in types, or\n use a similar formatting option syntax.\n\n See *Format Specification Mini-Language* for a description of the\n standard formatting syntax.\n\n The return value must be a string object.\n\nobject.__lt__(self, other)\nobject.__le__(self, other)\nobject.__eq__(self, other)\nobject.__ne__(self, other)\nobject.__gt__(self, other)\nobject.__ge__(self, other)\n\n These are the so-called "rich comparison" methods. The\n correspondence between operator symbols and method names is as\n follows: ``x<y`` calls ``x.__lt__(y)``, ``x<=y`` calls\n ``x.__le__(y)``, ``x==y`` calls ``x.__eq__(y)``, ``x!=y`` calls\n ``x.__ne__(y)``, ``x>y`` calls ``x.__gt__(y)``, and ``x>=y`` calls\n ``x.__ge__(y)``.\n\n A rich comparison method may return the singleton\n ``NotImplemented`` if it does not implement the operation for a\n given pair of arguments. By convention, ``False`` and ``True`` are\n returned for a successful comparison. However, these methods can\n return any value, so if the comparison operator is used in a\n Boolean context (e.g., in the condition of an ``if`` statement),\n Python will call ``bool()`` on the value to determine if the result\n is true or false.\n\n There are no implied relationships among the comparison operators.\n The truth of ``x==y`` does not imply that ``x!=y`` is false.\n Accordingly, when defining ``__eq__()``, one should also define\n ``__ne__()`` so that the operators will behave as expected. See\n the paragraph on ``__hash__()`` for some important notes on\n creating *hashable* objects which support custom comparison\n operations and are usable as dictionary keys.\n\n There are no swapped-argument versions of these methods (to be used\n when the left argument does not support the operation but the right\n argument does); rather, ``__lt__()`` and ``__gt__()`` are each\n other\'s reflection, ``__le__()`` and ``__ge__()`` are each other\'s\n reflection, and ``__eq__()`` and ``__ne__()`` are their own\n reflection.\n\n Arguments to rich comparison methods are never coerced.\n\n To automatically generate ordering operations from a single root\n operation, see ``functools.total_ordering()``.\n\nobject.__hash__(self)\n\n Called by built-in function ``hash()`` and for operations on\n members of hashed collections including ``set``, ``frozenset``, and\n ``dict``. ``__hash__()`` should return an integer. The only\n required property is that objects which compare equal have the same\n hash value; it is advised to somehow mix together (e.g. using\n exclusive or) the hash values for the components of the object that\n also play a part in comparison of objects.\n\n If a class does not define an ``__eq__()`` method it should not\n define a ``__hash__()`` operation either; if it defines\n ``__eq__()`` but not ``__hash__()``, its instances will not be\n usable as items in hashable collections. If a class defines\n mutable objects and implements an ``__eq__()`` method, it should\n not implement ``__hash__()``, since the implementation of hashable\n collections requires that a key\'s hash value is immutable (if the\n object\'s hash value changes, it will be in the wrong hash bucket).\n\n User-defined classes have ``__eq__()`` and ``__hash__()`` methods\n by default; with them, all objects compare unequal (except with\n themselves) and ``x.__hash__()`` returns ``id(x)``.\n\n Classes which inherit a ``__hash__()`` method from a parent class\n but change the meaning of ``__eq__()`` such that the hash value\n returned is no longer appropriate (e.g. by switching to a value-\n based concept of equality instead of the default identity based\n equality) can explicitly flag themselves as being unhashable by\n setting ``__hash__ = None`` in the class definition. Doing so means\n that not only will instances of the class raise an appropriate\n ``TypeError`` when a program attempts to retrieve their hash value,\n but they will also be correctly identified as unhashable when\n checking ``isinstance(obj, collections.Hashable)`` (unlike classes\n which define their own ``__hash__()`` to explicitly raise\n ``TypeError``).\n\n If a class that overrides ``__eq__()`` needs to retain the\n implementation of ``__hash__()`` from a parent class, the\n interpreter must be told this explicitly by setting ``__hash__ =\n <ParentClass>.__hash__``. Otherwise the inheritance of\n ``__hash__()`` will be blocked, just as if ``__hash__`` had been\n explicitly set to ``None``.\n\n Note: Note by default the ``__hash__()`` values of str, bytes and\n datetime objects are "salted" with an unpredictable random value.\n Although they remain constant within an individual Python\n process, they are not predictable between repeated invocations of\n Python.This is intended to provide protection against a denial-\n of-service caused by carefully-chosen inputs that exploit the\n worst case performance of a dict insertion, O(n^2) complexity.\n See http://www.ocert.org/advisories/ocert-2011-003.html for\n details.Changing hash values affects the order in which keys are\n retrieved from a dict. Note Python has never made guarantees\n about this ordering (and it typically varies between 32-bit and\n 64-bit builds).See also ``PYTHONHASHSEED``.\n\n Changed in version 3.3: Hash randomization is enabled by default.\n\nobject.__bool__(self)\n\n Called to implement truth value testing and the built-in operation\n ``bool()``; should return ``False`` or ``True``. When this method\n is not defined, ``__len__()`` is called, if it is defined, and the\n object is considered true if its result is nonzero. If a class\n defines neither ``__len__()`` nor ``__bool__()``, all its instances\n are considered true.\n',
'debugger': '\n``pdb`` --- The Python Debugger\n*******************************\n\nThe module ``pdb`` defines an interactive source code debugger for\nPython programs. It supports setting (conditional) breakpoints and\nsingle stepping at the source line level, inspection of stack frames,\nsource code listing, and evaluation of arbitrary Python code in the\ncontext of any stack frame. It also supports post-mortem debugging\nand can be called under program control.\n\nThe debugger is extensible -- it is actually defined as the class\n``Pdb``. This is currently undocumented but easily understood by\nreading the source. The extension interface uses the modules ``bdb``\nand ``cmd``.\n\nThe debugger\'s prompt is ``(Pdb)``. Typical usage to run a program\nunder control of the debugger is:\n\n >>> import pdb\n >>> import mymodule\n >>> pdb.run(\'mymodule.test()\')\n > <string>(0)?()\n (Pdb) continue\n > <string>(1)?()\n (Pdb) continue\n NameError: \'spam\'\n > <string>(1)?()\n (Pdb)\n\n``pdb.py`` can also be invoked as a script to debug other scripts.\nFor example:\n\n python3 -m pdb myscript.py\n\nWhen invoked as a script, pdb will automatically enter post-mortem\ndebugging if the program being debugged exits abnormally. After post-\nmortem debugging (or after normal exit of the program), pdb will\nrestart the program. Automatic restarting preserves pdb\'s state (such\nas breakpoints) and in most cases is more useful than quitting the\ndebugger upon program\'s exit.\n\nNew in version 3.2: ``pdb.py`` now accepts a ``-c`` option that\nexecutes commands as if given in a ``.pdbrc`` file, see *Debugger\nCommands*.\n\nThe typical usage to break into the debugger from a running program is\nto insert\n\n import pdb; pdb.set_trace()\n\nat the location you want to break into the debugger. You can then\nstep through the code following this statement, and continue running\nwithout the debugger using the ``continue`` command.\n\nThe typical usage to inspect a crashed program is:\n\n >>> import pdb\n >>> import mymodule\n >>> mymodule.test()\n Traceback (most recent call last):\n File "<stdin>", line 1, in ?\n File "./mymodule.py", line 4, in test\n test2()\n File "./mymodule.py", line 3, in test2\n print(spam)\n NameError: spam\n >>> pdb.pm()\n > ./mymodule.py(3)test2()\n -> print(spam)\n (Pdb)\n\nThe module defines the following functions; each enters the debugger\nin a slightly different way:\n\npdb.run(statement, globals=None, locals=None)\n\n Execute the *statement* (given as a string or a code object) under\n debugger control. The debugger prompt appears before any code is\n executed; you can set breakpoints and type ``continue``, or you can\n step through the statement using ``step`` or ``next`` (all these\n commands are explained below). The optional *globals* and *locals*\n arguments specify the environment in which the code is executed; by\n default the dictionary of the module ``__main__`` is used. (See\n the explanation of the built-in ``exec()`` or ``eval()``\n functions.)\n\npdb.runeval(expression, globals=None, locals=None)\n\n Evaluate the *expression* (given as a string or a code object)\n under debugger control. When ``runeval()`` returns, it returns the\n value of the expression. Otherwise this function is similar to\n ``run()``.\n\npdb.runcall(function, *args, **kwds)\n\n Call the *function* (a function or method object, not a string)\n with the given arguments. When ``runcall()`` returns, it returns\n whatever the function call returned. The debugger prompt appears\n as soon as the function is entered.\n\npdb.set_trace()\n\n Enter the debugger at the calling stack frame. This is useful to\n hard-code a breakpoint at a given point in a program, even if the\n code is not otherwise being debugged (e.g. when an assertion\n fails).\n\npdb.post_mortem(traceback=None)\n\n Enter post-mortem debugging of the given *traceback* object. If no\n *traceback* is given, it uses the one of the exception that is\n currently being handled (an exception must be being handled if the\n default is to be used).\n\npdb.pm()\n\n Enter post-mortem debugging of the traceback found in\n ``sys.last_traceback``.\n\nThe ``run*`` functions and ``set_trace()`` are aliases for\ninstantiating the ``Pdb`` class and calling the method of the same\nname. If you want to access further features, you have to do this\nyourself:\n\nclass class pdb.Pdb(completekey=\'tab\', stdin=None, stdout=None, skip=None, nosigint=False)\n\n ``Pdb`` is the debugger class.\n\n The *completekey*, *stdin* and *stdout* arguments are passed to the\n underlying ``cmd.Cmd`` class; see the description there.\n\n The *skip* argument, if given, must be an iterable of glob-style\n module name patterns. The debugger will not step into frames that\n originate in a module that matches one of these patterns. [1]\n\n By default, Pdb sets a handler for the SIGINT signal (which is sent\n when the user presses Ctrl-C on the console) when you give a\n ``continue`` command. This allows you to break into the debugger\n again by pressing Ctrl-C. If you want Pdb not to touch the SIGINT\n handler, set *nosigint* tot true.\n\n Example call to enable tracing with *skip*:\n\n import pdb; pdb.Pdb(skip=[\'django.*\']).set_trace()\n\n New in version 3.1: The *skip* argument.\n\n New in version 3.2: The *nosigint* argument. Previously, a SIGINT\n handler was never set by Pdb.\n\n run(statement, globals=None, locals=None)\n runeval(expression, globals=None, locals=None)\n runcall(function, *args, **kwds)\n set_trace()\n\n See the documentation for the functions explained above.\n\n\nDebugger Commands\n=================\n\nThe commands recognized by the debugger are listed below. Most\ncommands can be abbreviated to one or two letters as indicated; e.g.\n``h(elp)`` means that either ``h`` or ``help`` can be used to enter\nthe help command (but not ``he`` or ``hel``, nor ``H`` or ``Help`` or\n``HELP``). Arguments to commands must be separated by whitespace\n(spaces or tabs). Optional arguments are enclosed in square brackets\n(``[]``) in the command syntax; the square brackets must not be typed.\nAlternatives in the command syntax are separated by a vertical bar\n(``|``).\n\nEntering a blank line repeats the last command entered. Exception: if\nthe last command was a ``list`` command, the next 11 lines are listed.\n\nCommands that the debugger doesn\'t recognize are assumed to be Python\nstatements and are executed in the context of the program being\ndebugged. Python statements can also be prefixed with an exclamation\npoint (``!``). This is a powerful way to inspect the program being\ndebugged; it is even possible to change a variable or call a function.\nWhen an exception occurs in such a statement, the exception name is\nprinted but the debugger\'s state is not changed.\n\nThe debugger supports *aliases*. Aliases can have parameters which\nallows one a certain level of adaptability to the context under\nexamination.\n\nMultiple commands may be entered on a single line, separated by\n``;;``. (A single ``;`` is not used as it is the separator for\nmultiple commands in a line that is passed to the Python parser.) No\nintelligence is applied to separating the commands; the input is split\nat the first ``;;`` pair, even if it is in the middle of a quoted\nstring.\n\nIf a file ``.pdbrc`` exists in the user\'s home directory or in the\ncurrent directory, it is read in and executed as if it had been typed\nat the debugger prompt. This is particularly useful for aliases. If\nboth files exist, the one in the home directory is read first and\naliases defined there can be overridden by the local file.\n\nChanged in version 3.2: ``.pdbrc`` can now contain commands that\ncontinue debugging, such as ``continue`` or ``next``. Previously,\nthese commands had no effect.\n\nh(elp) [command]\n\n Without argument, print the list of available commands. With a\n *command* as argument, print help about that command. ``help pdb``\n displays the full documentation (the docstring of the ``pdb``\n module). Since the *command* argument must be an identifier,\n ``help exec`` must be entered to get help on the ``!`` command.\n\nw(here)\n\n Print a stack trace, with the most recent frame at the bottom. An\n arrow indicates the current frame, which determines the context of\n most commands.\n\nd(own) [count]\n\n Move the current frame *count* (default one) levels down in the\n stack trace (to a newer frame).\n\nu(p) [count]\n\n Move the current frame *count* (default one) levels up in the stack\n trace (to an older frame).\n\nb(reak) [([filename:]lineno | function) [, condition]]\n\n With a *lineno* argument, set a break there in the current file.\n With a *function* argument, set a break at the first executable\n statement within that function. The line number may be prefixed\n with a filename and a colon, to specify a breakpoint in another\n file (probably one that hasn\'t been loaded yet). The file is\n searched on ``sys.path``. Note that each breakpoint is assigned a\n number to which all the other breakpoint commands refer.\n\n If a second argument is present, it is an expression which must\n evaluate to true before the breakpoint is honored.\n\n Without argument, list all breaks, including for each breakpoint,\n the number of times that breakpoint has been hit, the current\n ignore count, and the associated condition if any.\n\ntbreak [([filename:]lineno | function) [, condition]]\n\n Temporary breakpoint, which is removed automatically when it is\n first hit. The arguments are the same as for ``break``.\n\ncl(ear) [filename:lineno | bpnumber [bpnumber ...]]\n\n With a *filename:lineno* argument, clear all the breakpoints at\n this line. With a space separated list of breakpoint numbers, clear\n those breakpoints. Without argument, clear all breaks (but first\n ask confirmation).\n\ndisable [bpnumber [bpnumber ...]]\n\n Disable the breakpoints given as a space separated list of\n breakpoint numbers. Disabling a breakpoint means it cannot cause\n the program to stop execution, but unlike clearing a breakpoint, it\n remains in the list of breakpoints and can be (re-)enabled.\n\nenable [bpnumber [bpnumber ...]]\n\n Enable the breakpoints specified.\n\nignore bpnumber [count]\n\n Set the ignore count for the given breakpoint number. If count is\n omitted, the ignore count is set to 0. A breakpoint becomes active\n when the ignore count is zero. When non-zero, the count is\n decremented each time the breakpoint is reached and the breakpoint\n is not disabled and any associated condition evaluates to true.\n\ncondition bpnumber [condition]\n\n Set a new *condition* for the breakpoint, an expression which must\n evaluate to true before the breakpoint is honored. If *condition*\n is absent, any existing condition is removed; i.e., the breakpoint\n is made unconditional.\n\ncommands [bpnumber]\n\n Specify a list of commands for breakpoint number *bpnumber*. The\n commands themselves appear on the following lines. Type a line\n containing just ``end`` to terminate the commands. An example:\n\n (Pdb) commands 1\n (com) print some_variable\n (com) end\n (Pdb)\n\n To remove all commands from a breakpoint, type commands and follow\n it immediately with ``end``; that is, give no commands.\n\n With no *bpnumber* argument, commands refers to the last breakpoint\n set.\n\n You can use breakpoint commands to start your program up again.\n Simply use the continue command, or step, or any other command that\n resumes execution.\n\n Specifying any command resuming execution (currently continue,\n step, next, return, jump, quit and their abbreviations) terminates\n the command list (as if that command was immediately followed by\n end). This is because any time you resume execution (even with a\n simple next or step), you may encounter another breakpoint--which\n could have its own command list, leading to ambiguities about which\n list to execute.\n\n If you use the \'silent\' command in the command list, the usual\n message about stopping at a breakpoint is not printed. This may be\n desirable for breakpoints that are to print a specific message and\n then continue. If none of the other commands print anything, you\n see no sign that the breakpoint was reached.\n\ns(tep)\n\n Execute the current line, stop at the first possible occasion\n (either in a function that is called or on the next line in the\n current function).\n\nn(ext)\n\n Continue execution until the next line in the current function is\n reached or it returns. (The difference between ``next`` and\n ``step`` is that ``step`` stops inside a called function, while\n ``next`` executes called functions at (nearly) full speed, only\n stopping at the next line in the current function.)\n\nunt(il) [lineno]\n\n Without argument, continue execution until the line with a number\n greater than the current one is reached.\n\n With a line number, continue execution until a line with a number\n greater or equal to that is reached. In both cases, also stop when\n the current frame returns.\n\n Changed in version 3.2: Allow giving an explicit line number.\n\nr(eturn)\n\n Continue execution until the current function returns.\n\nc(ont(inue))\n\n Continue execution, only stop when a breakpoint is encountered.\n\nj(ump) lineno\n\n Set the next line that will be executed. Only available in the\n bottom-most frame. This lets you jump back and execute code again,\n or jump forward to skip code that you don\'t want to run.\n\n It should be noted that not all jumps are allowed -- for instance\n it is not possible to jump into the middle of a ``for`` loop or out\n of a ``finally`` clause.\n\nl(ist) [first[, last]]\n\n List source code for the current file. Without arguments, list 11\n lines around the current line or continue the previous listing.\n With ``.`` as argument, list 11 lines around the current line.\n With one argument, list 11 lines around at that line. With two\n arguments, list the given range; if the second argument is less\n than the first, it is interpreted as a count.\n\n The current line in the current frame is indicated by ``->``. If\n an exception is being debugged, the line where the exception was\n originally raised or propagated is indicated by ``>>``, if it\n differs from the current line.\n\n New in version 3.2: The ``>>`` marker.\n\nll | longlist\n\n List all source code for the current function or frame.\n Interesting lines are marked as for ``list``.\n\n New in version 3.2.\n\na(rgs)\n\n Print the argument list of the current function.\n\np(rint) expression\n\n Evaluate the *expression* in the current context and print its\n value.\n\npp expression\n\n Like the ``print`` command, except the value of the expression is\n pretty-printed using the ``pprint`` module.\n\nwhatis expression\n\n Print the type of the *expression*.\n\nsource expression\n\n Try to get source code for the given object and display it.\n\n New in version 3.2.\n\ndisplay [expression]\n\n Display the value of the expression if it changed, each time\n execution stops in the current frame.\n\n Without expression, list all display expressions for the current\n frame.\n\n New in version 3.2.\n\nundisplay [expression]\n\n Do not display the expression any more in the current frame.\n Without expression, clear all display expressions for the current\n frame.\n\n New in version 3.2.\n\ninteract\n\n Start an interative interpreter (using the ``code`` module) whose\n global namespace contains all the (global and local) names found in\n the current scope.\n\n New in version 3.2.\n\nalias [name [command]]\n\n Create an alias called *name* that executes *command*. The command\n must *not* be enclosed in quotes. Replaceable parameters can be\n indicated by ``%1``, ``%2``, and so on, while ``%*`` is replaced by\n all the parameters. If no command is given, the current alias for\n *name* is shown. If no arguments are given, all aliases are listed.\n\n Aliases may be nested and can contain anything that can be legally\n typed at the pdb prompt. Note that internal pdb commands *can* be\n overridden by aliases. Such a command is then hidden until the\n alias is removed. Aliasing is recursively applied to the first\n word of the command line; all other words in the line are left\n alone.\n\n As an example, here are two useful aliases (especially when placed\n in the ``.pdbrc`` file):\n\n # Print instance variables (usage "pi classInst")\n alias pi for k in %1.__dict__.keys(): print("%1.",k,"=",%1.__dict__[k])\n # Print instance variables in self\n alias ps pi self\n\nunalias name\n\n Delete the specified alias.\n\n! statement\n\n Execute the (one-line) *statement* in the context of the current\n stack frame. The exclamation point can be omitted unless the first\n word of the statement resembles a debugger command. To set a\n global variable, you can prefix the assignment command with a\n ``global`` statement on the same line, e.g.:\n\n (Pdb) global list_options; list_options = [\'-l\']\n (Pdb)\n\nrun [args ...]\nrestart [args ...]\n\n Restart the debugged Python program. If an argument is supplied,\n it is split with ``shlex`` and the result is used as the new\n ``sys.argv``. History, breakpoints, actions and debugger options\n are preserved. ``restart`` is an alias for ``run``.\n\nq(uit)\n\n Quit from the debugger. The program being executed is aborted.\n\n-[ Footnotes ]-\n\n[1] Whether a frame is considered to originate in a certain module is\n determined by the ``__name__`` in the frame globals.\n',
- 'del': '\nThe ``del`` statement\n*********************\n\n del_stmt ::= "del" target_list\n\nDeletion is recursively defined very similar to the way assignment is\ndefined. Rather that spelling it out in full details, here are some\nhints.\n\nDeletion of a target list recursively deletes each target, from left\nto right.\n\nDeletion of a name removes the binding of that name from the local or\nglobal namespace, depending on whether the name occurs in a ``global``\nstatement in the same code block. If the name is unbound, a\n``NameError`` exception will be raised.\n\nDeletion of attribute references, subscriptions and slicings is passed\nto the primary object involved; deletion of a slicing is in general\nequivalent to assignment of an empty slice of the right type (but even\nthis is determined by the sliced object).\n\nChanged in version 3.2.\n',
+ 'del': '\nThe ``del`` statement\n*********************\n\n del_stmt ::= "del" target_list\n\nDeletion is recursively defined very similar to the way assignment is\ndefined. Rather than spelling it out in full details, here are some\nhints.\n\nDeletion of a target list recursively deletes each target, from left\nto right.\n\nDeletion of a name removes the binding of that name from the local or\nglobal namespace, depending on whether the name occurs in a ``global``\nstatement in the same code block. If the name is unbound, a\n``NameError`` exception will be raised.\n\nDeletion of attribute references, subscriptions and slicings is passed\nto the primary object involved; deletion of a slicing is in general\nequivalent to assignment of an empty slice of the right type (but even\nthis is determined by the sliced object).\n\nChanged in version 3.2.\n',
'dict': '\nDictionary displays\n*******************\n\nA dictionary display is a possibly empty series of key/datum pairs\nenclosed in curly braces:\n\n dict_display ::= "{" [key_datum_list | dict_comprehension] "}"\n key_datum_list ::= key_datum ("," key_datum)* [","]\n key_datum ::= expression ":" expression\n dict_comprehension ::= expression ":" expression comp_for\n\nA dictionary display yields a new dictionary object.\n\nIf a comma-separated sequence of key/datum pairs is given, they are\nevaluated from left to right to define the entries of the dictionary:\neach key object is used as a key into the dictionary to store the\ncorresponding datum. This means that you can specify the same key\nmultiple times in the key/datum list, and the final dictionary\'s value\nfor that key will be the last one given.\n\nA dict comprehension, in contrast to list and set comprehensions,\nneeds two expressions separated with a colon followed by the usual\n"for" and "if" clauses. When the comprehension is run, the resulting\nkey and value elements are inserted in the new dictionary in the order\nthey are produced.\n\nRestrictions on the types of the key values are listed earlier in\nsection *The standard type hierarchy*. (To summarize, the key type\nshould be *hashable*, which excludes all mutable objects.) Clashes\nbetween duplicate keys are not detected; the last datum (textually\nrightmost in the display) stored for a given key value prevails.\n',
'dynamic-features': '\nInteraction with dynamic features\n*********************************\n\nThere are several cases where Python statements are illegal when used\nin conjunction with nested scopes that contain free variables.\n\nIf a variable is referenced in an enclosing scope, it is illegal to\ndelete the name. An error will be reported at compile time.\n\nIf the wild card form of import --- ``import *`` --- is used in a\nfunction and the function contains or is a nested block with free\nvariables, the compiler will raise a ``SyntaxError``.\n\nThe ``eval()`` and ``exec()`` functions do not have access to the full\nenvironment for resolving names. Names may be resolved in the local\nand global namespaces of the caller. Free variables are not resolved\nin the nearest enclosing namespace, but in the global namespace. [1]\nThe ``exec()`` and ``eval()`` functions have optional arguments to\noverride the global and local namespace. If only one namespace is\nspecified, it is used for both.\n',
'else': '\nThe ``if`` statement\n********************\n\nThe ``if`` statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the ``if`` statement is executed or evaluated).\nIf all expressions are false, the suite of the ``else`` clause, if\npresent, is executed.\n',
@@ -33,8 +34,8 @@
'exprlists': '\nExpression lists\n****************\n\n expression_list ::= expression ( "," expression )* [","]\n\nAn expression list containing at least one comma yields a tuple. The\nlength of the tuple is the number of expressions in the list. The\nexpressions are evaluated from left to right.\n\nThe trailing comma is required only to create a single tuple (a.k.a. a\n*singleton*); it is optional in all other cases. A single expression\nwithout a trailing comma doesn\'t create a tuple, but rather yields the\nvalue of that expression. (To create an empty tuple, use an empty pair\nof parentheses: ``()``.)\n',
'floating': '\nFloating point literals\n***********************\n\nFloating point literals are described by the following lexical\ndefinitions:\n\n floatnumber ::= pointfloat | exponentfloat\n pointfloat ::= [intpart] fraction | intpart "."\n exponentfloat ::= (intpart | pointfloat) exponent\n intpart ::= digit+\n fraction ::= "." digit+\n exponent ::= ("e" | "E") ["+" | "-"] digit+\n\nNote that the integer and exponent parts are always interpreted using\nradix 10. For example, ``077e010`` is legal, and denotes the same\nnumber as ``77e10``. The allowed range of floating point literals is\nimplementation-dependent. Some examples of floating point literals:\n\n 3.14 10. .001 1e100 3.14e-10 0e0\n\nNote that numeric literals do not include a sign; a phrase like ``-1``\nis actually an expression composed of the unary operator ``-`` and the\nliteral ``1``.\n',
'for': '\nThe ``for`` statement\n*********************\n\nThe ``for`` statement is used to iterate over the elements of a\nsequence (such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" expression_list ":" suite\n ["else" ":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject. An iterator is created for the result of the\n``expression_list``. The suite is then executed once for each item\nprovided by the iterator, in the order of ascending indices. Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments (see *Assignment statements*), and then the suite is\nexecuted. When the items are exhausted (which is immediately when the\nsequence is empty or an iterator raises a ``StopIteration``\nexception), the suite in the ``else`` clause, if present, is executed,\nand the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ncontinues with the next item, or with the ``else`` clause if there was\nno next item.\n\nThe suite may assign to the variable(s) in the target list; this does\nnot affect the next item assigned to it.\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, it will not have been assigned to at all\nby the loop. Hint: the built-in function ``range()`` returns an\niterator of integers suitable to emulate the effect of Pascal\'s ``for\ni := a to b do``; e.g., ``list(range(3))`` returns the list ``[0, 1,\n2]``.\n\nNote: There is a subtlety when the sequence is being modified by the loop\n (this can only occur for mutable sequences, i.e. lists). An\n internal counter is used to keep track of which item is used next,\n and this is incremented on each iteration. When this counter has\n reached the length of the sequence the loop terminates. This means\n that if the suite deletes the current (or a previous) item from the\n sequence, the next item will be skipped (since it gets the index of\n the current item which has already been treated). Likewise, if the\n suite inserts an item in the sequence before the current item, the\n current item will be treated again the next time through the loop.\n This can lead to nasty bugs that can be avoided by making a\n temporary copy using a slice of the whole sequence, e.g.,\n\n for x in a[:]:\n if x < 0: a.remove(x)\n',
- 'formatstrings': '\nFormat String Syntax\n********************\n\nThe ``str.format()`` method and the ``Formatter`` class share the same\nsyntax for format strings (although in the case of ``Formatter``,\nsubclasses can define their own format string syntax).\n\nFormat strings contain "replacement fields" surrounded by curly braces\n``{}``. Anything that is not contained in braces is considered literal\ntext, which is copied unchanged to the output. If you need to include\na brace character in the literal text, it can be escaped by doubling:\n``{{`` and ``}}``.\n\nThe grammar for a replacement field is as follows:\n\n replacement_field ::= "{" [field_name] ["!" conversion] [":" format_spec] "}"\n field_name ::= arg_name ("." attribute_name | "[" element_index "]")*\n arg_name ::= [identifier | integer]\n attribute_name ::= identifier\n element_index ::= integer | index_string\n index_string ::= <any source character except "]"> +\n conversion ::= "r" | "s" | "a"\n format_spec ::= <described in the next section>\n\nIn less formal terms, the replacement field can start with a\n*field_name* that specifies the object whose value is to be formatted\nand inserted into the output instead of the replacement field. The\n*field_name* is optionally followed by a *conversion* field, which is\npreceded by an exclamation point ``\'!\'``, and a *format_spec*, which\nis preceded by a colon ``\':\'``. These specify a non-default format\nfor the replacement value.\n\nSee also the *Format Specification Mini-Language* section.\n\nThe *field_name* itself begins with an *arg_name* that is either\neither a number or a keyword. If it\'s a number, it refers to a\npositional argument, and if it\'s a keyword, it refers to a named\nkeyword argument. If the numerical arg_names in a format string are\n0, 1, 2, ... in sequence, they can all be omitted (not just some) and\nthe numbers 0, 1, 2, ... will be automatically inserted in that order.\nThe *arg_name* can be followed by any number of index or attribute\nexpressions. An expression of the form ``\'.name\'`` selects the named\nattribute using ``getattr()``, while an expression of the form\n``\'[index]\'`` does an index lookup using ``__getitem__()``.\n\nChanged in version 3.1: The positional argument specifiers can be\nomitted, so ``\'{} {}\'`` is equivalent to ``\'{0} {1}\'``.\n\nSome simple format string examples:\n\n "First, thou shalt count to {0}" # References first positional argument\n "Bring me a {}" # Implicitly references the first positional argument\n "From {} to {}" # Same as "From {0} to {1}"\n "My quest is {name}" # References keyword argument \'name\'\n "Weight in tons {0.weight}" # \'weight\' attribute of first positional arg\n "Units destroyed: {players[0]}" # First element of keyword argument \'players\'.\n\nThe *conversion* field causes a type coercion before formatting.\nNormally, the job of formatting a value is done by the\n``__format__()`` method of the value itself. However, in some cases\nit is desirable to force a type to be formatted as a string,\noverriding its own definition of formatting. By converting the value\nto a string before calling ``__format__()``, the normal formatting\nlogic is bypassed.\n\nThree conversion flags are currently supported: ``\'!s\'`` which calls\n``str()`` on the value, ``\'!r\'`` which calls ``repr()`` and ``\'!a\'``\nwhich calls ``ascii()``.\n\nSome examples:\n\n "Harold\'s a clever {0!s}" # Calls str() on the argument first\n "Bring out the holy {name!r}" # Calls repr() on the argument first\n "More {!a}" # Calls ascii() on the argument first\n\nThe *format_spec* field contains a specification of how the value\nshould be presented, including such details as field width, alignment,\npadding, decimal precision and so on. Each value type can define its\nown "formatting mini-language" or interpretation of the *format_spec*.\n\nMost built-in types support a common formatting mini-language, which\nis described in the next section.\n\nA *format_spec* field can also include nested replacement fields\nwithin it. These nested replacement fields can contain only a field\nname; conversion flags and format specifications are not allowed. The\nreplacement fields within the format_spec are substituted before the\n*format_spec* string is interpreted. This allows the formatting of a\nvalue to be dynamically specified.\n\nSee the *Format examples* section for some examples.\n\n\nFormat Specification Mini-Language\n==================================\n\n"Format specifications" are used within replacement fields contained\nwithin a format string to define how individual values are presented\n(see *Format String Syntax*). They can also be passed directly to the\nbuilt-in ``format()`` function. Each formattable type may define how\nthe format specification is to be interpreted.\n\nMost built-in types implement the following options for format\nspecifications, although some of the formatting options are only\nsupported by the numeric types.\n\nA general convention is that an empty format string (``""``) produces\nthe same result as if you had called ``str()`` on the value. A non-\nempty format string typically modifies the result.\n\nThe general form of a *standard format specifier* is:\n\n format_spec ::= [[fill]align][sign][#][0][width][,][.precision][type]\n fill ::= <a character other than \'}\'>\n align ::= "<" | ">" | "=" | "^"\n sign ::= "+" | "-" | " "\n width ::= integer\n precision ::= integer\n type ::= "b" | "c" | "d" | "e" | "E" | "f" | "F" | "g" | "G" | "n" | "o" | "s" | "x" | "X" | "%"\n\nThe *fill* character can be any character other than \'{\' or \'}\'. The\npresence of a fill character is signaled by the character following\nit, which must be one of the alignment options. If the second\ncharacter of *format_spec* is not a valid alignment option, then it is\nassumed that both the fill character and the alignment option are\nabsent.\n\nThe meaning of the various alignment options is as follows:\n\n +-----------+------------------------------------------------------------+\n | Option | Meaning |\n +===========+============================================================+\n | ``\'<\'`` | Forces the field to be left-aligned within the available |\n | | space (this is the default for most objects). |\n +-----------+------------------------------------------------------------+\n | ``\'>\'`` | Forces the field to be right-aligned within the available |\n | | space (this is the default for numbers). |\n +-----------+------------------------------------------------------------+\n | ``\'=\'`` | Forces the padding to be placed after the sign (if any) |\n | | but before the digits. This is used for printing fields |\n | | in the form \'+000000120\'. This alignment option is only |\n | | valid for numeric types. |\n +-----------+------------------------------------------------------------+\n | ``\'^\'`` | Forces the field to be centered within the available |\n | | space. |\n +-----------+------------------------------------------------------------+\n\nNote that unless a minimum field width is defined, the field width\nwill always be the same size as the data to fill it, so that the\nalignment option has no meaning in this case.\n\nThe *sign* option is only valid for number types, and can be one of\nthe following:\n\n +-----------+------------------------------------------------------------+\n | Option | Meaning |\n +===========+============================================================+\n | ``\'+\'`` | indicates that a sign should be used for both positive as |\n | | well as negative numbers. |\n +-----------+------------------------------------------------------------+\n | ``\'-\'`` | indicates that a sign should be used only for negative |\n | | numbers (this is the default behavior). |\n +-----------+------------------------------------------------------------+\n | space | indicates that a leading space should be used on positive |\n | | numbers, and a minus sign on negative numbers. |\n +-----------+------------------------------------------------------------+\n\nThe ``\'#\'`` option causes the "alternate form" to be used for the\nconversion. The alternate form is defined differently for different\ntypes. This option is only valid for integer, float, complex and\nDecimal types. For integers, when binary, octal, or hexadecimal output\nis used, this option adds the prefix respective ``\'0b\'``, ``\'0o\'``, or\n``\'0x\'`` to the output value. For floats, complex and Decimal the\nalternate form causes the result of the conversion to always contain a\ndecimal-point character, even if no digits follow it. Normally, a\ndecimal-point character appears in the result of these conversions\nonly if a digit follows it. In addition, for ``\'g\'`` and ``\'G\'``\nconversions, trailing zeros are not removed from the result.\n\nThe ``\',\'`` option signals the use of a comma for a thousands\nseparator. For a locale aware separator, use the ``\'n\'`` integer\npresentation type instead.\n\nChanged in version 3.1: Added the ``\',\'`` option (see also **PEP\n378**).\n\n*width* is a decimal integer defining the minimum field width. If not\nspecified, then the field width will be determined by the content.\n\nIf the *width* field is preceded by a zero (``\'0\'``) character, this\nenables zero-padding. This is equivalent to an *alignment* type of\n``\'=\'`` and a *fill* character of ``\'0\'``.\n\nThe *precision* is a decimal number indicating how many digits should\nbe displayed after the decimal point for a floating point value\nformatted with ``\'f\'`` and ``\'F\'``, or before and after the decimal\npoint for a floating point value formatted with ``\'g\'`` or ``\'G\'``.\nFor non-number types the field indicates the maximum field size - in\nother words, how many characters will be used from the field content.\nThe *precision* is not allowed for integer values.\n\nFinally, the *type* determines how the data should be presented.\n\nThe available string presentation types are:\n\n +-----------+------------------------------------------------------------+\n | Type | Meaning |\n +===========+============================================================+\n | ``\'s\'`` | String format. This is the default type for strings and |\n | | may be omitted. |\n +-----------+------------------------------------------------------------+\n | None | The same as ``\'s\'``. |\n +-----------+------------------------------------------------------------+\n\nThe available integer presentation types are:\n\n +-----------+------------------------------------------------------------+\n | Type | Meaning |\n +===========+============================================================+\n | ``\'b\'`` | Binary format. Outputs the number in base 2. |\n +-----------+------------------------------------------------------------+\n | ``\'c\'`` | Character. Converts the integer to the corresponding |\n | | unicode character before printing. |\n +-----------+------------------------------------------------------------+\n | ``\'d\'`` | Decimal Integer. Outputs the number in base 10. |\n +-----------+------------------------------------------------------------+\n | ``\'o\'`` | Octal format. Outputs the number in base 8. |\n +-----------+------------------------------------------------------------+\n | ``\'x\'`` | Hex format. Outputs the number in base 16, using lower- |\n | | case letters for the digits above 9. |\n +-----------+------------------------------------------------------------+\n | ``\'X\'`` | Hex format. Outputs the number in base 16, using upper- |\n | | case letters for the digits above 9. |\n +-----------+------------------------------------------------------------+\n | ``\'n\'`` | Number. This is the same as ``\'d\'``, except that it uses |\n | | the current locale setting to insert the appropriate |\n | | number separator characters. |\n +-----------+------------------------------------------------------------+\n | None | The same as ``\'d\'``. |\n +-----------+------------------------------------------------------------+\n\nIn addition to the above presentation types, integers can be formatted\nwith the floating point presentation types listed below (except\n``\'n\'`` and None). When doing so, ``float()`` is used to convert the\ninteger to a floating point number before formatting.\n\nThe available presentation types for floating point and decimal values\nare:\n\n +-----------+------------------------------------------------------------+\n | Type | Meaning |\n +===========+============================================================+\n | ``\'e\'`` | Exponent notation. Prints the number in scientific |\n | | notation using the letter \'e\' to indicate the exponent. |\n +-----------+------------------------------------------------------------+\n | ``\'E\'`` | Exponent notation. Same as ``\'e\'`` except it uses an upper |\n | | case \'E\' as the separator character. |\n +-----------+------------------------------------------------------------+\n | ``\'f\'`` | Fixed point. Displays the number as a fixed-point number. |\n +-----------+------------------------------------------------------------+\n | ``\'F\'`` | Fixed point. Same as ``\'f\'``, but converts ``nan`` to |\n | | ``NAN`` and ``inf`` to ``INF``. |\n +-----------+------------------------------------------------------------+\n | ``\'g\'`` | General format. For a given precision ``p >= 1``, this |\n | | rounds the number to ``p`` significant digits and then |\n | | formats the result in either fixed-point format or in |\n | | scientific notation, depending on its magnitude. The |\n | | precise rules are as follows: suppose that the result |\n | | formatted with presentation type ``\'e\'`` and precision |\n | | ``p-1`` would have exponent ``exp``. Then if ``-4 <= exp |\n | | < p``, the number is formatted with presentation type |\n | | ``\'f\'`` and precision ``p-1-exp``. Otherwise, the number |\n | | is formatted with presentation type ``\'e\'`` and precision |\n | | ``p-1``. In both cases insignificant trailing zeros are |\n | | removed from the significand, and the decimal point is |\n | | also removed if there are no remaining digits following |\n | | it. Positive and negative infinity, positive and negative |\n | | zero, and nans, are formatted as ``inf``, ``-inf``, ``0``, |\n | | ``-0`` and ``nan`` respectively, regardless of the |\n | | precision. A precision of ``0`` is treated as equivalent |\n | | to a precision of ``1``. |\n +-----------+------------------------------------------------------------+\n | ``\'G\'`` | General format. Same as ``\'g\'`` except switches to ``\'E\'`` |\n | | if the number gets too large. The representations of |\n | | infinity and NaN are uppercased, too. |\n +-----------+------------------------------------------------------------+\n | ``\'n\'`` | Number. This is the same as ``\'g\'``, except that it uses |\n | | the current locale setting to insert the appropriate |\n | | number separator characters. |\n +-----------+------------------------------------------------------------+\n | ``\'%\'`` | Percentage. Multiplies the number by 100 and displays in |\n | | fixed (``\'f\'``) format, followed by a percent sign. |\n +-----------+------------------------------------------------------------+\n | None | Similar to ``\'g\'``, except with at least one digit past |\n | | the decimal point and a default precision of 12. This is |\n | | intended to match ``str()``, except you can add the other |\n | | format modifiers. |\n +-----------+------------------------------------------------------------+\n\n\nFormat examples\n===============\n\nThis section contains examples of the new format syntax and comparison\nwith the old ``%``-formatting.\n\nIn most of the cases the syntax is similar to the old\n``%``-formatting, with the addition of the ``{}`` and with ``:`` used\ninstead of ``%``. For example, ``\'%03.2f\'`` can be translated to\n``\'{:03.2f}\'``.\n\nThe new format syntax also supports new and different options, shown\nin the follow examples.\n\nAccessing arguments by position:\n\n >>> \'{0}, {1}, {2}\'.format(\'a\', \'b\', \'c\')\n \'a, b, c\'\n >>> \'{}, {}, {}\'.format(\'a\', \'b\', \'c\') # 3.1+ only\n \'a, b, c\'\n >>> \'{2}, {1}, {0}\'.format(\'a\', \'b\', \'c\')\n \'c, b, a\'\n >>> \'{2}, {1}, {0}\'.format(*\'abc\') # unpacking argument sequence\n \'c, b, a\'\n >>> \'{0}{1}{0}\'.format(\'abra\', \'cad\') # arguments\' indices can be repeated\n \'abracadabra\'\n\nAccessing arguments by name:\n\n >>> \'Coordinates: {latitude}, {longitude}\'.format(latitude=\'37.24N\', longitude=\'-115.81W\')\n \'Coordinates: 37.24N, -115.81W\'\n >>> coord = {\'latitude\': \'37.24N\', \'longitude\': \'-115.81W\'}\n >>> \'Coordinates: {latitude}, {longitude}\'.format(**coord)\n \'Coordinates: 37.24N, -115.81W\'\n\nAccessing arguments\' attributes:\n\n >>> c = 3-5j\n >>> (\'The complex number {0} is formed from the real part {0.real} \'\n ... \'and the imaginary part {0.imag}.\').format(c)\n \'The complex number (3-5j) is formed from the real part 3.0 and the imaginary part -5.0.\'\n >>> class Point:\n ... def __init__(self, x, y):\n ... self.x, self.y = x, y\n ... def __str__(self):\n ... return \'Point({self.x}, {self.y})\'.format(self=self)\n ...\n >>> str(Point(4, 2))\n \'Point(4, 2)\'\n\nAccessing arguments\' items:\n\n >>> coord = (3, 5)\n >>> \'X: {0[0]}; Y: {0[1]}\'.format(coord)\n \'X: 3; Y: 5\'\n\nReplacing ``%s`` and ``%r``:\n\n >>> "repr() shows quotes: {!r}; str() doesn\'t: {!s}".format(\'test1\', \'test2\')\n "repr() shows quotes: \'test1\'; str() doesn\'t: test2"\n\nAligning the text and specifying a width:\n\n >>> \'{:<30}\'.format(\'left aligned\')\n \'left aligned \'\n >>> \'{:>30}\'.format(\'right aligned\')\n \' right aligned\'\n >>> \'{:^30}\'.format(\'centered\')\n \' centered \'\n >>> \'{:*^30}\'.format(\'centered\') # use \'*\' as a fill char\n \'***********centered***********\'\n\nReplacing ``%+f``, ``%-f``, and ``% f`` and specifying a sign:\n\n >>> \'{:+f}; {:+f}\'.format(3.14, -3.14) # show it always\n \'+3.140000; -3.140000\'\n >>> \'{: f}; {: f}\'.format(3.14, -3.14) # show a space for positive numbers\n \' 3.140000; -3.140000\'\n >>> \'{:-f}; {:-f}\'.format(3.14, -3.14) # show only the minus -- same as \'{:f}; {:f}\'\n \'3.140000; -3.140000\'\n\nReplacing ``%x`` and ``%o`` and converting the value to different\nbases:\n\n >>> # format also supports binary numbers\n >>> "int: {0:d}; hex: {0:x}; oct: {0:o}; bin: {0:b}".format(42)\n \'int: 42; hex: 2a; oct: 52; bin: 101010\'\n >>> # with 0x, 0o, or 0b as prefix:\n >>> "int: {0:d}; hex: {0:#x}; oct: {0:#o}; bin: {0:#b}".format(42)\n \'int: 42; hex: 0x2a; oct: 0o52; bin: 0b101010\'\n\nUsing the comma as a thousands separator:\n\n >>> \'{:,}\'.format(1234567890)\n \'1,234,567,890\'\n\nExpressing a percentage:\n\n >>> points = 19\n >>> total = 22\n >>> \'Correct answers: {:.2%}.\'.format(points/total)\n \'Correct answers: 86.36%\'\n\nUsing type-specific formatting:\n\n >>> import datetime\n >>> d = datetime.datetime(2010, 7, 4, 12, 15, 58)\n >>> \'{:%Y-%m-%d %H:%M:%S}\'.format(d)\n \'2010-07-04 12:15:58\'\n\nNesting arguments and more complex examples:\n\n >>> for align, text in zip(\'<^>\', [\'left\', \'center\', \'right\']):\n ... \'{0:{fill}{align}16}\'.format(text, fill=align, align=align)\n ...\n \'left<<<<<<<<<<<<\'\n \'^^^^^center^^^^^\'\n \'>>>>>>>>>>>right\'\n >>>\n >>> octets = [192, 168, 0, 1]\n >>> \'{:02X}{:02X}{:02X}{:02X}\'.format(*octets)\n \'C0A80001\'\n >>> int(_, 16)\n 3232235521\n >>>\n >>> width = 5\n >>> for num in range(5,12):\n ... for base in \'dXob\':\n ... print(\'{0:{width}{base}}\'.format(num, base=base, width=width), end=\' \')\n ... print()\n ...\n 5 5 5 101\n 6 6 6 110\n 7 7 7 111\n 8 8 10 1000\n 9 9 11 1001\n 10 A 12 1010\n 11 B 13 1011\n',
- 'function': '\nFunction definitions\n********************\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n funcdef ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n ( "*" [parameter] ("," defparameter)*\n [, "**" parameter]\n | "**" parameter\n | defparameter [","] )\n parameter ::= identifier [":" expression]\n defparameter ::= parameter ["=" expression]\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more parameters have the form *parameter* ``=``\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding argument may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted. If a parameter has a default value, all following\nparameters up until the "``*``" must also have a default value ---\nthis is a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.** This means that the expression is evaluated once, when\nthe function is defined, and that that same "pre-computed" value is\nused for each call. This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended. A way around this is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple. If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary. Parameters after "``*``" or "``*identifier``" are\nkeyword-only parameters and may only be passed used keyword arguments.\n\nParameters may have annotations of the form "``: expression``"\nfollowing the parameter name. Any parameter may have an annotation\neven those of the form ``*identifier`` or ``**identifier``. Functions\nmay have "return" annotation of the form "``-> expression``" after the\nparameter list. These annotations can be any valid Python expression\nand are evaluated when the function definition is executed.\nAnnotations may be evaluated in a different order than they appear in\nthe source code. The presence of annotations does not change the\nsemantics of a function. The annotation values are available as\nvalues of a dictionary keyed by the parameters\' names in the\n``__annotations__`` attribute of the function object.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda forms,\ndescribed in section *Lambdas*. Note that the lambda form is merely a\nshorthand for a simplified function definition; a function defined in\na "``def``" statement can be passed around or assigned to another name\njust like a function defined by a lambda form. The "``def``" form is\nactually more powerful since it allows the execution of multiple\nstatements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A "``def``"\nform executed inside a function definition defines a local function\nthat can be returned or passed around. Free variables used in the\nnested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n',
+ 'formatstrings': '\nFormat String Syntax\n********************\n\nThe ``str.format()`` method and the ``Formatter`` class share the same\nsyntax for format strings (although in the case of ``Formatter``,\nsubclasses can define their own format string syntax).\n\nFormat strings contain "replacement fields" surrounded by curly braces\n``{}``. Anything that is not contained in braces is considered literal\ntext, which is copied unchanged to the output. If you need to include\na brace character in the literal text, it can be escaped by doubling:\n``{{`` and ``}}``.\n\nThe grammar for a replacement field is as follows:\n\n replacement_field ::= "{" [field_name] ["!" conversion] [":" format_spec] "}"\n field_name ::= arg_name ("." attribute_name | "[" element_index "]")*\n arg_name ::= [identifier | integer]\n attribute_name ::= identifier\n element_index ::= integer | index_string\n index_string ::= <any source character except "]"> +\n conversion ::= "r" | "s" | "a"\n format_spec ::= <described in the next section>\n\nIn less formal terms, the replacement field can start with a\n*field_name* that specifies the object whose value is to be formatted\nand inserted into the output instead of the replacement field. The\n*field_name* is optionally followed by a *conversion* field, which is\npreceded by an exclamation point ``\'!\'``, and a *format_spec*, which\nis preceded by a colon ``\':\'``. These specify a non-default format\nfor the replacement value.\n\nSee also the *Format Specification Mini-Language* section.\n\nThe *field_name* itself begins with an *arg_name* that is either a\nnumber or a keyword. If it\'s a number, it refers to a positional\nargument, and if it\'s a keyword, it refers to a named keyword\nargument. If the numerical arg_names in a format string are 0, 1, 2,\n... in sequence, they can all be omitted (not just some) and the\nnumbers 0, 1, 2, ... will be automatically inserted in that order.\nBecause *arg_name* is not quote-delimited, it is not possible to\nspecify arbitrary dictionary keys (e.g., the strings ``\'10\'`` or\n``\':-]\'``) within a format string. The *arg_name* can be followed by\nany number of index or attribute expressions. An expression of the\nform ``\'.name\'`` selects the named attribute using ``getattr()``,\nwhile an expression of the form ``\'[index]\'`` does an index lookup\nusing ``__getitem__()``.\n\nChanged in version 3.1: The positional argument specifiers can be\nomitted, so ``\'{} {}\'`` is equivalent to ``\'{0} {1}\'``.\n\nSome simple format string examples:\n\n "First, thou shalt count to {0}" # References first positional argument\n "Bring me a {}" # Implicitly references the first positional argument\n "From {} to {}" # Same as "From {0} to {1}"\n "My quest is {name}" # References keyword argument \'name\'\n "Weight in tons {0.weight}" # \'weight\' attribute of first positional arg\n "Units destroyed: {players[0]}" # First element of keyword argument \'players\'.\n\nThe *conversion* field causes a type coercion before formatting.\nNormally, the job of formatting a value is done by the\n``__format__()`` method of the value itself. However, in some cases\nit is desirable to force a type to be formatted as a string,\noverriding its own definition of formatting. By converting the value\nto a string before calling ``__format__()``, the normal formatting\nlogic is bypassed.\n\nThree conversion flags are currently supported: ``\'!s\'`` which calls\n``str()`` on the value, ``\'!r\'`` which calls ``repr()`` and ``\'!a\'``\nwhich calls ``ascii()``.\n\nSome examples:\n\n "Harold\'s a clever {0!s}" # Calls str() on the argument first\n "Bring out the holy {name!r}" # Calls repr() on the argument first\n "More {!a}" # Calls ascii() on the argument first\n\nThe *format_spec* field contains a specification of how the value\nshould be presented, including such details as field width, alignment,\npadding, decimal precision and so on. Each value type can define its\nown "formatting mini-language" or interpretation of the *format_spec*.\n\nMost built-in types support a common formatting mini-language, which\nis described in the next section.\n\nA *format_spec* field can also include nested replacement fields\nwithin it. These nested replacement fields can contain only a field\nname; conversion flags and format specifications are not allowed. The\nreplacement fields within the format_spec are substituted before the\n*format_spec* string is interpreted. This allows the formatting of a\nvalue to be dynamically specified.\n\nSee the *Format examples* section for some examples.\n\n\nFormat Specification Mini-Language\n==================================\n\n"Format specifications" are used within replacement fields contained\nwithin a format string to define how individual values are presented\n(see *Format String Syntax*). They can also be passed directly to the\nbuilt-in ``format()`` function. Each formattable type may define how\nthe format specification is to be interpreted.\n\nMost built-in types implement the following options for format\nspecifications, although some of the formatting options are only\nsupported by the numeric types.\n\nA general convention is that an empty format string (``""``) produces\nthe same result as if you had called ``str()`` on the value. A non-\nempty format string typically modifies the result.\n\nThe general form of a *standard format specifier* is:\n\n format_spec ::= [[fill]align][sign][#][0][width][,][.precision][type]\n fill ::= <a character other than \'}\'>\n align ::= "<" | ">" | "=" | "^"\n sign ::= "+" | "-" | " "\n width ::= integer\n precision ::= integer\n type ::= "b" | "c" | "d" | "e" | "E" | "f" | "F" | "g" | "G" | "n" | "o" | "s" | "x" | "X" | "%"\n\nThe *fill* character can be any character other than \'{\' or \'}\'. The\npresence of a fill character is signaled by the character following\nit, which must be one of the alignment options. If the second\ncharacter of *format_spec* is not a valid alignment option, then it is\nassumed that both the fill character and the alignment option are\nabsent.\n\nThe meaning of the various alignment options is as follows:\n\n +-----------+------------------------------------------------------------+\n | Option | Meaning |\n +===========+============================================================+\n | ``\'<\'`` | Forces the field to be left-aligned within the available |\n | | space (this is the default for most objects). |\n +-----------+------------------------------------------------------------+\n | ``\'>\'`` | Forces the field to be right-aligned within the available |\n | | space (this is the default for numbers). |\n +-----------+------------------------------------------------------------+\n | ``\'=\'`` | Forces the padding to be placed after the sign (if any) |\n | | but before the digits. This is used for printing fields |\n | | in the form \'+000000120\'. This alignment option is only |\n | | valid for numeric types. |\n +-----------+------------------------------------------------------------+\n | ``\'^\'`` | Forces the field to be centered within the available |\n | | space. |\n +-----------+------------------------------------------------------------+\n\nNote that unless a minimum field width is defined, the field width\nwill always be the same size as the data to fill it, so that the\nalignment option has no meaning in this case.\n\nThe *sign* option is only valid for number types, and can be one of\nthe following:\n\n +-----------+------------------------------------------------------------+\n | Option | Meaning |\n +===========+============================================================+\n | ``\'+\'`` | indicates that a sign should be used for both positive as |\n | | well as negative numbers. |\n +-----------+------------------------------------------------------------+\n | ``\'-\'`` | indicates that a sign should be used only for negative |\n | | numbers (this is the default behavior). |\n +-----------+------------------------------------------------------------+\n | space | indicates that a leading space should be used on positive |\n | | numbers, and a minus sign on negative numbers. |\n +-----------+------------------------------------------------------------+\n\nThe ``\'#\'`` option causes the "alternate form" to be used for the\nconversion. The alternate form is defined differently for different\ntypes. This option is only valid for integer, float, complex and\nDecimal types. For integers, when binary, octal, or hexadecimal output\nis used, this option adds the prefix respective ``\'0b\'``, ``\'0o\'``, or\n``\'0x\'`` to the output value. For floats, complex and Decimal the\nalternate form causes the result of the conversion to always contain a\ndecimal-point character, even if no digits follow it. Normally, a\ndecimal-point character appears in the result of these conversions\nonly if a digit follows it. In addition, for ``\'g\'`` and ``\'G\'``\nconversions, trailing zeros are not removed from the result.\n\nThe ``\',\'`` option signals the use of a comma for a thousands\nseparator. For a locale aware separator, use the ``\'n\'`` integer\npresentation type instead.\n\nChanged in version 3.1: Added the ``\',\'`` option (see also **PEP\n378**).\n\n*width* is a decimal integer defining the minimum field width. If not\nspecified, then the field width will be determined by the content.\n\nIf the *width* field is preceded by a zero (``\'0\'``) character, this\nenables zero-padding. This is equivalent to an *alignment* type of\n``\'=\'`` and a *fill* character of ``\'0\'``.\n\nThe *precision* is a decimal number indicating how many digits should\nbe displayed after the decimal point for a floating point value\nformatted with ``\'f\'`` and ``\'F\'``, or before and after the decimal\npoint for a floating point value formatted with ``\'g\'`` or ``\'G\'``.\nFor non-number types the field indicates the maximum field size - in\nother words, how many characters will be used from the field content.\nThe *precision* is not allowed for integer values.\n\nFinally, the *type* determines how the data should be presented.\n\nThe available string presentation types are:\n\n +-----------+------------------------------------------------------------+\n | Type | Meaning |\n +===========+============================================================+\n | ``\'s\'`` | String format. This is the default type for strings and |\n | | may be omitted. |\n +-----------+------------------------------------------------------------+\n | None | The same as ``\'s\'``. |\n +-----------+------------------------------------------------------------+\n\nThe available integer presentation types are:\n\n +-----------+------------------------------------------------------------+\n | Type | Meaning |\n +===========+============================================================+\n | ``\'b\'`` | Binary format. Outputs the number in base 2. |\n +-----------+------------------------------------------------------------+\n | ``\'c\'`` | Character. Converts the integer to the corresponding |\n | | unicode character before printing. |\n +-----------+------------------------------------------------------------+\n | ``\'d\'`` | Decimal Integer. Outputs the number in base 10. |\n +-----------+------------------------------------------------------------+\n | ``\'o\'`` | Octal format. Outputs the number in base 8. |\n +-----------+------------------------------------------------------------+\n | ``\'x\'`` | Hex format. Outputs the number in base 16, using lower- |\n | | case letters for the digits above 9. |\n +-----------+------------------------------------------------------------+\n | ``\'X\'`` | Hex format. Outputs the number in base 16, using upper- |\n | | case letters for the digits above 9. |\n +-----------+------------------------------------------------------------+\n | ``\'n\'`` | Number. This is the same as ``\'d\'``, except that it uses |\n | | the current locale setting to insert the appropriate |\n | | number separator characters. |\n +-----------+------------------------------------------------------------+\n | None | The same as ``\'d\'``. |\n +-----------+------------------------------------------------------------+\n\nIn addition to the above presentation types, integers can be formatted\nwith the floating point presentation types listed below (except\n``\'n\'`` and None). When doing so, ``float()`` is used to convert the\ninteger to a floating point number before formatting.\n\nThe available presentation types for floating point and decimal values\nare:\n\n +-----------+------------------------------------------------------------+\n | Type | Meaning |\n +===========+============================================================+\n | ``\'e\'`` | Exponent notation. Prints the number in scientific |\n | | notation using the letter \'e\' to indicate the exponent. |\n +-----------+------------------------------------------------------------+\n | ``\'E\'`` | Exponent notation. Same as ``\'e\'`` except it uses an upper |\n | | case \'E\' as the separator character. |\n +-----------+------------------------------------------------------------+\n | ``\'f\'`` | Fixed point. Displays the number as a fixed-point number. |\n +-----------+------------------------------------------------------------+\n | ``\'F\'`` | Fixed point. Same as ``\'f\'``, but converts ``nan`` to |\n | | ``NAN`` and ``inf`` to ``INF``. |\n +-----------+------------------------------------------------------------+\n | ``\'g\'`` | General format. For a given precision ``p >= 1``, this |\n | | rounds the number to ``p`` significant digits and then |\n | | formats the result in either fixed-point format or in |\n | | scientific notation, depending on its magnitude. The |\n | | precise rules are as follows: suppose that the result |\n | | formatted with presentation type ``\'e\'`` and precision |\n | | ``p-1`` would have exponent ``exp``. Then if ``-4 <= exp |\n | | < p``, the number is formatted with presentation type |\n | | ``\'f\'`` and precision ``p-1-exp``. Otherwise, the number |\n | | is formatted with presentation type ``\'e\'`` and precision |\n | | ``p-1``. In both cases insignificant trailing zeros are |\n | | removed from the significand, and the decimal point is |\n | | also removed if there are no remaining digits following |\n | | it. Positive and negative infinity, positive and negative |\n | | zero, and nans, are formatted as ``inf``, ``-inf``, ``0``, |\n | | ``-0`` and ``nan`` respectively, regardless of the |\n | | precision. A precision of ``0`` is treated as equivalent |\n | | to a precision of ``1``. |\n +-----------+------------------------------------------------------------+\n | ``\'G\'`` | General format. Same as ``\'g\'`` except switches to ``\'E\'`` |\n | | if the number gets too large. The representations of |\n | | infinity and NaN are uppercased, too. |\n +-----------+------------------------------------------------------------+\n | ``\'n\'`` | Number. This is the same as ``\'g\'``, except that it uses |\n | | the current locale setting to insert the appropriate |\n | | number separator characters. |\n +-----------+------------------------------------------------------------+\n | ``\'%\'`` | Percentage. Multiplies the number by 100 and displays in |\n | | fixed (``\'f\'``) format, followed by a percent sign. |\n +-----------+------------------------------------------------------------+\n | None | Similar to ``\'g\'``, except with at least one digit past |\n | | the decimal point and a default precision of 12. This is |\n | | intended to match ``str()``, except you can add the other |\n | | format modifiers. |\n +-----------+------------------------------------------------------------+\n\n\nFormat examples\n===============\n\nThis section contains examples of the new format syntax and comparison\nwith the old ``%``-formatting.\n\nIn most of the cases the syntax is similar to the old\n``%``-formatting, with the addition of the ``{}`` and with ``:`` used\ninstead of ``%``. For example, ``\'%03.2f\'`` can be translated to\n``\'{:03.2f}\'``.\n\nThe new format syntax also supports new and different options, shown\nin the follow examples.\n\nAccessing arguments by position:\n\n >>> \'{0}, {1}, {2}\'.format(\'a\', \'b\', \'c\')\n \'a, b, c\'\n >>> \'{}, {}, {}\'.format(\'a\', \'b\', \'c\') # 3.1+ only\n \'a, b, c\'\n >>> \'{2}, {1}, {0}\'.format(\'a\', \'b\', \'c\')\n \'c, b, a\'\n >>> \'{2}, {1}, {0}\'.format(*\'abc\') # unpacking argument sequence\n \'c, b, a\'\n >>> \'{0}{1}{0}\'.format(\'abra\', \'cad\') # arguments\' indices can be repeated\n \'abracadabra\'\n\nAccessing arguments by name:\n\n >>> \'Coordinates: {latitude}, {longitude}\'.format(latitude=\'37.24N\', longitude=\'-115.81W\')\n \'Coordinates: 37.24N, -115.81W\'\n >>> coord = {\'latitude\': \'37.24N\', \'longitude\': \'-115.81W\'}\n >>> \'Coordinates: {latitude}, {longitude}\'.format(**coord)\n \'Coordinates: 37.24N, -115.81W\'\n\nAccessing arguments\' attributes:\n\n >>> c = 3-5j\n >>> (\'The complex number {0} is formed from the real part {0.real} \'\n ... \'and the imaginary part {0.imag}.\').format(c)\n \'The complex number (3-5j) is formed from the real part 3.0 and the imaginary part -5.0.\'\n >>> class Point:\n ... def __init__(self, x, y):\n ... self.x, self.y = x, y\n ... def __str__(self):\n ... return \'Point({self.x}, {self.y})\'.format(self=self)\n ...\n >>> str(Point(4, 2))\n \'Point(4, 2)\'\n\nAccessing arguments\' items:\n\n >>> coord = (3, 5)\n >>> \'X: {0[0]}; Y: {0[1]}\'.format(coord)\n \'X: 3; Y: 5\'\n\nReplacing ``%s`` and ``%r``:\n\n >>> "repr() shows quotes: {!r}; str() doesn\'t: {!s}".format(\'test1\', \'test2\')\n "repr() shows quotes: \'test1\'; str() doesn\'t: test2"\n\nAligning the text and specifying a width:\n\n >>> \'{:<30}\'.format(\'left aligned\')\n \'left aligned \'\n >>> \'{:>30}\'.format(\'right aligned\')\n \' right aligned\'\n >>> \'{:^30}\'.format(\'centered\')\n \' centered \'\n >>> \'{:*^30}\'.format(\'centered\') # use \'*\' as a fill char\n \'***********centered***********\'\n\nReplacing ``%+f``, ``%-f``, and ``% f`` and specifying a sign:\n\n >>> \'{:+f}; {:+f}\'.format(3.14, -3.14) # show it always\n \'+3.140000; -3.140000\'\n >>> \'{: f}; {: f}\'.format(3.14, -3.14) # show a space for positive numbers\n \' 3.140000; -3.140000\'\n >>> \'{:-f}; {:-f}\'.format(3.14, -3.14) # show only the minus -- same as \'{:f}; {:f}\'\n \'3.140000; -3.140000\'\n\nReplacing ``%x`` and ``%o`` and converting the value to different\nbases:\n\n >>> # format also supports binary numbers\n >>> "int: {0:d}; hex: {0:x}; oct: {0:o}; bin: {0:b}".format(42)\n \'int: 42; hex: 2a; oct: 52; bin: 101010\'\n >>> # with 0x, 0o, or 0b as prefix:\n >>> "int: {0:d}; hex: {0:#x}; oct: {0:#o}; bin: {0:#b}".format(42)\n \'int: 42; hex: 0x2a; oct: 0o52; bin: 0b101010\'\n\nUsing the comma as a thousands separator:\n\n >>> \'{:,}\'.format(1234567890)\n \'1,234,567,890\'\n\nExpressing a percentage:\n\n >>> points = 19\n >>> total = 22\n >>> \'Correct answers: {:.2%}\'.format(points/total)\n \'Correct answers: 86.36%\'\n\nUsing type-specific formatting:\n\n >>> import datetime\n >>> d = datetime.datetime(2010, 7, 4, 12, 15, 58)\n >>> \'{:%Y-%m-%d %H:%M:%S}\'.format(d)\n \'2010-07-04 12:15:58\'\n\nNesting arguments and more complex examples:\n\n >>> for align, text in zip(\'<^>\', [\'left\', \'center\', \'right\']):\n ... \'{0:{fill}{align}16}\'.format(text, fill=align, align=align)\n ...\n \'left<<<<<<<<<<<<\'\n \'^^^^^center^^^^^\'\n \'>>>>>>>>>>>right\'\n >>>\n >>> octets = [192, 168, 0, 1]\n >>> \'{:02X}{:02X}{:02X}{:02X}\'.format(*octets)\n \'C0A80001\'\n >>> int(_, 16)\n 3232235521\n >>>\n >>> width = 5\n >>> for num in range(5,12):\n ... for base in \'dXob\':\n ... print(\'{0:{width}{base}}\'.format(num, base=base, width=width), end=\' \')\n ... print()\n ...\n 5 5 5 101\n 6 6 6 110\n 7 7 7 111\n 8 8 10 1000\n 9 9 11 1001\n 10 A 12 1010\n 11 B 13 1011\n',
+ 'function': '\nFunction definitions\n********************\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n funcdef ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [parameter_list [","]] ")"] NEWLINE\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n ( "*" [parameter] ("," defparameter)*\n [, "**" parameter]\n | "**" parameter\n | defparameter [","] )\n parameter ::= identifier [":" expression]\n defparameter ::= parameter ["=" expression]\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more parameters have the form *parameter* ``=``\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding argument may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted. If a parameter has a default value, all following\nparameters up until the "``*``" must also have a default value ---\nthis is a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.** This means that the expression is evaluated once, when\nthe function is defined, and that the same "pre-computed" value is\nused for each call. This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended. A way around this is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple. If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary. Parameters after "``*``" or "``*identifier``" are\nkeyword-only parameters and may only be passed used keyword arguments.\n\nParameters may have annotations of the form "``: expression``"\nfollowing the parameter name. Any parameter may have an annotation\neven those of the form ``*identifier`` or ``**identifier``. Functions\nmay have "return" annotation of the form "``-> expression``" after the\nparameter list. These annotations can be any valid Python expression\nand are evaluated when the function definition is executed.\nAnnotations may be evaluated in a different order than they appear in\nthe source code. The presence of annotations does not change the\nsemantics of a function. The annotation values are available as\nvalues of a dictionary keyed by the parameters\' names in the\n``__annotations__`` attribute of the function object.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda forms,\ndescribed in section *Lambdas*. Note that the lambda form is merely a\nshorthand for a simplified function definition; a function defined in\na "``def``" statement can be passed around or assigned to another name\njust like a function defined by a lambda form. The "``def``" form is\nactually more powerful since it allows the execution of multiple\nstatements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A "``def``"\nform executed inside a function definition defines a local function\nthat can be returned or passed around. Free variables used in the\nnested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n',
'global': '\nThe ``global`` statement\n************************\n\n global_stmt ::= "global" identifier ("," identifier)*\n\nThe ``global`` statement is a declaration which holds for the entire\ncurrent code block. It means that the listed identifiers are to be\ninterpreted as globals. It would be impossible to assign to a global\nvariable without ``global``, although free variables may refer to\nglobals without being declared global.\n\nNames listed in a ``global`` statement must not be used in the same\ncode block textually preceding that ``global`` statement.\n\nNames listed in a ``global`` statement must not be defined as formal\nparameters or in a ``for`` loop control target, ``class`` definition,\nfunction definition, or ``import`` statement.\n\n**CPython implementation detail:** The current implementation does not\nenforce the latter two restrictions, but programs should not abuse\nthis freedom, as future implementations may enforce them or silently\nchange the meaning of the program.\n\n**Programmer\'s note:** the ``global`` is a directive to the parser.\nIt applies only to code parsed at the same time as the ``global``\nstatement. In particular, a ``global`` statement contained in a string\nor code object supplied to the built-in ``exec()`` function does not\naffect the code block *containing* the function call, and code\ncontained in such a string is unaffected by ``global`` statements in\nthe code containing the function call. The same applies to the\n``eval()`` and ``compile()`` functions.\n',
'id-classes': '\nReserved classes of identifiers\n*******************************\n\nCertain classes of identifiers (besides keywords) have special\nmeanings. These classes are identified by the patterns of leading and\ntrailing underscore characters:\n\n``_*``\n Not imported by ``from module import *``. The special identifier\n ``_`` is used in the interactive interpreter to store the result of\n the last evaluation; it is stored in the ``builtins`` module. When\n not in interactive mode, ``_`` has no special meaning and is not\n defined. See section *The import statement*.\n\n Note: The name ``_`` is often used in conjunction with\n internationalization; refer to the documentation for the\n ``gettext`` module for more information on this convention.\n\n``__*__``\n System-defined names. These names are defined by the interpreter\n and its implementation (including the standard library). Current\n system names are discussed in the *Special method names* section\n and elsewhere. More will likely be defined in future versions of\n Python. *Any* use of ``__*__`` names, in any context, that does\n not follow explicitly documented use, is subject to breakage\n without warning.\n\n``__*``\n Class-private names. Names in this category, when used within the\n context of a class definition, are re-written to use a mangled form\n to help avoid name clashes between "private" attributes of base and\n derived classes. See section *Identifiers (Names)*.\n',
'identifiers': '\nIdentifiers and keywords\n************************\n\nIdentifiers (also referred to as *names*) are described by the\nfollowing lexical definitions.\n\nThe syntax of identifiers in Python is based on the Unicode standard\nannex UAX-31, with elaboration and changes as defined below; see also\n**PEP 3131** for further details.\n\nWithin the ASCII range (U+0001..U+007F), the valid characters for\nidentifiers are the same as in Python 2.x: the uppercase and lowercase\nletters ``A`` through ``Z``, the underscore ``_`` and, except for the\nfirst character, the digits ``0`` through ``9``.\n\nPython 3.0 introduces additional characters from outside the ASCII\nrange (see **PEP 3131**). For these characters, the classification\nuses the version of the Unicode Character Database as included in the\n``unicodedata`` module.\n\nIdentifiers are unlimited in length. Case is significant.\n\n identifier ::= xid_start xid_continue*\n id_start ::= <all characters in general categories Lu, Ll, Lt, Lm, Lo, Nl, the underscore, and characters with the Other_ID_Start property>\n id_continue ::= <all characters in id_start, plus characters in the categories Mn, Mc, Nd, Pc and others with the Other_ID_Continue property>\n xid_start ::= <all characters in id_start whose NFKC normalization is in "id_start xid_continue*">\n xid_continue ::= <all characters in id_continue whose NFKC normalization is in "id_continue*">\n\nThe Unicode category codes mentioned above stand for:\n\n* *Lu* - uppercase letters\n\n* *Ll* - lowercase letters\n\n* *Lt* - titlecase letters\n\n* *Lm* - modifier letters\n\n* *Lo* - other letters\n\n* *Nl* - letter numbers\n\n* *Mn* - nonspacing marks\n\n* *Mc* - spacing combining marks\n\n* *Nd* - decimal numbers\n\n* *Pc* - connector punctuations\n\n* *Other_ID_Start* - explicit list of characters in PropList.txt to\n support backwards compatibility\n\n* *Other_ID_Continue* - likewise\n\nAll identifiers are converted into the normal form NFKC while parsing;\ncomparison of identifiers is based on NFKC.\n\nA non-normative HTML file listing all valid identifier characters for\nUnicode 4.1 can be found at http://www.dcl.hpi.uni-\npotsdam.de/home/loewis/table-3131.html.\n\n\nKeywords\n========\n\nThe following identifiers are used as reserved words, or *keywords* of\nthe language, and cannot be used as ordinary identifiers. They must\nbe spelled exactly as written here:\n\n False class finally is return\n None continue for lambda try\n True def from nonlocal while\n and del global not with\n as elif if or yield\n assert else import pass\n break except in raise\n\n\nReserved classes of identifiers\n===============================\n\nCertain classes of identifiers (besides keywords) have special\nmeanings. These classes are identified by the patterns of leading and\ntrailing underscore characters:\n\n``_*``\n Not imported by ``from module import *``. The special identifier\n ``_`` is used in the interactive interpreter to store the result of\n the last evaluation; it is stored in the ``builtins`` module. When\n not in interactive mode, ``_`` has no special meaning and is not\n defined. See section *The import statement*.\n\n Note: The name ``_`` is often used in conjunction with\n internationalization; refer to the documentation for the\n ``gettext`` module for more information on this convention.\n\n``__*__``\n System-defined names. These names are defined by the interpreter\n and its implementation (including the standard library). Current\n system names are discussed in the *Special method names* section\n and elsewhere. More will likely be defined in future versions of\n Python. *Any* use of ``__*__`` names, in any context, that does\n not follow explicitly documented use, is subject to breakage\n without warning.\n\n``__*``\n Class-private names. Names in this category, when used within the\n context of a class definition, are re-written to use a mangled form\n to help avoid name clashes between "private" attributes of base and\n derived classes. See section *Identifiers (Names)*.\n',
@@ -53,26 +54,26 @@
'operator-summary': '\nSummary\n*******\n\nThe following table summarizes the operator precedences in Python,\nfrom lowest precedence (least binding) to highest precedence (most\nbinding). Operators in the same box have the same precedence. Unless\nthe syntax is explicitly given, operators are binary. Operators in\nthe same box group left to right (except for comparisons, including\ntests, which all have the same precedence and chain from left to right\n--- see section *Comparisons* --- and exponentiation, which groups\nfrom right to left).\n\n+-------------------------------------------------+---------------------------------------+\n| Operator | Description |\n+=================================================+=======================================+\n| ``lambda`` | Lambda expression |\n+-------------------------------------------------+---------------------------------------+\n| ``if`` -- ``else`` | Conditional expression |\n+-------------------------------------------------+---------------------------------------+\n| ``or`` | Boolean OR |\n+-------------------------------------------------+---------------------------------------+\n| ``and`` | Boolean AND |\n+-------------------------------------------------+---------------------------------------+\n| ``not`` *x* | Boolean NOT |\n+-------------------------------------------------+---------------------------------------+\n| ``in``, ``not`` ``in``, ``is``, ``is not``, | Comparisons, including membership |\n| ``<``, ``<=``, ``>``, ``>=``, ``!=``, ``==`` | tests and identity tests, |\n+-------------------------------------------------+---------------------------------------+\n| ``|`` | Bitwise OR |\n+-------------------------------------------------+---------------------------------------+\n| ``^`` | Bitwise XOR |\n+-------------------------------------------------+---------------------------------------+\n| ``&`` | Bitwise AND |\n+-------------------------------------------------+---------------------------------------+\n| ``<<``, ``>>`` | Shifts |\n+-------------------------------------------------+---------------------------------------+\n| ``+``, ``-`` | Addition and subtraction |\n+-------------------------------------------------+---------------------------------------+\n| ``*``, ``/``, ``//``, ``%`` | Multiplication, division, remainder |\n| | [5] |\n+-------------------------------------------------+---------------------------------------+\n| ``+x``, ``-x``, ``~x`` | Positive, negative, bitwise NOT |\n+-------------------------------------------------+---------------------------------------+\n| ``**`` | Exponentiation [6] |\n+-------------------------------------------------+---------------------------------------+\n| ``x[index]``, ``x[index:index]``, | Subscription, slicing, call, |\n| ``x(arguments...)``, ``x.attribute`` | attribute reference |\n+-------------------------------------------------+---------------------------------------+\n| ``(expressions...)``, ``[expressions...]``, | Binding or tuple display, list |\n| ``{key:datum...}``, ``{expressions...}`` | display, dictionary display, set |\n| | display |\n+-------------------------------------------------+---------------------------------------+\n\n-[ Footnotes ]-\n\n[1] While ``abs(x%y) < abs(y)`` is true mathematically, for floats it\n may not be true numerically due to roundoff. For example, and\n assuming a platform on which a Python float is an IEEE 754 double-\n precision number, in order that ``-1e-100 % 1e100`` have the same\n sign as ``1e100``, the computed result is ``-1e-100 + 1e100``,\n which is numerically exactly equal to ``1e100``. The function\n ``math.fmod()`` returns a result whose sign matches the sign of\n the first argument instead, and so returns ``-1e-100`` in this\n case. Which approach is more appropriate depends on the\n application.\n\n[2] If x is very close to an exact integer multiple of y, it\'s\n possible for ``x//y`` to be one larger than ``(x-x%y)//y`` due to\n rounding. In such cases, Python returns the latter result, in\n order to preserve that ``divmod(x,y)[0] * y + x % y`` be very\n close to ``x``.\n\n[3] While comparisons between strings make sense at the byte level,\n they may be counter-intuitive to users. For example, the strings\n ``"\\u00C7"`` and ``"\\u0327\\u0043"`` compare differently, even\n though they both represent the same unicode character (LATIN\n CAPITAL LETTER C WITH CEDILLA). To compare strings in a human\n recognizable way, compare using ``unicodedata.normalize()``.\n\n[4] Due to automatic garbage-collection, free lists, and the dynamic\n nature of descriptors, you may notice seemingly unusual behaviour\n in certain uses of the ``is`` operator, like those involving\n comparisons between instance methods, or constants. Check their\n documentation for more info.\n\n[5] The ``%`` operator is also used for string formatting; the same\n precedence applies.\n\n[6] The power operator ``**`` binds less tightly than an arithmetic or\n bitwise unary operator on its right, that is, ``2**-1`` is\n ``0.5``.\n',
'pass': '\nThe ``pass`` statement\n**********************\n\n pass_stmt ::= "pass"\n\n``pass`` is a null operation --- when it is executed, nothing happens.\nIt is useful as a placeholder when a statement is required\nsyntactically, but no code needs to be executed, for example:\n\n def f(arg): pass # a function that does nothing (yet)\n\n class C: pass # a class with no methods (yet)\n',
'power': '\nThe power operator\n******************\n\nThe power operator binds more tightly than unary operators on its\nleft; it binds less tightly than unary operators on its right. The\nsyntax is:\n\n power ::= primary ["**" u_expr]\n\nThus, in an unparenthesized sequence of power and unary operators, the\noperators are evaluated from right to left (this does not constrain\nthe evaluation order for the operands): ``-1**2`` results in ``-1``.\n\nThe power operator has the same semantics as the built-in ``pow()``\nfunction, when called with two arguments: it yields its left argument\nraised to the power of its right argument. The numeric arguments are\nfirst converted to a common type, and the result is of that type.\n\nFor int operands, the result has the same type as the operands unless\nthe second argument is negative; in that case, all arguments are\nconverted to float and a float result is delivered. For example,\n``10**2`` returns ``100``, but ``10**-2`` returns ``0.01``.\n\nRaising ``0.0`` to a negative power results in a\n``ZeroDivisionError``. Raising a negative number to a fractional power\nresults in a ``complex`` number. (In earlier versions it raised a\n``ValueError``.)\n',
- 'raise': '\nThe ``raise`` statement\n***********************\n\n raise_stmt ::= "raise" [expression ["from" expression]]\n\nIf no expressions are present, ``raise`` re-raises the last exception\nthat was active in the current scope. If no exception is active in\nthe current scope, a ``TypeError`` exception is raised indicating that\nthis is an error (if running under IDLE, a ``queue.Empty`` exception\nis raised instead).\n\nOtherwise, ``raise`` evaluates the first expression as the exception\nobject. It must be either a subclass or an instance of\n``BaseException``. If it is a class, the exception instance will be\nobtained when needed by instantiating the class with no arguments.\n\nThe *type* of the exception is the exception instance\'s class, the\n*value* is the instance itself.\n\nA traceback object is normally created automatically when an exception\nis raised and attached to it as the ``__traceback__`` attribute, which\nis writable. You can create an exception and set your own traceback in\none step using the ``with_traceback()`` exception method (which\nreturns the same exception instance, with its traceback set to its\nargument), like so:\n\n raise Exception("foo occurred").with_traceback(tracebackobj)\n\nThe ``from`` clause is used for exception chaining: if given, the\nsecond *expression* must be another exception class or instance, which\nwill then be attached to the raised exception as the ``__cause__``\nattribute (which is writable). If the raised exception is not\nhandled, both exceptions will be printed:\n\n >>> try:\n ... print(1 / 0)\n ... except Exception as exc:\n ... raise RuntimeError("Something bad happened") from exc\n ...\n Traceback (most recent call last):\n File "<stdin>", line 2, in <module>\n ZeroDivisionError: int division or modulo by zero\n\n The above exception was the direct cause of the following exception:\n\n Traceback (most recent call last):\n File "<stdin>", line 4, in <module>\n RuntimeError: Something bad happened\n\nA similar mechanism works implicitly if an exception is raised inside\nan exception handler: the previous exception is then attached as the\nnew exception\'s ``__context__`` attribute:\n\n >>> try:\n ... print(1 / 0)\n ... except:\n ... raise RuntimeError("Something bad happened")\n ...\n Traceback (most recent call last):\n File "<stdin>", line 2, in <module>\n ZeroDivisionError: int division or modulo by zero\n\n During handling of the above exception, another exception occurred:\n\n Traceback (most recent call last):\n File "<stdin>", line 4, in <module>\n RuntimeError: Something bad happened\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information about handling exceptions is in section\n*The try statement*.\n',
- 'return': '\nThe ``return`` statement\n************************\n\n return_stmt ::= "return" [expression_list]\n\n``return`` may only occur syntactically nested in a function\ndefinition, not within a nested class definition.\n\nIf an expression list is present, it is evaluated, else ``None`` is\nsubstituted.\n\n``return`` leaves the current function call with the expression list\n(or ``None``) as return value.\n\nWhen ``return`` passes control out of a ``try`` statement with a\n``finally`` clause, that ``finally`` clause is executed before really\nleaving the function.\n\nIn a generator function, the ``return`` statement is not allowed to\ninclude an ``expression_list``. In that context, a bare ``return``\nindicates that the generator is done and will cause ``StopIteration``\nto be raised.\n',
+ 'raise': '\nThe ``raise`` statement\n***********************\n\n raise_stmt ::= "raise" [expression ["from" expression]]\n\nIf no expressions are present, ``raise`` re-raises the last exception\nthat was active in the current scope. If no exception is active in\nthe current scope, a ``RuntimeError`` exception is raised indicating\nthat this is an error.\n\nOtherwise, ``raise`` evaluates the first expression as the exception\nobject. It must be either a subclass or an instance of\n``BaseException``. If it is a class, the exception instance will be\nobtained when needed by instantiating the class with no arguments.\n\nThe *type* of the exception is the exception instance\'s class, the\n*value* is the instance itself.\n\nA traceback object is normally created automatically when an exception\nis raised and attached to it as the ``__traceback__`` attribute, which\nis writable. You can create an exception and set your own traceback in\none step using the ``with_traceback()`` exception method (which\nreturns the same exception instance, with its traceback set to its\nargument), like so:\n\n raise Exception("foo occurred").with_traceback(tracebackobj)\n\nThe ``from`` clause is used for exception chaining: if given, the\nsecond *expression* must be another exception class or instance, which\nwill then be attached to the raised exception as the ``__cause__``\nattribute (which is writable). If the raised exception is not\nhandled, both exceptions will be printed:\n\n >>> try:\n ... print(1 / 0)\n ... except Exception as exc:\n ... raise RuntimeError("Something bad happened") from exc\n ...\n Traceback (most recent call last):\n File "<stdin>", line 2, in <module>\n ZeroDivisionError: int division or modulo by zero\n\n The above exception was the direct cause of the following exception:\n\n Traceback (most recent call last):\n File "<stdin>", line 4, in <module>\n RuntimeError: Something bad happened\n\nA similar mechanism works implicitly if an exception is raised inside\nan exception handler: the previous exception is then attached as the\nnew exception\'s ``__context__`` attribute:\n\n >>> try:\n ... print(1 / 0)\n ... except:\n ... raise RuntimeError("Something bad happened")\n ...\n Traceback (most recent call last):\n File "<stdin>", line 2, in <module>\n ZeroDivisionError: int division or modulo by zero\n\n During handling of the above exception, another exception occurred:\n\n Traceback (most recent call last):\n File "<stdin>", line 4, in <module>\n RuntimeError: Something bad happened\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information about handling exceptions is in section\n*The try statement*.\n',
+ 'return': '\nThe ``return`` statement\n************************\n\n return_stmt ::= "return" [expression_list]\n\n``return`` may only occur syntactically nested in a function\ndefinition, not within a nested class definition.\n\nIf an expression list is present, it is evaluated, else ``None`` is\nsubstituted.\n\n``return`` leaves the current function call with the expression list\n(or ``None``) as return value.\n\nWhen ``return`` passes control out of a ``try`` statement with a\n``finally`` clause, that ``finally`` clause is executed before really\nleaving the function.\n\nIn a generator function, the ``return`` statement indicates that the\ngenerator is done and will cause ``StopIteration`` to be raised. The\nreturned value (if any) is used as an argument to construct\n``StopIteration`` and becomes the ``StopIteration.value`` attribute.\n',
'sequence-types': "\nEmulating container types\n*************************\n\nThe following methods can be defined to implement container objects.\nContainers usually are sequences (such as lists or tuples) or mappings\n(like dictionaries), but can represent other containers as well. The\nfirst set of methods is used either to emulate a sequence or to\nemulate a mapping; the difference is that for a sequence, the\nallowable keys should be the integers *k* for which ``0 <= k < N``\nwhere *N* is the length of the sequence, or slice objects, which\ndefine a range of items. It is also recommended that mappings provide\nthe methods ``keys()``, ``values()``, ``items()``, ``get()``,\n``clear()``, ``setdefault()``, ``pop()``, ``popitem()``, ``copy()``,\nand ``update()`` behaving similar to those for Python's standard\ndictionary objects. The ``collections`` module provides a\n``MutableMapping`` abstract base class to help create those methods\nfrom a base set of ``__getitem__()``, ``__setitem__()``,\n``__delitem__()``, and ``keys()``. Mutable sequences should provide\nmethods ``append()``, ``count()``, ``index()``, ``extend()``,\n``insert()``, ``pop()``, ``remove()``, ``reverse()`` and ``sort()``,\nlike Python standard list objects. Finally, sequence types should\nimplement addition (meaning concatenation) and multiplication (meaning\nrepetition) by defining the methods ``__add__()``, ``__radd__()``,\n``__iadd__()``, ``__mul__()``, ``__rmul__()`` and ``__imul__()``\ndescribed below; they should not define other numerical operators. It\nis recommended that both mappings and sequences implement the\n``__contains__()`` method to allow efficient use of the ``in``\noperator; for mappings, ``in`` should search the mapping's keys; for\nsequences, it should search through the values. It is further\nrecommended that both mappings and sequences implement the\n``__iter__()`` method to allow efficient iteration through the\ncontainer; for mappings, ``__iter__()`` should be the same as\n``keys()``; for sequences, it should iterate through the values.\n\nobject.__len__(self)\n\n Called to implement the built-in function ``len()``. Should return\n the length of the object, an integer ``>=`` 0. Also, an object\n that doesn't define a ``__bool__()`` method and whose ``__len__()``\n method returns zero is considered to be false in a Boolean context.\n\nNote: Slicing is done exclusively with the following three methods. A\n call like\n\n a[1:2] = b\n\n is translated to\n\n a[slice(1, 2, None)] = b\n\n and so forth. Missing slice items are always filled in with\n ``None``.\n\nobject.__getitem__(self, key)\n\n Called to implement evaluation of ``self[key]``. For sequence\n types, the accepted keys should be integers and slice objects.\n Note that the special interpretation of negative indexes (if the\n class wishes to emulate a sequence type) is up to the\n ``__getitem__()`` method. If *key* is of an inappropriate type,\n ``TypeError`` may be raised; if of a value outside the set of\n indexes for the sequence (after any special interpretation of\n negative values), ``IndexError`` should be raised. For mapping\n types, if *key* is missing (not in the container), ``KeyError``\n should be raised.\n\n Note: ``for`` loops expect that an ``IndexError`` will be raised for\n illegal indexes to allow proper detection of the end of the\n sequence.\n\nobject.__setitem__(self, key, value)\n\n Called to implement assignment to ``self[key]``. Same note as for\n ``__getitem__()``. This should only be implemented for mappings if\n the objects support changes to the values for keys, or if new keys\n can be added, or for sequences if elements can be replaced. The\n same exceptions should be raised for improper *key* values as for\n the ``__getitem__()`` method.\n\nobject.__delitem__(self, key)\n\n Called to implement deletion of ``self[key]``. Same note as for\n ``__getitem__()``. This should only be implemented for mappings if\n the objects support removal of keys, or for sequences if elements\n can be removed from the sequence. The same exceptions should be\n raised for improper *key* values as for the ``__getitem__()``\n method.\n\nobject.__iter__(self)\n\n This method is called when an iterator is required for a container.\n This method should return a new iterator object that can iterate\n over all the objects in the container. For mappings, it should\n iterate over the keys of the container, and should also be made\n available as the method ``keys()``.\n\n Iterator objects also need to implement this method; they are\n required to return themselves. For more information on iterator\n objects, see *Iterator Types*.\n\nobject.__reversed__(self)\n\n Called (if present) by the ``reversed()`` built-in to implement\n reverse iteration. It should return a new iterator object that\n iterates over all the objects in the container in reverse order.\n\n If the ``__reversed__()`` method is not provided, the\n ``reversed()`` built-in will fall back to using the sequence\n protocol (``__len__()`` and ``__getitem__()``). Objects that\n support the sequence protocol should only provide\n ``__reversed__()`` if they can provide an implementation that is\n more efficient than the one provided by ``reversed()``.\n\nThe membership test operators (``in`` and ``not in``) are normally\nimplemented as an iteration through a sequence. However, container\nobjects can supply the following special method with a more efficient\nimplementation, which also does not require the object be a sequence.\n\nobject.__contains__(self, item)\n\n Called to implement membership test operators. Should return true\n if *item* is in *self*, false otherwise. For mapping objects, this\n should consider the keys of the mapping rather than the values or\n the key-item pairs.\n\n For objects that don't define ``__contains__()``, the membership\n test first tries iteration via ``__iter__()``, then the old\n sequence iteration protocol via ``__getitem__()``, see *this\n section in the language reference*.\n",
'shifting': '\nShifting operations\n*******************\n\nThe shifting operations have lower priority than the arithmetic\noperations:\n\n shift_expr ::= a_expr | shift_expr ( "<<" | ">>" ) a_expr\n\nThese operators accept integers as arguments. They shift the first\nargument to the left or right by the number of bits given by the\nsecond argument.\n\nA right shift by *n* bits is defined as division by ``pow(2,n)``. A\nleft shift by *n* bits is defined as multiplication with ``pow(2,n)``.\n\nNote: In the current implementation, the right-hand operand is required to\n be at most ``sys.maxsize``. If the right-hand operand is larger\n than ``sys.maxsize`` an ``OverflowError`` exception is raised.\n',
'slicings': '\nSlicings\n********\n\nA slicing selects a range of items in a sequence object (e.g., a\nstring, tuple or list). Slicings may be used as expressions or as\ntargets in assignment or ``del`` statements. The syntax for a\nslicing:\n\n slicing ::= primary "[" slice_list "]"\n slice_list ::= slice_item ("," slice_item)* [","]\n slice_item ::= expression | proper_slice\n proper_slice ::= [lower_bound] ":" [upper_bound] [ ":" [stride] ]\n lower_bound ::= expression\n upper_bound ::= expression\n stride ::= expression\n\nThere is ambiguity in the formal syntax here: anything that looks like\nan expression list also looks like a slice list, so any subscription\ncan be interpreted as a slicing. Rather than further complicating the\nsyntax, this is disambiguated by defining that in this case the\ninterpretation as a subscription takes priority over the\ninterpretation as a slicing (this is the case if the slice list\ncontains no proper slice).\n\nThe semantics for a slicing are as follows. The primary must evaluate\nto a mapping object, and it is indexed (using the same\n``__getitem__()`` method as normal subscription) with a key that is\nconstructed from the slice list, as follows. If the slice list\ncontains at least one comma, the key is a tuple containing the\nconversion of the slice items; otherwise, the conversion of the lone\nslice item is the key. The conversion of a slice item that is an\nexpression is that expression. The conversion of a proper slice is a\nslice object (see section *The standard type hierarchy*) whose\n``start``, ``stop`` and ``step`` attributes are the values of the\nexpressions given as lower bound, upper bound and stride,\nrespectively, substituting ``None`` for missing expressions.\n',
- 'specialattrs': "\nSpecial Attributes\n******************\n\nThe implementation adds a few special read-only attributes to several\nobject types, where they are relevant. Some of these are not reported\nby the ``dir()`` built-in function.\n\nobject.__dict__\n\n A dictionary or other mapping object used to store an object's\n (writable) attributes.\n\ninstance.__class__\n\n The class to which a class instance belongs.\n\nclass.__bases__\n\n The tuple of base classes of a class object.\n\nclass.__name__\n\n The name of the class or type.\n\nThe following attributes are only supported by *new-style class*es.\n\nclass.__mro__\n\n This attribute is a tuple of classes that are considered when\n looking for base classes during method resolution.\n\nclass.mro()\n\n This method can be overridden by a metaclass to customize the\n method resolution order for its instances. It is called at class\n instantiation, and its result is stored in ``__mro__``.\n\nclass.__subclasses__()\n\n Each new-style class keeps a list of weak references to its\n immediate subclasses. This method returns a list of all those\n references still alive. Example:\n\n >>> int.__subclasses__()\n [<type 'bool'>]\n\n-[ Footnotes ]-\n\n[1] Additional information on these special methods may be found in\n the Python Reference Manual (*Basic customization*).\n\n[2] As a consequence, the list ``[1, 2]`` is considered equal to\n ``[1.0, 2.0]``, and similarly for tuples.\n\n[3] They must have since the parser can't tell the type of the\n operands.\n\n[4] To format only a tuple you should therefore provide a singleton\n tuple whose only element is the tuple to be formatted.\n",
- 'specialnames': '\nSpecial method names\n********************\n\nA class can implement certain operations that are invoked by special\nsyntax (such as arithmetic operations or subscripting and slicing) by\ndefining methods with special names. This is Python\'s approach to\n*operator overloading*, allowing classes to define their own behavior\nwith respect to language operators. For instance, if a class defines\na method named ``__getitem__()``, and ``x`` is an instance of this\nclass, then ``x[i]`` is roughly equivalent to ``type(x).__getitem__(x,\ni)``. Except where mentioned, attempts to execute an operation raise\nan exception when no appropriate method is defined (typically\n``AttributeError`` or ``TypeError``).\n\nWhen implementing a class that emulates any built-in type, it is\nimportant that the emulation only be implemented to the degree that it\nmakes sense for the object being modelled. For example, some\nsequences may work well with retrieval of individual elements, but\nextracting a slice may not make sense. (One example of this is the\n``NodeList`` interface in the W3C\'s Document Object Model.)\n\n\nBasic customization\n===================\n\nobject.__new__(cls[, ...])\n\n Called to create a new instance of class *cls*. ``__new__()`` is a\n static method (special-cased so you need not declare it as such)\n that takes the class of which an instance was requested as its\n first argument. The remaining arguments are those passed to the\n object constructor expression (the call to the class). The return\n value of ``__new__()`` should be the new object instance (usually\n an instance of *cls*).\n\n Typical implementations create a new instance of the class by\n invoking the superclass\'s ``__new__()`` method using\n ``super(currentclass, cls).__new__(cls[, ...])`` with appropriate\n arguments and then modifying the newly-created instance as\n necessary before returning it.\n\n If ``__new__()`` returns an instance of *cls*, then the new\n instance\'s ``__init__()`` method will be invoked like\n ``__init__(self[, ...])``, where *self* is the new instance and the\n remaining arguments are the same as were passed to ``__new__()``.\n\n If ``__new__()`` does not return an instance of *cls*, then the new\n instance\'s ``__init__()`` method will not be invoked.\n\n ``__new__()`` is intended mainly to allow subclasses of immutable\n types (like int, str, or tuple) to customize instance creation. It\n is also commonly overridden in custom metaclasses in order to\n customize class creation.\n\nobject.__init__(self[, ...])\n\n Called when the instance is created. The arguments are those\n passed to the class constructor expression. If a base class has an\n ``__init__()`` method, the derived class\'s ``__init__()`` method,\n if any, must explicitly call it to ensure proper initialization of\n the base class part of the instance; for example:\n ``BaseClass.__init__(self, [args...])``. As a special constraint\n on constructors, no value may be returned; doing so will cause a\n ``TypeError`` to be raised at runtime.\n\nobject.__del__(self)\n\n Called when the instance is about to be destroyed. This is also\n called a destructor. If a base class has a ``__del__()`` method,\n the derived class\'s ``__del__()`` method, if any, must explicitly\n call it to ensure proper deletion of the base class part of the\n instance. Note that it is possible (though not recommended!) for\n the ``__del__()`` method to postpone destruction of the instance by\n creating a new reference to it. It may then be called at a later\n time when this new reference is deleted. It is not guaranteed that\n ``__del__()`` methods are called for objects that still exist when\n the interpreter exits.\n\n Note: ``del x`` doesn\'t directly call ``x.__del__()`` --- the former\n decrements the reference count for ``x`` by one, and the latter\n is only called when ``x``\'s reference count reaches zero. Some\n common situations that may prevent the reference count of an\n object from going to zero include: circular references between\n objects (e.g., a doubly-linked list or a tree data structure with\n parent and child pointers); a reference to the object on the\n stack frame of a function that caught an exception (the traceback\n stored in ``sys.exc_info()[2]`` keeps the stack frame alive); or\n a reference to the object on the stack frame that raised an\n unhandled exception in interactive mode (the traceback stored in\n ``sys.last_traceback`` keeps the stack frame alive). The first\n situation can only be remedied by explicitly breaking the cycles;\n the latter two situations can be resolved by storing ``None`` in\n ``sys.last_traceback``. Circular references which are garbage are\n detected when the option cycle detector is enabled (it\'s on by\n default), but can only be cleaned up if there are no Python-\n level ``__del__()`` methods involved. Refer to the documentation\n for the ``gc`` module for more information about how\n ``__del__()`` methods are handled by the cycle detector,\n particularly the description of the ``garbage`` value.\n\n Warning: Due to the precarious circumstances under which ``__del__()``\n methods are invoked, exceptions that occur during their execution\n are ignored, and a warning is printed to ``sys.stderr`` instead.\n Also, when ``__del__()`` is invoked in response to a module being\n deleted (e.g., when execution of the program is done), other\n globals referenced by the ``__del__()`` method may already have\n been deleted or in the process of being torn down (e.g. the\n import machinery shutting down). For this reason, ``__del__()``\n methods should do the absolute minimum needed to maintain\n external invariants. Starting with version 1.5, Python\n guarantees that globals whose name begins with a single\n underscore are deleted from their module before other globals are\n deleted; if no other references to such globals exist, this may\n help in assuring that imported modules are still available at the\n time when the ``__del__()`` method is called.\n\nobject.__repr__(self)\n\n Called by the ``repr()`` built-in function to compute the\n "official" string representation of an object. If at all possible,\n this should look like a valid Python expression that could be used\n to recreate an object with the same value (given an appropriate\n environment). If this is not possible, a string of the form\n ``<...some useful description...>`` should be returned. The return\n value must be a string object. If a class defines ``__repr__()``\n but not ``__str__()``, then ``__repr__()`` is also used when an\n "informal" string representation of instances of that class is\n required.\n\n This is typically used for debugging, so it is important that the\n representation is information-rich and unambiguous.\n\nobject.__str__(self)\n\n Called by the ``str()`` built-in function and by the ``print()``\n function to compute the "informal" string representation of an\n object. This differs from ``__repr__()`` in that it does not have\n to be a valid Python expression: a more convenient or concise\n representation may be used instead. The return value must be a\n string object.\n\nobject.__format__(self, format_spec)\n\n Called by the ``format()`` built-in function (and by extension, the\n ``format()`` method of class ``str``) to produce a "formatted"\n string representation of an object. The ``format_spec`` argument is\n a string that contains a description of the formatting options\n desired. The interpretation of the ``format_spec`` argument is up\n to the type implementing ``__format__()``, however most classes\n will either delegate formatting to one of the built-in types, or\n use a similar formatting option syntax.\n\n See *Format Specification Mini-Language* for a description of the\n standard formatting syntax.\n\n The return value must be a string object.\n\nobject.__lt__(self, other)\nobject.__le__(self, other)\nobject.__eq__(self, other)\nobject.__ne__(self, other)\nobject.__gt__(self, other)\nobject.__ge__(self, other)\n\n These are the so-called "rich comparison" methods. The\n correspondence between operator symbols and method names is as\n follows: ``x<y`` calls ``x.__lt__(y)``, ``x<=y`` calls\n ``x.__le__(y)``, ``x==y`` calls ``x.__eq__(y)``, ``x!=y`` calls\n ``x.__ne__(y)``, ``x>y`` calls ``x.__gt__(y)``, and ``x>=y`` calls\n ``x.__ge__(y)``.\n\n A rich comparison method may return the singleton\n ``NotImplemented`` if it does not implement the operation for a\n given pair of arguments. By convention, ``False`` and ``True`` are\n returned for a successful comparison. However, these methods can\n return any value, so if the comparison operator is used in a\n Boolean context (e.g., in the condition of an ``if`` statement),\n Python will call ``bool()`` on the value to determine if the result\n is true or false.\n\n There are no implied relationships among the comparison operators.\n The truth of ``x==y`` does not imply that ``x!=y`` is false.\n Accordingly, when defining ``__eq__()``, one should also define\n ``__ne__()`` so that the operators will behave as expected. See\n the paragraph on ``__hash__()`` for some important notes on\n creating *hashable* objects which support custom comparison\n operations and are usable as dictionary keys.\n\n There are no swapped-argument versions of these methods (to be used\n when the left argument does not support the operation but the right\n argument does); rather, ``__lt__()`` and ``__gt__()`` are each\n other\'s reflection, ``__le__()`` and ``__ge__()`` are each other\'s\n reflection, and ``__eq__()`` and ``__ne__()`` are their own\n reflection.\n\n Arguments to rich comparison methods are never coerced.\n\n To automatically generate ordering operations from a single root\n operation, see ``functools.total_ordering()``.\n\nobject.__hash__(self)\n\n Called by built-in function ``hash()`` and for operations on\n members of hashed collections including ``set``, ``frozenset``, and\n ``dict``. ``__hash__()`` should return an integer. The only\n required property is that objects which compare equal have the same\n hash value; it is advised to somehow mix together (e.g. using\n exclusive or) the hash values for the components of the object that\n also play a part in comparison of objects.\n\n If a class does not define an ``__eq__()`` method it should not\n define a ``__hash__()`` operation either; if it defines\n ``__eq__()`` but not ``__hash__()``, its instances will not be\n usable as items in hashable collections. If a class defines\n mutable objects and implements an ``__eq__()`` method, it should\n not implement ``__hash__()``, since the implementation of hashable\n collections requires that a key\'s hash value is immutable (if the\n object\'s hash value changes, it will be in the wrong hash bucket).\n\n User-defined classes have ``__eq__()`` and ``__hash__()`` methods\n by default; with them, all objects compare unequal (except with\n themselves) and ``x.__hash__()`` returns ``id(x)``.\n\n Classes which inherit a ``__hash__()`` method from a parent class\n but change the meaning of ``__eq__()`` such that the hash value\n returned is no longer appropriate (e.g. by switching to a value-\n based concept of equality instead of the default identity based\n equality) can explicitly flag themselves as being unhashable by\n setting ``__hash__ = None`` in the class definition. Doing so means\n that not only will instances of the class raise an appropriate\n ``TypeError`` when a program attempts to retrieve their hash value,\n but they will also be correctly identified as unhashable when\n checking ``isinstance(obj, collections.Hashable)`` (unlike classes\n which define their own ``__hash__()`` to explicitly raise\n ``TypeError``).\n\n If a class that overrides ``__eq__()`` needs to retain the\n implementation of ``__hash__()`` from a parent class, the\n interpreter must be told this explicitly by setting ``__hash__ =\n <ParentClass>.__hash__``. Otherwise the inheritance of\n ``__hash__()`` will be blocked, just as if ``__hash__`` had been\n explicitly set to ``None``.\n\nobject.__bool__(self)\n\n Called to implement truth value testing and the built-in operation\n ``bool()``; should return ``False`` or ``True``. When this method\n is not defined, ``__len__()`` is called, if it is defined, and the\n object is considered true if its result is nonzero. If a class\n defines neither ``__len__()`` nor ``__bool__()``, all its instances\n are considered true.\n\n\nCustomizing attribute access\n============================\n\nThe following methods can be defined to customize the meaning of\nattribute access (use of, assignment to, or deletion of ``x.name``)\nfor class instances.\n\nobject.__getattr__(self, name)\n\n Called when an attribute lookup has not found the attribute in the\n usual places (i.e. it is not an instance attribute nor is it found\n in the class tree for ``self``). ``name`` is the attribute name.\n This method should return the (computed) attribute value or raise\n an ``AttributeError`` exception.\n\n Note that if the attribute is found through the normal mechanism,\n ``__getattr__()`` is not called. (This is an intentional asymmetry\n between ``__getattr__()`` and ``__setattr__()``.) This is done both\n for efficiency reasons and because otherwise ``__getattr__()``\n would have no way to access other attributes of the instance. Note\n that at least for instance variables, you can fake total control by\n not inserting any values in the instance attribute dictionary (but\n instead inserting them in another object). See the\n ``__getattribute__()`` method below for a way to actually get total\n control over attribute access.\n\nobject.__getattribute__(self, name)\n\n Called unconditionally to implement attribute accesses for\n instances of the class. If the class also defines\n ``__getattr__()``, the latter will not be called unless\n ``__getattribute__()`` either calls it explicitly or raises an\n ``AttributeError``. This method should return the (computed)\n attribute value or raise an ``AttributeError`` exception. In order\n to avoid infinite recursion in this method, its implementation\n should always call the base class method with the same name to\n access any attributes it needs, for example,\n ``object.__getattribute__(self, name)``.\n\n Note: This method may still be bypassed when looking up special methods\n as the result of implicit invocation via language syntax or\n built-in functions. See *Special method lookup*.\n\nobject.__setattr__(self, name, value)\n\n Called when an attribute assignment is attempted. This is called\n instead of the normal mechanism (i.e. store the value in the\n instance dictionary). *name* is the attribute name, *value* is the\n value to be assigned to it.\n\n If ``__setattr__()`` wants to assign to an instance attribute, it\n should call the base class method with the same name, for example,\n ``object.__setattr__(self, name, value)``.\n\nobject.__delattr__(self, name)\n\n Like ``__setattr__()`` but for attribute deletion instead of\n assignment. This should only be implemented if ``del obj.name`` is\n meaningful for the object.\n\nobject.__dir__(self)\n\n Called when ``dir()`` is called on the object. A list must be\n returned.\n\n\nImplementing Descriptors\n------------------------\n\nThe following methods only apply when an instance of the class\ncontaining the method (a so-called *descriptor* class) appears in an\n*owner* class (the descriptor must be in either the owner\'s class\ndictionary or in the class dictionary for one of its parents). In the\nexamples below, "the attribute" refers to the attribute whose name is\nthe key of the property in the owner class\' ``__dict__``.\n\nobject.__get__(self, instance, owner)\n\n Called to get the attribute of the owner class (class attribute\n access) or of an instance of that class (instance attribute\n access). *owner* is always the owner class, while *instance* is the\n instance that the attribute was accessed through, or ``None`` when\n the attribute is accessed through the *owner*. This method should\n return the (computed) attribute value or raise an\n ``AttributeError`` exception.\n\nobject.__set__(self, instance, value)\n\n Called to set the attribute on an instance *instance* of the owner\n class to a new value, *value*.\n\nobject.__delete__(self, instance)\n\n Called to delete the attribute on an instance *instance* of the\n owner class.\n\n\nInvoking Descriptors\n--------------------\n\nIn general, a descriptor is an object attribute with "binding\nbehavior", one whose attribute access has been overridden by methods\nin the descriptor protocol: ``__get__()``, ``__set__()``, and\n``__delete__()``. If any of those methods are defined for an object,\nit is said to be a descriptor.\n\nThe default behavior for attribute access is to get, set, or delete\nthe attribute from an object\'s dictionary. For instance, ``a.x`` has a\nlookup chain starting with ``a.__dict__[\'x\']``, then\n``type(a).__dict__[\'x\']``, and continuing through the base classes of\n``type(a)`` excluding metaclasses.\n\nHowever, if the looked-up value is an object defining one of the\ndescriptor methods, then Python may override the default behavior and\ninvoke the descriptor method instead. Where this occurs in the\nprecedence chain depends on which descriptor methods were defined and\nhow they were called.\n\nThe starting point for descriptor invocation is a binding, ``a.x``.\nHow the arguments are assembled depends on ``a``:\n\nDirect Call\n The simplest and least common call is when user code directly\n invokes a descriptor method: ``x.__get__(a)``.\n\nInstance Binding\n If binding to an object instance, ``a.x`` is transformed into the\n call: ``type(a).__dict__[\'x\'].__get__(a, type(a))``.\n\nClass Binding\n If binding to a class, ``A.x`` is transformed into the call:\n ``A.__dict__[\'x\'].__get__(None, A)``.\n\nSuper Binding\n If ``a`` is an instance of ``super``, then the binding ``super(B,\n obj).m()`` searches ``obj.__class__.__mro__`` for the base class\n ``A`` immediately preceding ``B`` and then invokes the descriptor\n with the call: ``A.__dict__[\'m\'].__get__(obj, obj.__class__)``.\n\nFor instance bindings, the precedence of descriptor invocation depends\non the which descriptor methods are defined. A descriptor can define\nany combination of ``__get__()``, ``__set__()`` and ``__delete__()``.\nIf it does not define ``__get__()``, then accessing the attribute will\nreturn the descriptor object itself unless there is a value in the\nobject\'s instance dictionary. If the descriptor defines ``__set__()``\nand/or ``__delete__()``, it is a data descriptor; if it defines\nneither, it is a non-data descriptor. Normally, data descriptors\ndefine both ``__get__()`` and ``__set__()``, while non-data\ndescriptors have just the ``__get__()`` method. Data descriptors with\n``__set__()`` and ``__get__()`` defined always override a redefinition\nin an instance dictionary. In contrast, non-data descriptors can be\noverridden by instances.\n\nPython methods (including ``staticmethod()`` and ``classmethod()``)\nare implemented as non-data descriptors. Accordingly, instances can\nredefine and override methods. This allows individual instances to\nacquire behaviors that differ from other instances of the same class.\n\nThe ``property()`` function is implemented as a data descriptor.\nAccordingly, instances cannot override the behavior of a property.\n\n\n__slots__\n---------\n\nBy default, instances of classes have a dictionary for attribute\nstorage. This wastes space for objects having very few instance\nvariables. The space consumption can become acute when creating large\nnumbers of instances.\n\nThe default can be overridden by defining *__slots__* in a class\ndefinition. The *__slots__* declaration takes a sequence of instance\nvariables and reserves just enough space in each instance to hold a\nvalue for each variable. Space is saved because *__dict__* is not\ncreated for each instance.\n\nobject.__slots__\n\n This class variable can be assigned a string, iterable, or sequence\n of strings with variable names used by instances. If defined in a\n class, *__slots__* reserves space for the declared variables and\n prevents the automatic creation of *__dict__* and *__weakref__* for\n each instance.\n\n\nNotes on using *__slots__*\n~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n* When inheriting from a class without *__slots__*, the *__dict__*\n attribute of that class will always be accessible, so a *__slots__*\n definition in the subclass is meaningless.\n\n* Without a *__dict__* variable, instances cannot be assigned new\n variables not listed in the *__slots__* definition. Attempts to\n assign to an unlisted variable name raises ``AttributeError``. If\n dynamic assignment of new variables is desired, then add\n ``\'__dict__\'`` to the sequence of strings in the *__slots__*\n declaration.\n\n* Without a *__weakref__* variable for each instance, classes defining\n *__slots__* do not support weak references to its instances. If weak\n reference support is needed, then add ``\'__weakref__\'`` to the\n sequence of strings in the *__slots__* declaration.\n\n* *__slots__* are implemented at the class level by creating\n descriptors (*Implementing Descriptors*) for each variable name. As\n a result, class attributes cannot be used to set default values for\n instance variables defined by *__slots__*; otherwise, the class\n attribute would overwrite the descriptor assignment.\n\n* The action of a *__slots__* declaration is limited to the class\n where it is defined. As a result, subclasses will have a *__dict__*\n unless they also define *__slots__* (which must only contain names\n of any *additional* slots).\n\n* If a class defines a slot also defined in a base class, the instance\n variable defined by the base class slot is inaccessible (except by\n retrieving its descriptor directly from the base class). This\n renders the meaning of the program undefined. In the future, a\n check may be added to prevent this.\n\n* Nonempty *__slots__* does not work for classes derived from\n "variable-length" built-in types such as ``int``, ``str`` and\n ``tuple``.\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings may\n also be used; however, in the future, special meaning may be\n assigned to the values corresponding to each key.\n\n* *__class__* assignment works only if both classes have the same\n *__slots__*.\n\n\nCustomizing class creation\n==========================\n\nBy default, classes are constructed using ``type()``. A class\ndefinition is read into a separate namespace and the value of class\nname is bound to the result of ``type(name, bases, dict)``.\n\nWhen the class definition is read, if a callable ``metaclass`` keyword\nargument is passed after the bases in the class definition, the\ncallable given will be called instead of ``type()``. If other keyword\narguments are passed, they will also be passed to the metaclass. This\nallows classes or functions to be written which monitor or alter the\nclass creation process:\n\n* Modifying the class dictionary prior to the class being created.\n\n* Returning an instance of another class -- essentially performing the\n role of a factory function.\n\nThese steps will have to be performed in the metaclass\'s ``__new__()``\nmethod -- ``type.__new__()`` can then be called from this method to\ncreate a class with different properties. This example adds a new\nelement to the class dictionary before creating the class:\n\n class metacls(type):\n def __new__(mcs, name, bases, dict):\n dict[\'foo\'] = \'metacls was here\'\n return type.__new__(mcs, name, bases, dict)\n\nYou can of course also override other class methods (or add new\nmethods); for example defining a custom ``__call__()`` method in the\nmetaclass allows custom behavior when the class is called, e.g. not\nalways creating a new instance.\n\nIf the metaclass has a ``__prepare__()`` attribute (usually\nimplemented as a class or static method), it is called before the\nclass body is evaluated with the name of the class and a tuple of its\nbases for arguments. It should return an object that supports the\nmapping interface that will be used to store the namespace of the\nclass. The default is a plain dictionary. This could be used, for\nexample, to keep track of the order that class attributes are declared\nin by returning an ordered dictionary.\n\nThe appropriate metaclass is determined by the following precedence\nrules:\n\n* If the ``metaclass`` keyword argument is passed with the bases, it\n is used.\n\n* Otherwise, if there is at least one base class, its metaclass is\n used.\n\n* Otherwise, the default metaclass (``type``) is used.\n\nThe potential uses for metaclasses are boundless. Some ideas that have\nbeen explored including logging, interface checking, automatic\ndelegation, automatic property creation, proxies, frameworks, and\nautomatic resource locking/synchronization.\n\nHere is an example of a metaclass that uses an\n``collections.OrderedDict`` to remember the order that class members\nwere defined:\n\n class OrderedClass(type):\n\n @classmethod\n def __prepare__(metacls, name, bases, **kwds):\n return collections.OrderedDict()\n\n def __new__(cls, name, bases, classdict):\n result = type.__new__(cls, name, bases, dict(classdict))\n result.members = tuple(classdict)\n return result\n\n class A(metaclass=OrderedClass):\n def one(self): pass\n def two(self): pass\n def three(self): pass\n def four(self): pass\n\n >>> A.members\n (\'__module__\', \'one\', \'two\', \'three\', \'four\')\n\nWhen the class definition for *A* gets executed, the process begins\nwith calling the metaclass\'s ``__prepare__()`` method which returns an\nempty ``collections.OrderedDict``. That mapping records the methods\nand attributes of *A* as they are defined within the body of the class\nstatement. Once those definitions are executed, the ordered dictionary\nis fully populated and the metaclass\'s ``__new__()`` method gets\ninvoked. That method builds the new type and it saves the ordered\ndictionary keys in an attribute called ``members``.\n\n\nCustomizing instance and subclass checks\n========================================\n\nThe following methods are used to override the default behavior of the\n``isinstance()`` and ``issubclass()`` built-in functions.\n\nIn particular, the metaclass ``abc.ABCMeta`` implements these methods\nin order to allow the addition of Abstract Base Classes (ABCs) as\n"virtual base classes" to any class or type (including built-in\ntypes), including other ABCs.\n\nclass.__instancecheck__(self, instance)\n\n Return true if *instance* should be considered a (direct or\n indirect) instance of *class*. If defined, called to implement\n ``isinstance(instance, class)``.\n\nclass.__subclasscheck__(self, subclass)\n\n Return true if *subclass* should be considered a (direct or\n indirect) subclass of *class*. If defined, called to implement\n ``issubclass(subclass, class)``.\n\nNote that these methods are looked up on the type (metaclass) of a\nclass. They cannot be defined as class methods in the actual class.\nThis is consistent with the lookup of special methods that are called\non instances, only in this case the instance is itself a class.\n\nSee also:\n\n **PEP 3119** - Introducing Abstract Base Classes\n Includes the specification for customizing ``isinstance()`` and\n ``issubclass()`` behavior through ``__instancecheck__()`` and\n ``__subclasscheck__()``, with motivation for this functionality\n in the context of adding Abstract Base Classes (see the ``abc``\n module) to the language.\n\n\nEmulating callable objects\n==========================\n\nobject.__call__(self[, args...])\n\n Called when the instance is "called" as a function; if this method\n is defined, ``x(arg1, arg2, ...)`` is a shorthand for\n ``x.__call__(arg1, arg2, ...)``.\n\n\nEmulating container types\n=========================\n\nThe following methods can be defined to implement container objects.\nContainers usually are sequences (such as lists or tuples) or mappings\n(like dictionaries), but can represent other containers as well. The\nfirst set of methods is used either to emulate a sequence or to\nemulate a mapping; the difference is that for a sequence, the\nallowable keys should be the integers *k* for which ``0 <= k < N``\nwhere *N* is the length of the sequence, or slice objects, which\ndefine a range of items. It is also recommended that mappings provide\nthe methods ``keys()``, ``values()``, ``items()``, ``get()``,\n``clear()``, ``setdefault()``, ``pop()``, ``popitem()``, ``copy()``,\nand ``update()`` behaving similar to those for Python\'s standard\ndictionary objects. The ``collections`` module provides a\n``MutableMapping`` abstract base class to help create those methods\nfrom a base set of ``__getitem__()``, ``__setitem__()``,\n``__delitem__()``, and ``keys()``. Mutable sequences should provide\nmethods ``append()``, ``count()``, ``index()``, ``extend()``,\n``insert()``, ``pop()``, ``remove()``, ``reverse()`` and ``sort()``,\nlike Python standard list objects. Finally, sequence types should\nimplement addition (meaning concatenation) and multiplication (meaning\nrepetition) by defining the methods ``__add__()``, ``__radd__()``,\n``__iadd__()``, ``__mul__()``, ``__rmul__()`` and ``__imul__()``\ndescribed below; they should not define other numerical operators. It\nis recommended that both mappings and sequences implement the\n``__contains__()`` method to allow efficient use of the ``in``\noperator; for mappings, ``in`` should search the mapping\'s keys; for\nsequences, it should search through the values. It is further\nrecommended that both mappings and sequences implement the\n``__iter__()`` method to allow efficient iteration through the\ncontainer; for mappings, ``__iter__()`` should be the same as\n``keys()``; for sequences, it should iterate through the values.\n\nobject.__len__(self)\n\n Called to implement the built-in function ``len()``. Should return\n the length of the object, an integer ``>=`` 0. Also, an object\n that doesn\'t define a ``__bool__()`` method and whose ``__len__()``\n method returns zero is considered to be false in a Boolean context.\n\nNote: Slicing is done exclusively with the following three methods. A\n call like\n\n a[1:2] = b\n\n is translated to\n\n a[slice(1, 2, None)] = b\n\n and so forth. Missing slice items are always filled in with\n ``None``.\n\nobject.__getitem__(self, key)\n\n Called to implement evaluation of ``self[key]``. For sequence\n types, the accepted keys should be integers and slice objects.\n Note that the special interpretation of negative indexes (if the\n class wishes to emulate a sequence type) is up to the\n ``__getitem__()`` method. If *key* is of an inappropriate type,\n ``TypeError`` may be raised; if of a value outside the set of\n indexes for the sequence (after any special interpretation of\n negative values), ``IndexError`` should be raised. For mapping\n types, if *key* is missing (not in the container), ``KeyError``\n should be raised.\n\n Note: ``for`` loops expect that an ``IndexError`` will be raised for\n illegal indexes to allow proper detection of the end of the\n sequence.\n\nobject.__setitem__(self, key, value)\n\n Called to implement assignment to ``self[key]``. Same note as for\n ``__getitem__()``. This should only be implemented for mappings if\n the objects support changes to the values for keys, or if new keys\n can be added, or for sequences if elements can be replaced. The\n same exceptions should be raised for improper *key* values as for\n the ``__getitem__()`` method.\n\nobject.__delitem__(self, key)\n\n Called to implement deletion of ``self[key]``. Same note as for\n ``__getitem__()``. This should only be implemented for mappings if\n the objects support removal of keys, or for sequences if elements\n can be removed from the sequence. The same exceptions should be\n raised for improper *key* values as for the ``__getitem__()``\n method.\n\nobject.__iter__(self)\n\n This method is called when an iterator is required for a container.\n This method should return a new iterator object that can iterate\n over all the objects in the container. For mappings, it should\n iterate over the keys of the container, and should also be made\n available as the method ``keys()``.\n\n Iterator objects also need to implement this method; they are\n required to return themselves. For more information on iterator\n objects, see *Iterator Types*.\n\nobject.__reversed__(self)\n\n Called (if present) by the ``reversed()`` built-in to implement\n reverse iteration. It should return a new iterator object that\n iterates over all the objects in the container in reverse order.\n\n If the ``__reversed__()`` method is not provided, the\n ``reversed()`` built-in will fall back to using the sequence\n protocol (``__len__()`` and ``__getitem__()``). Objects that\n support the sequence protocol should only provide\n ``__reversed__()`` if they can provide an implementation that is\n more efficient than the one provided by ``reversed()``.\n\nThe membership test operators (``in`` and ``not in``) are normally\nimplemented as an iteration through a sequence. However, container\nobjects can supply the following special method with a more efficient\nimplementation, which also does not require the object be a sequence.\n\nobject.__contains__(self, item)\n\n Called to implement membership test operators. Should return true\n if *item* is in *self*, false otherwise. For mapping objects, this\n should consider the keys of the mapping rather than the values or\n the key-item pairs.\n\n For objects that don\'t define ``__contains__()``, the membership\n test first tries iteration via ``__iter__()``, then the old\n sequence iteration protocol via ``__getitem__()``, see *this\n section in the language reference*.\n\n\nEmulating numeric types\n=======================\n\nThe following methods can be defined to emulate numeric objects.\nMethods corresponding to operations that are not supported by the\nparticular kind of number implemented (e.g., bitwise operations for\nnon-integral numbers) should be left undefined.\n\nobject.__add__(self, other)\nobject.__sub__(self, other)\nobject.__mul__(self, other)\nobject.__truediv__(self, other)\nobject.__floordiv__(self, other)\nobject.__mod__(self, other)\nobject.__divmod__(self, other)\nobject.__pow__(self, other[, modulo])\nobject.__lshift__(self, other)\nobject.__rshift__(self, other)\nobject.__and__(self, other)\nobject.__xor__(self, other)\nobject.__or__(self, other)\n\n These methods are called to implement the binary arithmetic\n operations (``+``, ``-``, ``*``, ``/``, ``//``, ``%``,\n ``divmod()``, ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``,\n ``|``). For instance, to evaluate the expression ``x + y``, where\n *x* is an instance of a class that has an ``__add__()`` method,\n ``x.__add__(y)`` is called. The ``__divmod__()`` method should be\n the equivalent to using ``__floordiv__()`` and ``__mod__()``; it\n should not be related to ``__truediv__()``. Note that\n ``__pow__()`` should be defined to accept an optional third\n argument if the ternary version of the built-in ``pow()`` function\n is to be supported.\n\n If one of those methods does not support the operation with the\n supplied arguments, it should return ``NotImplemented``.\n\nobject.__radd__(self, other)\nobject.__rsub__(self, other)\nobject.__rmul__(self, other)\nobject.__rtruediv__(self, other)\nobject.__rfloordiv__(self, other)\nobject.__rmod__(self, other)\nobject.__rdivmod__(self, other)\nobject.__rpow__(self, other)\nobject.__rlshift__(self, other)\nobject.__rrshift__(self, other)\nobject.__rand__(self, other)\nobject.__rxor__(self, other)\nobject.__ror__(self, other)\n\n These methods are called to implement the binary arithmetic\n operations (``+``, ``-``, ``*``, ``/``, ``//``, ``%``,\n ``divmod()``, ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``,\n ``|``) with reflected (swapped) operands. These functions are only\n called if the left operand does not support the corresponding\n operation and the operands are of different types. [2] For\n instance, to evaluate the expression ``x - y``, where *y* is an\n instance of a class that has an ``__rsub__()`` method,\n ``y.__rsub__(x)`` is called if ``x.__sub__(y)`` returns\n *NotImplemented*.\n\n Note that ternary ``pow()`` will not try calling ``__rpow__()``\n (the coercion rules would become too complicated).\n\n Note: If the right operand\'s type is a subclass of the left operand\'s\n type and that subclass provides the reflected method for the\n operation, this method will be called before the left operand\'s\n non-reflected method. This behavior allows subclasses to\n override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__itruediv__(self, other)\nobject.__ifloordiv__(self, other)\nobject.__imod__(self, other)\nobject.__ipow__(self, other[, modulo])\nobject.__ilshift__(self, other)\nobject.__irshift__(self, other)\nobject.__iand__(self, other)\nobject.__ixor__(self, other)\nobject.__ior__(self, other)\n\n These methods are called to implement the augmented arithmetic\n assignments (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,\n ``**=``, ``<<=``, ``>>=``, ``&=``, ``^=``, ``|=``). These methods\n should attempt to do the operation in-place (modifying *self*) and\n return the result (which could be, but does not have to be,\n *self*). If a specific method is not defined, the augmented\n assignment falls back to the normal methods. For instance, to\n execute the statement ``x += y``, where *x* is an instance of a\n class that has an ``__iadd__()`` method, ``x.__iadd__(y)`` is\n called. If *x* is an instance of a class that does not define a\n ``__iadd__()`` method, ``x.__add__(y)`` and ``y.__radd__(x)`` are\n considered, as with the evaluation of ``x + y``.\n\nobject.__neg__(self)\nobject.__pos__(self)\nobject.__abs__(self)\nobject.__invert__(self)\n\n Called to implement the unary arithmetic operations (``-``, ``+``,\n ``abs()`` and ``~``).\n\nobject.__complex__(self)\nobject.__int__(self)\nobject.__float__(self)\nobject.__round__(self[, n])\n\n Called to implement the built-in functions ``complex()``,\n ``int()``, ``float()`` and ``round()``. Should return a value of\n the appropriate type.\n\nobject.__index__(self)\n\n Called to implement ``operator.index()``. Also called whenever\n Python needs an integer object (such as in slicing, or in the\n built-in ``bin()``, ``hex()`` and ``oct()`` functions). Must return\n an integer.\n\n\nWith Statement Context Managers\n===============================\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a ``with`` statement. The context\nmanager handles the entry into, and the exit from, the desired runtime\ncontext for the execution of the block of code. Context managers are\nnormally invoked using the ``with`` statement (described in section\n*The with statement*), but can also be used by directly invoking their\nmethods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n Enter the runtime context related to this object. The ``with``\n statement will bind this method\'s return value to the target(s)\n specified in the ``as`` clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n Exit the runtime context related to this object. The parameters\n describe the exception that caused the context to be exited. If the\n context was exited without an exception, all three arguments will\n be ``None``.\n\n If an exception is supplied, and the method wishes to suppress the\n exception (i.e., prevent it from being propagated), it should\n return a true value. Otherwise, the exception will be processed\n normally upon exit from this method.\n\n Note that ``__exit__()`` methods should not reraise the passed-in\n exception; this is the caller\'s responsibility.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n\n\nSpecial method lookup\n=====================\n\nFor custom classes, implicit invocations of special methods are only\nguaranteed to work correctly if defined on an object\'s type, not in\nthe object\'s instance dictionary. That behaviour is the reason why\nthe following code raises an exception:\n\n >>> class C:\n ... pass\n ...\n >>> c = C()\n >>> c.__len__ = lambda: 5\n >>> len(c)\n Traceback (most recent call last):\n File "<stdin>", line 1, in <module>\n TypeError: object of type \'C\' has no len()\n\nThe rationale behind this behaviour lies with a number of special\nmethods such as ``__hash__()`` and ``__repr__()`` that are implemented\nby all objects, including type objects. If the implicit lookup of\nthese methods used the conventional lookup process, they would fail\nwhen invoked on the type object itself:\n\n >>> 1 .__hash__() == hash(1)\n True\n >>> int.__hash__() == hash(int)\n Traceback (most recent call last):\n File "<stdin>", line 1, in <module>\n TypeError: descriptor \'__hash__\' of \'int\' object needs an argument\n\nIncorrectly attempting to invoke an unbound method of a class in this\nway is sometimes referred to as \'metaclass confusion\', and is avoided\nby bypassing the instance when looking up special methods:\n\n >>> type(1).__hash__(1) == hash(1)\n True\n >>> type(int).__hash__(int) == hash(int)\n True\n\nIn addition to bypassing any instance attributes in the interest of\ncorrectness, implicit special method lookup generally also bypasses\nthe ``__getattribute__()`` method even of the object\'s metaclass:\n\n >>> class Meta(type):\n ... def __getattribute__(*args):\n ... print("Metaclass getattribute invoked")\n ... return type.__getattribute__(*args)\n ...\n >>> class C(object, metaclass=Meta):\n ... def __len__(self):\n ... return 10\n ... def __getattribute__(*args):\n ... print("Class getattribute invoked")\n ... return object.__getattribute__(*args)\n ...\n >>> c = C()\n >>> c.__len__() # Explicit lookup via instance\n Class getattribute invoked\n 10\n >>> type(c).__len__(c) # Explicit lookup via type\n Metaclass getattribute invoked\n 10\n >>> len(c) # Implicit lookup\n 10\n\nBypassing the ``__getattribute__()`` machinery in this fashion\nprovides significant scope for speed optimisations within the\ninterpreter, at the cost of some flexibility in the handling of\nspecial methods (the special method *must* be set on the class object\nitself in order to be consistently invoked by the interpreter).\n\n-[ Footnotes ]-\n\n[1] It *is* possible in some cases to change an object\'s type, under\n certain controlled conditions. It generally isn\'t a good idea\n though, since it can lead to some very strange behaviour if it is\n handled incorrectly.\n\n[2] For operands of the same type, it is assumed that if the non-\n reflected method (such as ``__add__()``) fails the operation is\n not supported, which is why the reflected method is not called.\n',
- 'string-methods': '\nString Methods\n**************\n\nString objects support the methods listed below.\n\nIn addition, Python\'s strings support the sequence type methods\ndescribed in the *Sequence Types --- str, bytes, bytearray, list,\ntuple, range* section. To output formatted strings, see the *String\nFormatting* section. Also, see the ``re`` module for string functions\nbased on regular expressions.\n\nstr.capitalize()\n\n Return a copy of the string with its first character capitalized\n and the rest lowercased.\n\nstr.center(width[, fillchar])\n\n Return centered in a string of length *width*. Padding is done\n using the specified *fillchar* (default is a space).\n\nstr.count(sub[, start[, end]])\n\n Return the number of non-overlapping occurrences of substring *sub*\n in the range [*start*, *end*]. Optional arguments *start* and\n *end* are interpreted as in slice notation.\n\nstr.encode(encoding="utf-8", errors="strict")\n\n Return an encoded version of the string as a bytes object. Default\n encoding is ``\'utf-8\'``. *errors* may be given to set a different\n error handling scheme. The default for *errors* is ``\'strict\'``,\n meaning that encoding errors raise a ``UnicodeError``. Other\n possible values are ``\'ignore\'``, ``\'replace\'``,\n ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and any other name\n registered via ``codecs.register_error()``, see section *Codec Base\n Classes*. For a list of possible encodings, see section *Standard\n Encodings*.\n\n Changed in version 3.1: Support for keyword arguments added.\n\nstr.endswith(suffix[, start[, end]])\n\n Return ``True`` if the string ends with the specified *suffix*,\n otherwise return ``False``. *suffix* can also be a tuple of\n suffixes to look for. With optional *start*, test beginning at\n that position. With optional *end*, stop comparing at that\n position.\n\nstr.expandtabs([tabsize])\n\n Return a copy of the string where all tab characters are replaced\n by one or more spaces, depending on the current column and the\n given tab size. The column number is reset to zero after each\n newline occurring in the string. If *tabsize* is not given, a tab\n size of ``8`` characters is assumed. This doesn\'t understand other\n non-printing characters or escape sequences.\n\nstr.find(sub[, start[, end]])\n\n Return the lowest index in the string where substring *sub* is\n found, such that *sub* is contained in the slice ``s[start:end]``.\n Optional arguments *start* and *end* are interpreted as in slice\n notation. Return ``-1`` if *sub* is not found.\n\nstr.format(*args, **kwargs)\n\n Perform a string formatting operation. The string on which this\n method is called can contain literal text or replacement fields\n delimited by braces ``{}``. Each replacement field contains either\n the numeric index of a positional argument, or the name of a\n keyword argument. Returns a copy of the string where each\n replacement field is replaced with the string value of the\n corresponding argument.\n\n >>> "The sum of 1 + 2 is {0}".format(1+2)\n \'The sum of 1 + 2 is 3\'\n\n See *Format String Syntax* for a description of the various\n formatting options that can be specified in format strings.\n\nstr.format_map(mapping)\n\n Similar to ``str.format(**mapping)``, except that ``mapping`` is\n used directly and not copied to a ``dict`` . This is useful if for\n example ``mapping`` is a dict subclass:\n\n >>> class Default(dict):\n ... def __missing__(self, key):\n ... return key\n ...\n >>> \'{name} was born in {country}\'.format_map(Default(name=\'Guido\'))\n \'Guido was born in country\'\n\n New in version 3.2.\n\nstr.index(sub[, start[, end]])\n\n Like ``find()``, but raise ``ValueError`` when the substring is not\n found.\n\nstr.isalnum()\n\n Return true if all characters in the string are alphanumeric and\n there is at least one character, false otherwise. A character\n ``c`` is alphanumeric if one of the following returns ``True``:\n ``c.isalpha()``, ``c.isdecimal()``, ``c.isdigit()``, or\n ``c.isnumeric()``.\n\nstr.isalpha()\n\n Return true if all characters in the string are alphabetic and\n there is at least one character, false otherwise. Alphabetic\n characters are those characters defined in the Unicode character\n database as "Letter", i.e., those with general category property\n being one of "Lm", "Lt", "Lu", "Ll", or "Lo". Note that this is\n different from the "Alphabetic" property defined in the Unicode\n Standard.\n\nstr.isdecimal()\n\n Return true if all characters in the string are decimal characters\n and there is at least one character, false otherwise. Decimal\n characters are those from general category "Nd". This category\n includes digit characters, and all characters that that can be used\n to form decimal-radix numbers, e.g. U+0660, ARABIC-INDIC DIGIT\n ZERO.\n\nstr.isdigit()\n\n Return true if all characters in the string are digits and there is\n at least one character, false otherwise. Digits include decimal\n characters and digits that need special handling, such as the\n compatibility superscript digits. Formally, a digit is a character\n that has the property value Numeric_Type=Digit or\n Numeric_Type=Decimal.\n\nstr.isidentifier()\n\n Return true if the string is a valid identifier according to the\n language definition, section *Identifiers and keywords*.\n\nstr.islower()\n\n Return true if all cased characters in the string are lowercase and\n there is at least one cased character, false otherwise. Cased\n characters are those with general category property being one of\n "Lu", "Ll", or "Lt" and lowercase characters are those with general\n category property "Ll".\n\nstr.isnumeric()\n\n Return true if all characters in the string are numeric characters,\n and there is at least one character, false otherwise. Numeric\n characters include digit characters, and all characters that have\n the Unicode numeric value property, e.g. U+2155, VULGAR FRACTION\n ONE FIFTH. Formally, numeric characters are those with the\n property value Numeric_Type=Digit, Numeric_Type=Decimal or\n Numeric_Type=Numeric.\n\nstr.isprintable()\n\n Return true if all characters in the string are printable or the\n string is empty, false otherwise. Nonprintable characters are\n those characters defined in the Unicode character database as\n "Other" or "Separator", excepting the ASCII space (0x20) which is\n considered printable. (Note that printable characters in this\n context are those which should not be escaped when ``repr()`` is\n invoked on a string. It has no bearing on the handling of strings\n written to ``sys.stdout`` or ``sys.stderr``.)\n\nstr.isspace()\n\n Return true if there are only whitespace characters in the string\n and there is at least one character, false otherwise. Whitespace\n characters are those characters defined in the Unicode character\n database as "Other" or "Separator" and those with bidirectional\n property being one of "WS", "B", or "S".\n\nstr.istitle()\n\n Return true if the string is a titlecased string and there is at\n least one character, for example uppercase characters may only\n follow uncased characters and lowercase characters only cased ones.\n Return false otherwise.\n\nstr.isupper()\n\n Return true if all cased characters in the string are uppercase and\n there is at least one cased character, false otherwise. Cased\n characters are those with general category property being one of\n "Lu", "Ll", or "Lt" and uppercase characters are those with general\n category property "Lu".\n\nstr.join(iterable)\n\n Return a string which is the concatenation of the strings in the\n *iterable* *iterable*. A ``TypeError`` will be raised if there are\n any non-string values in *seq*, including ``bytes`` objects. The\n separator between elements is the string providing this method.\n\nstr.ljust(width[, fillchar])\n\n Return the string left justified in a string of length *width*.\n Padding is done using the specified *fillchar* (default is a\n space). The original string is returned if *width* is less than\n ``len(s)``.\n\nstr.lower()\n\n Return a copy of the string converted to lowercase.\n\nstr.lstrip([chars])\n\n Return a copy of the string with leading characters removed. The\n *chars* argument is a string specifying the set of characters to be\n removed. If omitted or ``None``, the *chars* argument defaults to\n removing whitespace. The *chars* argument is not a prefix; rather,\n all combinations of its values are stripped:\n\n >>> \' spacious \'.lstrip()\n \'spacious \'\n >>> \'www.example.com\'.lstrip(\'cmowz.\')\n \'example.com\'\n\nstatic str.maketrans(x[, y[, z]])\n\n This static method returns a translation table usable for\n ``str.translate()``.\n\n If there is only one argument, it must be a dictionary mapping\n Unicode ordinals (integers) or characters (strings of length 1) to\n Unicode ordinals, strings (of arbitrary lengths) or None.\n Character keys will then be converted to ordinals.\n\n If there are two arguments, they must be strings of equal length,\n and in the resulting dictionary, each character in x will be mapped\n to the character at the same position in y. If there is a third\n argument, it must be a string, whose characters will be mapped to\n None in the result.\n\nstr.partition(sep)\n\n Split the string at the first occurrence of *sep*, and return a\n 3-tuple containing the part before the separator, the separator\n itself, and the part after the separator. If the separator is not\n found, return a 3-tuple containing the string itself, followed by\n two empty strings.\n\nstr.replace(old, new[, count])\n\n Return a copy of the string with all occurrences of substring *old*\n replaced by *new*. If the optional argument *count* is given, only\n the first *count* occurrences are replaced.\n\nstr.rfind(sub[, start[, end]])\n\n Return the highest index in the string where substring *sub* is\n found, such that *sub* is contained within ``s[start:end]``.\n Optional arguments *start* and *end* are interpreted as in slice\n notation. Return ``-1`` on failure.\n\nstr.rindex(sub[, start[, end]])\n\n Like ``rfind()`` but raises ``ValueError`` when the substring *sub*\n is not found.\n\nstr.rjust(width[, fillchar])\n\n Return the string right justified in a string of length *width*.\n Padding is done using the specified *fillchar* (default is a\n space). The original string is returned if *width* is less than\n ``len(s)``.\n\nstr.rpartition(sep)\n\n Split the string at the last occurrence of *sep*, and return a\n 3-tuple containing the part before the separator, the separator\n itself, and the part after the separator. If the separator is not\n found, return a 3-tuple containing two empty strings, followed by\n the string itself.\n\nstr.rsplit([sep[, maxsplit]])\n\n Return a list of the words in the string, using *sep* as the\n delimiter string. If *maxsplit* is given, at most *maxsplit* splits\n are done, the *rightmost* ones. If *sep* is not specified or\n ``None``, any whitespace string is a separator. Except for\n splitting from the right, ``rsplit()`` behaves like ``split()``\n which is described in detail below.\n\nstr.rstrip([chars])\n\n Return a copy of the string with trailing characters removed. The\n *chars* argument is a string specifying the set of characters to be\n removed. If omitted or ``None``, the *chars* argument defaults to\n removing whitespace. The *chars* argument is not a suffix; rather,\n all combinations of its values are stripped:\n\n >>> \' spacious \'.rstrip()\n \' spacious\'\n >>> \'mississippi\'.rstrip(\'ipz\')\n \'mississ\'\n\nstr.split([sep[, maxsplit]])\n\n Return a list of the words in the string, using *sep* as the\n delimiter string. If *maxsplit* is given, at most *maxsplit*\n splits are done (thus, the list will have at most ``maxsplit+1``\n elements). If *maxsplit* is not specified, then there is no limit\n on the number of splits (all possible splits are made).\n\n If *sep* is given, consecutive delimiters are not grouped together\n and are deemed to delimit empty strings (for example,\n ``\'1,,2\'.split(\',\')`` returns ``[\'1\', \'\', \'2\']``). The *sep*\n argument may consist of multiple characters (for example,\n ``\'1<>2<>3\'.split(\'<>\')`` returns ``[\'1\', \'2\', \'3\']``). Splitting\n an empty string with a specified separator returns ``[\'\']``.\n\n If *sep* is not specified or is ``None``, a different splitting\n algorithm is applied: runs of consecutive whitespace are regarded\n as a single separator, and the result will contain no empty strings\n at the start or end if the string has leading or trailing\n whitespace. Consequently, splitting an empty string or a string\n consisting of just whitespace with a ``None`` separator returns\n ``[]``.\n\n For example, ``\' 1 2 3 \'.split()`` returns ``[\'1\', \'2\', \'3\']``,\n and ``\' 1 2 3 \'.split(None, 1)`` returns ``[\'1\', \'2 3 \']``.\n\nstr.splitlines([keepends])\n\n Return a list of the lines in the string, breaking at line\n boundaries. Line breaks are not included in the resulting list\n unless *keepends* is given and true.\n\nstr.startswith(prefix[, start[, end]])\n\n Return ``True`` if string starts with the *prefix*, otherwise\n return ``False``. *prefix* can also be a tuple of prefixes to look\n for. With optional *start*, test string beginning at that\n position. With optional *end*, stop comparing string at that\n position.\n\nstr.strip([chars])\n\n Return a copy of the string with the leading and trailing\n characters removed. The *chars* argument is a string specifying the\n set of characters to be removed. If omitted or ``None``, the\n *chars* argument defaults to removing whitespace. The *chars*\n argument is not a prefix or suffix; rather, all combinations of its\n values are stripped:\n\n >>> \' spacious \'.strip()\n \'spacious\'\n >>> \'www.example.com\'.strip(\'cmowz.\')\n \'example\'\n\nstr.swapcase()\n\n Return a copy of the string with uppercase characters converted to\n lowercase and vice versa.\n\nstr.title()\n\n Return a titlecased version of the string where words start with an\n uppercase character and the remaining characters are lowercase.\n\n The algorithm uses a simple language-independent definition of a\n word as groups of consecutive letters. The definition works in\n many contexts but it means that apostrophes in contractions and\n possessives form word boundaries, which may not be the desired\n result:\n\n >>> "they\'re bill\'s friends from the UK".title()\n "They\'Re Bill\'S Friends From The Uk"\n\n A workaround for apostrophes can be constructed using regular\n expressions:\n\n >>> import re\n >>> def titlecase(s):\n return re.sub(r"[A-Za-z]+(\'[A-Za-z]+)?",\n lambda mo: mo.group(0)[0].upper() +\n mo.group(0)[1:].lower(),\n s)\n\n >>> titlecase("they\'re bill\'s friends.")\n "They\'re Bill\'s Friends."\n\nstr.translate(map)\n\n Return a copy of the *s* where all characters have been mapped\n through the *map* which must be a dictionary of Unicode ordinals\n (integers) to Unicode ordinals, strings or ``None``. Unmapped\n characters are left untouched. Characters mapped to ``None`` are\n deleted.\n\n You can use ``str.maketrans()`` to create a translation map from\n character-to-character mappings in different formats.\n\n Note: An even more flexible approach is to create a custom character\n mapping codec using the ``codecs`` module (see\n ``encodings.cp1251`` for an example).\n\nstr.upper()\n\n Return a copy of the string converted to uppercase.\n\nstr.zfill(width)\n\n Return the numeric string left filled with zeros in a string of\n length *width*. A sign prefix is handled correctly. The original\n string is returned if *width* is less than ``len(s)``.\n',
- 'strings': '\nString and Bytes literals\n*************************\n\nString literals are described by the following lexical definitions:\n\n stringliteral ::= [stringprefix](shortstring | longstring)\n stringprefix ::= "r" | "R"\n shortstring ::= "\'" shortstringitem* "\'" | \'"\' shortstringitem* \'"\'\n longstring ::= "\'\'\'" longstringitem* "\'\'\'" | \'"""\' longstringitem* \'"""\'\n shortstringitem ::= shortstringchar | stringescapeseq\n longstringitem ::= longstringchar | stringescapeseq\n shortstringchar ::= <any source character except "\\" or newline or the quote>\n longstringchar ::= <any source character except "\\">\n stringescapeseq ::= "\\" <any source character>\n\n bytesliteral ::= bytesprefix(shortbytes | longbytes)\n bytesprefix ::= "b" | "B" | "br" | "Br" | "bR" | "BR"\n shortbytes ::= "\'" shortbytesitem* "\'" | \'"\' shortbytesitem* \'"\'\n longbytes ::= "\'\'\'" longbytesitem* "\'\'\'" | \'"""\' longbytesitem* \'"""\'\n shortbytesitem ::= shortbyteschar | bytesescapeseq\n longbytesitem ::= longbyteschar | bytesescapeseq\n shortbyteschar ::= <any ASCII character except "\\" or newline or the quote>\n longbyteschar ::= <any ASCII character except "\\">\n bytesescapeseq ::= "\\" <any ASCII character>\n\nOne syntactic restriction not indicated by these productions is that\nwhitespace is not allowed between the ``stringprefix`` or\n``bytesprefix`` and the rest of the literal. The source character set\nis defined by the encoding declaration; it is UTF-8 if no encoding\ndeclaration is given in the source file; see section *Encoding\ndeclarations*.\n\nIn plain English: Both types of literals can be enclosed in matching\nsingle quotes (``\'``) or double quotes (``"``). They can also be\nenclosed in matching groups of three single or double quotes (these\nare generally referred to as *triple-quoted strings*). The backslash\n(``\\``) character is used to escape characters that otherwise have a\nspecial meaning, such as newline, backslash itself, or the quote\ncharacter.\n\nBytes literals are always prefixed with ``\'b\'`` or ``\'B\'``; they\nproduce an instance of the ``bytes`` type instead of the ``str`` type.\nThey may only contain ASCII characters; bytes with a numeric value of\n128 or greater must be expressed with escapes.\n\nBoth string and bytes literals may optionally be prefixed with a\nletter ``\'r\'`` or ``\'R\'``; such strings are called *raw strings* and\ntreat backslashes as literal characters. As a result, in string\nliterals, ``\'\\U\'`` and ``\'\\u\'`` escapes in raw strings are not treated\nspecially.\n\nIn triple-quoted strings, unescaped newlines and quotes are allowed\n(and are retained), except that three unescaped quotes in a row\nterminate the string. (A "quote" is the character used to open the\nstring, i.e. either ``\'`` or ``"``.)\n\nUnless an ``\'r\'`` or ``\'R\'`` prefix is present, escape sequences in\nstrings are interpreted according to rules similar to those used by\nStandard C. The recognized escape sequences are:\n\n+-------------------+-----------------------------------+---------+\n| Escape Sequence | Meaning | Notes |\n+===================+===================================+=========+\n| ``\\newline`` | Backslash and newline ignored | |\n+-------------------+-----------------------------------+---------+\n| ``\\\\`` | Backslash (``\\``) | |\n+-------------------+-----------------------------------+---------+\n| ``\\\'`` | Single quote (``\'``) | |\n+-------------------+-----------------------------------+---------+\n| ``\\"`` | Double quote (``"``) | |\n+-------------------+-----------------------------------+---------+\n| ``\\a`` | ASCII Bell (BEL) | |\n+-------------------+-----------------------------------+---------+\n| ``\\b`` | ASCII Backspace (BS) | |\n+-------------------+-----------------------------------+---------+\n| ``\\f`` | ASCII Formfeed (FF) | |\n+-------------------+-----------------------------------+---------+\n| ``\\n`` | ASCII Linefeed (LF) | |\n+-------------------+-----------------------------------+---------+\n| ``\\r`` | ASCII Carriage Return (CR) | |\n+-------------------+-----------------------------------+---------+\n| ``\\t`` | ASCII Horizontal Tab (TAB) | |\n+-------------------+-----------------------------------+---------+\n| ``\\v`` | ASCII Vertical Tab (VT) | |\n+-------------------+-----------------------------------+---------+\n| ``\\ooo`` | Character with octal value *ooo* | (1,3) |\n+-------------------+-----------------------------------+---------+\n| ``\\xhh`` | Character with hex value *hh* | (2,3) |\n+-------------------+-----------------------------------+---------+\n\nEscape sequences only recognized in string literals are:\n\n+-------------------+-----------------------------------+---------+\n| Escape Sequence | Meaning | Notes |\n+===================+===================================+=========+\n| ``\\N{name}`` | Character named *name* in the | |\n| | Unicode database | |\n+-------------------+-----------------------------------+---------+\n| ``\\uxxxx`` | Character with 16-bit hex value | (4) |\n| | *xxxx* | |\n+-------------------+-----------------------------------+---------+\n| ``\\Uxxxxxxxx`` | Character with 32-bit hex value | (5) |\n| | *xxxxxxxx* | |\n+-------------------+-----------------------------------+---------+\n\nNotes:\n\n1. As in Standard C, up to three octal digits are accepted.\n\n2. Unlike in Standard C, exactly two hex digits are required.\n\n3. In a bytes literal, hexadecimal and octal escapes denote the byte\n with the given value. In a string literal, these escapes denote a\n Unicode character with the given value.\n\n4. Individual code units which form parts of a surrogate pair can be\n encoded using this escape sequence. Exactly four hex digits are\n required.\n\n5. Any Unicode character can be encoded this way, but characters\n outside the Basic Multilingual Plane (BMP) will be encoded using a\n surrogate pair if Python is compiled to use 16-bit code units (the\n default). Exactly eight hex digits are required.\n\nUnlike Standard C, all unrecognized escape sequences are left in the\nstring unchanged, i.e., *the backslash is left in the string*. (This\nbehavior is useful when debugging: if an escape sequence is mistyped,\nthe resulting output is more easily recognized as broken.) It is also\nimportant to note that the escape sequences only recognized in string\nliterals fall into the category of unrecognized escapes for bytes\nliterals.\n\nEven in a raw string, string quotes can be escaped with a backslash,\nbut the backslash remains in the string; for example, ``r"\\""`` is a\nvalid string literal consisting of two characters: a backslash and a\ndouble quote; ``r"\\"`` is not a valid string literal (even a raw\nstring cannot end in an odd number of backslashes). Specifically, *a\nraw string cannot end in a single backslash* (since the backslash\nwould escape the following quote character). Note also that a single\nbackslash followed by a newline is interpreted as those two characters\nas part of the string, *not* as a line continuation.\n',
+ 'specialattrs': '\nSpecial Attributes\n******************\n\nThe implementation adds a few special read-only attributes to several\nobject types, where they are relevant. Some of these are not reported\nby the ``dir()`` built-in function.\n\nobject.__dict__\n\n A dictionary or other mapping object used to store an object\'s\n (writable) attributes.\n\ninstance.__class__\n\n The class to which a class instance belongs.\n\nclass.__bases__\n\n The tuple of base classes of a class object.\n\nclass.__name__\n\n The name of the class or type.\n\nclass.__qualname__\n\n The *qualified name* of the class or type.\n\n New in version 3.3.\n\nclass.__mro__\n\n This attribute is a tuple of classes that are considered when\n looking for base classes during method resolution.\n\nclass.mro()\n\n This method can be overridden by a metaclass to customize the\n method resolution order for its instances. It is called at class\n instantiation, and its result is stored in ``__mro__``.\n\nclass.__subclasses__()\n\n Each class keeps a list of weak references to its immediate\n subclasses. This method returns a list of all those references\n still alive. Example:\n\n >>> int.__subclasses__()\n [<class \'bool\'>]\n\n-[ Footnotes ]-\n\n[1] Additional information on these special methods may be found in\n the Python Reference Manual (*Basic customization*).\n\n[2] As a consequence, the list ``[1, 2]`` is considered equal to\n ``[1.0, 2.0]``, and similarly for tuples.\n\n[3] They must have since the parser can\'t tell the type of the\n operands.\n\n[4] Cased characters are those with general category property being\n one of "Lu" (Letter, uppercase), "Ll" (Letter, lowercase), or "Lt"\n (Letter, titlecase).\n\n[5] To format only a tuple you should therefore provide a singleton\n tuple whose only element is the tuple to be formatted.\n',
+ 'specialnames': '\nSpecial method names\n********************\n\nA class can implement certain operations that are invoked by special\nsyntax (such as arithmetic operations or subscripting and slicing) by\ndefining methods with special names. This is Python\'s approach to\n*operator overloading*, allowing classes to define their own behavior\nwith respect to language operators. For instance, if a class defines\na method named ``__getitem__()``, and ``x`` is an instance of this\nclass, then ``x[i]`` is roughly equivalent to ``type(x).__getitem__(x,\ni)``. Except where mentioned, attempts to execute an operation raise\nan exception when no appropriate method is defined (typically\n``AttributeError`` or ``TypeError``).\n\nWhen implementing a class that emulates any built-in type, it is\nimportant that the emulation only be implemented to the degree that it\nmakes sense for the object being modelled. For example, some\nsequences may work well with retrieval of individual elements, but\nextracting a slice may not make sense. (One example of this is the\n``NodeList`` interface in the W3C\'s Document Object Model.)\n\n\nBasic customization\n===================\n\nobject.__new__(cls[, ...])\n\n Called to create a new instance of class *cls*. ``__new__()`` is a\n static method (special-cased so you need not declare it as such)\n that takes the class of which an instance was requested as its\n first argument. The remaining arguments are those passed to the\n object constructor expression (the call to the class). The return\n value of ``__new__()`` should be the new object instance (usually\n an instance of *cls*).\n\n Typical implementations create a new instance of the class by\n invoking the superclass\'s ``__new__()`` method using\n ``super(currentclass, cls).__new__(cls[, ...])`` with appropriate\n arguments and then modifying the newly-created instance as\n necessary before returning it.\n\n If ``__new__()`` returns an instance of *cls*, then the new\n instance\'s ``__init__()`` method will be invoked like\n ``__init__(self[, ...])``, where *self* is the new instance and the\n remaining arguments are the same as were passed to ``__new__()``.\n\n If ``__new__()`` does not return an instance of *cls*, then the new\n instance\'s ``__init__()`` method will not be invoked.\n\n ``__new__()`` is intended mainly to allow subclasses of immutable\n types (like int, str, or tuple) to customize instance creation. It\n is also commonly overridden in custom metaclasses in order to\n customize class creation.\n\nobject.__init__(self[, ...])\n\n Called when the instance is created. The arguments are those\n passed to the class constructor expression. If a base class has an\n ``__init__()`` method, the derived class\'s ``__init__()`` method,\n if any, must explicitly call it to ensure proper initialization of\n the base class part of the instance; for example:\n ``BaseClass.__init__(self, [args...])``. As a special constraint\n on constructors, no value may be returned; doing so will cause a\n ``TypeError`` to be raised at runtime.\n\nobject.__del__(self)\n\n Called when the instance is about to be destroyed. This is also\n called a destructor. If a base class has a ``__del__()`` method,\n the derived class\'s ``__del__()`` method, if any, must explicitly\n call it to ensure proper deletion of the base class part of the\n instance. Note that it is possible (though not recommended!) for\n the ``__del__()`` method to postpone destruction of the instance by\n creating a new reference to it. It may then be called at a later\n time when this new reference is deleted. It is not guaranteed that\n ``__del__()`` methods are called for objects that still exist when\n the interpreter exits.\n\n Note: ``del x`` doesn\'t directly call ``x.__del__()`` --- the former\n decrements the reference count for ``x`` by one, and the latter\n is only called when ``x``\'s reference count reaches zero. Some\n common situations that may prevent the reference count of an\n object from going to zero include: circular references between\n objects (e.g., a doubly-linked list or a tree data structure with\n parent and child pointers); a reference to the object on the\n stack frame of a function that caught an exception (the traceback\n stored in ``sys.exc_info()[2]`` keeps the stack frame alive); or\n a reference to the object on the stack frame that raised an\n unhandled exception in interactive mode (the traceback stored in\n ``sys.last_traceback`` keeps the stack frame alive). The first\n situation can only be remedied by explicitly breaking the cycles;\n the latter two situations can be resolved by storing ``None`` in\n ``sys.last_traceback``. Circular references which are garbage are\n detected when the option cycle detector is enabled (it\'s on by\n default), but can only be cleaned up if there are no Python-\n level ``__del__()`` methods involved. Refer to the documentation\n for the ``gc`` module for more information about how\n ``__del__()`` methods are handled by the cycle detector,\n particularly the description of the ``garbage`` value.\n\n Warning: Due to the precarious circumstances under which ``__del__()``\n methods are invoked, exceptions that occur during their execution\n are ignored, and a warning is printed to ``sys.stderr`` instead.\n Also, when ``__del__()`` is invoked in response to a module being\n deleted (e.g., when execution of the program is done), other\n globals referenced by the ``__del__()`` method may already have\n been deleted or in the process of being torn down (e.g. the\n import machinery shutting down). For this reason, ``__del__()``\n methods should do the absolute minimum needed to maintain\n external invariants. Starting with version 1.5, Python\n guarantees that globals whose name begins with a single\n underscore are deleted from their module before other globals are\n deleted; if no other references to such globals exist, this may\n help in assuring that imported modules are still available at the\n time when the ``__del__()`` method is called.\n\nobject.__repr__(self)\n\n Called by the ``repr()`` built-in function to compute the\n "official" string representation of an object. If at all possible,\n this should look like a valid Python expression that could be used\n to recreate an object with the same value (given an appropriate\n environment). If this is not possible, a string of the form\n ``<...some useful description...>`` should be returned. The return\n value must be a string object. If a class defines ``__repr__()``\n but not ``__str__()``, then ``__repr__()`` is also used when an\n "informal" string representation of instances of that class is\n required.\n\n This is typically used for debugging, so it is important that the\n representation is information-rich and unambiguous.\n\nobject.__str__(self)\n\n Called by the ``str()`` built-in function and by the ``print()``\n function to compute the "informal" string representation of an\n object. This differs from ``__repr__()`` in that it does not have\n to be a valid Python expression: a more convenient or concise\n representation may be used instead. The return value must be a\n string object.\n\nobject.__bytes__(self)\n\n Called by ``bytes()`` to compute a byte-string representation of an\n object. This should return a ``bytes`` object.\n\nobject.__format__(self, format_spec)\n\n Called by the ``format()`` built-in function (and by extension, the\n ``format()`` method of class ``str``) to produce a "formatted"\n string representation of an object. The ``format_spec`` argument is\n a string that contains a description of the formatting options\n desired. The interpretation of the ``format_spec`` argument is up\n to the type implementing ``__format__()``, however most classes\n will either delegate formatting to one of the built-in types, or\n use a similar formatting option syntax.\n\n See *Format Specification Mini-Language* for a description of the\n standard formatting syntax.\n\n The return value must be a string object.\n\nobject.__lt__(self, other)\nobject.__le__(self, other)\nobject.__eq__(self, other)\nobject.__ne__(self, other)\nobject.__gt__(self, other)\nobject.__ge__(self, other)\n\n These are the so-called "rich comparison" methods. The\n correspondence between operator symbols and method names is as\n follows: ``x<y`` calls ``x.__lt__(y)``, ``x<=y`` calls\n ``x.__le__(y)``, ``x==y`` calls ``x.__eq__(y)``, ``x!=y`` calls\n ``x.__ne__(y)``, ``x>y`` calls ``x.__gt__(y)``, and ``x>=y`` calls\n ``x.__ge__(y)``.\n\n A rich comparison method may return the singleton\n ``NotImplemented`` if it does not implement the operation for a\n given pair of arguments. By convention, ``False`` and ``True`` are\n returned for a successful comparison. However, these methods can\n return any value, so if the comparison operator is used in a\n Boolean context (e.g., in the condition of an ``if`` statement),\n Python will call ``bool()`` on the value to determine if the result\n is true or false.\n\n There are no implied relationships among the comparison operators.\n The truth of ``x==y`` does not imply that ``x!=y`` is false.\n Accordingly, when defining ``__eq__()``, one should also define\n ``__ne__()`` so that the operators will behave as expected. See\n the paragraph on ``__hash__()`` for some important notes on\n creating *hashable* objects which support custom comparison\n operations and are usable as dictionary keys.\n\n There are no swapped-argument versions of these methods (to be used\n when the left argument does not support the operation but the right\n argument does); rather, ``__lt__()`` and ``__gt__()`` are each\n other\'s reflection, ``__le__()`` and ``__ge__()`` are each other\'s\n reflection, and ``__eq__()`` and ``__ne__()`` are their own\n reflection.\n\n Arguments to rich comparison methods are never coerced.\n\n To automatically generate ordering operations from a single root\n operation, see ``functools.total_ordering()``.\n\nobject.__hash__(self)\n\n Called by built-in function ``hash()`` and for operations on\n members of hashed collections including ``set``, ``frozenset``, and\n ``dict``. ``__hash__()`` should return an integer. The only\n required property is that objects which compare equal have the same\n hash value; it is advised to somehow mix together (e.g. using\n exclusive or) the hash values for the components of the object that\n also play a part in comparison of objects.\n\n If a class does not define an ``__eq__()`` method it should not\n define a ``__hash__()`` operation either; if it defines\n ``__eq__()`` but not ``__hash__()``, its instances will not be\n usable as items in hashable collections. If a class defines\n mutable objects and implements an ``__eq__()`` method, it should\n not implement ``__hash__()``, since the implementation of hashable\n collections requires that a key\'s hash value is immutable (if the\n object\'s hash value changes, it will be in the wrong hash bucket).\n\n User-defined classes have ``__eq__()`` and ``__hash__()`` methods\n by default; with them, all objects compare unequal (except with\n themselves) and ``x.__hash__()`` returns ``id(x)``.\n\n Classes which inherit a ``__hash__()`` method from a parent class\n but change the meaning of ``__eq__()`` such that the hash value\n returned is no longer appropriate (e.g. by switching to a value-\n based concept of equality instead of the default identity based\n equality) can explicitly flag themselves as being unhashable by\n setting ``__hash__ = None`` in the class definition. Doing so means\n that not only will instances of the class raise an appropriate\n ``TypeError`` when a program attempts to retrieve their hash value,\n but they will also be correctly identified as unhashable when\n checking ``isinstance(obj, collections.Hashable)`` (unlike classes\n which define their own ``__hash__()`` to explicitly raise\n ``TypeError``).\n\n If a class that overrides ``__eq__()`` needs to retain the\n implementation of ``__hash__()`` from a parent class, the\n interpreter must be told this explicitly by setting ``__hash__ =\n <ParentClass>.__hash__``. Otherwise the inheritance of\n ``__hash__()`` will be blocked, just as if ``__hash__`` had been\n explicitly set to ``None``.\n\n Note: Note by default the ``__hash__()`` values of str, bytes and\n datetime objects are "salted" with an unpredictable random value.\n Although they remain constant within an individual Python\n process, they are not predictable between repeated invocations of\n Python.This is intended to provide protection against a denial-\n of-service caused by carefully-chosen inputs that exploit the\n worst case performance of a dict insertion, O(n^2) complexity.\n See http://www.ocert.org/advisories/ocert-2011-003.html for\n details.Changing hash values affects the order in which keys are\n retrieved from a dict. Note Python has never made guarantees\n about this ordering (and it typically varies between 32-bit and\n 64-bit builds).See also ``PYTHONHASHSEED``.\n\n Changed in version 3.3: Hash randomization is enabled by default.\n\nobject.__bool__(self)\n\n Called to implement truth value testing and the built-in operation\n ``bool()``; should return ``False`` or ``True``. When this method\n is not defined, ``__len__()`` is called, if it is defined, and the\n object is considered true if its result is nonzero. If a class\n defines neither ``__len__()`` nor ``__bool__()``, all its instances\n are considered true.\n\n\nCustomizing attribute access\n============================\n\nThe following methods can be defined to customize the meaning of\nattribute access (use of, assignment to, or deletion of ``x.name``)\nfor class instances.\n\nobject.__getattr__(self, name)\n\n Called when an attribute lookup has not found the attribute in the\n usual places (i.e. it is not an instance attribute nor is it found\n in the class tree for ``self``). ``name`` is the attribute name.\n This method should return the (computed) attribute value or raise\n an ``AttributeError`` exception.\n\n Note that if the attribute is found through the normal mechanism,\n ``__getattr__()`` is not called. (This is an intentional asymmetry\n between ``__getattr__()`` and ``__setattr__()``.) This is done both\n for efficiency reasons and because otherwise ``__getattr__()``\n would have no way to access other attributes of the instance. Note\n that at least for instance variables, you can fake total control by\n not inserting any values in the instance attribute dictionary (but\n instead inserting them in another object). See the\n ``__getattribute__()`` method below for a way to actually get total\n control over attribute access.\n\nobject.__getattribute__(self, name)\n\n Called unconditionally to implement attribute accesses for\n instances of the class. If the class also defines\n ``__getattr__()``, the latter will not be called unless\n ``__getattribute__()`` either calls it explicitly or raises an\n ``AttributeError``. This method should return the (computed)\n attribute value or raise an ``AttributeError`` exception. In order\n to avoid infinite recursion in this method, its implementation\n should always call the base class method with the same name to\n access any attributes it needs, for example,\n ``object.__getattribute__(self, name)``.\n\n Note: This method may still be bypassed when looking up special methods\n as the result of implicit invocation via language syntax or\n built-in functions. See *Special method lookup*.\n\nobject.__setattr__(self, name, value)\n\n Called when an attribute assignment is attempted. This is called\n instead of the normal mechanism (i.e. store the value in the\n instance dictionary). *name* is the attribute name, *value* is the\n value to be assigned to it.\n\n If ``__setattr__()`` wants to assign to an instance attribute, it\n should call the base class method with the same name, for example,\n ``object.__setattr__(self, name, value)``.\n\nobject.__delattr__(self, name)\n\n Like ``__setattr__()`` but for attribute deletion instead of\n assignment. This should only be implemented if ``del obj.name`` is\n meaningful for the object.\n\nobject.__dir__(self)\n\n Called when ``dir()`` is called on the object. A sequence must be\n returned. ``dir()`` converts the returned sequence to a list and\n sorts it.\n\n\nImplementing Descriptors\n------------------------\n\nThe following methods only apply when an instance of the class\ncontaining the method (a so-called *descriptor* class) appears in an\n*owner* class (the descriptor must be in either the owner\'s class\ndictionary or in the class dictionary for one of its parents). In the\nexamples below, "the attribute" refers to the attribute whose name is\nthe key of the property in the owner class\' ``__dict__``.\n\nobject.__get__(self, instance, owner)\n\n Called to get the attribute of the owner class (class attribute\n access) or of an instance of that class (instance attribute\n access). *owner* is always the owner class, while *instance* is the\n instance that the attribute was accessed through, or ``None`` when\n the attribute is accessed through the *owner*. This method should\n return the (computed) attribute value or raise an\n ``AttributeError`` exception.\n\nobject.__set__(self, instance, value)\n\n Called to set the attribute on an instance *instance* of the owner\n class to a new value, *value*.\n\nobject.__delete__(self, instance)\n\n Called to delete the attribute on an instance *instance* of the\n owner class.\n\n\nInvoking Descriptors\n--------------------\n\nIn general, a descriptor is an object attribute with "binding\nbehavior", one whose attribute access has been overridden by methods\nin the descriptor protocol: ``__get__()``, ``__set__()``, and\n``__delete__()``. If any of those methods are defined for an object,\nit is said to be a descriptor.\n\nThe default behavior for attribute access is to get, set, or delete\nthe attribute from an object\'s dictionary. For instance, ``a.x`` has a\nlookup chain starting with ``a.__dict__[\'x\']``, then\n``type(a).__dict__[\'x\']``, and continuing through the base classes of\n``type(a)`` excluding metaclasses.\n\nHowever, if the looked-up value is an object defining one of the\ndescriptor methods, then Python may override the default behavior and\ninvoke the descriptor method instead. Where this occurs in the\nprecedence chain depends on which descriptor methods were defined and\nhow they were called.\n\nThe starting point for descriptor invocation is a binding, ``a.x``.\nHow the arguments are assembled depends on ``a``:\n\nDirect Call\n The simplest and least common call is when user code directly\n invokes a descriptor method: ``x.__get__(a)``.\n\nInstance Binding\n If binding to an object instance, ``a.x`` is transformed into the\n call: ``type(a).__dict__[\'x\'].__get__(a, type(a))``.\n\nClass Binding\n If binding to a class, ``A.x`` is transformed into the call:\n ``A.__dict__[\'x\'].__get__(None, A)``.\n\nSuper Binding\n If ``a`` is an instance of ``super``, then the binding ``super(B,\n obj).m()`` searches ``obj.__class__.__mro__`` for the base class\n ``A`` immediately preceding ``B`` and then invokes the descriptor\n with the call: ``A.__dict__[\'m\'].__get__(obj, obj.__class__)``.\n\nFor instance bindings, the precedence of descriptor invocation depends\non the which descriptor methods are defined. A descriptor can define\nany combination of ``__get__()``, ``__set__()`` and ``__delete__()``.\nIf it does not define ``__get__()``, then accessing the attribute will\nreturn the descriptor object itself unless there is a value in the\nobject\'s instance dictionary. If the descriptor defines ``__set__()``\nand/or ``__delete__()``, it is a data descriptor; if it defines\nneither, it is a non-data descriptor. Normally, data descriptors\ndefine both ``__get__()`` and ``__set__()``, while non-data\ndescriptors have just the ``__get__()`` method. Data descriptors with\n``__set__()`` and ``__get__()`` defined always override a redefinition\nin an instance dictionary. In contrast, non-data descriptors can be\noverridden by instances.\n\nPython methods (including ``staticmethod()`` and ``classmethod()``)\nare implemented as non-data descriptors. Accordingly, instances can\nredefine and override methods. This allows individual instances to\nacquire behaviors that differ from other instances of the same class.\n\nThe ``property()`` function is implemented as a data descriptor.\nAccordingly, instances cannot override the behavior of a property.\n\n\n__slots__\n---------\n\nBy default, instances of classes have a dictionary for attribute\nstorage. This wastes space for objects having very few instance\nvariables. The space consumption can become acute when creating large\nnumbers of instances.\n\nThe default can be overridden by defining *__slots__* in a class\ndefinition. The *__slots__* declaration takes a sequence of instance\nvariables and reserves just enough space in each instance to hold a\nvalue for each variable. Space is saved because *__dict__* is not\ncreated for each instance.\n\nobject.__slots__\n\n This class variable can be assigned a string, iterable, or sequence\n of strings with variable names used by instances. If defined in a\n class, *__slots__* reserves space for the declared variables and\n prevents the automatic creation of *__dict__* and *__weakref__* for\n each instance.\n\n\nNotes on using *__slots__*\n~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n* When inheriting from a class without *__slots__*, the *__dict__*\n attribute of that class will always be accessible, so a *__slots__*\n definition in the subclass is meaningless.\n\n* Without a *__dict__* variable, instances cannot be assigned new\n variables not listed in the *__slots__* definition. Attempts to\n assign to an unlisted variable name raises ``AttributeError``. If\n dynamic assignment of new variables is desired, then add\n ``\'__dict__\'`` to the sequence of strings in the *__slots__*\n declaration.\n\n* Without a *__weakref__* variable for each instance, classes defining\n *__slots__* do not support weak references to its instances. If weak\n reference support is needed, then add ``\'__weakref__\'`` to the\n sequence of strings in the *__slots__* declaration.\n\n* *__slots__* are implemented at the class level by creating\n descriptors (*Implementing Descriptors*) for each variable name. As\n a result, class attributes cannot be used to set default values for\n instance variables defined by *__slots__*; otherwise, the class\n attribute would overwrite the descriptor assignment.\n\n* The action of a *__slots__* declaration is limited to the class\n where it is defined. As a result, subclasses will have a *__dict__*\n unless they also define *__slots__* (which must only contain names\n of any *additional* slots).\n\n* If a class defines a slot also defined in a base class, the instance\n variable defined by the base class slot is inaccessible (except by\n retrieving its descriptor directly from the base class). This\n renders the meaning of the program undefined. In the future, a\n check may be added to prevent this.\n\n* Nonempty *__slots__* does not work for classes derived from\n "variable-length" built-in types such as ``int``, ``str`` and\n ``tuple``.\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings may\n also be used; however, in the future, special meaning may be\n assigned to the values corresponding to each key.\n\n* *__class__* assignment works only if both classes have the same\n *__slots__*.\n\n\nCustomizing class creation\n==========================\n\nBy default, classes are constructed using ``type()``. A class\ndefinition is read into a separate namespace and the value of class\nname is bound to the result of ``type(name, bases, dict)``.\n\nWhen the class definition is read, if a callable ``metaclass`` keyword\nargument is passed after the bases in the class definition, the\ncallable given will be called instead of ``type()``. If other keyword\narguments are passed, they will also be passed to the metaclass. This\nallows classes or functions to be written which monitor or alter the\nclass creation process:\n\n* Modifying the class dictionary prior to the class being created.\n\n* Returning an instance of another class -- essentially performing the\n role of a factory function.\n\nThese steps will have to be performed in the metaclass\'s ``__new__()``\nmethod -- ``type.__new__()`` can then be called from this method to\ncreate a class with different properties. This example adds a new\nelement to the class dictionary before creating the class:\n\n class metacls(type):\n def __new__(mcs, name, bases, dict):\n dict[\'foo\'] = \'metacls was here\'\n return type.__new__(mcs, name, bases, dict)\n\nYou can of course also override other class methods (or add new\nmethods); for example defining a custom ``__call__()`` method in the\nmetaclass allows custom behavior when the class is called, e.g. not\nalways creating a new instance.\n\nIf the metaclass has a ``__prepare__()`` attribute (usually\nimplemented as a class or static method), it is called before the\nclass body is evaluated with the name of the class and a tuple of its\nbases for arguments. It should return an object that supports the\nmapping interface that will be used to store the namespace of the\nclass. The default is a plain dictionary. This could be used, for\nexample, to keep track of the order that class attributes are declared\nin by returning an ordered dictionary.\n\nThe appropriate metaclass is determined by the following precedence\nrules:\n\n* If the ``metaclass`` keyword argument is passed with the bases, it\n is used.\n\n* Otherwise, if there is at least one base class, its metaclass is\n used.\n\n* Otherwise, the default metaclass (``type``) is used.\n\nThe potential uses for metaclasses are boundless. Some ideas that have\nbeen explored including logging, interface checking, automatic\ndelegation, automatic property creation, proxies, frameworks, and\nautomatic resource locking/synchronization.\n\nHere is an example of a metaclass that uses an\n``collections.OrderedDict`` to remember the order that class members\nwere defined:\n\n class OrderedClass(type):\n\n @classmethod\n def __prepare__(metacls, name, bases, **kwds):\n return collections.OrderedDict()\n\n def __new__(cls, name, bases, classdict):\n result = type.__new__(cls, name, bases, dict(classdict))\n result.members = tuple(classdict)\n return result\n\n class A(metaclass=OrderedClass):\n def one(self): pass\n def two(self): pass\n def three(self): pass\n def four(self): pass\n\n >>> A.members\n (\'__module__\', \'one\', \'two\', \'three\', \'four\')\n\nWhen the class definition for *A* gets executed, the process begins\nwith calling the metaclass\'s ``__prepare__()`` method which returns an\nempty ``collections.OrderedDict``. That mapping records the methods\nand attributes of *A* as they are defined within the body of the class\nstatement. Once those definitions are executed, the ordered dictionary\nis fully populated and the metaclass\'s ``__new__()`` method gets\ninvoked. That method builds the new type and it saves the ordered\ndictionary keys in an attribute called ``members``.\n\n\nCustomizing instance and subclass checks\n========================================\n\nThe following methods are used to override the default behavior of the\n``isinstance()`` and ``issubclass()`` built-in functions.\n\nIn particular, the metaclass ``abc.ABCMeta`` implements these methods\nin order to allow the addition of Abstract Base Classes (ABCs) as\n"virtual base classes" to any class or type (including built-in\ntypes), including other ABCs.\n\nclass.__instancecheck__(self, instance)\n\n Return true if *instance* should be considered a (direct or\n indirect) instance of *class*. If defined, called to implement\n ``isinstance(instance, class)``.\n\nclass.__subclasscheck__(self, subclass)\n\n Return true if *subclass* should be considered a (direct or\n indirect) subclass of *class*. If defined, called to implement\n ``issubclass(subclass, class)``.\n\nNote that these methods are looked up on the type (metaclass) of a\nclass. They cannot be defined as class methods in the actual class.\nThis is consistent with the lookup of special methods that are called\non instances, only in this case the instance is itself a class.\n\nSee also:\n\n **PEP 3119** - Introducing Abstract Base Classes\n Includes the specification for customizing ``isinstance()`` and\n ``issubclass()`` behavior through ``__instancecheck__()`` and\n ``__subclasscheck__()``, with motivation for this functionality\n in the context of adding Abstract Base Classes (see the ``abc``\n module) to the language.\n\n\nEmulating callable objects\n==========================\n\nobject.__call__(self[, args...])\n\n Called when the instance is "called" as a function; if this method\n is defined, ``x(arg1, arg2, ...)`` is a shorthand for\n ``x.__call__(arg1, arg2, ...)``.\n\n\nEmulating container types\n=========================\n\nThe following methods can be defined to implement container objects.\nContainers usually are sequences (such as lists or tuples) or mappings\n(like dictionaries), but can represent other containers as well. The\nfirst set of methods is used either to emulate a sequence or to\nemulate a mapping; the difference is that for a sequence, the\nallowable keys should be the integers *k* for which ``0 <= k < N``\nwhere *N* is the length of the sequence, or slice objects, which\ndefine a range of items. It is also recommended that mappings provide\nthe methods ``keys()``, ``values()``, ``items()``, ``get()``,\n``clear()``, ``setdefault()``, ``pop()``, ``popitem()``, ``copy()``,\nand ``update()`` behaving similar to those for Python\'s standard\ndictionary objects. The ``collections`` module provides a\n``MutableMapping`` abstract base class to help create those methods\nfrom a base set of ``__getitem__()``, ``__setitem__()``,\n``__delitem__()``, and ``keys()``. Mutable sequences should provide\nmethods ``append()``, ``count()``, ``index()``, ``extend()``,\n``insert()``, ``pop()``, ``remove()``, ``reverse()`` and ``sort()``,\nlike Python standard list objects. Finally, sequence types should\nimplement addition (meaning concatenation) and multiplication (meaning\nrepetition) by defining the methods ``__add__()``, ``__radd__()``,\n``__iadd__()``, ``__mul__()``, ``__rmul__()`` and ``__imul__()``\ndescribed below; they should not define other numerical operators. It\nis recommended that both mappings and sequences implement the\n``__contains__()`` method to allow efficient use of the ``in``\noperator; for mappings, ``in`` should search the mapping\'s keys; for\nsequences, it should search through the values. It is further\nrecommended that both mappings and sequences implement the\n``__iter__()`` method to allow efficient iteration through the\ncontainer; for mappings, ``__iter__()`` should be the same as\n``keys()``; for sequences, it should iterate through the values.\n\nobject.__len__(self)\n\n Called to implement the built-in function ``len()``. Should return\n the length of the object, an integer ``>=`` 0. Also, an object\n that doesn\'t define a ``__bool__()`` method and whose ``__len__()``\n method returns zero is considered to be false in a Boolean context.\n\nNote: Slicing is done exclusively with the following three methods. A\n call like\n\n a[1:2] = b\n\n is translated to\n\n a[slice(1, 2, None)] = b\n\n and so forth. Missing slice items are always filled in with\n ``None``.\n\nobject.__getitem__(self, key)\n\n Called to implement evaluation of ``self[key]``. For sequence\n types, the accepted keys should be integers and slice objects.\n Note that the special interpretation of negative indexes (if the\n class wishes to emulate a sequence type) is up to the\n ``__getitem__()`` method. If *key* is of an inappropriate type,\n ``TypeError`` may be raised; if of a value outside the set of\n indexes for the sequence (after any special interpretation of\n negative values), ``IndexError`` should be raised. For mapping\n types, if *key* is missing (not in the container), ``KeyError``\n should be raised.\n\n Note: ``for`` loops expect that an ``IndexError`` will be raised for\n illegal indexes to allow proper detection of the end of the\n sequence.\n\nobject.__setitem__(self, key, value)\n\n Called to implement assignment to ``self[key]``. Same note as for\n ``__getitem__()``. This should only be implemented for mappings if\n the objects support changes to the values for keys, or if new keys\n can be added, or for sequences if elements can be replaced. The\n same exceptions should be raised for improper *key* values as for\n the ``__getitem__()`` method.\n\nobject.__delitem__(self, key)\n\n Called to implement deletion of ``self[key]``. Same note as for\n ``__getitem__()``. This should only be implemented for mappings if\n the objects support removal of keys, or for sequences if elements\n can be removed from the sequence. The same exceptions should be\n raised for improper *key* values as for the ``__getitem__()``\n method.\n\nobject.__iter__(self)\n\n This method is called when an iterator is required for a container.\n This method should return a new iterator object that can iterate\n over all the objects in the container. For mappings, it should\n iterate over the keys of the container, and should also be made\n available as the method ``keys()``.\n\n Iterator objects also need to implement this method; they are\n required to return themselves. For more information on iterator\n objects, see *Iterator Types*.\n\nobject.__reversed__(self)\n\n Called (if present) by the ``reversed()`` built-in to implement\n reverse iteration. It should return a new iterator object that\n iterates over all the objects in the container in reverse order.\n\n If the ``__reversed__()`` method is not provided, the\n ``reversed()`` built-in will fall back to using the sequence\n protocol (``__len__()`` and ``__getitem__()``). Objects that\n support the sequence protocol should only provide\n ``__reversed__()`` if they can provide an implementation that is\n more efficient than the one provided by ``reversed()``.\n\nThe membership test operators (``in`` and ``not in``) are normally\nimplemented as an iteration through a sequence. However, container\nobjects can supply the following special method with a more efficient\nimplementation, which also does not require the object be a sequence.\n\nobject.__contains__(self, item)\n\n Called to implement membership test operators. Should return true\n if *item* is in *self*, false otherwise. For mapping objects, this\n should consider the keys of the mapping rather than the values or\n the key-item pairs.\n\n For objects that don\'t define ``__contains__()``, the membership\n test first tries iteration via ``__iter__()``, then the old\n sequence iteration protocol via ``__getitem__()``, see *this\n section in the language reference*.\n\n\nEmulating numeric types\n=======================\n\nThe following methods can be defined to emulate numeric objects.\nMethods corresponding to operations that are not supported by the\nparticular kind of number implemented (e.g., bitwise operations for\nnon-integral numbers) should be left undefined.\n\nobject.__add__(self, other)\nobject.__sub__(self, other)\nobject.__mul__(self, other)\nobject.__truediv__(self, other)\nobject.__floordiv__(self, other)\nobject.__mod__(self, other)\nobject.__divmod__(self, other)\nobject.__pow__(self, other[, modulo])\nobject.__lshift__(self, other)\nobject.__rshift__(self, other)\nobject.__and__(self, other)\nobject.__xor__(self, other)\nobject.__or__(self, other)\n\n These methods are called to implement the binary arithmetic\n operations (``+``, ``-``, ``*``, ``/``, ``//``, ``%``,\n ``divmod()``, ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``,\n ``|``). For instance, to evaluate the expression ``x + y``, where\n *x* is an instance of a class that has an ``__add__()`` method,\n ``x.__add__(y)`` is called. The ``__divmod__()`` method should be\n the equivalent to using ``__floordiv__()`` and ``__mod__()``; it\n should not be related to ``__truediv__()``. Note that\n ``__pow__()`` should be defined to accept an optional third\n argument if the ternary version of the built-in ``pow()`` function\n is to be supported.\n\n If one of those methods does not support the operation with the\n supplied arguments, it should return ``NotImplemented``.\n\nobject.__radd__(self, other)\nobject.__rsub__(self, other)\nobject.__rmul__(self, other)\nobject.__rtruediv__(self, other)\nobject.__rfloordiv__(self, other)\nobject.__rmod__(self, other)\nobject.__rdivmod__(self, other)\nobject.__rpow__(self, other)\nobject.__rlshift__(self, other)\nobject.__rrshift__(self, other)\nobject.__rand__(self, other)\nobject.__rxor__(self, other)\nobject.__ror__(self, other)\n\n These methods are called to implement the binary arithmetic\n operations (``+``, ``-``, ``*``, ``/``, ``//``, ``%``,\n ``divmod()``, ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``,\n ``|``) with reflected (swapped) operands. These functions are only\n called if the left operand does not support the corresponding\n operation and the operands are of different types. [2] For\n instance, to evaluate the expression ``x - y``, where *y* is an\n instance of a class that has an ``__rsub__()`` method,\n ``y.__rsub__(x)`` is called if ``x.__sub__(y)`` returns\n *NotImplemented*.\n\n Note that ternary ``pow()`` will not try calling ``__rpow__()``\n (the coercion rules would become too complicated).\n\n Note: If the right operand\'s type is a subclass of the left operand\'s\n type and that subclass provides the reflected method for the\n operation, this method will be called before the left operand\'s\n non-reflected method. This behavior allows subclasses to\n override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__itruediv__(self, other)\nobject.__ifloordiv__(self, other)\nobject.__imod__(self, other)\nobject.__ipow__(self, other[, modulo])\nobject.__ilshift__(self, other)\nobject.__irshift__(self, other)\nobject.__iand__(self, other)\nobject.__ixor__(self, other)\nobject.__ior__(self, other)\n\n These methods are called to implement the augmented arithmetic\n assignments (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,\n ``**=``, ``<<=``, ``>>=``, ``&=``, ``^=``, ``|=``). These methods\n should attempt to do the operation in-place (modifying *self*) and\n return the result (which could be, but does not have to be,\n *self*). If a specific method is not defined, the augmented\n assignment falls back to the normal methods. For instance, to\n execute the statement ``x += y``, where *x* is an instance of a\n class that has an ``__iadd__()`` method, ``x.__iadd__(y)`` is\n called. If *x* is an instance of a class that does not define a\n ``__iadd__()`` method, ``x.__add__(y)`` and ``y.__radd__(x)`` are\n considered, as with the evaluation of ``x + y``.\n\nobject.__neg__(self)\nobject.__pos__(self)\nobject.__abs__(self)\nobject.__invert__(self)\n\n Called to implement the unary arithmetic operations (``-``, ``+``,\n ``abs()`` and ``~``).\n\nobject.__complex__(self)\nobject.__int__(self)\nobject.__float__(self)\nobject.__round__(self[, n])\n\n Called to implement the built-in functions ``complex()``,\n ``int()``, ``float()`` and ``round()``. Should return a value of\n the appropriate type.\n\nobject.__index__(self)\n\n Called to implement ``operator.index()``. Also called whenever\n Python needs an integer object (such as in slicing, or in the\n built-in ``bin()``, ``hex()`` and ``oct()`` functions). Must return\n an integer.\n\n\nWith Statement Context Managers\n===============================\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a ``with`` statement. The context\nmanager handles the entry into, and the exit from, the desired runtime\ncontext for the execution of the block of code. Context managers are\nnormally invoked using the ``with`` statement (described in section\n*The with statement*), but can also be used by directly invoking their\nmethods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n Enter the runtime context related to this object. The ``with``\n statement will bind this method\'s return value to the target(s)\n specified in the ``as`` clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n Exit the runtime context related to this object. The parameters\n describe the exception that caused the context to be exited. If the\n context was exited without an exception, all three arguments will\n be ``None``.\n\n If an exception is supplied, and the method wishes to suppress the\n exception (i.e., prevent it from being propagated), it should\n return a true value. Otherwise, the exception will be processed\n normally upon exit from this method.\n\n Note that ``__exit__()`` methods should not reraise the passed-in\n exception; this is the caller\'s responsibility.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n\n\nSpecial method lookup\n=====================\n\nFor custom classes, implicit invocations of special methods are only\nguaranteed to work correctly if defined on an object\'s type, not in\nthe object\'s instance dictionary. That behaviour is the reason why\nthe following code raises an exception:\n\n >>> class C:\n ... pass\n ...\n >>> c = C()\n >>> c.__len__ = lambda: 5\n >>> len(c)\n Traceback (most recent call last):\n File "<stdin>", line 1, in <module>\n TypeError: object of type \'C\' has no len()\n\nThe rationale behind this behaviour lies with a number of special\nmethods such as ``__hash__()`` and ``__repr__()`` that are implemented\nby all objects, including type objects. If the implicit lookup of\nthese methods used the conventional lookup process, they would fail\nwhen invoked on the type object itself:\n\n >>> 1 .__hash__() == hash(1)\n True\n >>> int.__hash__() == hash(int)\n Traceback (most recent call last):\n File "<stdin>", line 1, in <module>\n TypeError: descriptor \'__hash__\' of \'int\' object needs an argument\n\nIncorrectly attempting to invoke an unbound method of a class in this\nway is sometimes referred to as \'metaclass confusion\', and is avoided\nby bypassing the instance when looking up special methods:\n\n >>> type(1).__hash__(1) == hash(1)\n True\n >>> type(int).__hash__(int) == hash(int)\n True\n\nIn addition to bypassing any instance attributes in the interest of\ncorrectness, implicit special method lookup generally also bypasses\nthe ``__getattribute__()`` method even of the object\'s metaclass:\n\n >>> class Meta(type):\n ... def __getattribute__(*args):\n ... print("Metaclass getattribute invoked")\n ... return type.__getattribute__(*args)\n ...\n >>> class C(object, metaclass=Meta):\n ... def __len__(self):\n ... return 10\n ... def __getattribute__(*args):\n ... print("Class getattribute invoked")\n ... return object.__getattribute__(*args)\n ...\n >>> c = C()\n >>> c.__len__() # Explicit lookup via instance\n Class getattribute invoked\n 10\n >>> type(c).__len__(c) # Explicit lookup via type\n Metaclass getattribute invoked\n 10\n >>> len(c) # Implicit lookup\n 10\n\nBypassing the ``__getattribute__()`` machinery in this fashion\nprovides significant scope for speed optimisations within the\ninterpreter, at the cost of some flexibility in the handling of\nspecial methods (the special method *must* be set on the class object\nitself in order to be consistently invoked by the interpreter).\n\n-[ Footnotes ]-\n\n[1] It *is* possible in some cases to change an object\'s type, under\n certain controlled conditions. It generally isn\'t a good idea\n though, since it can lead to some very strange behaviour if it is\n handled incorrectly.\n\n[2] For operands of the same type, it is assumed that if the non-\n reflected method (such as ``__add__()``) fails the operation is\n not supported, which is why the reflected method is not called.\n',
+ 'string-methods': '\nString Methods\n**************\n\nString objects support the methods listed below.\n\nIn addition, Python\'s strings support the sequence type methods\ndescribed in the *Sequence Types --- str, bytes, bytearray, list,\ntuple, range* section. To output formatted strings, see the *String\nFormatting* section. Also, see the ``re`` module for string functions\nbased on regular expressions.\n\nstr.capitalize()\n\n Return a copy of the string with its first character capitalized\n and the rest lowercased.\n\nstr.casefold()\n\n Return a casefolded copy of the string. Casefolded strings may be\n used for caseless matching.\n\n Casefolding is similar to lowercasing but more aggressive because\n it is intended to remove all case distinctions in a string. For\n example, the German lowercase letter ``\'\xc3\x9f\'`` is equivalent to\n ``"ss"``. Since it is already lowercase, ``lower()`` would do\n nothing to ``\'\xc3\x9f\'``; ``casefold()`` converts it to ``"ss"``.\n\n The casefolding algorithm is described in section 3.13 of the\n Unicode Standard.\n\n New in version 3.3.\n\nstr.center(width[, fillchar])\n\n Return centered in a string of length *width*. Padding is done\n using the specified *fillchar* (default is a space).\n\nstr.count(sub[, start[, end]])\n\n Return the number of non-overlapping occurrences of substring *sub*\n in the range [*start*, *end*]. Optional arguments *start* and\n *end* are interpreted as in slice notation.\n\nstr.encode(encoding="utf-8", errors="strict")\n\n Return an encoded version of the string as a bytes object. Default\n encoding is ``\'utf-8\'``. *errors* may be given to set a different\n error handling scheme. The default for *errors* is ``\'strict\'``,\n meaning that encoding errors raise a ``UnicodeError``. Other\n possible values are ``\'ignore\'``, ``\'replace\'``,\n ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and any other name\n registered via ``codecs.register_error()``, see section *Codec Base\n Classes*. For a list of possible encodings, see section *Standard\n Encodings*.\n\n Changed in version 3.1: Support for keyword arguments added.\n\nstr.endswith(suffix[, start[, end]])\n\n Return ``True`` if the string ends with the specified *suffix*,\n otherwise return ``False``. *suffix* can also be a tuple of\n suffixes to look for. With optional *start*, test beginning at\n that position. With optional *end*, stop comparing at that\n position.\n\nstr.expandtabs([tabsize])\n\n Return a copy of the string where all tab characters are replaced\n by zero or more spaces, depending on the current column and the\n given tab size. The column number is reset to zero after each\n newline occurring in the string. If *tabsize* is not given, a tab\n size of ``8`` characters is assumed. This doesn\'t understand other\n non-printing characters or escape sequences.\n\nstr.find(sub[, start[, end]])\n\n Return the lowest index in the string where substring *sub* is\n found, such that *sub* is contained in the slice ``s[start:end]``.\n Optional arguments *start* and *end* are interpreted as in slice\n notation. Return ``-1`` if *sub* is not found.\n\n Note: The ``find()`` method should be used only if you need to know the\n position of *sub*. To check if *sub* is a substring or not, use\n the ``in`` operator:\n\n >>> \'Py\' in \'Python\'\n True\n\nstr.format(*args, **kwargs)\n\n Perform a string formatting operation. The string on which this\n method is called can contain literal text or replacement fields\n delimited by braces ``{}``. Each replacement field contains either\n the numeric index of a positional argument, or the name of a\n keyword argument. Returns a copy of the string where each\n replacement field is replaced with the string value of the\n corresponding argument.\n\n >>> "The sum of 1 + 2 is {0}".format(1+2)\n \'The sum of 1 + 2 is 3\'\n\n See *Format String Syntax* for a description of the various\n formatting options that can be specified in format strings.\n\nstr.format_map(mapping)\n\n Similar to ``str.format(**mapping)``, except that ``mapping`` is\n used directly and not copied to a ``dict`` . This is useful if for\n example ``mapping`` is a dict subclass:\n\n >>> class Default(dict):\n ... def __missing__(self, key):\n ... return key\n ...\n >>> \'{name} was born in {country}\'.format_map(Default(name=\'Guido\'))\n \'Guido was born in country\'\n\n New in version 3.2.\n\nstr.index(sub[, start[, end]])\n\n Like ``find()``, but raise ``ValueError`` when the substring is not\n found.\n\nstr.isalnum()\n\n Return true if all characters in the string are alphanumeric and\n there is at least one character, false otherwise. A character\n ``c`` is alphanumeric if one of the following returns ``True``:\n ``c.isalpha()``, ``c.isdecimal()``, ``c.isdigit()``, or\n ``c.isnumeric()``.\n\nstr.isalpha()\n\n Return true if all characters in the string are alphabetic and\n there is at least one character, false otherwise. Alphabetic\n characters are those characters defined in the Unicode character\n database as "Letter", i.e., those with general category property\n being one of "Lm", "Lt", "Lu", "Ll", or "Lo". Note that this is\n different from the "Alphabetic" property defined in the Unicode\n Standard.\n\nstr.isdecimal()\n\n Return true if all characters in the string are decimal characters\n and there is at least one character, false otherwise. Decimal\n characters are those from general category "Nd". This category\n includes digit characters, and all characters that can be used to\n form decimal-radix numbers, e.g. U+0660, ARABIC-INDIC DIGIT ZERO.\n\nstr.isdigit()\n\n Return true if all characters in the string are digits and there is\n at least one character, false otherwise. Digits include decimal\n characters and digits that need special handling, such as the\n compatibility superscript digits. Formally, a digit is a character\n that has the property value Numeric_Type=Digit or\n Numeric_Type=Decimal.\n\nstr.isidentifier()\n\n Return true if the string is a valid identifier according to the\n language definition, section *Identifiers and keywords*.\n\nstr.islower()\n\n Return true if all cased characters [4] in the string are lowercase\n and there is at least one cased character, false otherwise.\n\nstr.isnumeric()\n\n Return true if all characters in the string are numeric characters,\n and there is at least one character, false otherwise. Numeric\n characters include digit characters, and all characters that have\n the Unicode numeric value property, e.g. U+2155, VULGAR FRACTION\n ONE FIFTH. Formally, numeric characters are those with the\n property value Numeric_Type=Digit, Numeric_Type=Decimal or\n Numeric_Type=Numeric.\n\nstr.isprintable()\n\n Return true if all characters in the string are printable or the\n string is empty, false otherwise. Nonprintable characters are\n those characters defined in the Unicode character database as\n "Other" or "Separator", excepting the ASCII space (0x20) which is\n considered printable. (Note that printable characters in this\n context are those which should not be escaped when ``repr()`` is\n invoked on a string. It has no bearing on the handling of strings\n written to ``sys.stdout`` or ``sys.stderr``.)\n\nstr.isspace()\n\n Return true if there are only whitespace characters in the string\n and there is at least one character, false otherwise. Whitespace\n characters are those characters defined in the Unicode character\n database as "Other" or "Separator" and those with bidirectional\n property being one of "WS", "B", or "S".\n\nstr.istitle()\n\n Return true if the string is a titlecased string and there is at\n least one character, for example uppercase characters may only\n follow uncased characters and lowercase characters only cased ones.\n Return false otherwise.\n\nstr.isupper()\n\n Return true if all cased characters [4] in the string are uppercase\n and there is at least one cased character, false otherwise.\n\nstr.join(iterable)\n\n Return a string which is the concatenation of the strings in the\n *iterable* *iterable*. A ``TypeError`` will be raised if there are\n any non-string values in *iterable*, including ``bytes`` objects.\n The separator between elements is the string providing this method.\n\nstr.ljust(width[, fillchar])\n\n Return the string left justified in a string of length *width*.\n Padding is done using the specified *fillchar* (default is a\n space). The original string is returned if *width* is less than or\n equal to ``len(s)``.\n\nstr.lower()\n\n Return a copy of the string with all the cased characters [4]\n converted to lowercase.\n\n The lowercasing algorithm used is described in section 3.13 of the\n Unicode Standard.\n\nstr.lstrip([chars])\n\n Return a copy of the string with leading characters removed. The\n *chars* argument is a string specifying the set of characters to be\n removed. If omitted or ``None``, the *chars* argument defaults to\n removing whitespace. The *chars* argument is not a prefix; rather,\n all combinations of its values are stripped:\n\n >>> \' spacious \'.lstrip()\n \'spacious \'\n >>> \'www.example.com\'.lstrip(\'cmowz.\')\n \'example.com\'\n\nstatic str.maketrans(x[, y[, z]])\n\n This static method returns a translation table usable for\n ``str.translate()``.\n\n If there is only one argument, it must be a dictionary mapping\n Unicode ordinals (integers) or characters (strings of length 1) to\n Unicode ordinals, strings (of arbitrary lengths) or None.\n Character keys will then be converted to ordinals.\n\n If there are two arguments, they must be strings of equal length,\n and in the resulting dictionary, each character in x will be mapped\n to the character at the same position in y. If there is a third\n argument, it must be a string, whose characters will be mapped to\n None in the result.\n\nstr.partition(sep)\n\n Split the string at the first occurrence of *sep*, and return a\n 3-tuple containing the part before the separator, the separator\n itself, and the part after the separator. If the separator is not\n found, return a 3-tuple containing the string itself, followed by\n two empty strings.\n\nstr.replace(old, new[, count])\n\n Return a copy of the string with all occurrences of substring *old*\n replaced by *new*. If the optional argument *count* is given, only\n the first *count* occurrences are replaced.\n\nstr.rfind(sub[, start[, end]])\n\n Return the highest index in the string where substring *sub* is\n found, such that *sub* is contained within ``s[start:end]``.\n Optional arguments *start* and *end* are interpreted as in slice\n notation. Return ``-1`` on failure.\n\nstr.rindex(sub[, start[, end]])\n\n Like ``rfind()`` but raises ``ValueError`` when the substring *sub*\n is not found.\n\nstr.rjust(width[, fillchar])\n\n Return the string right justified in a string of length *width*.\n Padding is done using the specified *fillchar* (default is a\n space). The original string is returned if *width* is less than or\n equal to ``len(s)``.\n\nstr.rpartition(sep)\n\n Split the string at the last occurrence of *sep*, and return a\n 3-tuple containing the part before the separator, the separator\n itself, and the part after the separator. If the separator is not\n found, return a 3-tuple containing two empty strings, followed by\n the string itself.\n\nstr.rsplit(sep=None, maxsplit=-1)\n\n Return a list of the words in the string, using *sep* as the\n delimiter string. If *maxsplit* is given, at most *maxsplit* splits\n are done, the *rightmost* ones. If *sep* is not specified or\n ``None``, any whitespace string is a separator. Except for\n splitting from the right, ``rsplit()`` behaves like ``split()``\n which is described in detail below.\n\nstr.rstrip([chars])\n\n Return a copy of the string with trailing characters removed. The\n *chars* argument is a string specifying the set of characters to be\n removed. If omitted or ``None``, the *chars* argument defaults to\n removing whitespace. The *chars* argument is not a suffix; rather,\n all combinations of its values are stripped:\n\n >>> \' spacious \'.rstrip()\n \' spacious\'\n >>> \'mississippi\'.rstrip(\'ipz\')\n \'mississ\'\n\nstr.split(sep=None, maxsplit=-1)\n\n Return a list of the words in the string, using *sep* as the\n delimiter string. If *maxsplit* is given, at most *maxsplit*\n splits are done (thus, the list will have at most ``maxsplit+1``\n elements). If *maxsplit* is not specified, then there is no limit\n on the number of splits (all possible splits are made).\n\n If *sep* is given, consecutive delimiters are not grouped together\n and are deemed to delimit empty strings (for example,\n ``\'1,,2\'.split(\',\')`` returns ``[\'1\', \'\', \'2\']``). The *sep*\n argument may consist of multiple characters (for example,\n ``\'1<>2<>3\'.split(\'<>\')`` returns ``[\'1\', \'2\', \'3\']``). Splitting\n an empty string with a specified separator returns ``[\'\']``.\n\n If *sep* is not specified or is ``None``, a different splitting\n algorithm is applied: runs of consecutive whitespace are regarded\n as a single separator, and the result will contain no empty strings\n at the start or end if the string has leading or trailing\n whitespace. Consequently, splitting an empty string or a string\n consisting of just whitespace with a ``None`` separator returns\n ``[]``.\n\n For example, ``\' 1 2 3 \'.split()`` returns ``[\'1\', \'2\', \'3\']``,\n and ``\' 1 2 3 \'.split(None, 1)`` returns ``[\'1\', \'2 3 \']``.\n\nstr.splitlines([keepends])\n\n Return a list of the lines in the string, breaking at line\n boundaries. Line breaks are not included in the resulting list\n unless *keepends* is given and true.\n\nstr.startswith(prefix[, start[, end]])\n\n Return ``True`` if string starts with the *prefix*, otherwise\n return ``False``. *prefix* can also be a tuple of prefixes to look\n for. With optional *start*, test string beginning at that\n position. With optional *end*, stop comparing string at that\n position.\n\nstr.strip([chars])\n\n Return a copy of the string with the leading and trailing\n characters removed. The *chars* argument is a string specifying the\n set of characters to be removed. If omitted or ``None``, the\n *chars* argument defaults to removing whitespace. The *chars*\n argument is not a prefix or suffix; rather, all combinations of its\n values are stripped:\n\n >>> \' spacious \'.strip()\n \'spacious\'\n >>> \'www.example.com\'.strip(\'cmowz.\')\n \'example\'\n\nstr.swapcase()\n\n Return a copy of the string with uppercase characters converted to\n lowercase and vice versa. Note that it is not necessarily true that\n ``s.swapcase().swapcase() == s``.\n\nstr.title()\n\n Return a titlecased version of the string where words start with an\n uppercase character and the remaining characters are lowercase.\n\n The algorithm uses a simple language-independent definition of a\n word as groups of consecutive letters. The definition works in\n many contexts but it means that apostrophes in contractions and\n possessives form word boundaries, which may not be the desired\n result:\n\n >>> "they\'re bill\'s friends from the UK".title()\n "They\'Re Bill\'S Friends From The Uk"\n\n A workaround for apostrophes can be constructed using regular\n expressions:\n\n >>> import re\n >>> def titlecase(s):\n return re.sub(r"[A-Za-z]+(\'[A-Za-z]+)?",\n lambda mo: mo.group(0)[0].upper() +\n mo.group(0)[1:].lower(),\n s)\n\n >>> titlecase("they\'re bill\'s friends.")\n "They\'re Bill\'s Friends."\n\nstr.translate(map)\n\n Return a copy of the *s* where all characters have been mapped\n through the *map* which must be a dictionary of Unicode ordinals\n (integers) to Unicode ordinals, strings or ``None``. Unmapped\n characters are left untouched. Characters mapped to ``None`` are\n deleted.\n\n You can use ``str.maketrans()`` to create a translation map from\n character-to-character mappings in different formats.\n\n Note: An even more flexible approach is to create a custom character\n mapping codec using the ``codecs`` module (see\n ``encodings.cp1251`` for an example).\n\nstr.upper()\n\n Return a copy of the string with all the cased characters [4]\n converted to uppercase. Note that ``str.upper().isupper()`` might\n be ``False`` if ``s`` contains uncased characters or if the Unicode\n category of the resulting character(s) is not "Lu" (Letter,\n uppercase), but e.g. "Lt" (Letter, titlecase).\n\n The uppercasing algorithm used is described in section 3.13 of the\n Unicode Standard.\n\nstr.zfill(width)\n\n Return the numeric string left filled with zeros in a string of\n length *width*. A sign prefix is handled correctly. The original\n string is returned if *width* is less than or equal to ``len(s)``.\n',
+ 'strings': '\nString and Bytes literals\n*************************\n\nString literals are described by the following lexical definitions:\n\n stringliteral ::= [stringprefix](shortstring | longstring)\n stringprefix ::= "r" | "u" | "ur" | "R" | "U" | "UR" | "Ur" | "uR"\n shortstring ::= "\'" shortstringitem* "\'" | \'"\' shortstringitem* \'"\'\n longstring ::= "\'\'\'" longstringitem* "\'\'\'" | \'"""\' longstringitem* \'"""\'\n shortstringitem ::= shortstringchar | stringescapeseq\n longstringitem ::= longstringchar | stringescapeseq\n shortstringchar ::= <any source character except "\\" or newline or the quote>\n longstringchar ::= <any source character except "\\">\n stringescapeseq ::= "\\" <any source character>\n\n bytesliteral ::= bytesprefix(shortbytes | longbytes)\n bytesprefix ::= "b" | "B" | "br" | "Br" | "bR" | "BR" | "rb" | "rB" | "Rb" | "RB"\n shortbytes ::= "\'" shortbytesitem* "\'" | \'"\' shortbytesitem* \'"\'\n longbytes ::= "\'\'\'" longbytesitem* "\'\'\'" | \'"""\' longbytesitem* \'"""\'\n shortbytesitem ::= shortbyteschar | bytesescapeseq\n longbytesitem ::= longbyteschar | bytesescapeseq\n shortbyteschar ::= <any ASCII character except "\\" or newline or the quote>\n longbyteschar ::= <any ASCII character except "\\">\n bytesescapeseq ::= "\\" <any ASCII character>\n\nOne syntactic restriction not indicated by these productions is that\nwhitespace is not allowed between the ``stringprefix`` or\n``bytesprefix`` and the rest of the literal. The source character set\nis defined by the encoding declaration; it is UTF-8 if no encoding\ndeclaration is given in the source file; see section *Encoding\ndeclarations*.\n\nIn plain English: Both types of literals can be enclosed in matching\nsingle quotes (``\'``) or double quotes (``"``). They can also be\nenclosed in matching groups of three single or double quotes (these\nare generally referred to as *triple-quoted strings*). The backslash\n(``\\``) character is used to escape characters that otherwise have a\nspecial meaning, such as newline, backslash itself, or the quote\ncharacter.\n\nBytes literals are always prefixed with ``\'b\'`` or ``\'B\'``; they\nproduce an instance of the ``bytes`` type instead of the ``str`` type.\nThey may only contain ASCII characters; bytes with a numeric value of\n128 or greater must be expressed with escapes.\n\nAs of Python 3.3 it is possible again to prefix unicode strings with a\n``u`` prefix to simplify maintenance of dual 2.x and 3.x codebases.\n\nBoth string and bytes literals may optionally be prefixed with a\nletter ``\'r\'`` or ``\'R\'``; such strings are called *raw strings* and\ntreat backslashes as literal characters. As a result, in string\nliterals, ``\'\\U\'`` and ``\'\\u\'`` escapes in raw strings are not treated\nspecially.\n\n New in version 3.3: The ``\'rb\'`` prefix of raw bytes literals has\n been added as a synonym of ``\'br\'``.\n\n New in version 3.3: Support for the unicode legacy literal\n (``u\'value\'``) and other versions were reintroduced to simplify the\n maintenance of dual Python 2.x and 3.x codebases. See **PEP 414**\n for more information.\n\nIn triple-quoted strings, unescaped newlines and quotes are allowed\n(and are retained), except that three unescaped quotes in a row\nterminate the string. (A "quote" is the character used to open the\nstring, i.e. either ``\'`` or ``"``.)\n\nUnless an ``\'r\'`` or ``\'R\'`` prefix is present, escape sequences in\nstrings are interpreted according to rules similar to those used by\nStandard C. The recognized escape sequences are:\n\n+-------------------+-----------------------------------+---------+\n| Escape Sequence | Meaning | Notes |\n+===================+===================================+=========+\n| ``\\newline`` | Backslash and newline ignored | |\n+-------------------+-----------------------------------+---------+\n| ``\\\\`` | Backslash (``\\``) | |\n+-------------------+-----------------------------------+---------+\n| ``\\\'`` | Single quote (``\'``) | |\n+-------------------+-----------------------------------+---------+\n| ``\\"`` | Double quote (``"``) | |\n+-------------------+-----------------------------------+---------+\n| ``\\a`` | ASCII Bell (BEL) | |\n+-------------------+-----------------------------------+---------+\n| ``\\b`` | ASCII Backspace (BS) | |\n+-------------------+-----------------------------------+---------+\n| ``\\f`` | ASCII Formfeed (FF) | |\n+-------------------+-----------------------------------+---------+\n| ``\\n`` | ASCII Linefeed (LF) | |\n+-------------------+-----------------------------------+---------+\n| ``\\r`` | ASCII Carriage Return (CR) | |\n+-------------------+-----------------------------------+---------+\n| ``\\t`` | ASCII Horizontal Tab (TAB) | |\n+-------------------+-----------------------------------+---------+\n| ``\\v`` | ASCII Vertical Tab (VT) | |\n+-------------------+-----------------------------------+---------+\n| ``\\ooo`` | Character with octal value *ooo* | (1,3) |\n+-------------------+-----------------------------------+---------+\n| ``\\xhh`` | Character with hex value *hh* | (2,3) |\n+-------------------+-----------------------------------+---------+\n\nEscape sequences only recognized in string literals are:\n\n+-------------------+-----------------------------------+---------+\n| Escape Sequence | Meaning | Notes |\n+===================+===================================+=========+\n| ``\\N{name}`` | Character named *name* in the | (4) |\n| | Unicode database | |\n+-------------------+-----------------------------------+---------+\n| ``\\uxxxx`` | Character with 16-bit hex value | (5) |\n| | *xxxx* | |\n+-------------------+-----------------------------------+---------+\n| ``\\Uxxxxxxxx`` | Character with 32-bit hex value | (6) |\n| | *xxxxxxxx* | |\n+-------------------+-----------------------------------+---------+\n\nNotes:\n\n1. As in Standard C, up to three octal digits are accepted.\n\n2. Unlike in Standard C, exactly two hex digits are required.\n\n3. In a bytes literal, hexadecimal and octal escapes denote the byte\n with the given value. In a string literal, these escapes denote a\n Unicode character with the given value.\n\n4. Changed in version 3.3: Support for name aliases [1] has been\n added.\n\n5. Individual code units which form parts of a surrogate pair can be\n encoded using this escape sequence. Exactly four hex digits are\n required.\n\n6. Any Unicode character can be encoded this way, but characters\n outside the Basic Multilingual Plane (BMP) will be encoded using a\n surrogate pair if Python is compiled to use 16-bit code units (the\n default). Exactly eight hex digits are required.\n\nUnlike Standard C, all unrecognized escape sequences are left in the\nstring unchanged, i.e., *the backslash is left in the string*. (This\nbehavior is useful when debugging: if an escape sequence is mistyped,\nthe resulting output is more easily recognized as broken.) It is also\nimportant to note that the escape sequences only recognized in string\nliterals fall into the category of unrecognized escapes for bytes\nliterals.\n\nEven in a raw string, string quotes can be escaped with a backslash,\nbut the backslash remains in the string; for example, ``r"\\""`` is a\nvalid string literal consisting of two characters: a backslash and a\ndouble quote; ``r"\\"`` is not a valid string literal (even a raw\nstring cannot end in an odd number of backslashes). Specifically, *a\nraw string cannot end in a single backslash* (since the backslash\nwould escape the following quote character). Note also that a single\nbackslash followed by a newline is interpreted as those two characters\nas part of the string, *not* as a line continuation.\n',
'subscriptions': '\nSubscriptions\n*************\n\nA subscription selects an item of a sequence (string, tuple or list)\nor mapping (dictionary) object:\n\n subscription ::= primary "[" expression_list "]"\n\nThe primary must evaluate to an object that supports subscription,\ne.g. a list or dictionary. User-defined objects can support\nsubscription by defining a ``__getitem__()`` method.\n\nFor built-in objects, there are two types of objects that support\nsubscription:\n\nIf the primary is a mapping, the expression list must evaluate to an\nobject whose value is one of the keys of the mapping, and the\nsubscription selects the value in the mapping that corresponds to that\nkey. (The expression list is a tuple except if it has exactly one\nitem.)\n\nIf the primary is a sequence, the expression (list) must evaluate to\nan integer or a slice (as discussed in the following section).\n\nThe formal syntax makes no special provision for negative indices in\nsequences; however, built-in sequences all provide a ``__getitem__()``\nmethod that interprets negative indices by adding the length of the\nsequence to the index (so that ``x[-1]`` selects the last item of\n``x``). The resulting value must be a nonnegative integer less than\nthe number of items in the sequence, and the subscription selects the\nitem whose index is that value (counting from zero). Since the support\nfor negative indices and slicing occurs in the object\'s\n``__getitem__()`` method, subclasses overriding this method will need\nto explicitly add that support.\n\nA string\'s items are characters. A character is not a separate data\ntype but a string of exactly one character.\n',
'truth': "\nTruth Value Testing\n*******************\n\nAny object can be tested for truth value, for use in an ``if`` or\n``while`` condition or as operand of the Boolean operations below. The\nfollowing values are considered false:\n\n* ``None``\n\n* ``False``\n\n* zero of any numeric type, for example, ``0``, ``0.0``, ``0j``.\n\n* any empty sequence, for example, ``''``, ``()``, ``[]``.\n\n* any empty mapping, for example, ``{}``.\n\n* instances of user-defined classes, if the class defines a\n ``__bool__()`` or ``__len__()`` method, when that method returns the\n integer zero or ``bool`` value ``False``. [1]\n\nAll other values are considered true --- so objects of many types are\nalways true.\n\nOperations and built-in functions that have a Boolean result always\nreturn ``0`` or ``False`` for false and ``1`` or ``True`` for true,\nunless otherwise stated. (Important exception: the Boolean operations\n``or`` and ``and`` always return one of their operands.)\n",
- 'try': '\nThe ``try`` statement\n*********************\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n try_stmt ::= try1_stmt | try2_stmt\n try1_stmt ::= "try" ":" suite\n ("except" [expression ["as" target]] ":" suite)+\n ["else" ":" suite]\n ["finally" ":" suite]\n try2_stmt ::= "try" ":" suite\n "finally" ":" suite\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started. This search inspects the except\nclauses in turn until one is found that matches the exception. An\nexpression-less except clause, if present, must be last; it matches\nany exception. For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception. An object is\ncompatible with an exception if it is the class or a base class of the\nexception object or a tuple containing an item compatible with the\nexception.\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified after the ``as`` keyword in that except clause,\nif present, and the except clause\'s suite is executed. All except\nclauses must have an executable block. When the end of this block is\nreached, execution continues normally after the entire try statement.\n(This means that if two nested handlers exist for the same exception,\nand the exception occurs in the try clause of the inner handler, the\nouter handler will not handle the exception.)\n\nWhen an exception has been assigned using ``as target``, it is cleared\nat the end of the except clause. This is as if\n\n except E as N:\n foo\n\nwas translated to\n\n except E as N:\n try:\n foo\n finally:\n del N\n\nThis means the exception must be assigned to a different name to be\nable to refer to it after the except clause. Exceptions are cleared\nbecause with the traceback attached to them, they form a reference\ncycle with the stack frame, keeping all locals in that frame alive\nuntil the next garbage collection occurs.\n\nBefore an except clause\'s suite is executed, details about the\nexception are stored in the ``sys`` module and can be access via\n``sys.exc_info()``. ``sys.exc_info()`` returns a 3-tuple consisting of\nthe exception class, the exception instance and a traceback object\n(see section *The standard type hierarchy*) identifying the point in\nthe program where the exception occurred. ``sys.exc_info()`` values\nare restored to their previous values (before the call) when returning\nfrom a function that handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler. The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses. If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted. If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the saved\nexception is lost. The exception information is not available to the\nprogram during execution of the ``finally`` clause.\n\nWhen a ``return``, ``break`` or ``continue`` statement is executed in\nthe ``try`` suite of a ``try``...``finally`` statement, the\n``finally`` clause is also executed \'on the way out.\' A ``continue``\nstatement is illegal in the ``finally`` clause. (The reason is a\nproblem with the current implementation --- this restriction may be\nlifted in the future).\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n',
- 'types': '\nThe standard type hierarchy\n***************************\n\nBelow is a list of the types that are built into Python. Extension\nmodules (written in C, Java, or other languages, depending on the\nimplementation) can define additional types. Future versions of\nPython may add types to the type hierarchy (e.g., rational numbers,\nefficiently stored arrays of integers, etc.), although such additions\nwill often be provided via the standard library instead.\n\nSome of the type descriptions below contain a paragraph listing\n\'special attributes.\' These are attributes that provide access to the\nimplementation and are not intended for general use. Their definition\nmay change in the future.\n\nNone\n This type has a single value. There is a single object with this\n value. This object is accessed through the built-in name ``None``.\n It is used to signify the absence of a value in many situations,\n e.g., it is returned from functions that don\'t explicitly return\n anything. Its truth value is false.\n\nNotImplemented\n This type has a single value. There is a single object with this\n value. This object is accessed through the built-in name\n ``NotImplemented``. Numeric methods and rich comparison methods may\n return this value if they do not implement the operation for the\n operands provided. (The interpreter will then try the reflected\n operation, or some other fallback, depending on the operator.) Its\n truth value is true.\n\nEllipsis\n This type has a single value. There is a single object with this\n value. This object is accessed through the literal ``...`` or the\n built-in name ``Ellipsis``. Its truth value is true.\n\n``numbers.Number``\n These are created by numeric literals and returned as results by\n arithmetic operators and arithmetic built-in functions. Numeric\n objects are immutable; once created their value never changes.\n Python numbers are of course strongly related to mathematical\n numbers, but subject to the limitations of numerical representation\n in computers.\n\n Python distinguishes between integers, floating point numbers, and\n complex numbers:\n\n ``numbers.Integral``\n These represent elements from the mathematical set of integers\n (positive and negative).\n\n There are two types of integers:\n\n Integers (``int``)\n\n These represent numbers in an unlimited range, subject to\n available (virtual) memory only. For the purpose of shift\n and mask operations, a binary representation is assumed, and\n negative numbers are represented in a variant of 2\'s\n complement which gives the illusion of an infinite string of\n sign bits extending to the left.\n\n Booleans (``bool``)\n These represent the truth values False and True. The two\n objects representing the values False and True are the only\n Boolean objects. The Boolean type is a subtype of the integer\n type, and Boolean values behave like the values 0 and 1,\n respectively, in almost all contexts, the exception being\n that when converted to a string, the strings ``"False"`` or\n ``"True"`` are returned, respectively.\n\n The rules for integer representation are intended to give the\n most meaningful interpretation of shift and mask operations\n involving negative integers.\n\n ``numbers.Real`` (``float``)\n These represent machine-level double precision floating point\n numbers. You are at the mercy of the underlying machine\n architecture (and C or Java implementation) for the accepted\n range and handling of overflow. Python does not support single-\n precision floating point numbers; the savings in processor and\n memory usage that are usually the reason for using these is\n dwarfed by the overhead of using objects in Python, so there is\n no reason to complicate the language with two kinds of floating\n point numbers.\n\n ``numbers.Complex`` (``complex``)\n These represent complex numbers as a pair of machine-level\n double precision floating point numbers. The same caveats apply\n as for floating point numbers. The real and imaginary parts of a\n complex number ``z`` can be retrieved through the read-only\n attributes ``z.real`` and ``z.imag``.\n\nSequences\n These represent finite ordered sets indexed by non-negative\n numbers. The built-in function ``len()`` returns the number of\n items of a sequence. When the length of a sequence is *n*, the\n index set contains the numbers 0, 1, ..., *n*-1. Item *i* of\n sequence *a* is selected by ``a[i]``.\n\n Sequences also support slicing: ``a[i:j]`` selects all items with\n index *k* such that *i* ``<=`` *k* ``<`` *j*. When used as an\n expression, a slice is a sequence of the same type. This implies\n that the index set is renumbered so that it starts at 0.\n\n Some sequences also support "extended slicing" with a third "step"\n parameter: ``a[i:j:k]`` selects all items of *a* with index *x*\n where ``x = i + n*k``, *n* ``>=`` ``0`` and *i* ``<=`` *x* ``<``\n *j*.\n\n Sequences are distinguished according to their mutability:\n\n Immutable sequences\n An object of an immutable sequence type cannot change once it is\n created. (If the object contains references to other objects,\n these other objects may be mutable and may be changed; however,\n the collection of objects directly referenced by an immutable\n object cannot change.)\n\n The following types are immutable sequences:\n\n Strings\n The items of a string object are Unicode code units. A\n Unicode code unit is represented by a string object of one\n item and can hold either a 16-bit or 32-bit value\n representing a Unicode ordinal (the maximum value for the\n ordinal is given in ``sys.maxunicode``, and depends on how\n Python is configured at compile time). Surrogate pairs may\n be present in the Unicode object, and will be reported as two\n separate items. The built-in functions ``chr()`` and\n ``ord()`` convert between code units and nonnegative integers\n representing the Unicode ordinals as defined in the Unicode\n Standard 3.0. Conversion from and to other encodings are\n possible through the string method ``encode()``.\n\n Tuples\n The items of a tuple are arbitrary Python objects. Tuples of\n two or more items are formed by comma-separated lists of\n expressions. A tuple of one item (a \'singleton\') can be\n formed by affixing a comma to an expression (an expression by\n itself does not create a tuple, since parentheses must be\n usable for grouping of expressions). An empty tuple can be\n formed by an empty pair of parentheses.\n\n Bytes\n A bytes object is an immutable array. The items are 8-bit\n bytes, represented by integers in the range 0 <= x < 256.\n Bytes literals (like ``b\'abc\'`` and the built-in function\n ``bytes()`` can be used to construct bytes objects. Also,\n bytes objects can be decoded to strings via the ``decode()``\n method.\n\n Mutable sequences\n Mutable sequences can be changed after they are created. The\n subscription and slicing notations can be used as the target of\n assignment and ``del`` (delete) statements.\n\n There are currently two intrinsic mutable sequence types:\n\n Lists\n The items of a list are arbitrary Python objects. Lists are\n formed by placing a comma-separated list of expressions in\n square brackets. (Note that there are no special cases needed\n to form lists of length 0 or 1.)\n\n Byte Arrays\n A bytearray object is a mutable array. They are created by\n the built-in ``bytearray()`` constructor. Aside from being\n mutable (and hence unhashable), byte arrays otherwise provide\n the same interface and functionality as immutable bytes\n objects.\n\n The extension module ``array`` provides an additional example of\n a mutable sequence type, as does the ``collections`` module.\n\nSet types\n These represent unordered, finite sets of unique, immutable\n objects. As such, they cannot be indexed by any subscript. However,\n they can be iterated over, and the built-in function ``len()``\n returns the number of items in a set. Common uses for sets are fast\n membership testing, removing duplicates from a sequence, and\n computing mathematical operations such as intersection, union,\n difference, and symmetric difference.\n\n For set elements, the same immutability rules apply as for\n dictionary keys. Note that numeric types obey the normal rules for\n numeric comparison: if two numbers compare equal (e.g., ``1`` and\n ``1.0``), only one of them can be contained in a set.\n\n There are currently two intrinsic set types:\n\n Sets\n These represent a mutable set. They are created by the built-in\n ``set()`` constructor and can be modified afterwards by several\n methods, such as ``add()``.\n\n Frozen sets\n These represent an immutable set. They are created by the\n built-in ``frozenset()`` constructor. As a frozenset is\n immutable and *hashable*, it can be used again as an element of\n another set, or as a dictionary key.\n\nMappings\n These represent finite sets of objects indexed by arbitrary index\n sets. The subscript notation ``a[k]`` selects the item indexed by\n ``k`` from the mapping ``a``; this can be used in expressions and\n as the target of assignments or ``del`` statements. The built-in\n function ``len()`` returns the number of items in a mapping.\n\n There is currently a single intrinsic mapping type:\n\n Dictionaries\n These represent finite sets of objects indexed by nearly\n arbitrary values. The only types of values not acceptable as\n keys are values containing lists or dictionaries or other\n mutable types that are compared by value rather than by object\n identity, the reason being that the efficient implementation of\n dictionaries requires a key\'s hash value to remain constant.\n Numeric types used for keys obey the normal rules for numeric\n comparison: if two numbers compare equal (e.g., ``1`` and\n ``1.0``) then they can be used interchangeably to index the same\n dictionary entry.\n\n Dictionaries are mutable; they can be created by the ``{...}``\n notation (see section *Dictionary displays*).\n\n The extension modules ``dbm.ndbm`` and ``dbm.gnu`` provide\n additional examples of mapping types, as does the\n ``collections`` module.\n\nCallable types\n These are the types to which the function call operation (see\n section *Calls*) can be applied:\n\n User-defined functions\n A user-defined function object is created by a function\n definition (see section *Function definitions*). It should be\n called with an argument list containing the same number of items\n as the function\'s formal parameter list.\n\n Special attributes:\n\n +---------------------------+---------------------------------+-------------+\n | Attribute | Meaning | |\n +===========================+=================================+=============+\n | ``__doc__`` | The function\'s documentation | Writable |\n | | string, or ``None`` if | |\n | | unavailable | |\n +---------------------------+---------------------------------+-------------+\n | ``__name__`` | The function\'s name | Writable |\n +---------------------------+---------------------------------+-------------+\n | ``__module__`` | The name of the module the | Writable |\n | | function was defined in, or | |\n | | ``None`` if unavailable. | |\n +---------------------------+---------------------------------+-------------+\n | ``__defaults__`` | A tuple containing default | Writable |\n | | argument values for those | |\n | | arguments that have defaults, | |\n | | or ``None`` if no arguments | |\n | | have a default value | |\n +---------------------------+---------------------------------+-------------+\n | ``__code__`` | The code object representing | Writable |\n | | the compiled function body. | |\n +---------------------------+---------------------------------+-------------+\n | ``__globals__`` | A reference to the dictionary | Read-only |\n | | that holds the function\'s | |\n | | global variables --- the global | |\n | | namespace of the module in | |\n | | which the function was defined. | |\n +---------------------------+---------------------------------+-------------+\n | ``__dict__`` | The namespace supporting | Writable |\n | | arbitrary function attributes. | |\n +---------------------------+---------------------------------+-------------+\n | ``__closure__`` | ``None`` or a tuple of cells | Read-only |\n | | that contain bindings for the | |\n | | function\'s free variables. | |\n +---------------------------+---------------------------------+-------------+\n | ``__annotations__`` | A dict containing annotations | Writable |\n | | of parameters. The keys of the | |\n | | dict are the parameter names, | |\n | | or ``\'return\'`` for the return | |\n | | annotation, if provided. | |\n +---------------------------+---------------------------------+-------------+\n | ``__kwdefaults__`` | A dict containing defaults for | Writable |\n | | keyword-only parameters. | |\n +---------------------------+---------------------------------+-------------+\n\n Most of the attributes labelled "Writable" check the type of the\n assigned value.\n\n Function objects also support getting and setting arbitrary\n attributes, which can be used, for example, to attach metadata\n to functions. Regular attribute dot-notation is used to get and\n set such attributes. *Note that the current implementation only\n supports function attributes on user-defined functions. Function\n attributes on built-in functions may be supported in the\n future.*\n\n Additional information about a function\'s definition can be\n retrieved from its code object; see the description of internal\n types below.\n\n Instance methods\n An instance method object combines a class, a class instance and\n any callable object (normally a user-defined function).\n\n Special read-only attributes: ``__self__`` is the class instance\n object, ``__func__`` is the function object; ``__doc__`` is the\n method\'s documentation (same as ``__func__.__doc__``);\n ``__name__`` is the method name (same as ``__func__.__name__``);\n ``__module__`` is the name of the module the method was defined\n in, or ``None`` if unavailable.\n\n Methods also support accessing (but not setting) the arbitrary\n function attributes on the underlying function object.\n\n User-defined method objects may be created when getting an\n attribute of a class (perhaps via an instance of that class), if\n that attribute is a user-defined function object or a class\n method object.\n\n When an instance method object is created by retrieving a user-\n defined function object from a class via one of its instances,\n its ``__self__`` attribute is the instance, and the method\n object is said to be bound. The new method\'s ``__func__``\n attribute is the original function object.\n\n When a user-defined method object is created by retrieving\n another method object from a class or instance, the behaviour is\n the same as for a function object, except that the ``__func__``\n attribute of the new instance is not the original method object\n but its ``__func__`` attribute.\n\n When an instance method object is created by retrieving a class\n method object from a class or instance, its ``__self__``\n attribute is the class itself, and its ``__func__`` attribute is\n the function object underlying the class method.\n\n When an instance method object is called, the underlying\n function (``__func__``) is called, inserting the class instance\n (``__self__``) in front of the argument list. For instance,\n when ``C`` is a class which contains a definition for a function\n ``f()``, and ``x`` is an instance of ``C``, calling ``x.f(1)``\n is equivalent to calling ``C.f(x, 1)``.\n\n When an instance method object is derived from a class method\n object, the "class instance" stored in ``__self__`` will\n actually be the class itself, so that calling either ``x.f(1)``\n or ``C.f(1)`` is equivalent to calling ``f(C,1)`` where ``f`` is\n the underlying function.\n\n Note that the transformation from function object to instance\n method object happens each time the attribute is retrieved from\n the instance. In some cases, a fruitful optimization is to\n assign the attribute to a local variable and call that local\n variable. Also notice that this transformation only happens for\n user-defined functions; other callable objects (and all non-\n callable objects) are retrieved without transformation. It is\n also important to note that user-defined functions which are\n attributes of a class instance are not converted to bound\n methods; this *only* happens when the function is an attribute\n of the class.\n\n Generator functions\n A function or method which uses the ``yield`` statement (see\n section *The yield statement*) is called a *generator function*.\n Such a function, when called, always returns an iterator object\n which can be used to execute the body of the function: calling\n the iterator\'s ``__next__()`` method will cause the function to\n execute until it provides a value using the ``yield`` statement.\n When the function executes a ``return`` statement or falls off\n the end, a ``StopIteration`` exception is raised and the\n iterator will have reached the end of the set of values to be\n returned.\n\n Built-in functions\n A built-in function object is a wrapper around a C function.\n Examples of built-in functions are ``len()`` and ``math.sin()``\n (``math`` is a standard built-in module). The number and type of\n the arguments are determined by the C function. Special read-\n only attributes: ``__doc__`` is the function\'s documentation\n string, or ``None`` if unavailable; ``__name__`` is the\n function\'s name; ``__self__`` is set to ``None`` (but see the\n next item); ``__module__`` is the name of the module the\n function was defined in or ``None`` if unavailable.\n\n Built-in methods\n This is really a different disguise of a built-in function, this\n time containing an object passed to the C function as an\n implicit extra argument. An example of a built-in method is\n ``alist.append()``, assuming *alist* is a list object. In this\n case, the special read-only attribute ``__self__`` is set to the\n object denoted by *alist*.\n\n Classes\n Classes are callable. These objects normally act as factories\n for new instances of themselves, but variations are possible for\n class types that override ``__new__()``. The arguments of the\n call are passed to ``__new__()`` and, in the typical case, to\n ``__init__()`` to initialize the new instance.\n\n Class Instances\n Instances of arbitrary classes can be made callable by defining\n a ``__call__()`` method in their class.\n\nModules\n Modules are imported by the ``import`` statement (see section *The\n import statement*). A module object has a namespace implemented by\n a dictionary object (this is the dictionary referenced by the\n __globals__ attribute of functions defined in the module).\n Attribute references are translated to lookups in this dictionary,\n e.g., ``m.x`` is equivalent to ``m.__dict__["x"]``. A module object\n does not contain the code object used to initialize the module\n (since it isn\'t needed once the initialization is done).\n\n Attribute assignment updates the module\'s namespace dictionary,\n e.g., ``m.x = 1`` is equivalent to ``m.__dict__["x"] = 1``.\n\n Special read-only attribute: ``__dict__`` is the module\'s namespace\n as a dictionary object.\n\n **CPython implementation detail:** Because of the way CPython\n clears module dictionaries, the module dictionary will be cleared\n when the module falls out of scope even if the dictionary still has\n live references. To avoid this, copy the dictionary or keep the\n module around while using its dictionary directly.\n\n Predefined (writable) attributes: ``__name__`` is the module\'s\n name; ``__doc__`` is the module\'s documentation string, or ``None``\n if unavailable; ``__file__`` is the pathname of the file from which\n the module was loaded, if it was loaded from a file. The\n ``__file__`` attribute is not present for C modules that are\n statically linked into the interpreter; for extension modules\n loaded dynamically from a shared library, it is the pathname of the\n shared library file.\n\nCustom classes\n Custom class types are typically created by class definitions (see\n section *Class definitions*). A class has a namespace implemented\n by a dictionary object. Class attribute references are translated\n to lookups in this dictionary, e.g., ``C.x`` is translated to\n ``C.__dict__["x"]`` (although there are a number of hooks which\n allow for other means of locating attributes). When the attribute\n name is not found there, the attribute search continues in the base\n classes. This search of the base classes uses the C3 method\n resolution order which behaves correctly even in the presence of\n \'diamond\' inheritance structures where there are multiple\n inheritance paths leading back to a common ancestor. Additional\n details on the C3 MRO used by Python can be found in the\n documentation accompanying the 2.3 release at\n http://www.python.org/download/releases/2.3/mro/.\n\n When a class attribute reference (for class ``C``, say) would yield\n a class method object, it is transformed into an instance method\n object whose ``__self__`` attributes is ``C``. When it would yield\n a static method object, it is transformed into the object wrapped\n by the static method object. See section *Implementing Descriptors*\n for another way in which attributes retrieved from a class may\n differ from those actually contained in its ``__dict__``.\n\n Class attribute assignments update the class\'s dictionary, never\n the dictionary of a base class.\n\n A class object can be called (see above) to yield a class instance\n (see below).\n\n Special attributes: ``__name__`` is the class name; ``__module__``\n is the module name in which the class was defined; ``__dict__`` is\n the dictionary containing the class\'s namespace; ``__bases__`` is a\n tuple (possibly empty or a singleton) containing the base classes,\n in the order of their occurrence in the base class list;\n ``__doc__`` is the class\'s documentation string, or None if\n undefined.\n\nClass instances\n A class instance is created by calling a class object (see above).\n A class instance has a namespace implemented as a dictionary which\n is the first place in which attribute references are searched.\n When an attribute is not found there, and the instance\'s class has\n an attribute by that name, the search continues with the class\n attributes. If a class attribute is found that is a user-defined\n function object, it is transformed into an instance method object\n whose ``__self__`` attribute is the instance. Static method and\n class method objects are also transformed; see above under\n "Classes". See section *Implementing Descriptors* for another way\n in which attributes of a class retrieved via its instances may\n differ from the objects actually stored in the class\'s\n ``__dict__``. If no class attribute is found, and the object\'s\n class has a ``__getattr__()`` method, that is called to satisfy the\n lookup.\n\n Attribute assignments and deletions update the instance\'s\n dictionary, never a class\'s dictionary. If the class has a\n ``__setattr__()`` or ``__delattr__()`` method, this is called\n instead of updating the instance dictionary directly.\n\n Class instances can pretend to be numbers, sequences, or mappings\n if they have methods with certain special names. See section\n *Special method names*.\n\n Special attributes: ``__dict__`` is the attribute dictionary;\n ``__class__`` is the instance\'s class.\n\nI/O objects (also known as file objects)\n A *file object* represents an open file. Various shortcuts are\n available to create file objects: the ``open()`` built-in function,\n and also ``os.popen()``, ``os.fdopen()``, and the ``makefile()``\n method of socket objects (and perhaps by other functions or methods\n provided by extension modules).\n\n The objects ``sys.stdin``, ``sys.stdout`` and ``sys.stderr`` are\n initialized to file objects corresponding to the interpreter\'s\n standard input, output and error streams; they are all open in text\n mode and therefore follow the interface defined by the\n ``io.TextIOBase`` abstract class.\n\nInternal types\n A few types used internally by the interpreter are exposed to the\n user. Their definitions may change with future versions of the\n interpreter, but they are mentioned here for completeness.\n\n Code objects\n Code objects represent *byte-compiled* executable Python code,\n or *bytecode*. The difference between a code object and a\n function object is that the function object contains an explicit\n reference to the function\'s globals (the module in which it was\n defined), while a code object contains no context; also the\n default argument values are stored in the function object, not\n in the code object (because they represent values calculated at\n run-time). Unlike function objects, code objects are immutable\n and contain no references (directly or indirectly) to mutable\n objects.\n\n Special read-only attributes: ``co_name`` gives the function\n name; ``co_argcount`` is the number of positional arguments\n (including arguments with default values); ``co_nlocals`` is the\n number of local variables used by the function (including\n arguments); ``co_varnames`` is a tuple containing the names of\n the local variables (starting with the argument names);\n ``co_cellvars`` is a tuple containing the names of local\n variables that are referenced by nested functions;\n ``co_freevars`` is a tuple containing the names of free\n variables; ``co_code`` is a string representing the sequence of\n bytecode instructions; ``co_consts`` is a tuple containing the\n literals used by the bytecode; ``co_names`` is a tuple\n containing the names used by the bytecode; ``co_filename`` is\n the filename from which the code was compiled;\n ``co_firstlineno`` is the first line number of the function;\n ``co_lnotab`` is a string encoding the mapping from bytecode\n offsets to line numbers (for details see the source code of the\n interpreter); ``co_stacksize`` is the required stack size\n (including local variables); ``co_flags`` is an integer encoding\n a number of flags for the interpreter.\n\n The following flag bits are defined for ``co_flags``: bit\n ``0x04`` is set if the function uses the ``*arguments`` syntax\n to accept an arbitrary number of positional arguments; bit\n ``0x08`` is set if the function uses the ``**keywords`` syntax\n to accept arbitrary keyword arguments; bit ``0x20`` is set if\n the function is a generator.\n\n Future feature declarations (``from __future__ import\n division``) also use bits in ``co_flags`` to indicate whether a\n code object was compiled with a particular feature enabled: bit\n ``0x2000`` is set if the function was compiled with future\n division enabled; bits ``0x10`` and ``0x1000`` were used in\n earlier versions of Python.\n\n Other bits in ``co_flags`` are reserved for internal use.\n\n If a code object represents a function, the first item in\n ``co_consts`` is the documentation string of the function, or\n ``None`` if undefined.\n\n Frame objects\n Frame objects represent execution frames. They may occur in\n traceback objects (see below).\n\n Special read-only attributes: ``f_back`` is to the previous\n stack frame (towards the caller), or ``None`` if this is the\n bottom stack frame; ``f_code`` is the code object being executed\n in this frame; ``f_locals`` is the dictionary used to look up\n local variables; ``f_globals`` is used for global variables;\n ``f_builtins`` is used for built-in (intrinsic) names;\n ``f_lasti`` gives the precise instruction (this is an index into\n the bytecode string of the code object).\n\n Special writable attributes: ``f_trace``, if not ``None``, is a\n function called at the start of each source code line (this is\n used by the debugger); ``f_lineno`` is the current line number\n of the frame --- writing to this from within a trace function\n jumps to the given line (only for the bottom-most frame). A\n debugger can implement a Jump command (aka Set Next Statement)\n by writing to f_lineno.\n\n Traceback objects\n Traceback objects represent a stack trace of an exception. A\n traceback object is created when an exception occurs. When the\n search for an exception handler unwinds the execution stack, at\n each unwound level a traceback object is inserted in front of\n the current traceback. When an exception handler is entered,\n the stack trace is made available to the program. (See section\n *The try statement*.) It is accessible as the third item of the\n tuple returned by ``sys.exc_info()``. When the program contains\n no suitable handler, the stack trace is written (nicely\n formatted) to the standard error stream; if the interpreter is\n interactive, it is also made available to the user as\n ``sys.last_traceback``.\n\n Special read-only attributes: ``tb_next`` is the next level in\n the stack trace (towards the frame where the exception\n occurred), or ``None`` if there is no next level; ``tb_frame``\n points to the execution frame of the current level;\n ``tb_lineno`` gives the line number where the exception\n occurred; ``tb_lasti`` indicates the precise instruction. The\n line number and last instruction in the traceback may differ\n from the line number of its frame object if the exception\n occurred in a ``try`` statement with no matching except clause\n or with a finally clause.\n\n Slice objects\n Slice objects are used to represent slices for ``__getitem__()``\n methods. They are also created by the built-in ``slice()``\n function.\n\n Special read-only attributes: ``start`` is the lower bound;\n ``stop`` is the upper bound; ``step`` is the step value; each is\n ``None`` if omitted. These attributes can have any type.\n\n Slice objects support one method:\n\n slice.indices(self, length)\n\n This method takes a single integer argument *length* and\n computes information about the slice that the slice object\n would describe if applied to a sequence of *length* items.\n It returns a tuple of three integers; respectively these are\n the *start* and *stop* indices and the *step* or stride\n length of the slice. Missing or out-of-bounds indices are\n handled in a manner consistent with regular slices.\n\n Static method objects\n Static method objects provide a way of defeating the\n transformation of function objects to method objects described\n above. A static method object is a wrapper around any other\n object, usually a user-defined method object. When a static\n method object is retrieved from a class or a class instance, the\n object actually returned is the wrapped object, which is not\n subject to any further transformation. Static method objects are\n not themselves callable, although the objects they wrap usually\n are. Static method objects are created by the built-in\n ``staticmethod()`` constructor.\n\n Class method objects\n A class method object, like a static method object, is a wrapper\n around another object that alters the way in which that object\n is retrieved from classes and class instances. The behaviour of\n class method objects upon such retrieval is described above,\n under "User-defined methods". Class method objects are created\n by the built-in ``classmethod()`` constructor.\n',
+ 'try': '\nThe ``try`` statement\n*********************\n\nThe ``try`` statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n try_stmt ::= try1_stmt | try2_stmt\n try1_stmt ::= "try" ":" suite\n ("except" [expression ["as" target]] ":" suite)+\n ["else" ":" suite]\n ["finally" ":" suite]\n try2_stmt ::= "try" ":" suite\n "finally" ":" suite\n\nThe ``except`` clause(s) specify one or more exception handlers. When\nno exception occurs in the ``try`` clause, no exception handler is\nexecuted. When an exception occurs in the ``try`` suite, a search for\nan exception handler is started. This search inspects the except\nclauses in turn until one is found that matches the exception. An\nexpression-less except clause, if present, must be last; it matches\nany exception. For an except clause with an expression, that\nexpression is evaluated, and the clause matches the exception if the\nresulting object is "compatible" with the exception. An object is\ncompatible with an exception if it is the class or a base class of the\nexception object or a tuple containing an item compatible with the\nexception.\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire ``try`` statement\nraised the exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified after the ``as`` keyword in that except clause,\nif present, and the except clause\'s suite is executed. All except\nclauses must have an executable block. When the end of this block is\nreached, execution continues normally after the entire try statement.\n(This means that if two nested handlers exist for the same exception,\nand the exception occurs in the try clause of the inner handler, the\nouter handler will not handle the exception.)\n\nWhen an exception has been assigned using ``as target``, it is cleared\nat the end of the except clause. This is as if\n\n except E as N:\n foo\n\nwas translated to\n\n except E as N:\n try:\n foo\n finally:\n del N\n\nThis means the exception must be assigned to a different name to be\nable to refer to it after the except clause. Exceptions are cleared\nbecause with the traceback attached to them, they form a reference\ncycle with the stack frame, keeping all locals in that frame alive\nuntil the next garbage collection occurs.\n\nBefore an except clause\'s suite is executed, details about the\nexception are stored in the ``sys`` module and can be access via\n``sys.exc_info()``. ``sys.exc_info()`` returns a 3-tuple consisting of\nthe exception class, the exception instance and a traceback object\n(see section *The standard type hierarchy*) identifying the point in\nthe program where the exception occurred. ``sys.exc_info()`` values\nare restored to their previous values (before the call) when returning\nfrom a function that handled an exception.\n\nThe optional ``else`` clause is executed if and when control flows off\nthe end of the ``try`` clause. [2] Exceptions in the ``else`` clause\nare not handled by the preceding ``except`` clauses.\n\nIf ``finally`` is present, it specifies a \'cleanup\' handler. The\n``try`` clause is executed, including any ``except`` and ``else``\nclauses. If an exception occurs in any of the clauses and is not\nhandled, the exception is temporarily saved. The ``finally`` clause is\nexecuted. If there is a saved exception, it is re-raised at the end\nof the ``finally`` clause. If the ``finally`` clause raises another\nexception or executes a ``return`` or ``break`` statement, the saved\nexception is set as the context of the new exception. The exception\ninformation is not available to the program during execution of the\n``finally`` clause.\n\nWhen a ``return``, ``break`` or ``continue`` statement is executed in\nthe ``try`` suite of a ``try``...``finally`` statement, the\n``finally`` clause is also executed \'on the way out.\' A ``continue``\nstatement is illegal in the ``finally`` clause. (The reason is a\nproblem with the current implementation --- this restriction may be\nlifted in the future).\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the ``raise`` statement to\ngenerate exceptions may be found in section *The raise statement*.\n',
+ 'types': '\nThe standard type hierarchy\n***************************\n\nBelow is a list of the types that are built into Python. Extension\nmodules (written in C, Java, or other languages, depending on the\nimplementation) can define additional types. Future versions of\nPython may add types to the type hierarchy (e.g., rational numbers,\nefficiently stored arrays of integers, etc.), although such additions\nwill often be provided via the standard library instead.\n\nSome of the type descriptions below contain a paragraph listing\n\'special attributes.\' These are attributes that provide access to the\nimplementation and are not intended for general use. Their definition\nmay change in the future.\n\nNone\n This type has a single value. There is a single object with this\n value. This object is accessed through the built-in name ``None``.\n It is used to signify the absence of a value in many situations,\n e.g., it is returned from functions that don\'t explicitly return\n anything. Its truth value is false.\n\nNotImplemented\n This type has a single value. There is a single object with this\n value. This object is accessed through the built-in name\n ``NotImplemented``. Numeric methods and rich comparison methods may\n return this value if they do not implement the operation for the\n operands provided. (The interpreter will then try the reflected\n operation, or some other fallback, depending on the operator.) Its\n truth value is true.\n\nEllipsis\n This type has a single value. There is a single object with this\n value. This object is accessed through the literal ``...`` or the\n built-in name ``Ellipsis``. Its truth value is true.\n\n``numbers.Number``\n These are created by numeric literals and returned as results by\n arithmetic operators and arithmetic built-in functions. Numeric\n objects are immutable; once created their value never changes.\n Python numbers are of course strongly related to mathematical\n numbers, but subject to the limitations of numerical representation\n in computers.\n\n Python distinguishes between integers, floating point numbers, and\n complex numbers:\n\n ``numbers.Integral``\n These represent elements from the mathematical set of integers\n (positive and negative).\n\n There are two types of integers:\n\n Integers (``int``)\n\n These represent numbers in an unlimited range, subject to\n available (virtual) memory only. For the purpose of shift\n and mask operations, a binary representation is assumed, and\n negative numbers are represented in a variant of 2\'s\n complement which gives the illusion of an infinite string of\n sign bits extending to the left.\n\n Booleans (``bool``)\n These represent the truth values False and True. The two\n objects representing the values False and True are the only\n Boolean objects. The Boolean type is a subtype of the integer\n type, and Boolean values behave like the values 0 and 1,\n respectively, in almost all contexts, the exception being\n that when converted to a string, the strings ``"False"`` or\n ``"True"`` are returned, respectively.\n\n The rules for integer representation are intended to give the\n most meaningful interpretation of shift and mask operations\n involving negative integers.\n\n ``numbers.Real`` (``float``)\n These represent machine-level double precision floating point\n numbers. You are at the mercy of the underlying machine\n architecture (and C or Java implementation) for the accepted\n range and handling of overflow. Python does not support single-\n precision floating point numbers; the savings in processor and\n memory usage that are usually the reason for using these is\n dwarfed by the overhead of using objects in Python, so there is\n no reason to complicate the language with two kinds of floating\n point numbers.\n\n ``numbers.Complex`` (``complex``)\n These represent complex numbers as a pair of machine-level\n double precision floating point numbers. The same caveats apply\n as for floating point numbers. The real and imaginary parts of a\n complex number ``z`` can be retrieved through the read-only\n attributes ``z.real`` and ``z.imag``.\n\nSequences\n These represent finite ordered sets indexed by non-negative\n numbers. The built-in function ``len()`` returns the number of\n items of a sequence. When the length of a sequence is *n*, the\n index set contains the numbers 0, 1, ..., *n*-1. Item *i* of\n sequence *a* is selected by ``a[i]``.\n\n Sequences also support slicing: ``a[i:j]`` selects all items with\n index *k* such that *i* ``<=`` *k* ``<`` *j*. When used as an\n expression, a slice is a sequence of the same type. This implies\n that the index set is renumbered so that it starts at 0.\n\n Some sequences also support "extended slicing" with a third "step"\n parameter: ``a[i:j:k]`` selects all items of *a* with index *x*\n where ``x = i + n*k``, *n* ``>=`` ``0`` and *i* ``<=`` *x* ``<``\n *j*.\n\n Sequences are distinguished according to their mutability:\n\n Immutable sequences\n An object of an immutable sequence type cannot change once it is\n created. (If the object contains references to other objects,\n these other objects may be mutable and may be changed; however,\n the collection of objects directly referenced by an immutable\n object cannot change.)\n\n The following types are immutable sequences:\n\n Strings\n A string is a sequence of values that represent Unicode\n codepoints. All the codepoints in range ``U+0000 - U+10FFFF``\n can be represented in a string. Python doesn\'t have a\n ``chr`` type, and every character in the string is\n represented as a string object with length ``1``. The built-\n in function ``ord()`` converts a character to its codepoint\n (as an integer); ``chr()`` converts an integer in range ``0 -\n 10FFFF`` to the corresponding character. ``str.encode()`` can\n be used to convert a ``str`` to ``bytes`` using the given\n encoding, and ``bytes.decode()`` can be used to achieve the\n opposite.\n\n Tuples\n The items of a tuple are arbitrary Python objects. Tuples of\n two or more items are formed by comma-separated lists of\n expressions. A tuple of one item (a \'singleton\') can be\n formed by affixing a comma to an expression (an expression by\n itself does not create a tuple, since parentheses must be\n usable for grouping of expressions). An empty tuple can be\n formed by an empty pair of parentheses.\n\n Bytes\n A bytes object is an immutable array. The items are 8-bit\n bytes, represented by integers in the range 0 <= x < 256.\n Bytes literals (like ``b\'abc\'`` and the built-in function\n ``bytes()`` can be used to construct bytes objects. Also,\n bytes objects can be decoded to strings via the ``decode()``\n method.\n\n Mutable sequences\n Mutable sequences can be changed after they are created. The\n subscription and slicing notations can be used as the target of\n assignment and ``del`` (delete) statements.\n\n There are currently two intrinsic mutable sequence types:\n\n Lists\n The items of a list are arbitrary Python objects. Lists are\n formed by placing a comma-separated list of expressions in\n square brackets. (Note that there are no special cases needed\n to form lists of length 0 or 1.)\n\n Byte Arrays\n A bytearray object is a mutable array. They are created by\n the built-in ``bytearray()`` constructor. Aside from being\n mutable (and hence unhashable), byte arrays otherwise provide\n the same interface and functionality as immutable bytes\n objects.\n\n The extension module ``array`` provides an additional example of\n a mutable sequence type, as does the ``collections`` module.\n\nSet types\n These represent unordered, finite sets of unique, immutable\n objects. As such, they cannot be indexed by any subscript. However,\n they can be iterated over, and the built-in function ``len()``\n returns the number of items in a set. Common uses for sets are fast\n membership testing, removing duplicates from a sequence, and\n computing mathematical operations such as intersection, union,\n difference, and symmetric difference.\n\n For set elements, the same immutability rules apply as for\n dictionary keys. Note that numeric types obey the normal rules for\n numeric comparison: if two numbers compare equal (e.g., ``1`` and\n ``1.0``), only one of them can be contained in a set.\n\n There are currently two intrinsic set types:\n\n Sets\n These represent a mutable set. They are created by the built-in\n ``set()`` constructor and can be modified afterwards by several\n methods, such as ``add()``.\n\n Frozen sets\n These represent an immutable set. They are created by the\n built-in ``frozenset()`` constructor. As a frozenset is\n immutable and *hashable*, it can be used again as an element of\n another set, or as a dictionary key.\n\nMappings\n These represent finite sets of objects indexed by arbitrary index\n sets. The subscript notation ``a[k]`` selects the item indexed by\n ``k`` from the mapping ``a``; this can be used in expressions and\n as the target of assignments or ``del`` statements. The built-in\n function ``len()`` returns the number of items in a mapping.\n\n There is currently a single intrinsic mapping type:\n\n Dictionaries\n These represent finite sets of objects indexed by nearly\n arbitrary values. The only types of values not acceptable as\n keys are values containing lists or dictionaries or other\n mutable types that are compared by value rather than by object\n identity, the reason being that the efficient implementation of\n dictionaries requires a key\'s hash value to remain constant.\n Numeric types used for keys obey the normal rules for numeric\n comparison: if two numbers compare equal (e.g., ``1`` and\n ``1.0``) then they can be used interchangeably to index the same\n dictionary entry.\n\n Dictionaries are mutable; they can be created by the ``{...}``\n notation (see section *Dictionary displays*).\n\n The extension modules ``dbm.ndbm`` and ``dbm.gnu`` provide\n additional examples of mapping types, as does the\n ``collections`` module.\n\nCallable types\n These are the types to which the function call operation (see\n section *Calls*) can be applied:\n\n User-defined functions\n A user-defined function object is created by a function\n definition (see section *Function definitions*). It should be\n called with an argument list containing the same number of items\n as the function\'s formal parameter list.\n\n Special attributes:\n\n +---------------------------+---------------------------------+-------------+\n | Attribute | Meaning | |\n +===========================+=================================+=============+\n | ``__doc__`` | The function\'s documentation | Writable |\n | | string, or ``None`` if | |\n | | unavailable | |\n +---------------------------+---------------------------------+-------------+\n | ``__name__`` | The function\'s name | Writable |\n +---------------------------+---------------------------------+-------------+\n | ``__qualname__`` | The function\'s *qualified name* | Writable |\n | | New in version 3.3. | |\n +---------------------------+---------------------------------+-------------+\n | ``__module__`` | The name of the module the | Writable |\n | | function was defined in, or | |\n | | ``None`` if unavailable. | |\n +---------------------------+---------------------------------+-------------+\n | ``__defaults__`` | A tuple containing default | Writable |\n | | argument values for those | |\n | | arguments that have defaults, | |\n | | or ``None`` if no arguments | |\n | | have a default value | |\n +---------------------------+---------------------------------+-------------+\n | ``__code__`` | The code object representing | Writable |\n | | the compiled function body. | |\n +---------------------------+---------------------------------+-------------+\n | ``__globals__`` | A reference to the dictionary | Read-only |\n | | that holds the function\'s | |\n | | global variables --- the global | |\n | | namespace of the module in | |\n | | which the function was defined. | |\n +---------------------------+---------------------------------+-------------+\n | ``__dict__`` | The namespace supporting | Writable |\n | | arbitrary function attributes. | |\n +---------------------------+---------------------------------+-------------+\n | ``__closure__`` | ``None`` or a tuple of cells | Read-only |\n | | that contain bindings for the | |\n | | function\'s free variables. | |\n +---------------------------+---------------------------------+-------------+\n | ``__annotations__`` | A dict containing annotations | Writable |\n | | of parameters. The keys of the | |\n | | dict are the parameter names, | |\n | | or ``\'return\'`` for the return | |\n | | annotation, if provided. | |\n +---------------------------+---------------------------------+-------------+\n | ``__kwdefaults__`` | A dict containing defaults for | Writable |\n | | keyword-only parameters. | |\n +---------------------------+---------------------------------+-------------+\n\n Most of the attributes labelled "Writable" check the type of the\n assigned value.\n\n Function objects also support getting and setting arbitrary\n attributes, which can be used, for example, to attach metadata\n to functions. Regular attribute dot-notation is used to get and\n set such attributes. *Note that the current implementation only\n supports function attributes on user-defined functions. Function\n attributes on built-in functions may be supported in the\n future.*\n\n Additional information about a function\'s definition can be\n retrieved from its code object; see the description of internal\n types below.\n\n Instance methods\n An instance method object combines a class, a class instance and\n any callable object (normally a user-defined function).\n\n Special read-only attributes: ``__self__`` is the class instance\n object, ``__func__`` is the function object; ``__doc__`` is the\n method\'s documentation (same as ``__func__.__doc__``);\n ``__name__`` is the method name (same as ``__func__.__name__``);\n ``__module__`` is the name of the module the method was defined\n in, or ``None`` if unavailable.\n\n Methods also support accessing (but not setting) the arbitrary\n function attributes on the underlying function object.\n\n User-defined method objects may be created when getting an\n attribute of a class (perhaps via an instance of that class), if\n that attribute is a user-defined function object or a class\n method object.\n\n When an instance method object is created by retrieving a user-\n defined function object from a class via one of its instances,\n its ``__self__`` attribute is the instance, and the method\n object is said to be bound. The new method\'s ``__func__``\n attribute is the original function object.\n\n When a user-defined method object is created by retrieving\n another method object from a class or instance, the behaviour is\n the same as for a function object, except that the ``__func__``\n attribute of the new instance is not the original method object\n but its ``__func__`` attribute.\n\n When an instance method object is created by retrieving a class\n method object from a class or instance, its ``__self__``\n attribute is the class itself, and its ``__func__`` attribute is\n the function object underlying the class method.\n\n When an instance method object is called, the underlying\n function (``__func__``) is called, inserting the class instance\n (``__self__``) in front of the argument list. For instance,\n when ``C`` is a class which contains a definition for a function\n ``f()``, and ``x`` is an instance of ``C``, calling ``x.f(1)``\n is equivalent to calling ``C.f(x, 1)``.\n\n When an instance method object is derived from a class method\n object, the "class instance" stored in ``__self__`` will\n actually be the class itself, so that calling either ``x.f(1)``\n or ``C.f(1)`` is equivalent to calling ``f(C,1)`` where ``f`` is\n the underlying function.\n\n Note that the transformation from function object to instance\n method object happens each time the attribute is retrieved from\n the instance. In some cases, a fruitful optimization is to\n assign the attribute to a local variable and call that local\n variable. Also notice that this transformation only happens for\n user-defined functions; other callable objects (and all non-\n callable objects) are retrieved without transformation. It is\n also important to note that user-defined functions which are\n attributes of a class instance are not converted to bound\n methods; this *only* happens when the function is an attribute\n of the class.\n\n Generator functions\n A function or method which uses the ``yield`` statement (see\n section *The yield statement*) is called a *generator function*.\n Such a function, when called, always returns an iterator object\n which can be used to execute the body of the function: calling\n the iterator\'s ``__next__()`` method will cause the function to\n execute until it provides a value using the ``yield`` statement.\n When the function executes a ``return`` statement or falls off\n the end, a ``StopIteration`` exception is raised and the\n iterator will have reached the end of the set of values to be\n returned.\n\n Built-in functions\n A built-in function object is a wrapper around a C function.\n Examples of built-in functions are ``len()`` and ``math.sin()``\n (``math`` is a standard built-in module). The number and type of\n the arguments are determined by the C function. Special read-\n only attributes: ``__doc__`` is the function\'s documentation\n string, or ``None`` if unavailable; ``__name__`` is the\n function\'s name; ``__self__`` is set to ``None`` (but see the\n next item); ``__module__`` is the name of the module the\n function was defined in or ``None`` if unavailable.\n\n Built-in methods\n This is really a different disguise of a built-in function, this\n time containing an object passed to the C function as an\n implicit extra argument. An example of a built-in method is\n ``alist.append()``, assuming *alist* is a list object. In this\n case, the special read-only attribute ``__self__`` is set to the\n object denoted by *alist*.\n\n Classes\n Classes are callable. These objects normally act as factories\n for new instances of themselves, but variations are possible for\n class types that override ``__new__()``. The arguments of the\n call are passed to ``__new__()`` and, in the typical case, to\n ``__init__()`` to initialize the new instance.\n\n Class Instances\n Instances of arbitrary classes can be made callable by defining\n a ``__call__()`` method in their class.\n\nModules\n Modules are imported by the ``import`` statement (see section *The\n import statement*). A module object has a namespace implemented by\n a dictionary object (this is the dictionary referenced by the\n __globals__ attribute of functions defined in the module).\n Attribute references are translated to lookups in this dictionary,\n e.g., ``m.x`` is equivalent to ``m.__dict__["x"]``. A module object\n does not contain the code object used to initialize the module\n (since it isn\'t needed once the initialization is done).\n\n Attribute assignment updates the module\'s namespace dictionary,\n e.g., ``m.x = 1`` is equivalent to ``m.__dict__["x"] = 1``.\n\n Special read-only attribute: ``__dict__`` is the module\'s namespace\n as a dictionary object.\n\n **CPython implementation detail:** Because of the way CPython\n clears module dictionaries, the module dictionary will be cleared\n when the module falls out of scope even if the dictionary still has\n live references. To avoid this, copy the dictionary or keep the\n module around while using its dictionary directly.\n\n Predefined (writable) attributes: ``__name__`` is the module\'s\n name; ``__doc__`` is the module\'s documentation string, or ``None``\n if unavailable; ``__file__`` is the pathname of the file from which\n the module was loaded, if it was loaded from a file. The\n ``__file__`` attribute is not present for C modules that are\n statically linked into the interpreter; for extension modules\n loaded dynamically from a shared library, it is the pathname of the\n shared library file.\n\nCustom classes\n Custom class types are typically created by class definitions (see\n section *Class definitions*). A class has a namespace implemented\n by a dictionary object. Class attribute references are translated\n to lookups in this dictionary, e.g., ``C.x`` is translated to\n ``C.__dict__["x"]`` (although there are a number of hooks which\n allow for other means of locating attributes). When the attribute\n name is not found there, the attribute search continues in the base\n classes. This search of the base classes uses the C3 method\n resolution order which behaves correctly even in the presence of\n \'diamond\' inheritance structures where there are multiple\n inheritance paths leading back to a common ancestor. Additional\n details on the C3 MRO used by Python can be found in the\n documentation accompanying the 2.3 release at\n http://www.python.org/download/releases/2.3/mro/.\n\n When a class attribute reference (for class ``C``, say) would yield\n a class method object, it is transformed into an instance method\n object whose ``__self__`` attributes is ``C``. When it would yield\n a static method object, it is transformed into the object wrapped\n by the static method object. See section *Implementing Descriptors*\n for another way in which attributes retrieved from a class may\n differ from those actually contained in its ``__dict__``.\n\n Class attribute assignments update the class\'s dictionary, never\n the dictionary of a base class.\n\n A class object can be called (see above) to yield a class instance\n (see below).\n\n Special attributes: ``__name__`` is the class name; ``__module__``\n is the module name in which the class was defined; ``__dict__`` is\n the dictionary containing the class\'s namespace; ``__bases__`` is a\n tuple (possibly empty or a singleton) containing the base classes,\n in the order of their occurrence in the base class list;\n ``__doc__`` is the class\'s documentation string, or None if\n undefined.\n\nClass instances\n A class instance is created by calling a class object (see above).\n A class instance has a namespace implemented as a dictionary which\n is the first place in which attribute references are searched.\n When an attribute is not found there, and the instance\'s class has\n an attribute by that name, the search continues with the class\n attributes. If a class attribute is found that is a user-defined\n function object, it is transformed into an instance method object\n whose ``__self__`` attribute is the instance. Static method and\n class method objects are also transformed; see above under\n "Classes". See section *Implementing Descriptors* for another way\n in which attributes of a class retrieved via its instances may\n differ from the objects actually stored in the class\'s\n ``__dict__``. If no class attribute is found, and the object\'s\n class has a ``__getattr__()`` method, that is called to satisfy the\n lookup.\n\n Attribute assignments and deletions update the instance\'s\n dictionary, never a class\'s dictionary. If the class has a\n ``__setattr__()`` or ``__delattr__()`` method, this is called\n instead of updating the instance dictionary directly.\n\n Class instances can pretend to be numbers, sequences, or mappings\n if they have methods with certain special names. See section\n *Special method names*.\n\n Special attributes: ``__dict__`` is the attribute dictionary;\n ``__class__`` is the instance\'s class.\n\nI/O objects (also known as file objects)\n A *file object* represents an open file. Various shortcuts are\n available to create file objects: the ``open()`` built-in function,\n and also ``os.popen()``, ``os.fdopen()``, and the ``makefile()``\n method of socket objects (and perhaps by other functions or methods\n provided by extension modules).\n\n The objects ``sys.stdin``, ``sys.stdout`` and ``sys.stderr`` are\n initialized to file objects corresponding to the interpreter\'s\n standard input, output and error streams; they are all open in text\n mode and therefore follow the interface defined by the\n ``io.TextIOBase`` abstract class.\n\nInternal types\n A few types used internally by the interpreter are exposed to the\n user. Their definitions may change with future versions of the\n interpreter, but they are mentioned here for completeness.\n\n Code objects\n Code objects represent *byte-compiled* executable Python code,\n or *bytecode*. The difference between a code object and a\n function object is that the function object contains an explicit\n reference to the function\'s globals (the module in which it was\n defined), while a code object contains no context; also the\n default argument values are stored in the function object, not\n in the code object (because they represent values calculated at\n run-time). Unlike function objects, code objects are immutable\n and contain no references (directly or indirectly) to mutable\n objects.\n\n Special read-only attributes: ``co_name`` gives the function\n name; ``co_argcount`` is the number of positional arguments\n (including arguments with default values); ``co_nlocals`` is the\n number of local variables used by the function (including\n arguments); ``co_varnames`` is a tuple containing the names of\n the local variables (starting with the argument names);\n ``co_cellvars`` is a tuple containing the names of local\n variables that are referenced by nested functions;\n ``co_freevars`` is a tuple containing the names of free\n variables; ``co_code`` is a string representing the sequence of\n bytecode instructions; ``co_consts`` is a tuple containing the\n literals used by the bytecode; ``co_names`` is a tuple\n containing the names used by the bytecode; ``co_filename`` is\n the filename from which the code was compiled;\n ``co_firstlineno`` is the first line number of the function;\n ``co_lnotab`` is a string encoding the mapping from bytecode\n offsets to line numbers (for details see the source code of the\n interpreter); ``co_stacksize`` is the required stack size\n (including local variables); ``co_flags`` is an integer encoding\n a number of flags for the interpreter.\n\n The following flag bits are defined for ``co_flags``: bit\n ``0x04`` is set if the function uses the ``*arguments`` syntax\n to accept an arbitrary number of positional arguments; bit\n ``0x08`` is set if the function uses the ``**keywords`` syntax\n to accept arbitrary keyword arguments; bit ``0x20`` is set if\n the function is a generator.\n\n Future feature declarations (``from __future__ import\n division``) also use bits in ``co_flags`` to indicate whether a\n code object was compiled with a particular feature enabled: bit\n ``0x2000`` is set if the function was compiled with future\n division enabled; bits ``0x10`` and ``0x1000`` were used in\n earlier versions of Python.\n\n Other bits in ``co_flags`` are reserved for internal use.\n\n If a code object represents a function, the first item in\n ``co_consts`` is the documentation string of the function, or\n ``None`` if undefined.\n\n Frame objects\n Frame objects represent execution frames. They may occur in\n traceback objects (see below).\n\n Special read-only attributes: ``f_back`` is to the previous\n stack frame (towards the caller), or ``None`` if this is the\n bottom stack frame; ``f_code`` is the code object being executed\n in this frame; ``f_locals`` is the dictionary used to look up\n local variables; ``f_globals`` is used for global variables;\n ``f_builtins`` is used for built-in (intrinsic) names;\n ``f_lasti`` gives the precise instruction (this is an index into\n the bytecode string of the code object).\n\n Special writable attributes: ``f_trace``, if not ``None``, is a\n function called at the start of each source code line (this is\n used by the debugger); ``f_lineno`` is the current line number\n of the frame --- writing to this from within a trace function\n jumps to the given line (only for the bottom-most frame). A\n debugger can implement a Jump command (aka Set Next Statement)\n by writing to f_lineno.\n\n Traceback objects\n Traceback objects represent a stack trace of an exception. A\n traceback object is created when an exception occurs. When the\n search for an exception handler unwinds the execution stack, at\n each unwound level a traceback object is inserted in front of\n the current traceback. When an exception handler is entered,\n the stack trace is made available to the program. (See section\n *The try statement*.) It is accessible as the third item of the\n tuple returned by ``sys.exc_info()``. When the program contains\n no suitable handler, the stack trace is written (nicely\n formatted) to the standard error stream; if the interpreter is\n interactive, it is also made available to the user as\n ``sys.last_traceback``.\n\n Special read-only attributes: ``tb_next`` is the next level in\n the stack trace (towards the frame where the exception\n occurred), or ``None`` if there is no next level; ``tb_frame``\n points to the execution frame of the current level;\n ``tb_lineno`` gives the line number where the exception\n occurred; ``tb_lasti`` indicates the precise instruction. The\n line number and last instruction in the traceback may differ\n from the line number of its frame object if the exception\n occurred in a ``try`` statement with no matching except clause\n or with a finally clause.\n\n Slice objects\n Slice objects are used to represent slices for ``__getitem__()``\n methods. They are also created by the built-in ``slice()``\n function.\n\n Special read-only attributes: ``start`` is the lower bound;\n ``stop`` is the upper bound; ``step`` is the step value; each is\n ``None`` if omitted. These attributes can have any type.\n\n Slice objects support one method:\n\n slice.indices(self, length)\n\n This method takes a single integer argument *length* and\n computes information about the slice that the slice object\n would describe if applied to a sequence of *length* items.\n It returns a tuple of three integers; respectively these are\n the *start* and *stop* indices and the *step* or stride\n length of the slice. Missing or out-of-bounds indices are\n handled in a manner consistent with regular slices.\n\n Static method objects\n Static method objects provide a way of defeating the\n transformation of function objects to method objects described\n above. A static method object is a wrapper around any other\n object, usually a user-defined method object. When a static\n method object is retrieved from a class or a class instance, the\n object actually returned is the wrapped object, which is not\n subject to any further transformation. Static method objects are\n not themselves callable, although the objects they wrap usually\n are. Static method objects are created by the built-in\n ``staticmethod()`` constructor.\n\n Class method objects\n A class method object, like a static method object, is a wrapper\n around another object that alters the way in which that object\n is retrieved from classes and class instances. The behaviour of\n class method objects upon such retrieval is described above,\n under "User-defined methods". Class method objects are created\n by the built-in ``classmethod()`` constructor.\n',
'typesfunctions': '\nFunctions\n*********\n\nFunction objects are created by function definitions. The only\noperation on a function object is to call it: ``func(argument-list)``.\n\nThere are really two flavors of function objects: built-in functions\nand user-defined functions. Both support the same operation (to call\nthe function), but the implementation is different, hence the\ndifferent object types.\n\nSee *Function definitions* for more information.\n',
- 'typesmapping': '\nMapping Types --- ``dict``\n**************************\n\nA *mapping* object maps *hashable* values to arbitrary objects.\nMappings are mutable objects. There is currently only one standard\nmapping type, the *dictionary*. (For other containers see the built\nin ``list``, ``set``, and ``tuple`` classes, and the ``collections``\nmodule.)\n\nA dictionary\'s keys are *almost* arbitrary values. Values that are\nnot *hashable*, that is, values containing lists, dictionaries or\nother mutable types (that are compared by value rather than by object\nidentity) may not be used as keys. Numeric types used for keys obey\nthe normal rules for numeric comparison: if two numbers compare equal\n(such as ``1`` and ``1.0``) then they can be used interchangeably to\nindex the same dictionary entry. (Note however, that since computers\nstore floating-point numbers as approximations it is usually unwise to\nuse them as dictionary keys.)\n\nDictionaries can be created by placing a comma-separated list of\n``key: value`` pairs within braces, for example: ``{\'jack\': 4098,\n\'sjoerd\': 4127}`` or ``{4098: \'jack\', 4127: \'sjoerd\'}``, or by the\n``dict`` constructor.\n\nclass class dict([arg])\n\n Return a new dictionary initialized from an optional positional\n argument or from a set of keyword arguments. If no arguments are\n given, return a new empty dictionary. If the positional argument\n *arg* is a mapping object, return a dictionary mapping the same\n keys to the same values as does the mapping object. Otherwise the\n positional argument must be a sequence, a container that supports\n iteration, or an iterator object. The elements of the argument\n must each also be of one of those kinds, and each must in turn\n contain exactly two objects. The first is used as a key in the new\n dictionary, and the second as the key\'s value. If a given key is\n seen more than once, the last value associated with it is retained\n in the new dictionary.\n\n If keyword arguments are given, the keywords themselves with their\n associated values are added as items to the dictionary. If a key\n is specified both in the positional argument and as a keyword\n argument, the value associated with the keyword is retained in the\n dictionary. For example, these all return a dictionary equal to\n ``{"one": 1, "two": 2}``:\n\n * ``dict(one=1, two=2)``\n\n * ``dict({\'one\': 1, \'two\': 2})``\n\n * ``dict(zip((\'one\', \'two\'), (1, 2)))``\n\n * ``dict([[\'two\', 2], [\'one\', 1]])``\n\n The first example only works for keys that are valid Python\n identifiers; the others work with any valid keys.\n\n These are the operations that dictionaries support (and therefore,\n custom mapping types should support too):\n\n len(d)\n\n Return the number of items in the dictionary *d*.\n\n d[key]\n\n Return the item of *d* with key *key*. Raises a ``KeyError`` if\n *key* is not in the map.\n\n If a subclass of dict defines a method ``__missing__()``, if the\n key *key* is not present, the ``d[key]`` operation calls that\n method with the key *key* as argument. The ``d[key]`` operation\n then returns or raises whatever is returned or raised by the\n ``__missing__(key)`` call if the key is not present. No other\n operations or methods invoke ``__missing__()``. If\n ``__missing__()`` is not defined, ``KeyError`` is raised.\n ``__missing__()`` must be a method; it cannot be an instance\n variable:\n\n >>> class Counter(dict):\n ... def __missing__(self, key):\n ... return 0\n >>> c = Counter()\n >>> c[\'red\']\n 0\n >>> c[\'red\'] += 1\n >>> c[\'red\']\n 1\n\n See ``collections.Counter`` for a complete implementation\n including other methods helpful for accumulating and managing\n tallies.\n\n d[key] = value\n\n Set ``d[key]`` to *value*.\n\n del d[key]\n\n Remove ``d[key]`` from *d*. Raises a ``KeyError`` if *key* is\n not in the map.\n\n key in d\n\n Return ``True`` if *d* has a key *key*, else ``False``.\n\n key not in d\n\n Equivalent to ``not key in d``.\n\n iter(d)\n\n Return an iterator over the keys of the dictionary. This is a\n shortcut for ``iter(d.keys())``.\n\n clear()\n\n Remove all items from the dictionary.\n\n copy()\n\n Return a shallow copy of the dictionary.\n\n classmethod fromkeys(seq[, value])\n\n Create a new dictionary with keys from *seq* and values set to\n *value*.\n\n ``fromkeys()`` is a class method that returns a new dictionary.\n *value* defaults to ``None``.\n\n get(key[, default])\n\n Return the value for *key* if *key* is in the dictionary, else\n *default*. If *default* is not given, it defaults to ``None``,\n so that this method never raises a ``KeyError``.\n\n items()\n\n Return a new view of the dictionary\'s items (``(key, value)``\n pairs). See below for documentation of view objects.\n\n keys()\n\n Return a new view of the dictionary\'s keys. See below for\n documentation of view objects.\n\n pop(key[, default])\n\n If *key* is in the dictionary, remove it and return its value,\n else return *default*. If *default* is not given and *key* is\n not in the dictionary, a ``KeyError`` is raised.\n\n popitem()\n\n Remove and return an arbitrary ``(key, value)`` pair from the\n dictionary.\n\n ``popitem()`` is useful to destructively iterate over a\n dictionary, as often used in set algorithms. If the dictionary\n is empty, calling ``popitem()`` raises a ``KeyError``.\n\n setdefault(key[, default])\n\n If *key* is in the dictionary, return its value. If not, insert\n *key* with a value of *default* and return *default*. *default*\n defaults to ``None``.\n\n update([other])\n\n Update the dictionary with the key/value pairs from *other*,\n overwriting existing keys. Return ``None``.\n\n ``update()`` accepts either another dictionary object or an\n iterable of key/value pairs (as tuples or other iterables of\n length two). If keyword arguments are specified, the dictionary\n is then updated with those key/value pairs: ``d.update(red=1,\n blue=2)``.\n\n values()\n\n Return a new view of the dictionary\'s values. See below for\n documentation of view objects.\n\n\nDictionary view objects\n=======================\n\nThe objects returned by ``dict.keys()``, ``dict.values()`` and\n``dict.items()`` are *view objects*. They provide a dynamic view on\nthe dictionary\'s entries, which means that when the dictionary\nchanges, the view reflects these changes.\n\nDictionary views can be iterated over to yield their respective data,\nand support membership tests:\n\nlen(dictview)\n\n Return the number of entries in the dictionary.\n\niter(dictview)\n\n Return an iterator over the keys, values or items (represented as\n tuples of ``(key, value)``) in the dictionary.\n\n Keys and values are iterated over in an arbitrary order which is\n non-random, varies across Python implementations, and depends on\n the dictionary\'s history of insertions and deletions. If keys,\n values and items views are iterated over with no intervening\n modifications to the dictionary, the order of items will directly\n correspond. This allows the creation of ``(value, key)`` pairs\n using ``zip()``: ``pairs = zip(d.values(), d.keys())``. Another\n way to create the same list is ``pairs = [(v, k) for (k, v) in\n d.items()]``.\n\n Iterating views while adding or deleting entries in the dictionary\n may raise a ``RuntimeError`` or fail to iterate over all entries.\n\nx in dictview\n\n Return ``True`` if *x* is in the underlying dictionary\'s keys,\n values or items (in the latter case, *x* should be a ``(key,\n value)`` tuple).\n\nKeys views are set-like since their entries are unique and hashable.\nIf all values are hashable, so that ``(key, value)`` pairs are unique\nand hashable, then the items view is also set-like. (Values views are\nnot treated as set-like since the entries are generally not unique.)\nFor set-like views, all of the operations defined for the abstract\nbase class ``collections.Set`` are available (for example, ``==``,\n``<``, or ``^``).\n\nAn example of dictionary view usage:\n\n >>> dishes = {\'eggs\': 2, \'sausage\': 1, \'bacon\': 1, \'spam\': 500}\n >>> keys = dishes.keys()\n >>> values = dishes.values()\n\n >>> # iteration\n >>> n = 0\n >>> for val in values:\n ... n += val\n >>> print(n)\n 504\n\n >>> # keys and values are iterated over in the same order\n >>> list(keys)\n [\'eggs\', \'bacon\', \'sausage\', \'spam\']\n >>> list(values)\n [2, 1, 1, 500]\n\n >>> # view objects are dynamic and reflect dict changes\n >>> del dishes[\'eggs\']\n >>> del dishes[\'sausage\']\n >>> list(keys)\n [\'spam\', \'bacon\']\n\n >>> # set operations\n >>> keys & {\'eggs\', \'bacon\', \'salad\'}\n {\'bacon\'}\n >>> keys ^ {\'sausage\', \'juice\'}\n {\'juice\', \'eggs\', \'bacon\', \'spam\'}\n',
+ 'typesmapping': '\nMapping Types --- ``dict``\n**************************\n\nA *mapping* object maps *hashable* values to arbitrary objects.\nMappings are mutable objects. There is currently only one standard\nmapping type, the *dictionary*. (For other containers see the built\nin ``list``, ``set``, and ``tuple`` classes, and the ``collections``\nmodule.)\n\nA dictionary\'s keys are *almost* arbitrary values. Values that are\nnot *hashable*, that is, values containing lists, dictionaries or\nother mutable types (that are compared by value rather than by object\nidentity) may not be used as keys. Numeric types used for keys obey\nthe normal rules for numeric comparison: if two numbers compare equal\n(such as ``1`` and ``1.0``) then they can be used interchangeably to\nindex the same dictionary entry. (Note however, that since computers\nstore floating-point numbers as approximations it is usually unwise to\nuse them as dictionary keys.)\n\nDictionaries can be created by placing a comma-separated list of\n``key: value`` pairs within braces, for example: ``{\'jack\': 4098,\n\'sjoerd\': 4127}`` or ``{4098: \'jack\', 4127: \'sjoerd\'}``, or by the\n``dict`` constructor.\n\nclass class dict([arg])\n\n Return a new dictionary initialized from an optional positional\n argument or from a set of keyword arguments. If no arguments are\n given, return a new empty dictionary. If the positional argument\n *arg* is a mapping object, return a dictionary mapping the same\n keys to the same values as does the mapping object. Otherwise the\n positional argument must be a sequence, a container that supports\n iteration, or an iterator object. The elements of the argument\n must each also be of one of those kinds, and each must in turn\n contain exactly two objects. The first is used as a key in the new\n dictionary, and the second as the key\'s value. If a given key is\n seen more than once, the last value associated with it is retained\n in the new dictionary.\n\n If keyword arguments are given, the keywords themselves with their\n associated values are added as items to the dictionary. If a key\n is specified both in the positional argument and as a keyword\n argument, the value associated with the keyword is retained in the\n dictionary. For example, these all return a dictionary equal to\n ``{"one": 1, "two": 2}``:\n\n * ``dict(one=1, two=2)``\n\n * ``dict({\'one\': 1, \'two\': 2})``\n\n * ``dict(zip((\'one\', \'two\'), (1, 2)))``\n\n * ``dict([[\'two\', 2], [\'one\', 1]])``\n\n The first example only works for keys that are valid Python\n identifiers; the others work with any valid keys.\n\n These are the operations that dictionaries support (and therefore,\n custom mapping types should support too):\n\n len(d)\n\n Return the number of items in the dictionary *d*.\n\n d[key]\n\n Return the item of *d* with key *key*. Raises a ``KeyError`` if\n *key* is not in the map.\n\n If a subclass of dict defines a method ``__missing__()``, if the\n key *key* is not present, the ``d[key]`` operation calls that\n method with the key *key* as argument. The ``d[key]`` operation\n then returns or raises whatever is returned or raised by the\n ``__missing__(key)`` call if the key is not present. No other\n operations or methods invoke ``__missing__()``. If\n ``__missing__()`` is not defined, ``KeyError`` is raised.\n ``__missing__()`` must be a method; it cannot be an instance\n variable:\n\n >>> class Counter(dict):\n ... def __missing__(self, key):\n ... return 0\n >>> c = Counter()\n >>> c[\'red\']\n 0\n >>> c[\'red\'] += 1\n >>> c[\'red\']\n 1\n\n See ``collections.Counter`` for a complete implementation\n including other methods helpful for accumulating and managing\n tallies.\n\n d[key] = value\n\n Set ``d[key]`` to *value*.\n\n del d[key]\n\n Remove ``d[key]`` from *d*. Raises a ``KeyError`` if *key* is\n not in the map.\n\n key in d\n\n Return ``True`` if *d* has a key *key*, else ``False``.\n\n key not in d\n\n Equivalent to ``not key in d``.\n\n iter(d)\n\n Return an iterator over the keys of the dictionary. This is a\n shortcut for ``iter(d.keys())``.\n\n clear()\n\n Remove all items from the dictionary.\n\n copy()\n\n Return a shallow copy of the dictionary.\n\n classmethod fromkeys(seq[, value])\n\n Create a new dictionary with keys from *seq* and values set to\n *value*.\n\n ``fromkeys()`` is a class method that returns a new dictionary.\n *value* defaults to ``None``.\n\n get(key[, default])\n\n Return the value for *key* if *key* is in the dictionary, else\n *default*. If *default* is not given, it defaults to ``None``,\n so that this method never raises a ``KeyError``.\n\n items()\n\n Return a new view of the dictionary\'s items (``(key, value)``\n pairs). See below for documentation of view objects.\n\n keys()\n\n Return a new view of the dictionary\'s keys. See below for\n documentation of view objects.\n\n pop(key[, default])\n\n If *key* is in the dictionary, remove it and return its value,\n else return *default*. If *default* is not given and *key* is\n not in the dictionary, a ``KeyError`` is raised.\n\n popitem()\n\n Remove and return an arbitrary ``(key, value)`` pair from the\n dictionary.\n\n ``popitem()`` is useful to destructively iterate over a\n dictionary, as often used in set algorithms. If the dictionary\n is empty, calling ``popitem()`` raises a ``KeyError``.\n\n setdefault(key[, default])\n\n If *key* is in the dictionary, return its value. If not, insert\n *key* with a value of *default* and return *default*. *default*\n defaults to ``None``.\n\n update([other])\n\n Update the dictionary with the key/value pairs from *other*,\n overwriting existing keys. Return ``None``.\n\n ``update()`` accepts either another dictionary object or an\n iterable of key/value pairs (as tuples or other iterables of\n length two). If keyword arguments are specified, the dictionary\n is then updated with those key/value pairs: ``d.update(red=1,\n blue=2)``.\n\n values()\n\n Return a new view of the dictionary\'s values. See below for\n documentation of view objects.\n\n\nDictionary view objects\n=======================\n\nThe objects returned by ``dict.keys()``, ``dict.values()`` and\n``dict.items()`` are *view objects*. They provide a dynamic view on\nthe dictionary\'s entries, which means that when the dictionary\nchanges, the view reflects these changes.\n\nDictionary views can be iterated over to yield their respective data,\nand support membership tests:\n\nlen(dictview)\n\n Return the number of entries in the dictionary.\n\niter(dictview)\n\n Return an iterator over the keys, values or items (represented as\n tuples of ``(key, value)``) in the dictionary.\n\n Keys and values are iterated over in an arbitrary order which is\n non-random, varies across Python implementations, and depends on\n the dictionary\'s history of insertions and deletions. If keys,\n values and items views are iterated over with no intervening\n modifications to the dictionary, the order of items will directly\n correspond. This allows the creation of ``(value, key)`` pairs\n using ``zip()``: ``pairs = zip(d.values(), d.keys())``. Another\n way to create the same list is ``pairs = [(v, k) for (k, v) in\n d.items()]``.\n\n Iterating views while adding or deleting entries in the dictionary\n may raise a ``RuntimeError`` or fail to iterate over all entries.\n\nx in dictview\n\n Return ``True`` if *x* is in the underlying dictionary\'s keys,\n values or items (in the latter case, *x* should be a ``(key,\n value)`` tuple).\n\nKeys views are set-like since their entries are unique and hashable.\nIf all values are hashable, so that ``(key, value)`` pairs are unique\nand hashable, then the items view is also set-like. (Values views are\nnot treated as set-like since the entries are generally not unique.)\nFor set-like views, all of the operations defined for the abstract\nbase class ``collections.Set`` are available (for example, ``==``,\n``<``, or ``^``).\n\nAn example of dictionary view usage:\n\n >>> dishes = {\'eggs\': 2, \'sausage\': 1, \'bacon\': 1, \'spam\': 500}\n >>> keys = dishes.keys()\n >>> values = dishes.values()\n\n >>> # iteration\n >>> n = 0\n >>> for val in values:\n ... n += val\n >>> print(n)\n 504\n\n >>> # keys and values are iterated over in the same order\n >>> list(keys)\n [\'eggs\', \'bacon\', \'sausage\', \'spam\']\n >>> list(values)\n [2, 1, 1, 500]\n\n >>> # view objects are dynamic and reflect dict changes\n >>> del dishes[\'eggs\']\n >>> del dishes[\'sausage\']\n >>> list(keys)\n [\'spam\', \'bacon\']\n\n >>> # set operations\n >>> keys & {\'eggs\', \'bacon\', \'salad\'}\n {\'bacon\'}\n >>> keys ^ {\'sausage\', \'juice\'}\n {\'juice\', \'sausage\', \'bacon\', \'spam\'}\n',
'typesmethods': "\nMethods\n*******\n\nMethods are functions that are called using the attribute notation.\nThere are two flavors: built-in methods (such as ``append()`` on\nlists) and class instance methods. Built-in methods are described\nwith the types that support them.\n\nIf you access a method (a function defined in a class namespace)\nthrough an instance, you get a special object: a *bound method* (also\ncalled *instance method*) object. When called, it will add the\n``self`` argument to the argument list. Bound methods have two\nspecial read-only attributes: ``m.__self__`` is the object on which\nthe method operates, and ``m.__func__`` is the function implementing\nthe method. Calling ``m(arg-1, arg-2, ..., arg-n)`` is completely\nequivalent to calling ``m.__func__(m.__self__, arg-1, arg-2, ...,\narg-n)``.\n\nLike function objects, bound method objects support getting arbitrary\nattributes. However, since method attributes are actually stored on\nthe underlying function object (``meth.__func__``), setting method\nattributes on bound methods is disallowed. Attempting to set a method\nattribute results in a ``TypeError`` being raised. In order to set a\nmethod attribute, you need to explicitly set it on the underlying\nfunction object:\n\n class C:\n def method(self):\n pass\n\n c = C()\n c.method.__func__.whoami = 'my name is c'\n\nSee *The standard type hierarchy* for more information.\n",
- 'typesmodules': "\nModules\n*******\n\nThe only special operation on a module is attribute access:\n``m.name``, where *m* is a module and *name* accesses a name defined\nin *m*'s symbol table. Module attributes can be assigned to. (Note\nthat the ``import`` statement is not, strictly speaking, an operation\non a module object; ``import foo`` does not require a module object\nnamed *foo* to exist, rather it requires an (external) *definition*\nfor a module named *foo* somewhere.)\n\nA special member of every module is ``__dict__``. This is the\ndictionary containing the module's symbol table. Modifying this\ndictionary will actually change the module's symbol table, but direct\nassignment to the ``__dict__`` attribute is not possible (you can\nwrite ``m.__dict__['a'] = 1``, which defines ``m.a`` to be ``1``, but\nyou can't write ``m.__dict__ = {}``). Modifying ``__dict__`` directly\nis not recommended.\n\nModules built into the interpreter are written like this: ``<module\n'sys' (built-in)>``. If loaded from a file, they are written as\n``<module 'os' from '/usr/local/lib/pythonX.Y/os.pyc'>``.\n",
- 'typesseq': '\nSequence Types --- ``str``, ``bytes``, ``bytearray``, ``list``, ``tuple``, ``range``\n************************************************************************************\n\nThere are six sequence types: strings, byte sequences (``bytes``\nobjects), byte arrays (``bytearray`` objects), lists, tuples, and\nrange objects. For other containers see the built in ``dict`` and\n``set`` classes, and the ``collections`` module.\n\nStrings contain Unicode characters. Their literals are written in\nsingle or double quotes: ``\'xyzzy\'``, ``"frobozz"``. See *String and\nBytes literals* for more about string literals. In addition to the\nfunctionality described here, there are also string-specific methods\ndescribed in the *String Methods* section.\n\nBytes and bytearray objects contain single bytes -- the former is\nimmutable while the latter is a mutable sequence. Bytes objects can\nbe constructed the constructor, ``bytes()``, and from literals; use a\n``b`` prefix with normal string syntax: ``b\'xyzzy\'``. To construct\nbyte arrays, use the ``bytearray()`` function.\n\nWhile string objects are sequences of characters (represented by\nstrings of length 1), bytes and bytearray objects are sequences of\n*integers* (between 0 and 255), representing the ASCII value of single\nbytes. That means that for a bytes or bytearray object *b*, ``b[0]``\nwill be an integer, while ``b[0:1]`` will be a bytes or bytearray\nobject of length 1. The representation of bytes objects uses the\nliteral format (``b\'...\'``) since it is generally more useful than\ne.g. ``bytes([50, 19, 100])``. You can always convert a bytes object\ninto a list of integers using ``list(b)``.\n\nAlso, while in previous Python versions, byte strings and Unicode\nstrings could be exchanged for each other rather freely (barring\nencoding issues), strings and bytes are now completely separate\nconcepts. There\'s no implicit en-/decoding if you pass an object of\nthe wrong type. A string always compares unequal to a bytes or\nbytearray object.\n\nLists are constructed with square brackets, separating items with\ncommas: ``[a, b, c]``. Tuples are constructed by the comma operator\n(not within square brackets), with or without enclosing parentheses,\nbut an empty tuple must have the enclosing parentheses, such as ``a,\nb, c`` or ``()``. A single item tuple must have a trailing comma,\nsuch as ``(d,)``.\n\nObjects of type range are created using the ``range()`` function.\nThey don\'t support concatenation or repetition, and using ``min()`` or\n``max()`` on them is inefficient.\n\nMost sequence types support the following operations. The ``in`` and\n``not in`` operations have the same priorities as the comparison\noperations. The ``+`` and ``*`` operations have the same priority as\nthe corresponding numeric operations. [3] Additional methods are\nprovided for *Mutable Sequence Types*.\n\nThis table lists the sequence operations sorted in ascending priority\n(operations in the same box have the same priority). In the table,\n*s* and *t* are sequences of the same type; *n*, *i*, *j* and *k* are\nintegers.\n\n+--------------------+----------------------------------+------------+\n| Operation | Result | Notes |\n+====================+==================================+============+\n| ``x in s`` | ``True`` if an item of *s* is | (1) |\n| | equal to *x*, else ``False`` | |\n+--------------------+----------------------------------+------------+\n| ``x not in s`` | ``False`` if an item of *s* is | (1) |\n| | equal to *x*, else ``True`` | |\n+--------------------+----------------------------------+------------+\n| ``s + t`` | the concatenation of *s* and *t* | (6) |\n+--------------------+----------------------------------+------------+\n| ``s * n, n * s`` | *n* shallow copies of *s* | (2) |\n| | concatenated | |\n+--------------------+----------------------------------+------------+\n| ``s[i]`` | *i*\'th item of *s*, origin 0 | (3) |\n+--------------------+----------------------------------+------------+\n| ``s[i:j]`` | slice of *s* from *i* to *j* | (3)(4) |\n+--------------------+----------------------------------+------------+\n| ``s[i:j:k]`` | slice of *s* from *i* to *j* | (3)(5) |\n| | with step *k* | |\n+--------------------+----------------------------------+------------+\n| ``len(s)`` | length of *s* | |\n+--------------------+----------------------------------+------------+\n| ``min(s)`` | smallest item of *s* | |\n+--------------------+----------------------------------+------------+\n| ``max(s)`` | largest item of *s* | |\n+--------------------+----------------------------------+------------+\n| ``s.index(i)`` | index of the first occurence of | |\n| | *i* in *s* | |\n+--------------------+----------------------------------+------------+\n| ``s.count(i)`` | total number of occurences of | |\n| | *i* in *s* | |\n+--------------------+----------------------------------+------------+\n\nSequence types also support comparisons. In particular, tuples and\nlists are compared lexicographically by comparing corresponding\nelements. This means that to compare equal, every element must\ncompare equal and the two sequences must be of the same type and have\nthe same length. (For full details see *Comparisons* in the language\nreference.)\n\nNotes:\n\n1. When *s* is a string object, the ``in`` and ``not in`` operations\n act like a substring test.\n\n2. Values of *n* less than ``0`` are treated as ``0`` (which yields an\n empty sequence of the same type as *s*). Note also that the copies\n are shallow; nested structures are not copied. This often haunts\n new Python programmers; consider:\n\n >>> lists = [[]] * 3\n >>> lists\n [[], [], []]\n >>> lists[0].append(3)\n >>> lists\n [[3], [3], [3]]\n\n What has happened is that ``[[]]`` is a one-element list containing\n an empty list, so all three elements of ``[[]] * 3`` are (pointers\n to) this single empty list. Modifying any of the elements of\n ``lists`` modifies this single list. You can create a list of\n different lists this way:\n\n >>> lists = [[] for i in range(3)]\n >>> lists[0].append(3)\n >>> lists[1].append(5)\n >>> lists[2].append(7)\n >>> lists\n [[3], [5], [7]]\n\n3. If *i* or *j* is negative, the index is relative to the end of the\n string: ``len(s) + i`` or ``len(s) + j`` is substituted. But note\n that ``-0`` is still ``0``.\n\n4. The slice of *s* from *i* to *j* is defined as the sequence of\n items with index *k* such that ``i <= k < j``. If *i* or *j* is\n greater than ``len(s)``, use ``len(s)``. If *i* is omitted or\n ``None``, use ``0``. If *j* is omitted or ``None``, use\n ``len(s)``. If *i* is greater than or equal to *j*, the slice is\n empty.\n\n5. The slice of *s* from *i* to *j* with step *k* is defined as the\n sequence of items with index ``x = i + n*k`` such that ``0 <= n <\n (j-i)/k``. In other words, the indices are ``i``, ``i+k``,\n ``i+2*k``, ``i+3*k`` and so on, stopping when *j* is reached (but\n never including *j*). If *i* or *j* is greater than ``len(s)``,\n use ``len(s)``. If *i* or *j* are omitted or ``None``, they become\n "end" values (which end depends on the sign of *k*). Note, *k*\n cannot be zero. If *k* is ``None``, it is treated like ``1``.\n\n6. **CPython implementation detail:** If *s* and *t* are both strings,\n some Python implementations such as CPython can usually perform an\n in-place optimization for assignments of the form ``s = s + t`` or\n ``s += t``. When applicable, this optimization makes quadratic\n run-time much less likely. This optimization is both version and\n implementation dependent. For performance sensitive code, it is\n preferable to use the ``str.join()`` method which assures\n consistent linear concatenation performance across versions and\n implementations.\n\n\nString Methods\n==============\n\nString objects support the methods listed below.\n\nIn addition, Python\'s strings support the sequence type methods\ndescribed in the *Sequence Types --- str, bytes, bytearray, list,\ntuple, range* section. To output formatted strings, see the *String\nFormatting* section. Also, see the ``re`` module for string functions\nbased on regular expressions.\n\nstr.capitalize()\n\n Return a copy of the string with its first character capitalized\n and the rest lowercased.\n\nstr.center(width[, fillchar])\n\n Return centered in a string of length *width*. Padding is done\n using the specified *fillchar* (default is a space).\n\nstr.count(sub[, start[, end]])\n\n Return the number of non-overlapping occurrences of substring *sub*\n in the range [*start*, *end*]. Optional arguments *start* and\n *end* are interpreted as in slice notation.\n\nstr.encode(encoding="utf-8", errors="strict")\n\n Return an encoded version of the string as a bytes object. Default\n encoding is ``\'utf-8\'``. *errors* may be given to set a different\n error handling scheme. The default for *errors* is ``\'strict\'``,\n meaning that encoding errors raise a ``UnicodeError``. Other\n possible values are ``\'ignore\'``, ``\'replace\'``,\n ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and any other name\n registered via ``codecs.register_error()``, see section *Codec Base\n Classes*. For a list of possible encodings, see section *Standard\n Encodings*.\n\n Changed in version 3.1: Support for keyword arguments added.\n\nstr.endswith(suffix[, start[, end]])\n\n Return ``True`` if the string ends with the specified *suffix*,\n otherwise return ``False``. *suffix* can also be a tuple of\n suffixes to look for. With optional *start*, test beginning at\n that position. With optional *end*, stop comparing at that\n position.\n\nstr.expandtabs([tabsize])\n\n Return a copy of the string where all tab characters are replaced\n by one or more spaces, depending on the current column and the\n given tab size. The column number is reset to zero after each\n newline occurring in the string. If *tabsize* is not given, a tab\n size of ``8`` characters is assumed. This doesn\'t understand other\n non-printing characters or escape sequences.\n\nstr.find(sub[, start[, end]])\n\n Return the lowest index in the string where substring *sub* is\n found, such that *sub* is contained in the slice ``s[start:end]``.\n Optional arguments *start* and *end* are interpreted as in slice\n notation. Return ``-1`` if *sub* is not found.\n\nstr.format(*args, **kwargs)\n\n Perform a string formatting operation. The string on which this\n method is called can contain literal text or replacement fields\n delimited by braces ``{}``. Each replacement field contains either\n the numeric index of a positional argument, or the name of a\n keyword argument. Returns a copy of the string where each\n replacement field is replaced with the string value of the\n corresponding argument.\n\n >>> "The sum of 1 + 2 is {0}".format(1+2)\n \'The sum of 1 + 2 is 3\'\n\n See *Format String Syntax* for a description of the various\n formatting options that can be specified in format strings.\n\nstr.format_map(mapping)\n\n Similar to ``str.format(**mapping)``, except that ``mapping`` is\n used directly and not copied to a ``dict`` . This is useful if for\n example ``mapping`` is a dict subclass:\n\n >>> class Default(dict):\n ... def __missing__(self, key):\n ... return key\n ...\n >>> \'{name} was born in {country}\'.format_map(Default(name=\'Guido\'))\n \'Guido was born in country\'\n\n New in version 3.2.\n\nstr.index(sub[, start[, end]])\n\n Like ``find()``, but raise ``ValueError`` when the substring is not\n found.\n\nstr.isalnum()\n\n Return true if all characters in the string are alphanumeric and\n there is at least one character, false otherwise. A character\n ``c`` is alphanumeric if one of the following returns ``True``:\n ``c.isalpha()``, ``c.isdecimal()``, ``c.isdigit()``, or\n ``c.isnumeric()``.\n\nstr.isalpha()\n\n Return true if all characters in the string are alphabetic and\n there is at least one character, false otherwise. Alphabetic\n characters are those characters defined in the Unicode character\n database as "Letter", i.e., those with general category property\n being one of "Lm", "Lt", "Lu", "Ll", or "Lo". Note that this is\n different from the "Alphabetic" property defined in the Unicode\n Standard.\n\nstr.isdecimal()\n\n Return true if all characters in the string are decimal characters\n and there is at least one character, false otherwise. Decimal\n characters are those from general category "Nd". This category\n includes digit characters, and all characters that that can be used\n to form decimal-radix numbers, e.g. U+0660, ARABIC-INDIC DIGIT\n ZERO.\n\nstr.isdigit()\n\n Return true if all characters in the string are digits and there is\n at least one character, false otherwise. Digits include decimal\n characters and digits that need special handling, such as the\n compatibility superscript digits. Formally, a digit is a character\n that has the property value Numeric_Type=Digit or\n Numeric_Type=Decimal.\n\nstr.isidentifier()\n\n Return true if the string is a valid identifier according to the\n language definition, section *Identifiers and keywords*.\n\nstr.islower()\n\n Return true if all cased characters in the string are lowercase and\n there is at least one cased character, false otherwise. Cased\n characters are those with general category property being one of\n "Lu", "Ll", or "Lt" and lowercase characters are those with general\n category property "Ll".\n\nstr.isnumeric()\n\n Return true if all characters in the string are numeric characters,\n and there is at least one character, false otherwise. Numeric\n characters include digit characters, and all characters that have\n the Unicode numeric value property, e.g. U+2155, VULGAR FRACTION\n ONE FIFTH. Formally, numeric characters are those with the\n property value Numeric_Type=Digit, Numeric_Type=Decimal or\n Numeric_Type=Numeric.\n\nstr.isprintable()\n\n Return true if all characters in the string are printable or the\n string is empty, false otherwise. Nonprintable characters are\n those characters defined in the Unicode character database as\n "Other" or "Separator", excepting the ASCII space (0x20) which is\n considered printable. (Note that printable characters in this\n context are those which should not be escaped when ``repr()`` is\n invoked on a string. It has no bearing on the handling of strings\n written to ``sys.stdout`` or ``sys.stderr``.)\n\nstr.isspace()\n\n Return true if there are only whitespace characters in the string\n and there is at least one character, false otherwise. Whitespace\n characters are those characters defined in the Unicode character\n database as "Other" or "Separator" and those with bidirectional\n property being one of "WS", "B", or "S".\n\nstr.istitle()\n\n Return true if the string is a titlecased string and there is at\n least one character, for example uppercase characters may only\n follow uncased characters and lowercase characters only cased ones.\n Return false otherwise.\n\nstr.isupper()\n\n Return true if all cased characters in the string are uppercase and\n there is at least one cased character, false otherwise. Cased\n characters are those with general category property being one of\n "Lu", "Ll", or "Lt" and uppercase characters are those with general\n category property "Lu".\n\nstr.join(iterable)\n\n Return a string which is the concatenation of the strings in the\n *iterable* *iterable*. A ``TypeError`` will be raised if there are\n any non-string values in *seq*, including ``bytes`` objects. The\n separator between elements is the string providing this method.\n\nstr.ljust(width[, fillchar])\n\n Return the string left justified in a string of length *width*.\n Padding is done using the specified *fillchar* (default is a\n space). The original string is returned if *width* is less than\n ``len(s)``.\n\nstr.lower()\n\n Return a copy of the string converted to lowercase.\n\nstr.lstrip([chars])\n\n Return a copy of the string with leading characters removed. The\n *chars* argument is a string specifying the set of characters to be\n removed. If omitted or ``None``, the *chars* argument defaults to\n removing whitespace. The *chars* argument is not a prefix; rather,\n all combinations of its values are stripped:\n\n >>> \' spacious \'.lstrip()\n \'spacious \'\n >>> \'www.example.com\'.lstrip(\'cmowz.\')\n \'example.com\'\n\nstatic str.maketrans(x[, y[, z]])\n\n This static method returns a translation table usable for\n ``str.translate()``.\n\n If there is only one argument, it must be a dictionary mapping\n Unicode ordinals (integers) or characters (strings of length 1) to\n Unicode ordinals, strings (of arbitrary lengths) or None.\n Character keys will then be converted to ordinals.\n\n If there are two arguments, they must be strings of equal length,\n and in the resulting dictionary, each character in x will be mapped\n to the character at the same position in y. If there is a third\n argument, it must be a string, whose characters will be mapped to\n None in the result.\n\nstr.partition(sep)\n\n Split the string at the first occurrence of *sep*, and return a\n 3-tuple containing the part before the separator, the separator\n itself, and the part after the separator. If the separator is not\n found, return a 3-tuple containing the string itself, followed by\n two empty strings.\n\nstr.replace(old, new[, count])\n\n Return a copy of the string with all occurrences of substring *old*\n replaced by *new*. If the optional argument *count* is given, only\n the first *count* occurrences are replaced.\n\nstr.rfind(sub[, start[, end]])\n\n Return the highest index in the string where substring *sub* is\n found, such that *sub* is contained within ``s[start:end]``.\n Optional arguments *start* and *end* are interpreted as in slice\n notation. Return ``-1`` on failure.\n\nstr.rindex(sub[, start[, end]])\n\n Like ``rfind()`` but raises ``ValueError`` when the substring *sub*\n is not found.\n\nstr.rjust(width[, fillchar])\n\n Return the string right justified in a string of length *width*.\n Padding is done using the specified *fillchar* (default is a\n space). The original string is returned if *width* is less than\n ``len(s)``.\n\nstr.rpartition(sep)\n\n Split the string at the last occurrence of *sep*, and return a\n 3-tuple containing the part before the separator, the separator\n itself, and the part after the separator. If the separator is not\n found, return a 3-tuple containing two empty strings, followed by\n the string itself.\n\nstr.rsplit([sep[, maxsplit]])\n\n Return a list of the words in the string, using *sep* as the\n delimiter string. If *maxsplit* is given, at most *maxsplit* splits\n are done, the *rightmost* ones. If *sep* is not specified or\n ``None``, any whitespace string is a separator. Except for\n splitting from the right, ``rsplit()`` behaves like ``split()``\n which is described in detail below.\n\nstr.rstrip([chars])\n\n Return a copy of the string with trailing characters removed. The\n *chars* argument is a string specifying the set of characters to be\n removed. If omitted or ``None``, the *chars* argument defaults to\n removing whitespace. The *chars* argument is not a suffix; rather,\n all combinations of its values are stripped:\n\n >>> \' spacious \'.rstrip()\n \' spacious\'\n >>> \'mississippi\'.rstrip(\'ipz\')\n \'mississ\'\n\nstr.split([sep[, maxsplit]])\n\n Return a list of the words in the string, using *sep* as the\n delimiter string. If *maxsplit* is given, at most *maxsplit*\n splits are done (thus, the list will have at most ``maxsplit+1``\n elements). If *maxsplit* is not specified, then there is no limit\n on the number of splits (all possible splits are made).\n\n If *sep* is given, consecutive delimiters are not grouped together\n and are deemed to delimit empty strings (for example,\n ``\'1,,2\'.split(\',\')`` returns ``[\'1\', \'\', \'2\']``). The *sep*\n argument may consist of multiple characters (for example,\n ``\'1<>2<>3\'.split(\'<>\')`` returns ``[\'1\', \'2\', \'3\']``). Splitting\n an empty string with a specified separator returns ``[\'\']``.\n\n If *sep* is not specified or is ``None``, a different splitting\n algorithm is applied: runs of consecutive whitespace are regarded\n as a single separator, and the result will contain no empty strings\n at the start or end if the string has leading or trailing\n whitespace. Consequently, splitting an empty string or a string\n consisting of just whitespace with a ``None`` separator returns\n ``[]``.\n\n For example, ``\' 1 2 3 \'.split()`` returns ``[\'1\', \'2\', \'3\']``,\n and ``\' 1 2 3 \'.split(None, 1)`` returns ``[\'1\', \'2 3 \']``.\n\nstr.splitlines([keepends])\n\n Return a list of the lines in the string, breaking at line\n boundaries. Line breaks are not included in the resulting list\n unless *keepends* is given and true.\n\nstr.startswith(prefix[, start[, end]])\n\n Return ``True`` if string starts with the *prefix*, otherwise\n return ``False``. *prefix* can also be a tuple of prefixes to look\n for. With optional *start*, test string beginning at that\n position. With optional *end*, stop comparing string at that\n position.\n\nstr.strip([chars])\n\n Return a copy of the string with the leading and trailing\n characters removed. The *chars* argument is a string specifying the\n set of characters to be removed. If omitted or ``None``, the\n *chars* argument defaults to removing whitespace. The *chars*\n argument is not a prefix or suffix; rather, all combinations of its\n values are stripped:\n\n >>> \' spacious \'.strip()\n \'spacious\'\n >>> \'www.example.com\'.strip(\'cmowz.\')\n \'example\'\n\nstr.swapcase()\n\n Return a copy of the string with uppercase characters converted to\n lowercase and vice versa.\n\nstr.title()\n\n Return a titlecased version of the string where words start with an\n uppercase character and the remaining characters are lowercase.\n\n The algorithm uses a simple language-independent definition of a\n word as groups of consecutive letters. The definition works in\n many contexts but it means that apostrophes in contractions and\n possessives form word boundaries, which may not be the desired\n result:\n\n >>> "they\'re bill\'s friends from the UK".title()\n "They\'Re Bill\'S Friends From The Uk"\n\n A workaround for apostrophes can be constructed using regular\n expressions:\n\n >>> import re\n >>> def titlecase(s):\n return re.sub(r"[A-Za-z]+(\'[A-Za-z]+)?",\n lambda mo: mo.group(0)[0].upper() +\n mo.group(0)[1:].lower(),\n s)\n\n >>> titlecase("they\'re bill\'s friends.")\n "They\'re Bill\'s Friends."\n\nstr.translate(map)\n\n Return a copy of the *s* where all characters have been mapped\n through the *map* which must be a dictionary of Unicode ordinals\n (integers) to Unicode ordinals, strings or ``None``. Unmapped\n characters are left untouched. Characters mapped to ``None`` are\n deleted.\n\n You can use ``str.maketrans()`` to create a translation map from\n character-to-character mappings in different formats.\n\n Note: An even more flexible approach is to create a custom character\n mapping codec using the ``codecs`` module (see\n ``encodings.cp1251`` for an example).\n\nstr.upper()\n\n Return a copy of the string converted to uppercase.\n\nstr.zfill(width)\n\n Return the numeric string left filled with zeros in a string of\n length *width*. A sign prefix is handled correctly. The original\n string is returned if *width* is less than ``len(s)``.\n\n\nOld String Formatting Operations\n================================\n\nNote: The formatting operations described here are obsolete and may go\n away in future versions of Python. Use the new *String Formatting*\n in new code.\n\nString objects have one unique built-in operation: the ``%`` operator\n(modulo). This is also known as the string *formatting* or\n*interpolation* operator. Given ``format % values`` (where *format* is\na string), ``%`` conversion specifications in *format* are replaced\nwith zero or more elements of *values*. The effect is similar to the\nusing ``sprintf()`` in the C language.\n\nIf *format* requires a single argument, *values* may be a single non-\ntuple object. [4] Otherwise, *values* must be a tuple with exactly\nthe number of items specified by the format string, or a single\nmapping object (for example, a dictionary).\n\nA conversion specifier contains two or more characters and has the\nfollowing components, which must occur in this order:\n\n1. The ``\'%\'`` character, which marks the start of the specifier.\n\n2. Mapping key (optional), consisting of a parenthesised sequence of\n characters (for example, ``(somename)``).\n\n3. Conversion flags (optional), which affect the result of some\n conversion types.\n\n4. Minimum field width (optional). If specified as an ``\'*\'``\n (asterisk), the actual width is read from the next element of the\n tuple in *values*, and the object to convert comes after the\n minimum field width and optional precision.\n\n5. Precision (optional), given as a ``\'.\'`` (dot) followed by the\n precision. If specified as ``\'*\'`` (an asterisk), the actual width\n is read from the next element of the tuple in *values*, and the\n value to convert comes after the precision.\n\n6. Length modifier (optional).\n\n7. Conversion type.\n\nWhen the right argument is a dictionary (or other mapping type), then\nthe formats in the string *must* include a parenthesised mapping key\ninto that dictionary inserted immediately after the ``\'%\'`` character.\nThe mapping key selects the value to be formatted from the mapping.\nFor example:\n\n>>> print(\'%(language)s has %(number)03d quote types.\' %\n... {\'language\': "Python", "number": 2})\nPython has 002 quote types.\n\nIn this case no ``*`` specifiers may occur in a format (since they\nrequire a sequential parameter list).\n\nThe conversion flag characters are:\n\n+-----------+-----------------------------------------------------------------------+\n| Flag | Meaning |\n+===========+=======================================================================+\n| ``\'#\'`` | The value conversion will use the "alternate form" (where defined |\n| | below). |\n+-----------+-----------------------------------------------------------------------+\n| ``\'0\'`` | The conversion will be zero padded for numeric values. |\n+-----------+-----------------------------------------------------------------------+\n| ``\'-\'`` | The converted value is left adjusted (overrides the ``\'0\'`` |\n| | conversion if both are given). |\n+-----------+-----------------------------------------------------------------------+\n| ``\' \'`` | (a space) A blank should be left before a positive number (or empty |\n| | string) produced by a signed conversion. |\n+-----------+-----------------------------------------------------------------------+\n| ``\'+\'`` | A sign character (``\'+\'`` or ``\'-\'``) will precede the conversion |\n| | (overrides a "space" flag). |\n+-----------+-----------------------------------------------------------------------+\n\nA length modifier (``h``, ``l``, or ``L``) may be present, but is\nignored as it is not necessary for Python -- so e.g. ``%ld`` is\nidentical to ``%d``.\n\nThe conversion types are:\n\n+--------------+-------------------------------------------------------+---------+\n| Conversion | Meaning | Notes |\n+==============+=======================================================+=========+\n| ``\'d\'`` | Signed integer decimal. | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'i\'`` | Signed integer decimal. | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'o\'`` | Signed octal value. | (1) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'u\'`` | Obsolete type -- it is identical to ``\'d\'``. | (7) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'x\'`` | Signed hexadecimal (lowercase). | (2) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'X\'`` | Signed hexadecimal (uppercase). | (2) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'e\'`` | Floating point exponential format (lowercase). | (3) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'E\'`` | Floating point exponential format (uppercase). | (3) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'f\'`` | Floating point decimal format. | (3) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'F\'`` | Floating point decimal format. | (3) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'g\'`` | Floating point format. Uses lowercase exponential | (4) |\n| | format if exponent is less than -4 or not less than | |\n| | precision, decimal format otherwise. | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'G\'`` | Floating point format. Uses uppercase exponential | (4) |\n| | format if exponent is less than -4 or not less than | |\n| | precision, decimal format otherwise. | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'c\'`` | Single character (accepts integer or single character | |\n| | string). | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'r\'`` | String (converts any Python object using ``repr()``). | (5) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'s\'`` | String (converts any Python object using ``str()``). | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'%\'`` | No argument is converted, results in a ``\'%\'`` | |\n| | character in the result. | |\n+--------------+-------------------------------------------------------+---------+\n\nNotes:\n\n1. The alternate form causes a leading zero (``\'0\'``) to be inserted\n between left-hand padding and the formatting of the number if the\n leading character of the result is not already a zero.\n\n2. The alternate form causes a leading ``\'0x\'`` or ``\'0X\'`` (depending\n on whether the ``\'x\'`` or ``\'X\'`` format was used) to be inserted\n between left-hand padding and the formatting of the number if the\n leading character of the result is not already a zero.\n\n3. The alternate form causes the result to always contain a decimal\n point, even if no digits follow it.\n\n The precision determines the number of digits after the decimal\n point and defaults to 6.\n\n4. The alternate form causes the result to always contain a decimal\n point, and trailing zeroes are not removed as they would otherwise\n be.\n\n The precision determines the number of significant digits before\n and after the decimal point and defaults to 6.\n\n5. The precision determines the maximal number of characters used.\n\n1. See **PEP 237**.\n\nSince Python strings have an explicit length, ``%s`` conversions do\nnot assume that ``\'\\0\'`` is the end of the string.\n\nChanged in version 3.1: ``%f`` conversions for numbers whose absolute\nvalue is over 1e50 are no longer replaced by ``%g`` conversions.\n\nAdditional string operations are defined in standard modules\n``string`` and ``re``.\n\n\nRange Type\n==========\n\nThe ``range`` type is an immutable sequence which is commonly used for\nlooping. The advantage of the ``range`` type is that an ``range``\nobject will always take the same amount of memory, no matter the size\nof the range it represents.\n\nRange objects have relatively little behavior: they support indexing,\ncontains, iteration, the ``len()`` function, and the following\nmethods:\n\nrange.count(x)\n\n Return the number of *i*\'s for which ``s[i] == x``.\n\n New in version 3.2.\n\nrange.index(x)\n\n Return the smallest *i* such that ``s[i] == x``. Raises\n ``ValueError`` when *x* is not in the range.\n\n New in version 3.2.\n\n\nMutable Sequence Types\n======================\n\nList and bytearray objects support additional operations that allow\nin-place modification of the object. Other mutable sequence types\n(when added to the language) should also support these operations.\nStrings and tuples are immutable sequence types: such objects cannot\nbe modified once created. The following operations are defined on\nmutable sequence types (where *x* is an arbitrary object).\n\nNote that while lists allow their items to be of any type, bytearray\nobject "items" are all integers in the range 0 <= x < 256.\n\n+--------------------------------+----------------------------------+-----------------------+\n| Operation | Result | Notes |\n+================================+==================================+=======================+\n| ``s[i] = x`` | item *i* of *s* is replaced by | |\n| | *x* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j] = t`` | slice of *s* from *i* to *j* is | |\n| | replaced by the contents of the | |\n| | iterable *t* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j]`` | same as ``s[i:j] = []`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j:k] = t`` | the elements of ``s[i:j:k]`` are | (1) |\n| | replaced by those of *t* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j:k]`` | removes the elements of | |\n| | ``s[i:j:k]`` from the list | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.append(x)`` | same as ``s[len(s):len(s)] = | |\n| | [x]`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.extend(x)`` | same as ``s[len(s):len(s)] = x`` | (2) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.clear()`` | remove all items from ``s`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.copy()`` | return a shallow copy of ``s`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.count(x)`` | return number of *i*\'s for which | |\n| | ``s[i] == x`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.index(x[, i[, j]])`` | return smallest *k* such that | (3) |\n| | ``s[k] == x`` and ``i <= k < j`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.insert(i, x)`` | same as ``s[i:i] = [x]`` | (4) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.pop([i])`` | same as ``x = s[i]; del s[i]; | (5) |\n| | return x`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.remove(x)`` | same as ``del s[s.index(x)]`` | (3) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.reverse()`` | reverses the items of *s* in | (6) |\n| | place | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.sort([key[, reverse]])`` | sort the items of *s* in place | (6), (7), (8) |\n+--------------------------------+----------------------------------+-----------------------+\n\nNotes:\n\n1. *t* must have the same length as the slice it is replacing.\n\n2. *x* can be any iterable object.\n\n3. Raises ``ValueError`` when *x* is not found in *s*. When a negative\n index is passed as the second or third parameter to the ``index()``\n method, the sequence length is added, as for slice indices. If it\n is still negative, it is truncated to zero, as for slice indices.\n\n4. When a negative index is passed as the first parameter to the\n ``insert()`` method, the sequence length is added, as for slice\n indices. If it is still negative, it is truncated to zero, as for\n slice indices.\n\n5. The optional argument *i* defaults to ``-1``, so that by default\n the last item is removed and returned.\n\n6. The ``sort()`` and ``reverse()`` methods modify the sequence in\n place for economy of space when sorting or reversing a large\n sequence. To remind you that they operate by side effect, they\n don\'t return the sorted or reversed sequence.\n\n7. The ``sort()`` method takes optional arguments for controlling the\n comparisons. Each must be specified as a keyword argument.\n\n *key* specifies a function of one argument that is used to extract\n a comparison key from each list element: ``key=str.lower``. The\n default value is ``None``. Use ``functools.cmp_to_key()`` to\n convert an old-style *cmp* function to a *key* function.\n\n *reverse* is a boolean value. If set to ``True``, then the list\n elements are sorted as if each comparison were reversed.\n\n The ``sort()`` method is guaranteed to be stable. A sort is stable\n if it guarantees not to change the relative order of elements that\n compare equal --- this is helpful for sorting in multiple passes\n (for example, sort by department, then by salary grade).\n\n **CPython implementation detail:** While a list is being sorted,\n the effect of attempting to mutate, or even inspect, the list is\n undefined. The C implementation of Python makes the list appear\n empty for the duration, and raises ``ValueError`` if it can detect\n that the list has been mutated during a sort.\n\n8. ``sort()`` is not supported by ``bytearray`` objects.\n\n New in version 3.3: ``clear()`` and ``copy()`` methods.\n\n\nBytes and Byte Array Methods\n============================\n\nBytes and bytearray objects, being "strings of bytes", have all\nmethods found on strings, with the exception of ``encode()``,\n``format()`` and ``isidentifier()``, which do not make sense with\nthese types. For converting the objects to strings, they have a\n``decode()`` method.\n\nWherever one of these methods needs to interpret the bytes as\ncharacters (e.g. the ``is...()`` methods), the ASCII character set is\nassumed.\n\nNote: The methods on bytes and bytearray objects don\'t accept strings as\n their arguments, just as the methods on strings don\'t accept bytes\n as their arguments. For example, you have to write\n\n a = "abc"\n b = a.replace("a", "f")\n\n and\n\n a = b"abc"\n b = a.replace(b"a", b"f")\n\nbytes.decode(encoding="utf-8", errors="strict")\nbytearray.decode(encoding="utf-8", errors="strict")\n\n Return a string decoded from the given bytes. Default encoding is\n ``\'utf-8\'``. *errors* may be given to set a different error\n handling scheme. The default for *errors* is ``\'strict\'``, meaning\n that encoding errors raise a ``UnicodeError``. Other possible\n values are ``\'ignore\'``, ``\'replace\'`` and any other name\n registered via ``codecs.register_error()``, see section *Codec Base\n Classes*. For a list of possible encodings, see section *Standard\n Encodings*.\n\n Changed in version 3.1: Added support for keyword arguments.\n\nThe bytes and bytearray types have an additional class method:\n\nclassmethod bytes.fromhex(string)\nclassmethod bytearray.fromhex(string)\n\n This ``bytes`` class method returns a bytes or bytearray object,\n decoding the given string object. The string must contain two\n hexadecimal digits per byte, spaces are ignored.\n\n >>> bytes.fromhex(\'f0 f1f2 \')\n b\'\\xf0\\xf1\\xf2\'\n\nThe maketrans and translate methods differ in semantics from the\nversions available on strings:\n\nbytes.translate(table[, delete])\nbytearray.translate(table[, delete])\n\n Return a copy of the bytes or bytearray object where all bytes\n occurring in the optional argument *delete* are removed, and the\n remaining bytes have been mapped through the given translation\n table, which must be a bytes object of length 256.\n\n You can use the ``bytes.maketrans()`` method to create a\n translation table.\n\n Set the *table* argument to ``None`` for translations that only\n delete characters:\n\n >>> b\'read this short text\'.translate(None, b\'aeiou\')\n b\'rd ths shrt txt\'\n\nstatic bytes.maketrans(from, to)\nstatic bytearray.maketrans(from, to)\n\n This static method returns a translation table usable for\n ``bytes.translate()`` that will map each character in *from* into\n the character at the same position in *to*; *from* and *to* must be\n bytes objects and have the same length.\n\n New in version 3.1.\n',
+ 'typesmodules': "\nModules\n*******\n\nThe only special operation on a module is attribute access:\n``m.name``, where *m* is a module and *name* accesses a name defined\nin *m*'s symbol table. Module attributes can be assigned to. (Note\nthat the ``import`` statement is not, strictly speaking, an operation\non a module object; ``import foo`` does not require a module object\nnamed *foo* to exist, rather it requires an (external) *definition*\nfor a module named *foo* somewhere.)\n\nA special attribute of every module is ``__dict__``. This is the\ndictionary containing the module's symbol table. Modifying this\ndictionary will actually change the module's symbol table, but direct\nassignment to the ``__dict__`` attribute is not possible (you can\nwrite ``m.__dict__['a'] = 1``, which defines ``m.a`` to be ``1``, but\nyou can't write ``m.__dict__ = {}``). Modifying ``__dict__`` directly\nis not recommended.\n\nModules built into the interpreter are written like this: ``<module\n'sys' (built-in)>``. If loaded from a file, they are written as\n``<module 'os' from '/usr/local/lib/pythonX.Y/os.pyc'>``.\n",
+ 'typesseq': '\nSequence Types --- ``str``, ``bytes``, ``bytearray``, ``list``, ``tuple``, ``range``\n************************************************************************************\n\nThere are six sequence types: strings, byte sequences (``bytes``\nobjects), byte arrays (``bytearray`` objects), lists, tuples, and\nrange objects. For other containers see the built in ``dict`` and\n``set`` classes, and the ``collections`` module.\n\nStrings contain Unicode characters. Their literals are written in\nsingle or double quotes: ``\'xyzzy\'``, ``"frobozz"``. See *String and\nBytes literals* for more about string literals. In addition to the\nfunctionality described here, there are also string-specific methods\ndescribed in the *String Methods* section.\n\nBytes and bytearray objects contain single bytes -- the former is\nimmutable while the latter is a mutable sequence. Bytes objects can\nbe constructed the constructor, ``bytes()``, and from literals; use a\n``b`` prefix with normal string syntax: ``b\'xyzzy\'``. To construct\nbyte arrays, use the ``bytearray()`` function.\n\nWhile string objects are sequences of characters (represented by\nstrings of length 1), bytes and bytearray objects are sequences of\n*integers* (between 0 and 255), representing the ASCII value of single\nbytes. That means that for a bytes or bytearray object *b*, ``b[0]``\nwill be an integer, while ``b[0:1]`` will be a bytes or bytearray\nobject of length 1. The representation of bytes objects uses the\nliteral format (``b\'...\'``) since it is generally more useful than\ne.g. ``bytes([50, 19, 100])``. You can always convert a bytes object\ninto a list of integers using ``list(b)``.\n\nAlso, while in previous Python versions, byte strings and Unicode\nstrings could be exchanged for each other rather freely (barring\nencoding issues), strings and bytes are now completely separate\nconcepts. There\'s no implicit en-/decoding if you pass an object of\nthe wrong type. A string always compares unequal to a bytes or\nbytearray object.\n\nLists are constructed with square brackets, separating items with\ncommas: ``[a, b, c]``. Tuples are constructed by the comma operator\n(not within square brackets), with or without enclosing parentheses,\nbut an empty tuple must have the enclosing parentheses, such as ``a,\nb, c`` or ``()``. A single item tuple must have a trailing comma,\nsuch as ``(d,)``.\n\nObjects of type range are created using the ``range()`` function.\nThey don\'t support concatenation or repetition, and using ``min()`` or\n``max()`` on them is inefficient.\n\nMost sequence types support the following operations. The ``in`` and\n``not in`` operations have the same priorities as the comparison\noperations. The ``+`` and ``*`` operations have the same priority as\nthe corresponding numeric operations. [3] Additional methods are\nprovided for *Mutable Sequence Types*.\n\nThis table lists the sequence operations sorted in ascending priority\n(operations in the same box have the same priority). In the table,\n*s* and *t* are sequences of the same type; *n*, *i*, *j* and *k* are\nintegers.\n\n+--------------------+----------------------------------+------------+\n| Operation | Result | Notes |\n+====================+==================================+============+\n| ``x in s`` | ``True`` if an item of *s* is | (1) |\n| | equal to *x*, else ``False`` | |\n+--------------------+----------------------------------+------------+\n| ``x not in s`` | ``False`` if an item of *s* is | (1) |\n| | equal to *x*, else ``True`` | |\n+--------------------+----------------------------------+------------+\n| ``s + t`` | the concatenation of *s* and *t* | (6) |\n+--------------------+----------------------------------+------------+\n| ``s * n, n * s`` | *n* shallow copies of *s* | (2) |\n| | concatenated | |\n+--------------------+----------------------------------+------------+\n| ``s[i]`` | *i*th item of *s*, origin 0 | (3) |\n+--------------------+----------------------------------+------------+\n| ``s[i:j]`` | slice of *s* from *i* to *j* | (3)(4) |\n+--------------------+----------------------------------+------------+\n| ``s[i:j:k]`` | slice of *s* from *i* to *j* | (3)(5) |\n| | with step *k* | |\n+--------------------+----------------------------------+------------+\n| ``len(s)`` | length of *s* | |\n+--------------------+----------------------------------+------------+\n| ``min(s)`` | smallest item of *s* | |\n+--------------------+----------------------------------+------------+\n| ``max(s)`` | largest item of *s* | |\n+--------------------+----------------------------------+------------+\n| ``s.index(i)`` | index of the first occurence of | |\n| | *i* in *s* | |\n+--------------------+----------------------------------+------------+\n| ``s.count(i)`` | total number of occurences of | |\n| | *i* in *s* | |\n+--------------------+----------------------------------+------------+\n\nSequence types also support comparisons. In particular, tuples and\nlists are compared lexicographically by comparing corresponding\nelements. This means that to compare equal, every element must\ncompare equal and the two sequences must be of the same type and have\nthe same length. (For full details see *Comparisons* in the language\nreference.)\n\nNotes:\n\n1. When *s* is a string object, the ``in`` and ``not in`` operations\n act like a substring test.\n\n2. Values of *n* less than ``0`` are treated as ``0`` (which yields an\n empty sequence of the same type as *s*). Note also that the copies\n are shallow; nested structures are not copied. This often haunts\n new Python programmers; consider:\n\n >>> lists = [[]] * 3\n >>> lists\n [[], [], []]\n >>> lists[0].append(3)\n >>> lists\n [[3], [3], [3]]\n\n What has happened is that ``[[]]`` is a one-element list containing\n an empty list, so all three elements of ``[[]] * 3`` are (pointers\n to) this single empty list. Modifying any of the elements of\n ``lists`` modifies this single list. You can create a list of\n different lists this way:\n\n >>> lists = [[] for i in range(3)]\n >>> lists[0].append(3)\n >>> lists[1].append(5)\n >>> lists[2].append(7)\n >>> lists\n [[3], [5], [7]]\n\n3. If *i* or *j* is negative, the index is relative to the end of the\n string: ``len(s) + i`` or ``len(s) + j`` is substituted. But note\n that ``-0`` is still ``0``.\n\n4. The slice of *s* from *i* to *j* is defined as the sequence of\n items with index *k* such that ``i <= k < j``. If *i* or *j* is\n greater than ``len(s)``, use ``len(s)``. If *i* is omitted or\n ``None``, use ``0``. If *j* is omitted or ``None``, use\n ``len(s)``. If *i* is greater than or equal to *j*, the slice is\n empty.\n\n5. The slice of *s* from *i* to *j* with step *k* is defined as the\n sequence of items with index ``x = i + n*k`` such that ``0 <= n <\n (j-i)/k``. In other words, the indices are ``i``, ``i+k``,\n ``i+2*k``, ``i+3*k`` and so on, stopping when *j* is reached (but\n never including *j*). If *i* or *j* is greater than ``len(s)``,\n use ``len(s)``. If *i* or *j* are omitted or ``None``, they become\n "end" values (which end depends on the sign of *k*). Note, *k*\n cannot be zero. If *k* is ``None``, it is treated like ``1``.\n\n6. Concatenating immutable strings always results in a new object.\n This means that building up a string by repeated concatenation will\n have a quadratic runtime cost in the total string length. To get a\n linear runtime cost, you must switch to one of the alternatives\n below:\n\n * if concatenating ``str`` objects, you can build a list and use\n ``str.join()`` at the end;\n\n * if concatenating ``bytes`` objects, you can similarly use\n ``bytes.join()``, or you can do in-place concatenation with a\n ``bytearray`` object. ``bytearray`` objects are mutable and have\n an efficient overallocation mechanism.\n\n\nString Methods\n==============\n\nString objects support the methods listed below.\n\nIn addition, Python\'s strings support the sequence type methods\ndescribed in the *Sequence Types --- str, bytes, bytearray, list,\ntuple, range* section. To output formatted strings, see the *String\nFormatting* section. Also, see the ``re`` module for string functions\nbased on regular expressions.\n\nstr.capitalize()\n\n Return a copy of the string with its first character capitalized\n and the rest lowercased.\n\nstr.casefold()\n\n Return a casefolded copy of the string. Casefolded strings may be\n used for caseless matching.\n\n Casefolding is similar to lowercasing but more aggressive because\n it is intended to remove all case distinctions in a string. For\n example, the German lowercase letter ``\'\xc3\x9f\'`` is equivalent to\n ``"ss"``. Since it is already lowercase, ``lower()`` would do\n nothing to ``\'\xc3\x9f\'``; ``casefold()`` converts it to ``"ss"``.\n\n The casefolding algorithm is described in section 3.13 of the\n Unicode Standard.\n\n New in version 3.3.\n\nstr.center(width[, fillchar])\n\n Return centered in a string of length *width*. Padding is done\n using the specified *fillchar* (default is a space).\n\nstr.count(sub[, start[, end]])\n\n Return the number of non-overlapping occurrences of substring *sub*\n in the range [*start*, *end*]. Optional arguments *start* and\n *end* are interpreted as in slice notation.\n\nstr.encode(encoding="utf-8", errors="strict")\n\n Return an encoded version of the string as a bytes object. Default\n encoding is ``\'utf-8\'``. *errors* may be given to set a different\n error handling scheme. The default for *errors* is ``\'strict\'``,\n meaning that encoding errors raise a ``UnicodeError``. Other\n possible values are ``\'ignore\'``, ``\'replace\'``,\n ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and any other name\n registered via ``codecs.register_error()``, see section *Codec Base\n Classes*. For a list of possible encodings, see section *Standard\n Encodings*.\n\n Changed in version 3.1: Support for keyword arguments added.\n\nstr.endswith(suffix[, start[, end]])\n\n Return ``True`` if the string ends with the specified *suffix*,\n otherwise return ``False``. *suffix* can also be a tuple of\n suffixes to look for. With optional *start*, test beginning at\n that position. With optional *end*, stop comparing at that\n position.\n\nstr.expandtabs([tabsize])\n\n Return a copy of the string where all tab characters are replaced\n by zero or more spaces, depending on the current column and the\n given tab size. The column number is reset to zero after each\n newline occurring in the string. If *tabsize* is not given, a tab\n size of ``8`` characters is assumed. This doesn\'t understand other\n non-printing characters or escape sequences.\n\nstr.find(sub[, start[, end]])\n\n Return the lowest index in the string where substring *sub* is\n found, such that *sub* is contained in the slice ``s[start:end]``.\n Optional arguments *start* and *end* are interpreted as in slice\n notation. Return ``-1`` if *sub* is not found.\n\n Note: The ``find()`` method should be used only if you need to know the\n position of *sub*. To check if *sub* is a substring or not, use\n the ``in`` operator:\n\n >>> \'Py\' in \'Python\'\n True\n\nstr.format(*args, **kwargs)\n\n Perform a string formatting operation. The string on which this\n method is called can contain literal text or replacement fields\n delimited by braces ``{}``. Each replacement field contains either\n the numeric index of a positional argument, or the name of a\n keyword argument. Returns a copy of the string where each\n replacement field is replaced with the string value of the\n corresponding argument.\n\n >>> "The sum of 1 + 2 is {0}".format(1+2)\n \'The sum of 1 + 2 is 3\'\n\n See *Format String Syntax* for a description of the various\n formatting options that can be specified in format strings.\n\nstr.format_map(mapping)\n\n Similar to ``str.format(**mapping)``, except that ``mapping`` is\n used directly and not copied to a ``dict`` . This is useful if for\n example ``mapping`` is a dict subclass:\n\n >>> class Default(dict):\n ... def __missing__(self, key):\n ... return key\n ...\n >>> \'{name} was born in {country}\'.format_map(Default(name=\'Guido\'))\n \'Guido was born in country\'\n\n New in version 3.2.\n\nstr.index(sub[, start[, end]])\n\n Like ``find()``, but raise ``ValueError`` when the substring is not\n found.\n\nstr.isalnum()\n\n Return true if all characters in the string are alphanumeric and\n there is at least one character, false otherwise. A character\n ``c`` is alphanumeric if one of the following returns ``True``:\n ``c.isalpha()``, ``c.isdecimal()``, ``c.isdigit()``, or\n ``c.isnumeric()``.\n\nstr.isalpha()\n\n Return true if all characters in the string are alphabetic and\n there is at least one character, false otherwise. Alphabetic\n characters are those characters defined in the Unicode character\n database as "Letter", i.e., those with general category property\n being one of "Lm", "Lt", "Lu", "Ll", or "Lo". Note that this is\n different from the "Alphabetic" property defined in the Unicode\n Standard.\n\nstr.isdecimal()\n\n Return true if all characters in the string are decimal characters\n and there is at least one character, false otherwise. Decimal\n characters are those from general category "Nd". This category\n includes digit characters, and all characters that can be used to\n form decimal-radix numbers, e.g. U+0660, ARABIC-INDIC DIGIT ZERO.\n\nstr.isdigit()\n\n Return true if all characters in the string are digits and there is\n at least one character, false otherwise. Digits include decimal\n characters and digits that need special handling, such as the\n compatibility superscript digits. Formally, a digit is a character\n that has the property value Numeric_Type=Digit or\n Numeric_Type=Decimal.\n\nstr.isidentifier()\n\n Return true if the string is a valid identifier according to the\n language definition, section *Identifiers and keywords*.\n\nstr.islower()\n\n Return true if all cased characters [4] in the string are lowercase\n and there is at least one cased character, false otherwise.\n\nstr.isnumeric()\n\n Return true if all characters in the string are numeric characters,\n and there is at least one character, false otherwise. Numeric\n characters include digit characters, and all characters that have\n the Unicode numeric value property, e.g. U+2155, VULGAR FRACTION\n ONE FIFTH. Formally, numeric characters are those with the\n property value Numeric_Type=Digit, Numeric_Type=Decimal or\n Numeric_Type=Numeric.\n\nstr.isprintable()\n\n Return true if all characters in the string are printable or the\n string is empty, false otherwise. Nonprintable characters are\n those characters defined in the Unicode character database as\n "Other" or "Separator", excepting the ASCII space (0x20) which is\n considered printable. (Note that printable characters in this\n context are those which should not be escaped when ``repr()`` is\n invoked on a string. It has no bearing on the handling of strings\n written to ``sys.stdout`` or ``sys.stderr``.)\n\nstr.isspace()\n\n Return true if there are only whitespace characters in the string\n and there is at least one character, false otherwise. Whitespace\n characters are those characters defined in the Unicode character\n database as "Other" or "Separator" and those with bidirectional\n property being one of "WS", "B", or "S".\n\nstr.istitle()\n\n Return true if the string is a titlecased string and there is at\n least one character, for example uppercase characters may only\n follow uncased characters and lowercase characters only cased ones.\n Return false otherwise.\n\nstr.isupper()\n\n Return true if all cased characters [4] in the string are uppercase\n and there is at least one cased character, false otherwise.\n\nstr.join(iterable)\n\n Return a string which is the concatenation of the strings in the\n *iterable* *iterable*. A ``TypeError`` will be raised if there are\n any non-string values in *iterable*, including ``bytes`` objects.\n The separator between elements is the string providing this method.\n\nstr.ljust(width[, fillchar])\n\n Return the string left justified in a string of length *width*.\n Padding is done using the specified *fillchar* (default is a\n space). The original string is returned if *width* is less than or\n equal to ``len(s)``.\n\nstr.lower()\n\n Return a copy of the string with all the cased characters [4]\n converted to lowercase.\n\n The lowercasing algorithm used is described in section 3.13 of the\n Unicode Standard.\n\nstr.lstrip([chars])\n\n Return a copy of the string with leading characters removed. The\n *chars* argument is a string specifying the set of characters to be\n removed. If omitted or ``None``, the *chars* argument defaults to\n removing whitespace. The *chars* argument is not a prefix; rather,\n all combinations of its values are stripped:\n\n >>> \' spacious \'.lstrip()\n \'spacious \'\n >>> \'www.example.com\'.lstrip(\'cmowz.\')\n \'example.com\'\n\nstatic str.maketrans(x[, y[, z]])\n\n This static method returns a translation table usable for\n ``str.translate()``.\n\n If there is only one argument, it must be a dictionary mapping\n Unicode ordinals (integers) or characters (strings of length 1) to\n Unicode ordinals, strings (of arbitrary lengths) or None.\n Character keys will then be converted to ordinals.\n\n If there are two arguments, they must be strings of equal length,\n and in the resulting dictionary, each character in x will be mapped\n to the character at the same position in y. If there is a third\n argument, it must be a string, whose characters will be mapped to\n None in the result.\n\nstr.partition(sep)\n\n Split the string at the first occurrence of *sep*, and return a\n 3-tuple containing the part before the separator, the separator\n itself, and the part after the separator. If the separator is not\n found, return a 3-tuple containing the string itself, followed by\n two empty strings.\n\nstr.replace(old, new[, count])\n\n Return a copy of the string with all occurrences of substring *old*\n replaced by *new*. If the optional argument *count* is given, only\n the first *count* occurrences are replaced.\n\nstr.rfind(sub[, start[, end]])\n\n Return the highest index in the string where substring *sub* is\n found, such that *sub* is contained within ``s[start:end]``.\n Optional arguments *start* and *end* are interpreted as in slice\n notation. Return ``-1`` on failure.\n\nstr.rindex(sub[, start[, end]])\n\n Like ``rfind()`` but raises ``ValueError`` when the substring *sub*\n is not found.\n\nstr.rjust(width[, fillchar])\n\n Return the string right justified in a string of length *width*.\n Padding is done using the specified *fillchar* (default is a\n space). The original string is returned if *width* is less than or\n equal to ``len(s)``.\n\nstr.rpartition(sep)\n\n Split the string at the last occurrence of *sep*, and return a\n 3-tuple containing the part before the separator, the separator\n itself, and the part after the separator. If the separator is not\n found, return a 3-tuple containing two empty strings, followed by\n the string itself.\n\nstr.rsplit(sep=None, maxsplit=-1)\n\n Return a list of the words in the string, using *sep* as the\n delimiter string. If *maxsplit* is given, at most *maxsplit* splits\n are done, the *rightmost* ones. If *sep* is not specified or\n ``None``, any whitespace string is a separator. Except for\n splitting from the right, ``rsplit()`` behaves like ``split()``\n which is described in detail below.\n\nstr.rstrip([chars])\n\n Return a copy of the string with trailing characters removed. The\n *chars* argument is a string specifying the set of characters to be\n removed. If omitted or ``None``, the *chars* argument defaults to\n removing whitespace. The *chars* argument is not a suffix; rather,\n all combinations of its values are stripped:\n\n >>> \' spacious \'.rstrip()\n \' spacious\'\n >>> \'mississippi\'.rstrip(\'ipz\')\n \'mississ\'\n\nstr.split(sep=None, maxsplit=-1)\n\n Return a list of the words in the string, using *sep* as the\n delimiter string. If *maxsplit* is given, at most *maxsplit*\n splits are done (thus, the list will have at most ``maxsplit+1``\n elements). If *maxsplit* is not specified, then there is no limit\n on the number of splits (all possible splits are made).\n\n If *sep* is given, consecutive delimiters are not grouped together\n and are deemed to delimit empty strings (for example,\n ``\'1,,2\'.split(\',\')`` returns ``[\'1\', \'\', \'2\']``). The *sep*\n argument may consist of multiple characters (for example,\n ``\'1<>2<>3\'.split(\'<>\')`` returns ``[\'1\', \'2\', \'3\']``). Splitting\n an empty string with a specified separator returns ``[\'\']``.\n\n If *sep* is not specified or is ``None``, a different splitting\n algorithm is applied: runs of consecutive whitespace are regarded\n as a single separator, and the result will contain no empty strings\n at the start or end if the string has leading or trailing\n whitespace. Consequently, splitting an empty string or a string\n consisting of just whitespace with a ``None`` separator returns\n ``[]``.\n\n For example, ``\' 1 2 3 \'.split()`` returns ``[\'1\', \'2\', \'3\']``,\n and ``\' 1 2 3 \'.split(None, 1)`` returns ``[\'1\', \'2 3 \']``.\n\nstr.splitlines([keepends])\n\n Return a list of the lines in the string, breaking at line\n boundaries. Line breaks are not included in the resulting list\n unless *keepends* is given and true.\n\nstr.startswith(prefix[, start[, end]])\n\n Return ``True`` if string starts with the *prefix*, otherwise\n return ``False``. *prefix* can also be a tuple of prefixes to look\n for. With optional *start*, test string beginning at that\n position. With optional *end*, stop comparing string at that\n position.\n\nstr.strip([chars])\n\n Return a copy of the string with the leading and trailing\n characters removed. The *chars* argument is a string specifying the\n set of characters to be removed. If omitted or ``None``, the\n *chars* argument defaults to removing whitespace. The *chars*\n argument is not a prefix or suffix; rather, all combinations of its\n values are stripped:\n\n >>> \' spacious \'.strip()\n \'spacious\'\n >>> \'www.example.com\'.strip(\'cmowz.\')\n \'example\'\n\nstr.swapcase()\n\n Return a copy of the string with uppercase characters converted to\n lowercase and vice versa. Note that it is not necessarily true that\n ``s.swapcase().swapcase() == s``.\n\nstr.title()\n\n Return a titlecased version of the string where words start with an\n uppercase character and the remaining characters are lowercase.\n\n The algorithm uses a simple language-independent definition of a\n word as groups of consecutive letters. The definition works in\n many contexts but it means that apostrophes in contractions and\n possessives form word boundaries, which may not be the desired\n result:\n\n >>> "they\'re bill\'s friends from the UK".title()\n "They\'Re Bill\'S Friends From The Uk"\n\n A workaround for apostrophes can be constructed using regular\n expressions:\n\n >>> import re\n >>> def titlecase(s):\n return re.sub(r"[A-Za-z]+(\'[A-Za-z]+)?",\n lambda mo: mo.group(0)[0].upper() +\n mo.group(0)[1:].lower(),\n s)\n\n >>> titlecase("they\'re bill\'s friends.")\n "They\'re Bill\'s Friends."\n\nstr.translate(map)\n\n Return a copy of the *s* where all characters have been mapped\n through the *map* which must be a dictionary of Unicode ordinals\n (integers) to Unicode ordinals, strings or ``None``. Unmapped\n characters are left untouched. Characters mapped to ``None`` are\n deleted.\n\n You can use ``str.maketrans()`` to create a translation map from\n character-to-character mappings in different formats.\n\n Note: An even more flexible approach is to create a custom character\n mapping codec using the ``codecs`` module (see\n ``encodings.cp1251`` for an example).\n\nstr.upper()\n\n Return a copy of the string with all the cased characters [4]\n converted to uppercase. Note that ``str.upper().isupper()`` might\n be ``False`` if ``s`` contains uncased characters or if the Unicode\n category of the resulting character(s) is not "Lu" (Letter,\n uppercase), but e.g. "Lt" (Letter, titlecase).\n\n The uppercasing algorithm used is described in section 3.13 of the\n Unicode Standard.\n\nstr.zfill(width)\n\n Return the numeric string left filled with zeros in a string of\n length *width*. A sign prefix is handled correctly. The original\n string is returned if *width* is less than or equal to ``len(s)``.\n\n\nOld String Formatting Operations\n================================\n\nNote: The formatting operations described here are modelled on C\'s\n printf() syntax. They only support formatting of certain builtin\n types. The use of a binary operator means that care may be needed\n in order to format tuples and dictionaries correctly. As the new\n *String Formatting* syntax is more flexible and handles tuples and\n dictionaries naturally, it is recommended for new code. However,\n there are no current plans to deprecate printf-style formatting.\n\nString objects have one unique built-in operation: the ``%`` operator\n(modulo). This is also known as the string *formatting* or\n*interpolation* operator. Given ``format % values`` (where *format* is\na string), ``%`` conversion specifications in *format* are replaced\nwith zero or more elements of *values*. The effect is similar to the\nusing ``sprintf()`` in the C language.\n\nIf *format* requires a single argument, *values* may be a single non-\ntuple object. [5] Otherwise, *values* must be a tuple with exactly\nthe number of items specified by the format string, or a single\nmapping object (for example, a dictionary).\n\nA conversion specifier contains two or more characters and has the\nfollowing components, which must occur in this order:\n\n1. The ``\'%\'`` character, which marks the start of the specifier.\n\n2. Mapping key (optional), consisting of a parenthesised sequence of\n characters (for example, ``(somename)``).\n\n3. Conversion flags (optional), which affect the result of some\n conversion types.\n\n4. Minimum field width (optional). If specified as an ``\'*\'``\n (asterisk), the actual width is read from the next element of the\n tuple in *values*, and the object to convert comes after the\n minimum field width and optional precision.\n\n5. Precision (optional), given as a ``\'.\'`` (dot) followed by the\n precision. If specified as ``\'*\'`` (an asterisk), the actual\n precision is read from the next element of the tuple in *values*,\n and the value to convert comes after the precision.\n\n6. Length modifier (optional).\n\n7. Conversion type.\n\nWhen the right argument is a dictionary (or other mapping type), then\nthe formats in the string *must* include a parenthesised mapping key\ninto that dictionary inserted immediately after the ``\'%\'`` character.\nThe mapping key selects the value to be formatted from the mapping.\nFor example:\n\n>>> print(\'%(language)s has %(number)03d quote types.\' %\n... {\'language\': "Python", "number": 2})\nPython has 002 quote types.\n\nIn this case no ``*`` specifiers may occur in a format (since they\nrequire a sequential parameter list).\n\nThe conversion flag characters are:\n\n+-----------+-----------------------------------------------------------------------+\n| Flag | Meaning |\n+===========+=======================================================================+\n| ``\'#\'`` | The value conversion will use the "alternate form" (where defined |\n| | below). |\n+-----------+-----------------------------------------------------------------------+\n| ``\'0\'`` | The conversion will be zero padded for numeric values. |\n+-----------+-----------------------------------------------------------------------+\n| ``\'-\'`` | The converted value is left adjusted (overrides the ``\'0\'`` |\n| | conversion if both are given). |\n+-----------+-----------------------------------------------------------------------+\n| ``\' \'`` | (a space) A blank should be left before a positive number (or empty |\n| | string) produced by a signed conversion. |\n+-----------+-----------------------------------------------------------------------+\n| ``\'+\'`` | A sign character (``\'+\'`` or ``\'-\'``) will precede the conversion |\n| | (overrides a "space" flag). |\n+-----------+-----------------------------------------------------------------------+\n\nA length modifier (``h``, ``l``, or ``L``) may be present, but is\nignored as it is not necessary for Python -- so e.g. ``%ld`` is\nidentical to ``%d``.\n\nThe conversion types are:\n\n+--------------+-------------------------------------------------------+---------+\n| Conversion | Meaning | Notes |\n+==============+=======================================================+=========+\n| ``\'d\'`` | Signed integer decimal. | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'i\'`` | Signed integer decimal. | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'o\'`` | Signed octal value. | (1) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'u\'`` | Obsolete type -- it is identical to ``\'d\'``. | (7) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'x\'`` | Signed hexadecimal (lowercase). | (2) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'X\'`` | Signed hexadecimal (uppercase). | (2) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'e\'`` | Floating point exponential format (lowercase). | (3) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'E\'`` | Floating point exponential format (uppercase). | (3) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'f\'`` | Floating point decimal format. | (3) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'F\'`` | Floating point decimal format. | (3) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'g\'`` | Floating point format. Uses lowercase exponential | (4) |\n| | format if exponent is less than -4 or not less than | |\n| | precision, decimal format otherwise. | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'G\'`` | Floating point format. Uses uppercase exponential | (4) |\n| | format if exponent is less than -4 or not less than | |\n| | precision, decimal format otherwise. | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'c\'`` | Single character (accepts integer or single character | |\n| | string). | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'r\'`` | String (converts any Python object using ``repr()``). | (5) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'s\'`` | String (converts any Python object using ``str()``). | (5) |\n+--------------+-------------------------------------------------------+---------+\n| ``\'a\'`` | String (converts any Python object using | (5) |\n| | ``ascii()``). | |\n+--------------+-------------------------------------------------------+---------+\n| ``\'%\'`` | No argument is converted, results in a ``\'%\'`` | |\n| | character in the result. | |\n+--------------+-------------------------------------------------------+---------+\n\nNotes:\n\n1. The alternate form causes a leading zero (``\'0\'``) to be inserted\n between left-hand padding and the formatting of the number if the\n leading character of the result is not already a zero.\n\n2. The alternate form causes a leading ``\'0x\'`` or ``\'0X\'`` (depending\n on whether the ``\'x\'`` or ``\'X\'`` format was used) to be inserted\n between left-hand padding and the formatting of the number if the\n leading character of the result is not already a zero.\n\n3. The alternate form causes the result to always contain a decimal\n point, even if no digits follow it.\n\n The precision determines the number of digits after the decimal\n point and defaults to 6.\n\n4. The alternate form causes the result to always contain a decimal\n point, and trailing zeroes are not removed as they would otherwise\n be.\n\n The precision determines the number of significant digits before\n and after the decimal point and defaults to 6.\n\n5. If precision is ``N``, the output is truncated to ``N`` characters.\n\n1. See **PEP 237**.\n\nSince Python strings have an explicit length, ``%s`` conversions do\nnot assume that ``\'\\0\'`` is the end of the string.\n\nChanged in version 3.1: ``%f`` conversions for numbers whose absolute\nvalue is over 1e50 are no longer replaced by ``%g`` conversions.\n\nAdditional string operations are defined in standard modules\n``string`` and ``re``.\n\n\nRange Type\n==========\n\nThe ``range`` type is an immutable sequence which is commonly used for\nlooping. The advantage of the ``range`` type is that an ``range``\nobject will always take the same amount of memory, no matter the size\nof the range it represents.\n\nRange objects have relatively little behavior: they support indexing,\ncontains, iteration, the ``len()`` function, and the following\nmethods:\n\nrange.count(x)\n\n Return the number of *i*\'s for which ``s[i] == x``.\n\n New in version 3.2.\n\nrange.index(x)\n\n Return the smallest *i* such that ``s[i] == x``. Raises\n ``ValueError`` when *x* is not in the range.\n\n New in version 3.2.\n\n\nMutable Sequence Types\n======================\n\nList and bytearray objects support additional operations that allow\nin-place modification of the object. Other mutable sequence types\n(when added to the language) should also support these operations.\nStrings and tuples are immutable sequence types: such objects cannot\nbe modified once created. The following operations are defined on\nmutable sequence types (where *x* is an arbitrary object).\n\nNote that while lists allow their items to be of any type, bytearray\nobject "items" are all integers in the range 0 <= x < 256.\n\n+--------------------------------+----------------------------------+-----------------------+\n| Operation | Result | Notes |\n+================================+==================================+=======================+\n| ``s[i] = x`` | item *i* of *s* is replaced by | |\n| | *x* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j] = t`` | slice of *s* from *i* to *j* is | |\n| | replaced by the contents of the | |\n| | iterable *t* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j]`` | same as ``s[i:j] = []`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j:k] = t`` | the elements of ``s[i:j:k]`` are | (1) |\n| | replaced by those of *t* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j:k]`` | removes the elements of | |\n| | ``s[i:j:k]`` from the list | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.append(x)`` | same as ``s[len(s):len(s)] = | |\n| | [x]`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.extend(x)`` | same as ``s[len(s):len(s)] = x`` | (2) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.clear()`` | remove all items from ``s`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.copy()`` | return a shallow copy of ``s`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.count(x)`` | return number of *i*\'s for which | |\n| | ``s[i] == x`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.index(x[, i[, j]])`` | return smallest *k* such that | (3) |\n| | ``s[k] == x`` and ``i <= k < j`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.insert(i, x)`` | same as ``s[i:i] = [x]`` | (4) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.pop([i])`` | same as ``x = s[i]; del s[i]; | (5) |\n| | return x`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.remove(x)`` | same as ``del s[s.index(x)]`` | (3) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.reverse()`` | reverses the items of *s* in | (6) |\n| | place | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.sort([key[, reverse]])`` | sort the items of *s* in place | (6), (7), (8) |\n+--------------------------------+----------------------------------+-----------------------+\n\nNotes:\n\n1. *t* must have the same length as the slice it is replacing.\n\n2. *x* can be any iterable object.\n\n3. Raises ``ValueError`` when *x* is not found in *s*. When a negative\n index is passed as the second or third parameter to the ``index()``\n method, the sequence length is added, as for slice indices. If it\n is still negative, it is truncated to zero, as for slice indices.\n\n4. When a negative index is passed as the first parameter to the\n ``insert()`` method, the sequence length is added, as for slice\n indices. If it is still negative, it is truncated to zero, as for\n slice indices.\n\n5. The optional argument *i* defaults to ``-1``, so that by default\n the last item is removed and returned.\n\n6. The ``sort()`` and ``reverse()`` methods modify the sequence in\n place for economy of space when sorting or reversing a large\n sequence. To remind you that they operate by side effect, they\n don\'t return the sorted or reversed sequence.\n\n7. The ``sort()`` method takes optional arguments for controlling the\n comparisons. Each must be specified as a keyword argument.\n\n *key* specifies a function of one argument that is used to extract\n a comparison key from each list element: ``key=str.lower``. The\n default value is ``None``. Use ``functools.cmp_to_key()`` to\n convert an old-style *cmp* function to a *key* function.\n\n *reverse* is a boolean value. If set to ``True``, then the list\n elements are sorted as if each comparison were reversed.\n\n The ``sort()`` method is guaranteed to be stable. A sort is stable\n if it guarantees not to change the relative order of elements that\n compare equal --- this is helpful for sorting in multiple passes\n (for example, sort by department, then by salary grade).\n\n **CPython implementation detail:** While a list is being sorted,\n the effect of attempting to mutate, or even inspect, the list is\n undefined. The C implementation of Python makes the list appear\n empty for the duration, and raises ``ValueError`` if it can detect\n that the list has been mutated during a sort.\n\n8. ``sort()`` is not supported by ``bytearray`` objects.\n\n New in version 3.3: ``clear()`` and ``copy()`` methods.\n\n\nBytes and Byte Array Methods\n============================\n\nBytes and bytearray objects, being "strings of bytes", have all\nmethods found on strings, with the exception of ``encode()``,\n``format()`` and ``isidentifier()``, which do not make sense with\nthese types. For converting the objects to strings, they have a\n``decode()`` method.\n\nWherever one of these methods needs to interpret the bytes as\ncharacters (e.g. the ``is...()`` methods), the ASCII character set is\nassumed.\n\nNew in version 3.3: The functions ``count()``, ``find()``,\n``index()``, ``rfind()`` and ``rindex()`` have additional semantics\ncompared to the corresponding string functions: They also accept an\ninteger in range 0 to 255 (a byte) as their first argument.\n\nNote: The methods on bytes and bytearray objects don\'t accept strings as\n their arguments, just as the methods on strings don\'t accept bytes\n as their arguments. For example, you have to write\n\n a = "abc"\n b = a.replace("a", "f")\n\n and\n\n a = b"abc"\n b = a.replace(b"a", b"f")\n\nbytes.decode(encoding="utf-8", errors="strict")\nbytearray.decode(encoding="utf-8", errors="strict")\n\n Return a string decoded from the given bytes. Default encoding is\n ``\'utf-8\'``. *errors* may be given to set a different error\n handling scheme. The default for *errors* is ``\'strict\'``, meaning\n that encoding errors raise a ``UnicodeError``. Other possible\n values are ``\'ignore\'``, ``\'replace\'`` and any other name\n registered via ``codecs.register_error()``, see section *Codec Base\n Classes*. For a list of possible encodings, see section *Standard\n Encodings*.\n\n Changed in version 3.1: Added support for keyword arguments.\n\nThe bytes and bytearray types have an additional class method:\n\nclassmethod bytes.fromhex(string)\nclassmethod bytearray.fromhex(string)\n\n This ``bytes`` class method returns a bytes or bytearray object,\n decoding the given string object. The string must contain two\n hexadecimal digits per byte, spaces are ignored.\n\n >>> bytes.fromhex(\'f0 f1f2 \')\n b\'\\xf0\\xf1\\xf2\'\n\nThe maketrans and translate methods differ in semantics from the\nversions available on strings:\n\nbytes.translate(table[, delete])\nbytearray.translate(table[, delete])\n\n Return a copy of the bytes or bytearray object where all bytes\n occurring in the optional argument *delete* are removed, and the\n remaining bytes have been mapped through the given translation\n table, which must be a bytes object of length 256.\n\n You can use the ``bytes.maketrans()`` method to create a\n translation table.\n\n Set the *table* argument to ``None`` for translations that only\n delete characters:\n\n >>> b\'read this short text\'.translate(None, b\'aeiou\')\n b\'rd ths shrt txt\'\n\nstatic bytes.maketrans(from, to)\nstatic bytearray.maketrans(from, to)\n\n This static method returns a translation table usable for\n ``bytes.translate()`` that will map each character in *from* into\n the character at the same position in *to*; *from* and *to* must be\n bytes objects and have the same length.\n\n New in version 3.1.\n',
'typesseq-mutable': '\nMutable Sequence Types\n**********************\n\nList and bytearray objects support additional operations that allow\nin-place modification of the object. Other mutable sequence types\n(when added to the language) should also support these operations.\nStrings and tuples are immutable sequence types: such objects cannot\nbe modified once created. The following operations are defined on\nmutable sequence types (where *x* is an arbitrary object).\n\nNote that while lists allow their items to be of any type, bytearray\nobject "items" are all integers in the range 0 <= x < 256.\n\n+--------------------------------+----------------------------------+-----------------------+\n| Operation | Result | Notes |\n+================================+==================================+=======================+\n| ``s[i] = x`` | item *i* of *s* is replaced by | |\n| | *x* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j] = t`` | slice of *s* from *i* to *j* is | |\n| | replaced by the contents of the | |\n| | iterable *t* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j]`` | same as ``s[i:j] = []`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j:k] = t`` | the elements of ``s[i:j:k]`` are | (1) |\n| | replaced by those of *t* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j:k]`` | removes the elements of | |\n| | ``s[i:j:k]`` from the list | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.append(x)`` | same as ``s[len(s):len(s)] = | |\n| | [x]`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.extend(x)`` | same as ``s[len(s):len(s)] = x`` | (2) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.clear()`` | remove all items from ``s`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.copy()`` | return a shallow copy of ``s`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.count(x)`` | return number of *i*\'s for which | |\n| | ``s[i] == x`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.index(x[, i[, j]])`` | return smallest *k* such that | (3) |\n| | ``s[k] == x`` and ``i <= k < j`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.insert(i, x)`` | same as ``s[i:i] = [x]`` | (4) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.pop([i])`` | same as ``x = s[i]; del s[i]; | (5) |\n| | return x`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.remove(x)`` | same as ``del s[s.index(x)]`` | (3) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.reverse()`` | reverses the items of *s* in | (6) |\n| | place | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.sort([key[, reverse]])`` | sort the items of *s* in place | (6), (7), (8) |\n+--------------------------------+----------------------------------+-----------------------+\n\nNotes:\n\n1. *t* must have the same length as the slice it is replacing.\n\n2. *x* can be any iterable object.\n\n3. Raises ``ValueError`` when *x* is not found in *s*. When a negative\n index is passed as the second or third parameter to the ``index()``\n method, the sequence length is added, as for slice indices. If it\n is still negative, it is truncated to zero, as for slice indices.\n\n4. When a negative index is passed as the first parameter to the\n ``insert()`` method, the sequence length is added, as for slice\n indices. If it is still negative, it is truncated to zero, as for\n slice indices.\n\n5. The optional argument *i* defaults to ``-1``, so that by default\n the last item is removed and returned.\n\n6. The ``sort()`` and ``reverse()`` methods modify the sequence in\n place for economy of space when sorting or reversing a large\n sequence. To remind you that they operate by side effect, they\n don\'t return the sorted or reversed sequence.\n\n7. The ``sort()`` method takes optional arguments for controlling the\n comparisons. Each must be specified as a keyword argument.\n\n *key* specifies a function of one argument that is used to extract\n a comparison key from each list element: ``key=str.lower``. The\n default value is ``None``. Use ``functools.cmp_to_key()`` to\n convert an old-style *cmp* function to a *key* function.\n\n *reverse* is a boolean value. If set to ``True``, then the list\n elements are sorted as if each comparison were reversed.\n\n The ``sort()`` method is guaranteed to be stable. A sort is stable\n if it guarantees not to change the relative order of elements that\n compare equal --- this is helpful for sorting in multiple passes\n (for example, sort by department, then by salary grade).\n\n **CPython implementation detail:** While a list is being sorted,\n the effect of attempting to mutate, or even inspect, the list is\n undefined. The C implementation of Python makes the list appear\n empty for the duration, and raises ``ValueError`` if it can detect\n that the list has been mutated during a sort.\n\n8. ``sort()`` is not supported by ``bytearray`` objects.\n\n New in version 3.3: ``clear()`` and ``copy()`` methods.\n',
'unary': '\nUnary arithmetic and bitwise operations\n***************************************\n\nAll unary arithmetic and bitwise operations have the same priority:\n\n u_expr ::= power | "-" u_expr | "+" u_expr | "~" u_expr\n\nThe unary ``-`` (minus) operator yields the negation of its numeric\nargument.\n\nThe unary ``+`` (plus) operator yields its numeric argument unchanged.\n\nThe unary ``~`` (invert) operator yields the bitwise inversion of its\ninteger argument. The bitwise inversion of ``x`` is defined as\n``-(x+1)``. It only applies to integral numbers.\n\nIn all three cases, if the argument does not have the proper type, a\n``TypeError`` exception is raised.\n',
'while': '\nThe ``while`` statement\n***********************\n\nThe ``while`` statement is used for repeated execution as long as an\nexpression is true:\n\n while_stmt ::= "while" expression ":" suite\n ["else" ":" suite]\n\nThis repeatedly tests the expression and, if it is true, executes the\nfirst suite; if the expression is false (which may be the first time\nit is tested) the suite of the ``else`` clause, if present, is\nexecuted and the loop terminates.\n\nA ``break`` statement executed in the first suite terminates the loop\nwithout executing the ``else`` clause\'s suite. A ``continue``\nstatement executed in the first suite skips the rest of the suite and\ngoes back to testing the expression.\n',
'with': '\nThe ``with`` statement\n**********************\n\nThe ``with`` statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common\n``try``...``except``...``finally`` usage patterns to be encapsulated\nfor convenient reuse.\n\n with_stmt ::= "with" with_item ("," with_item)* ":" suite\n with_item ::= expression ["as" target]\n\nThe execution of the ``with`` statement with one "item" proceeds as\nfollows:\n\n1. The context expression (the expression given in the ``with_item``)\n is evaluated to obtain a context manager.\n\n2. The context manager\'s ``__exit__()`` is loaded for later use.\n\n3. The context manager\'s ``__enter__()`` method is invoked.\n\n4. If a target was included in the ``with`` statement, the return\n value from ``__enter__()`` is assigned to it.\n\n Note: The ``with`` statement guarantees that if the ``__enter__()``\n method returns without an error, then ``__exit__()`` will always\n be called. Thus, if an error occurs during the assignment to the\n target list, it will be treated the same as an error occurring\n within the suite would be. See step 6 below.\n\n5. The suite is executed.\n\n6. The context manager\'s ``__exit__()`` method is invoked. If an\n exception caused the suite to be exited, its type, value, and\n traceback are passed as arguments to ``__exit__()``. Otherwise,\n three ``None`` arguments are supplied.\n\n If the suite was exited due to an exception, and the return value\n from the ``__exit__()`` method was false, the exception is\n reraised. If the return value was true, the exception is\n suppressed, and execution continues with the statement following\n the ``with`` statement.\n\n If the suite was exited for any reason other than an exception, the\n return value from ``__exit__()`` is ignored, and execution proceeds\n at the normal location for the kind of exit that was taken.\n\nWith more than one item, the context managers are processed as if\nmultiple ``with`` statements were nested:\n\n with A() as a, B() as b:\n suite\n\nis equivalent to\n\n with A() as a:\n with B() as b:\n suite\n\nChanged in version 3.1: Support for multiple context expressions.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n',
- 'yield': '\nThe ``yield`` statement\n***********************\n\n yield_stmt ::= yield_expression\n\nThe ``yield`` statement is only used when defining a generator\nfunction, and is only used in the body of the generator function.\nUsing a ``yield`` statement in a function definition is sufficient to\ncause that definition to create a generator function instead of a\nnormal function. When a generator function is called, it returns an\niterator known as a generator iterator, or more commonly, a generator.\nThe body of the generator function is executed by calling the\n``next()`` function on the generator repeatedly until it raises an\nexception.\n\nWhen a ``yield`` statement is executed, the state of the generator is\nfrozen and the value of ``expression_list`` is returned to\n``next()``\'s caller. By "frozen" we mean that all local state is\nretained, including the current bindings of local variables, the\ninstruction pointer, and the internal evaluation stack: enough\ninformation is saved so that the next time ``next()`` is invoked, the\nfunction can proceed exactly as if the ``yield`` statement were just\nanother external call.\n\nThe ``yield`` statement is allowed in the ``try`` clause of a ``try``\n... ``finally`` construct. If the generator is not resumed before it\nis finalized (by reaching a zero reference count or by being garbage\ncollected), the generator-iterator\'s ``close()`` method will be\ncalled, allowing any pending ``finally`` clauses to execute.\n\nSee also:\n\n **PEP 0255** - Simple Generators\n The proposal for adding generators and the ``yield`` statement\n to Python.\n\n **PEP 0342** - Coroutines via Enhanced Generators\n The proposal that, among other generator enhancements, proposed\n allowing ``yield`` to appear inside a ``try`` ... ``finally``\n block.\n'}
+ 'yield': '\nThe ``yield`` statement\n***********************\n\n yield_stmt ::= yield_expression\n\nThe ``yield`` statement is only used when defining a generator\nfunction, and is only used in the body of the generator function.\nUsing a ``yield`` statement in a function definition is sufficient to\ncause that definition to create a generator function instead of a\nnormal function.\n\nWhen a generator function is called, it returns an iterator known as a\ngenerator iterator, or more commonly, a generator. The body of the\ngenerator function is executed by calling the ``next()`` function on\nthe generator repeatedly until it raises an exception.\n\nWhen a ``yield`` statement is executed, the state of the generator is\nfrozen and the value of ``expression_list`` is returned to\n``next()``\'s caller. By "frozen" we mean that all local state is\nretained, including the current bindings of local variables, the\ninstruction pointer, and the internal evaluation stack: enough\ninformation is saved so that the next time ``next()`` is invoked, the\nfunction can proceed exactly as if the ``yield`` statement were just\nanother external call.\n\nThe ``yield`` statement is allowed in the ``try`` clause of a ``try``\n... ``finally`` construct. If the generator is not resumed before it\nis finalized (by reaching a zero reference count or by being garbage\ncollected), the generator-iterator\'s ``close()`` method will be\ncalled, allowing any pending ``finally`` clauses to execute.\n\nWhen ``yield from <expr>`` is used, it treats the supplied expression\nas a subiterator, producing values from it until the underlying\niterator is exhausted.\n\n Changed in version 3.3: Added ``yield from <expr>`` to delegate\n control flow to a subiterator\n\nFor full details of ``yield`` semantics, refer to the *Yield\nexpressions* section.\n\nSee also:\n\n **PEP 0255** - Simple Generators\n The proposal for adding generators and the ``yield`` statement\n to Python.\n\n **PEP 0342** - Coroutines via Enhanced Generators\n The proposal to enhance the API and syntax of generators, making\n them usable as simple coroutines.\n\n **PEP 0380** - Syntax for Delegating to a Subgenerator\n The proposal to introduce the ``yield_from`` syntax, making\n delegation to sub-generators easy.\n'}
diff --git a/Lib/test/crashers/loosing_mro_ref.py b/Lib/test/crashers/losing_mro_ref.py
similarity index 100%
rename from Lib/test/crashers/loosing_mro_ref.py
rename to Lib/test/crashers/losing_mro_ref.py
diff --git a/Lib/test/crashers/nasty_eq_vs_dict.py b/Lib/test/crashers/nasty_eq_vs_dict.py
deleted file mode 100644
index 85f7caf..0000000
--- a/Lib/test/crashers/nasty_eq_vs_dict.py
+++ /dev/null
@@ -1,47 +0,0 @@
-# from http://mail.python.org/pipermail/python-dev/2001-June/015239.html
-
-# if you keep changing a dictionary while looking up a key, you can
-# provoke an infinite recursion in C
-
-# At the time neither Tim nor Michael could be bothered to think of a
-# way to fix it.
-
-class Yuck:
- def __init__(self):
- self.i = 0
-
- def make_dangerous(self):
- self.i = 1
-
- def __hash__(self):
- # direct to slot 4 in table of size 8; slot 12 when size 16
- return 4 + 8
-
- def __eq__(self, other):
- if self.i == 0:
- # leave dict alone
- pass
- elif self.i == 1:
- # fiddle to 16 slots
- self.__fill_dict(6)
- self.i = 2
- else:
- # fiddle to 8 slots
- self.__fill_dict(4)
- self.i = 1
-
- return 1
-
- def __fill_dict(self, n):
- self.i = 0
- dict.clear()
- for i in range(n):
- dict[i] = i
- dict[self] = "OK!"
-
-y = Yuck()
-dict = {y: "OK!"}
-
-z = Yuck()
-y.make_dangerous()
-print(dict[z])
diff --git a/Lib/test/pickletester.py b/Lib/test/pickletester.py
index 831306f..1a551c8 100644
--- a/Lib/test/pickletester.py
+++ b/Lib/test/pickletester.py
@@ -1605,6 +1605,105 @@
self.assertEqual(unpickler.load(), data)
+# Tests for dispatch_table attribute
+
+REDUCE_A = 'reduce_A'
+
+class AAA(object):
+ def __reduce__(self):
+ return str, (REDUCE_A,)
+
+class BBB(object):
+ pass
+
+class AbstractDispatchTableTests(unittest.TestCase):
+
+ def test_default_dispatch_table(self):
+ # No dispatch_table attribute by default
+ f = io.BytesIO()
+ p = self.pickler_class(f, 0)
+ with self.assertRaises(AttributeError):
+ p.dispatch_table
+ self.assertFalse(hasattr(p, 'dispatch_table'))
+
+ def test_class_dispatch_table(self):
+ # A dispatch_table attribute can be specified class-wide
+ dt = self.get_dispatch_table()
+
+ class MyPickler(self.pickler_class):
+ dispatch_table = dt
+
+ def dumps(obj, protocol=None):
+ f = io.BytesIO()
+ p = MyPickler(f, protocol)
+ self.assertEqual(p.dispatch_table, dt)
+ p.dump(obj)
+ return f.getvalue()
+
+ self._test_dispatch_table(dumps, dt)
+
+ def test_instance_dispatch_table(self):
+ # A dispatch_table attribute can also be specified instance-wide
+ dt = self.get_dispatch_table()
+
+ def dumps(obj, protocol=None):
+ f = io.BytesIO()
+ p = self.pickler_class(f, protocol)
+ p.dispatch_table = dt
+ self.assertEqual(p.dispatch_table, dt)
+ p.dump(obj)
+ return f.getvalue()
+
+ self._test_dispatch_table(dumps, dt)
+
+ def _test_dispatch_table(self, dumps, dispatch_table):
+ def custom_load_dump(obj):
+ return pickle.loads(dumps(obj, 0))
+
+ def default_load_dump(obj):
+ return pickle.loads(pickle.dumps(obj, 0))
+
+ # pickling complex numbers using protocol 0 relies on copyreg
+ # so check pickling a complex number still works
+ z = 1 + 2j
+ self.assertEqual(custom_load_dump(z), z)
+ self.assertEqual(default_load_dump(z), z)
+
+ # modify pickling of complex
+ REDUCE_1 = 'reduce_1'
+ def reduce_1(obj):
+ return str, (REDUCE_1,)
+ dispatch_table[complex] = reduce_1
+ self.assertEqual(custom_load_dump(z), REDUCE_1)
+ self.assertEqual(default_load_dump(z), z)
+
+ # check picklability of AAA and BBB
+ a = AAA()
+ b = BBB()
+ self.assertEqual(custom_load_dump(a), REDUCE_A)
+ self.assertIsInstance(custom_load_dump(b), BBB)
+ self.assertEqual(default_load_dump(a), REDUCE_A)
+ self.assertIsInstance(default_load_dump(b), BBB)
+
+ # modify pickling of BBB
+ dispatch_table[BBB] = reduce_1
+ self.assertEqual(custom_load_dump(a), REDUCE_A)
+ self.assertEqual(custom_load_dump(b), REDUCE_1)
+ self.assertEqual(default_load_dump(a), REDUCE_A)
+ self.assertIsInstance(default_load_dump(b), BBB)
+
+ # revert pickling of BBB and modify pickling of AAA
+ REDUCE_2 = 'reduce_2'
+ def reduce_2(obj):
+ return str, (REDUCE_2,)
+ dispatch_table[AAA] = reduce_2
+ del dispatch_table[BBB]
+ self.assertEqual(custom_load_dump(a), REDUCE_2)
+ self.assertIsInstance(custom_load_dump(b), BBB)
+ self.assertEqual(default_load_dump(a), REDUCE_A)
+ self.assertIsInstance(default_load_dump(b), BBB)
+
+
if __name__ == "__main__":
# Print some stuff that can be used to rewrite DATA{0,1,2}
from pickletools import dis
diff --git a/Lib/test/regrtest.py b/Lib/test/regrtest.py
index 871ae61..44d3426 100755
--- a/Lib/test/regrtest.py
+++ b/Lib/test/regrtest.py
@@ -749,10 +749,10 @@
if bad:
print(count(len(bad), "test"), "failed:")
printlist(bad)
- if environment_changed:
- print("{} altered the execution environment:".format(
- count(len(environment_changed), "test")))
- printlist(environment_changed)
+ if environment_changed:
+ print("{} altered the execution environment:".format(
+ count(len(environment_changed), "test")))
+ printlist(environment_changed)
if skipped and not quiet:
print(count(len(skipped), "test"), "skipped:")
printlist(skipped)
@@ -970,6 +970,7 @@
'multiprocessing.process._dangling',
'sysconfig._CONFIG_VARS', 'sysconfig._SCHEMES',
'packaging.command._COMMANDS', 'packaging.database_caches',
+ 'support.TESTFN',
)
def get_sys_argv(self):
@@ -1163,6 +1164,20 @@
sysconfig._SCHEMES._sections.clear()
sysconfig._SCHEMES._sections.update(saved[2])
+ def get_support_TESTFN(self):
+ if os.path.isfile(support.TESTFN):
+ result = 'f'
+ elif os.path.isdir(support.TESTFN):
+ result = 'd'
+ else:
+ result = None
+ return result
+ def restore_support_TESTFN(self, saved_value):
+ if saved_value is None:
+ if os.path.isfile(support.TESTFN):
+ os.unlink(support.TESTFN)
+ elif os.path.isdir(support.TESTFN):
+ shutil.rmtree(support.TESTFN)
def resource_info(self):
for name in self.resources:
diff --git a/Lib/test/test_base64.py b/Lib/test/test_base64.py
index b02f86d..2569476 100644
--- a/Lib/test/test_base64.py
+++ b/Lib/test/test_base64.py
@@ -2,6 +2,7 @@
from test import support
import base64
import binascii
+import os
import sys
import subprocess
@@ -274,6 +275,10 @@
class TestMain(unittest.TestCase):
+ def tearDown(self):
+ if os.path.exists(support.TESTFN):
+ os.unlink(support.TESTFN)
+
def get_output(self, *args, **options):
args = (sys.executable, '-m', 'base64') + args
return subprocess.check_output(args, **options)
diff --git a/Lib/test/test_buffer.py b/Lib/test/test_buffer.py
index 25324ef..e0006f2 100644
--- a/Lib/test/test_buffer.py
+++ b/Lib/test/test_buffer.py
@@ -3373,6 +3373,15 @@
del nd
m.release()
+ a = bytearray([1,2,3])
+ m = memoryview(a)
+ nd1 = ndarray(m, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
+ nd2 = ndarray(nd1, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
+ self.assertIs(nd2.obj, m)
+ self.assertRaises(BufferError, m.release)
+ del nd1, nd2
+ m.release()
+
# chained views
a = bytearray([1,2,3])
m1 = memoryview(a)
@@ -3383,6 +3392,17 @@
del nd
m2.release()
+ a = bytearray([1,2,3])
+ m1 = memoryview(a)
+ m2 = memoryview(m1)
+ nd1 = ndarray(m2, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
+ nd2 = ndarray(nd1, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
+ self.assertIs(nd2.obj, m2)
+ m1.release()
+ self.assertRaises(BufferError, m2.release)
+ del nd1, nd2
+ m2.release()
+
# Allow changing layout while buffers are exported.
nd = ndarray([1,2,3], shape=[3], flags=ND_VAREXPORT)
m1 = memoryview(nd)
@@ -3418,11 +3438,182 @@
catch22(m1)
self.assertEqual(m1[0], ord(b'1'))
- # XXX If m1 has exports, raise BufferError.
- # x = bytearray(b'123')
- # with memoryview(x) as m1:
- # ex = ndarray(m1)
- # m1[0] == ord(b'1')
+ x = ndarray(list(range(12)), shape=[2,2,3], format='l')
+ y = ndarray(x, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
+ z = ndarray(y, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
+ self.assertIs(z.obj, x)
+ with memoryview(z) as m:
+ catch22(m)
+ self.assertEqual(m[0:1].tolist(), [[[0, 1, 2], [3, 4, 5]]])
+
+ # Test garbage collection.
+ for flags in (0, ND_REDIRECT):
+ x = bytearray(b'123')
+ with memoryview(x) as m1:
+ del x
+ y = ndarray(m1, getbuf=PyBUF_FULL_RO, flags=flags)
+ with memoryview(y) as m2:
+ del y
+ z = ndarray(m2, getbuf=PyBUF_FULL_RO, flags=flags)
+ with memoryview(z) as m3:
+ del z
+ catch22(m3)
+ catch22(m2)
+ catch22(m1)
+ self.assertEqual(m1[0], ord(b'1'))
+ self.assertEqual(m2[1], ord(b'2'))
+ self.assertEqual(m3[2], ord(b'3'))
+ del m3
+ del m2
+ del m1
+
+ x = bytearray(b'123')
+ with memoryview(x) as m1:
+ del x
+ y = ndarray(m1, getbuf=PyBUF_FULL_RO, flags=flags)
+ with memoryview(y) as m2:
+ del y
+ z = ndarray(m2, getbuf=PyBUF_FULL_RO, flags=flags)
+ with memoryview(z) as m3:
+ del z
+ catch22(m1)
+ catch22(m2)
+ catch22(m3)
+ self.assertEqual(m1[0], ord(b'1'))
+ self.assertEqual(m2[1], ord(b'2'))
+ self.assertEqual(m3[2], ord(b'3'))
+ del m1, m2, m3
+
+ # memoryview.release() fails if the view has exported buffers.
+ x = bytearray(b'123')
+ with self.assertRaises(BufferError):
+ with memoryview(x) as m:
+ ex = ndarray(m)
+ m[0] == ord(b'1')
+
+ def test_memoryview_redirect(self):
+
+ nd = ndarray([1.0 * x for x in range(12)], shape=[12], format='d')
+ a = array.array('d', [1.0 * x for x in range(12)])
+
+ for x in (nd, a):
+ y = ndarray(x, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
+ z = ndarray(y, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
+ m = memoryview(z)
+
+ self.assertIs(y.obj, x)
+ self.assertIs(z.obj, x)
+ self.assertIs(m.obj, x)
+
+ self.assertEqual(m, x)
+ self.assertEqual(m, y)
+ self.assertEqual(m, z)
+
+ self.assertEqual(m[1:3], x[1:3])
+ self.assertEqual(m[1:3], y[1:3])
+ self.assertEqual(m[1:3], z[1:3])
+ del y, z
+ self.assertEqual(m[1:3], x[1:3])
+
+ def test_memoryview_from_static_exporter(self):
+
+ fmt = 'B'
+ lst = [0,1,2,3,4,5,6,7,8,9,10,11]
+
+ # exceptions
+ self.assertRaises(TypeError, staticarray, 1, 2, 3)
+
+ # view.obj==x
+ x = staticarray()
+ y = memoryview(x)
+ self.verify(y, obj=x,
+ itemsize=1, fmt=fmt, readonly=1,
+ ndim=1, shape=[12], strides=[1],
+ lst=lst)
+ for i in range(12):
+ self.assertEqual(y[i], i)
+ del x
+ del y
+
+ x = staticarray()
+ y = memoryview(x)
+ del y
+ del x
+
+ x = staticarray()
+ y = ndarray(x, getbuf=PyBUF_FULL_RO)
+ z = ndarray(y, getbuf=PyBUF_FULL_RO)
+ m = memoryview(z)
+ self.assertIs(y.obj, x)
+ self.assertIs(m.obj, z)
+ self.verify(m, obj=z,
+ itemsize=1, fmt=fmt, readonly=1,
+ ndim=1, shape=[12], strides=[1],
+ lst=lst)
+ del x, y, z, m
+
+ x = staticarray()
+ y = ndarray(x, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
+ z = ndarray(y, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
+ m = memoryview(z)
+ self.assertIs(y.obj, x)
+ self.assertIs(z.obj, x)
+ self.assertIs(m.obj, x)
+ self.verify(m, obj=x,
+ itemsize=1, fmt=fmt, readonly=1,
+ ndim=1, shape=[12], strides=[1],
+ lst=lst)
+ del x, y, z, m
+
+ # view.obj==NULL
+ x = staticarray(legacy_mode=True)
+ y = memoryview(x)
+ self.verify(y, obj=None,
+ itemsize=1, fmt=fmt, readonly=1,
+ ndim=1, shape=[12], strides=[1],
+ lst=lst)
+ for i in range(12):
+ self.assertEqual(y[i], i)
+ del x
+ del y
+
+ x = staticarray(legacy_mode=True)
+ y = memoryview(x)
+ del y
+ del x
+
+ x = staticarray(legacy_mode=True)
+ y = ndarray(x, getbuf=PyBUF_FULL_RO)
+ z = ndarray(y, getbuf=PyBUF_FULL_RO)
+ m = memoryview(z)
+ self.assertIs(y.obj, None)
+ self.assertIs(m.obj, z)
+ self.verify(m, obj=z,
+ itemsize=1, fmt=fmt, readonly=1,
+ ndim=1, shape=[12], strides=[1],
+ lst=lst)
+ del x, y, z, m
+
+ x = staticarray(legacy_mode=True)
+ y = ndarray(x, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
+ z = ndarray(y, getbuf=PyBUF_FULL_RO, flags=ND_REDIRECT)
+ m = memoryview(z)
+ # Clearly setting view.obj==NULL is inferior, since it
+ # messes up the redirection chain:
+ self.assertIs(y.obj, None)
+ self.assertIs(z.obj, y)
+ self.assertIs(m.obj, y)
+ self.verify(m, obj=y,
+ itemsize=1, fmt=fmt, readonly=1,
+ ndim=1, shape=[12], strides=[1],
+ lst=lst)
+ del x, y, z, m
+
+ def test_memoryview_getbuffer_undefined(self):
+
+ # getbufferproc does not adhere to the new documentation
+ nd = ndarray([1,2,3], [3], flags=ND_GETBUF_FAIL|ND_GETBUF_UNDEFINED)
+ self.assertRaises(BufferError, memoryview, nd)
def test_issue_7385(self):
x = ndarray([1,2,3], shape=[3], flags=ND_GETBUF_FAIL)
diff --git a/Lib/test/test_dict.py b/Lib/test/test_dict.py
index d2740a3..15db51d 100644
--- a/Lib/test/test_dict.py
+++ b/Lib/test/test_dict.py
@@ -379,7 +379,7 @@
x.fail = True
self.assertRaises(Exc, d.pop, x)
- def test_mutatingiteration(self):
+ def test_mutating_iteration(self):
# changing dict size during iteration
d = {}
d[1] = 1
@@ -387,6 +387,26 @@
for i in d:
d[i+1] = 1
+ def test_mutating_lookup(self):
+ # changing dict during a lookup
+ class NastyKey:
+ mutate_dict = None
+
+ def __hash__(self):
+ # hash collision!
+ return 1
+
+ def __eq__(self, other):
+ if self.mutate_dict:
+ self.mutate_dict[self] = 1
+ return self == other
+
+ d = {}
+ d[NastyKey()] = 0
+ NastyKey.mutate_dict = d
+ with self.assertRaises(RuntimeError):
+ d[NastyKey()] = None
+
def test_repr(self):
d = {}
self.assertEqual(repr(d), '{}')
diff --git a/Lib/test/test_exceptions.py b/Lib/test/test_exceptions.py
index 91d85ef..42536d3 100644
--- a/Lib/test/test_exceptions.py
+++ b/Lib/test/test_exceptions.py
@@ -38,7 +38,7 @@
try:
try:
import marshal
- marshal.loads('')
+ marshal.loads(b'')
except EOFError:
pass
finally:
diff --git a/Lib/test/test_logging.py b/Lib/test/test_logging.py
index b239f58..98a2819 100644
--- a/Lib/test/test_logging.py
+++ b/Lib/test/test_logging.py
@@ -3651,11 +3651,14 @@
def test_rollover(self):
fh = logging.handlers.TimedRotatingFileHandler(self.fn, 'S',
backupCount=1)
- r = logging.makeLogRecord({'msg': 'testing'})
- fh.emit(r)
+ fmt = logging.Formatter('%(asctime)s %(message)s')
+ fh.setFormatter(fmt)
+ r1 = logging.makeLogRecord({'msg': 'testing - initial'})
+ fh.emit(r1)
self.assertLogFile(self.fn)
- time.sleep(1.01) # just a little over a second ...
- fh.emit(r)
+ time.sleep(1.1) # a little over a second ...
+ r2 = logging.makeLogRecord({'msg': 'testing - after delay'})
+ fh.emit(r2)
fh.close()
# At this point, we should have a recent rotated file which we
# can test for the existence of. However, in practice, on some
@@ -3682,7 +3685,8 @@
print('The only matching files are: %s' % files, file=sys.stderr)
for f in files:
print('Contents of %s:' % f)
- with open(f, 'r') as tf:
+ path = os.path.join(dn, f)
+ with open(path, 'r') as tf:
print(tf.read())
self.assertTrue(found, msg=msg)
diff --git a/Lib/test/test_mailbox.py b/Lib/test/test_mailbox.py
index 4bb05a4..212ceb9 100644
--- a/Lib/test/test_mailbox.py
+++ b/Lib/test/test_mailbox.py
@@ -7,6 +7,7 @@
import email.message
import re
import io
+import shutil
import tempfile
from test import support
import unittest
@@ -38,12 +39,7 @@
def _delete_recursively(self, target):
# Delete a file or delete a directory recursively
if os.path.isdir(target):
- for path, dirs, files in os.walk(target, topdown=False):
- for name in files:
- os.remove(os.path.join(path, name))
- for name in dirs:
- os.rmdir(os.path.join(path, name))
- os.rmdir(target)
+ shutil.rmtree(target)
elif os.path.exists(target):
os.remove(target)
@@ -2028,6 +2024,10 @@
def setUp(self):
# create a new maildir mailbox to work with:
self._dir = support.TESTFN
+ if os.path.isdir(self._dir):
+ shutil.rmtree(self._dir)
+ elif os.path.isfile(self._dir):
+ os.unlink(self._dir)
os.mkdir(self._dir)
os.mkdir(os.path.join(self._dir, "cur"))
os.mkdir(os.path.join(self._dir, "tmp"))
diff --git a/Lib/test/test_marshal.py b/Lib/test/test_marshal.py
index dec8129..83c348c 100644
--- a/Lib/test/test_marshal.py
+++ b/Lib/test/test_marshal.py
@@ -1,6 +1,7 @@
#!/usr/bin/env python3
from test import support
+import array
import marshal
import sys
import unittest
@@ -154,6 +155,27 @@
for constructor in (set, frozenset):
self.helper(constructor(self.d.keys()))
+
+class BufferTestCase(unittest.TestCase, HelperMixin):
+
+ def test_bytearray(self):
+ b = bytearray(b"abc")
+ self.helper(b)
+ new = marshal.loads(marshal.dumps(b))
+ self.assertEqual(type(new), bytes)
+
+ def test_memoryview(self):
+ b = memoryview(b"abc")
+ self.helper(b)
+ new = marshal.loads(marshal.dumps(b))
+ self.assertEqual(type(new), bytes)
+
+ def test_array(self):
+ a = array.array('B', b"abc")
+ new = marshal.loads(marshal.dumps(a))
+ self.assertEqual(new, b"abc")
+
+
class BugsTestCase(unittest.TestCase):
def test_bug_5888452(self):
# Simple-minded check for SF 588452: Debug build crashes
@@ -179,7 +201,7 @@
pass
def test_loads_recursion(self):
- s = 'c' + ('X' * 4*4) + '{' * 2**20
+ s = b'c' + (b'X' * 4*4) + b'{' * 2**20
self.assertRaises(ValueError, marshal.loads, s)
def test_recursion_limit(self):
@@ -252,6 +274,11 @@
finally:
support.unlink(support.TESTFN)
+ def test_loads_reject_unicode_strings(self):
+ # Issue #14177: marshal.loads() should not accept unicode strings
+ unicode_string = 'T'
+ self.assertRaises(TypeError, marshal.loads, unicode_string)
+
def test_main():
support.run_unittest(IntTestCase,
@@ -260,6 +287,7 @@
CodeTestCase,
ContainerTestCase,
ExceptionTestCase,
+ BufferTestCase,
BugsTestCase)
if __name__ == "__main__":
diff --git a/Lib/test/test_minidom.py b/Lib/test/test_minidom.py
index 752a840..cc4c95b 100644
--- a/Lib/test/test_minidom.py
+++ b/Lib/test/test_minidom.py
@@ -362,11 +362,17 @@
def testGetAttrList(self):
pass
- def testGetAttrValues(self): pass
+ def testGetAttrValues(self):
+ pass
- def testGetAttrLength(self): pass
+ def testGetAttrLength(self):
+ pass
- def testGetAttribute(self): pass
+ def testGetAttribute(self):
+ dom = Document()
+ child = dom.appendChild(
+ dom.createElementNS("http://www.python.org", "python:abc"))
+ self.assertEqual(child.getAttribute('missing'), '')
def testGetAttributeNS(self):
dom = Document()
@@ -378,6 +384,9 @@
'http://www.python.org')
self.assertEqual(child.getAttributeNS("http://www.w3.org", "other"),
'')
+ child2 = child.appendChild(dom.createElement('abc'))
+ self.assertEqual(child2.getAttributeNS("http://www.python.org", "missing"),
+ '')
def testGetAttributeNode(self): pass
diff --git a/Lib/test/test_multiprocessing.py b/Lib/test/test_multiprocessing.py
index f141bd4..0db6352 100644
--- a/Lib/test/test_multiprocessing.py
+++ b/Lib/test/test_multiprocessing.py
@@ -1811,6 +1811,84 @@
p.join()
l.close()
+class _TestPoll(unittest.TestCase):
+
+ ALLOWED_TYPES = ('processes', 'threads')
+
+ def test_empty_string(self):
+ a, b = self.Pipe()
+ self.assertEqual(a.poll(), False)
+ b.send_bytes(b'')
+ self.assertEqual(a.poll(), True)
+ self.assertEqual(a.poll(), True)
+
+ @classmethod
+ def _child_strings(cls, conn, strings):
+ for s in strings:
+ time.sleep(0.1)
+ conn.send_bytes(s)
+ conn.close()
+
+ def test_strings(self):
+ strings = (b'hello', b'', b'a', b'b', b'', b'bye', b'', b'lop')
+ a, b = self.Pipe()
+ p = self.Process(target=self._child_strings, args=(b, strings))
+ p.start()
+
+ for s in strings:
+ for i in range(200):
+ if a.poll(0.01):
+ break
+ x = a.recv_bytes()
+ self.assertEqual(s, x)
+
+ p.join()
+
+ @classmethod
+ def _child_boundaries(cls, r):
+ # Polling may "pull" a message in to the child process, but we
+ # don't want it to pull only part of a message, as that would
+ # corrupt the pipe for any other processes which might later
+ # read from it.
+ r.poll(5)
+
+ def test_boundaries(self):
+ r, w = self.Pipe(False)
+ p = self.Process(target=self._child_boundaries, args=(r,))
+ p.start()
+ time.sleep(2)
+ L = [b"first", b"second"]
+ for obj in L:
+ w.send_bytes(obj)
+ w.close()
+ p.join()
+ self.assertIn(r.recv_bytes(), L)
+
+ @classmethod
+ def _child_dont_merge(cls, b):
+ b.send_bytes(b'a')
+ b.send_bytes(b'b')
+ b.send_bytes(b'cd')
+
+ def test_dont_merge(self):
+ a, b = self.Pipe()
+ self.assertEqual(a.poll(0.0), False)
+ self.assertEqual(a.poll(0.1), False)
+
+ p = self.Process(target=self._child_dont_merge, args=(b,))
+ p.start()
+
+ self.assertEqual(a.recv_bytes(), b'a')
+ self.assertEqual(a.poll(1.0), True)
+ self.assertEqual(a.poll(1.0), True)
+ self.assertEqual(a.recv_bytes(), b'b')
+ self.assertEqual(a.poll(1.0), True)
+ self.assertEqual(a.poll(1.0), True)
+ self.assertEqual(a.poll(0.0), True)
+ self.assertEqual(a.recv_bytes(), b'cd')
+
+ p.join()
+
#
# Test of sending connection and socket objects between processes
#
@@ -2404,8 +2482,164 @@
flike.flush()
assert sio.getvalue() == 'foo'
+
+class TestWait(unittest.TestCase):
+
+ @classmethod
+ def _child_test_wait(cls, w, slow):
+ for i in range(10):
+ if slow:
+ time.sleep(random.random()*0.1)
+ w.send((i, os.getpid()))
+ w.close()
+
+ def test_wait(self, slow=False):
+ from multiprocessing.connection import wait
+ readers = []
+ procs = []
+ messages = []
+
+ for i in range(4):
+ r, w = multiprocessing.Pipe(duplex=False)
+ p = multiprocessing.Process(target=self._child_test_wait, args=(w, slow))
+ p.daemon = True
+ p.start()
+ w.close()
+ readers.append(r)
+ procs.append(p)
+ self.addCleanup(p.join)
+
+ while readers:
+ for r in wait(readers):
+ try:
+ msg = r.recv()
+ except EOFError:
+ readers.remove(r)
+ r.close()
+ else:
+ messages.append(msg)
+
+ messages.sort()
+ expected = sorted((i, p.pid) for i in range(10) for p in procs)
+ self.assertEqual(messages, expected)
+
+ @classmethod
+ def _child_test_wait_socket(cls, address, slow):
+ s = socket.socket()
+ s.connect(address)
+ for i in range(10):
+ if slow:
+ time.sleep(random.random()*0.1)
+ s.sendall(('%s\n' % i).encode('ascii'))
+ s.close()
+
+ def test_wait_socket(self, slow=False):
+ from multiprocessing.connection import wait
+ l = socket.socket()
+ l.bind(('', 0))
+ l.listen(4)
+ addr = ('localhost', l.getsockname()[1])
+ readers = []
+ procs = []
+ dic = {}
+
+ for i in range(4):
+ p = multiprocessing.Process(target=self._child_test_wait_socket,
+ args=(addr, slow))
+ p.daemon = True
+ p.start()
+ procs.append(p)
+ self.addCleanup(p.join)
+
+ for i in range(4):
+ r, _ = l.accept()
+ readers.append(r)
+ dic[r] = []
+ l.close()
+
+ while readers:
+ for r in wait(readers):
+ msg = r.recv(32)
+ if not msg:
+ readers.remove(r)
+ r.close()
+ else:
+ dic[r].append(msg)
+
+ expected = ''.join('%s\n' % i for i in range(10)).encode('ascii')
+ for v in dic.values():
+ self.assertEqual(b''.join(v), expected)
+
+ def test_wait_slow(self):
+ self.test_wait(True)
+
+ def test_wait_socket_slow(self):
+ self.test_wait(True)
+
+ def test_wait_timeout(self):
+ from multiprocessing.connection import wait
+
+ expected = 1
+ a, b = multiprocessing.Pipe()
+
+ start = time.time()
+ res = wait([a, b], 1)
+ delta = time.time() - start
+
+ self.assertEqual(res, [])
+ self.assertLess(delta, expected + 0.2)
+ self.assertGreater(delta, expected - 0.2)
+
+ b.send(None)
+
+ start = time.time()
+ res = wait([a, b], 1)
+ delta = time.time() - start
+
+ self.assertEqual(res, [a])
+ self.assertLess(delta, 0.2)
+
+ def test_wait_integer(self):
+ from multiprocessing.connection import wait
+
+ expected = 5
+ a, b = multiprocessing.Pipe()
+ p = multiprocessing.Process(target=time.sleep, args=(expected,))
+
+ p.start()
+ self.assertIsInstance(p.sentinel, int)
+
+ start = time.time()
+ res = wait([a, p.sentinel, b], expected + 20)
+ delta = time.time() - start
+
+ self.assertEqual(res, [p.sentinel])
+ self.assertLess(delta, expected + 1)
+ self.assertGreater(delta, expected - 1)
+
+ a.send(None)
+
+ start = time.time()
+ res = wait([a, p.sentinel, b], 20)
+ delta = time.time() - start
+
+ self.assertEqual(res, [p.sentinel, b])
+ self.assertLess(delta, 0.2)
+
+ b.send(None)
+
+ start = time.time()
+ res = wait([a, p.sentinel, b], 20)
+ delta = time.time() - start
+
+ self.assertEqual(res, [a, p.sentinel, b])
+ self.assertLess(delta, 0.2)
+
+ p.join()
+
+
testcases_other = [OtherTest, TestInvalidHandle, TestInitializers,
- TestStdinBadfiledescriptor]
+ TestStdinBadfiledescriptor, TestWait]
#
#
diff --git a/Lib/test/test_mutants.py b/Lib/test/test_mutants.py
deleted file mode 100644
index b43fa47..0000000
--- a/Lib/test/test_mutants.py
+++ /dev/null
@@ -1,291 +0,0 @@
-from test.support import verbose, TESTFN
-import random
-import os
-
-# From SF bug #422121: Insecurities in dict comparison.
-
-# Safety of code doing comparisons has been an historical Python weak spot.
-# The problem is that comparison of structures written in C *naturally*
-# wants to hold on to things like the size of the container, or "the
-# biggest" containee so far, across a traversal of the container; but
-# code to do containee comparisons can call back into Python and mutate
-# the container in arbitrary ways while the C loop is in midstream. If the
-# C code isn't extremely paranoid about digging things out of memory on
-# each trip, and artificially boosting refcounts for the duration, anything
-# from infinite loops to OS crashes can result (yes, I use Windows <wink>).
-#
-# The other problem is that code designed to provoke a weakness is usually
-# white-box code, and so catches only the particular vulnerabilities the
-# author knew to protect against. For example, Python's list.sort() code
-# went thru many iterations as one "new" vulnerability after another was
-# discovered.
-#
-# So the dict comparison test here uses a black-box approach instead,
-# generating dicts of various sizes at random, and performing random
-# mutations on them at random times. This proved very effective,
-# triggering at least six distinct failure modes the first 20 times I
-# ran it. Indeed, at the start, the driver never got beyond 6 iterations
-# before the test died.
-
-# The dicts are global to make it easy to mutate tham from within functions.
-dict1 = {}
-dict2 = {}
-
-# The current set of keys in dict1 and dict2. These are materialized as
-# lists to make it easy to pick a dict key at random.
-dict1keys = []
-dict2keys = []
-
-# Global flag telling maybe_mutate() whether to *consider* mutating.
-mutate = 0
-
-# If global mutate is true, consider mutating a dict. May or may not
-# mutate a dict even if mutate is true. If it does decide to mutate a
-# dict, it picks one of {dict1, dict2} at random, and deletes a random
-# entry from it; or, more rarely, adds a random element.
-
-def maybe_mutate():
- global mutate
- if not mutate:
- return
- if random.random() < 0.5:
- return
-
- if random.random() < 0.5:
- target, keys = dict1, dict1keys
- else:
- target, keys = dict2, dict2keys
-
- if random.random() < 0.2:
- # Insert a new key.
- mutate = 0 # disable mutation until key inserted
- while 1:
- newkey = Horrid(random.randrange(100))
- if newkey not in target:
- break
- target[newkey] = Horrid(random.randrange(100))
- keys.append(newkey)
- mutate = 1
-
- elif keys:
- # Delete a key at random.
- mutate = 0 # disable mutation until key deleted
- i = random.randrange(len(keys))
- key = keys[i]
- del target[key]
- del keys[i]
- mutate = 1
-
-# A horrid class that triggers random mutations of dict1 and dict2 when
-# instances are compared.
-
-class Horrid:
- def __init__(self, i):
- # Comparison outcomes are determined by the value of i.
- self.i = i
-
- # An artificial hashcode is selected at random so that we don't
- # have any systematic relationship between comparison outcomes
- # (based on self.i and other.i) and relative position within the
- # hash vector (based on hashcode).
- # XXX This is no longer effective.
- ##self.hashcode = random.randrange(1000000000)
-
- def __hash__(self):
- return 42
- return self.hashcode
-
- def __eq__(self, other):
- maybe_mutate() # The point of the test.
- return self.i == other.i
-
- def __ne__(self, other):
- raise RuntimeError("I didn't expect some kind of Spanish inquisition!")
-
- __lt__ = __le__ = __gt__ = __ge__ = __ne__
-
- def __repr__(self):
- return "Horrid(%d)" % self.i
-
-# Fill dict d with numentries (Horrid(i), Horrid(j)) key-value pairs,
-# where i and j are selected at random from the candidates list.
-# Return d.keys() after filling.
-
-def fill_dict(d, candidates, numentries):
- d.clear()
- for i in range(numentries):
- d[Horrid(random.choice(candidates))] = \
- Horrid(random.choice(candidates))
- return list(d.keys())
-
-# Test one pair of randomly generated dicts, each with n entries.
-# Note that dict comparison is trivial if they don't have the same number
-# of entires (then the "shorter" dict is instantly considered to be the
-# smaller one, without even looking at the entries).
-
-def test_one(n):
- global mutate, dict1, dict2, dict1keys, dict2keys
-
- # Fill the dicts without mutating them.
- mutate = 0
- dict1keys = fill_dict(dict1, range(n), n)
- dict2keys = fill_dict(dict2, range(n), n)
-
- # Enable mutation, then compare the dicts so long as they have the
- # same size.
- mutate = 1
- if verbose:
- print("trying w/ lengths", len(dict1), len(dict2), end=' ')
- while dict1 and len(dict1) == len(dict2):
- if verbose:
- print(".", end=' ')
- c = dict1 == dict2
- if verbose:
- print()
-
-# Run test_one n times. At the start (before the bugs were fixed), 20
-# consecutive runs of this test each blew up on or before the sixth time
-# test_one was run. So n doesn't have to be large to get an interesting
-# test.
-# OTOH, calling with large n is also interesting, to ensure that the fixed
-# code doesn't hold on to refcounts *too* long (in which case memory would
-# leak).
-
-def test(n):
- for i in range(n):
- test_one(random.randrange(1, 100))
-
-# See last comment block for clues about good values for n.
-test(100)
-
-##########################################################################
-# Another segfault bug, distilled by Michael Hudson from a c.l.py post.
-
-class Child:
- def __init__(self, parent):
- self.__dict__['parent'] = parent
- def __getattr__(self, attr):
- self.parent.a = 1
- self.parent.b = 1
- self.parent.c = 1
- self.parent.d = 1
- self.parent.e = 1
- self.parent.f = 1
- self.parent.g = 1
- self.parent.h = 1
- self.parent.i = 1
- return getattr(self.parent, attr)
-
-class Parent:
- def __init__(self):
- self.a = Child(self)
-
-# Hard to say what this will print! May vary from time to time. But
-# we're specifically trying to test the tp_print slot here, and this is
-# the clearest way to do it. We print the result to a temp file so that
-# the expected-output file doesn't need to change.
-
-f = open(TESTFN, "w")
-print(Parent().__dict__, file=f)
-f.close()
-os.unlink(TESTFN)
-
-##########################################################################
-# And another core-dumper from Michael Hudson.
-
-dict = {}
-
-# Force dict to malloc its table.
-for i in range(1, 10):
- dict[i] = i
-
-f = open(TESTFN, "w")
-
-class Machiavelli:
- def __repr__(self):
- dict.clear()
-
- # Michael sez: "doesn't crash without this. don't know why."
- # Tim sez: "luck of the draw; crashes with or without for me."
- print(file=f)
-
- return repr("machiavelli")
-
- def __hash__(self):
- return 0
-
-dict[Machiavelli()] = Machiavelli()
-
-print(str(dict), file=f)
-f.close()
-os.unlink(TESTFN)
-del f, dict
-
-
-##########################################################################
-# And another core-dumper from Michael Hudson.
-
-dict = {}
-
-# let's force dict to malloc its table
-for i in range(1, 10):
- dict[i] = i
-
-class Machiavelli2:
- def __eq__(self, other):
- dict.clear()
- return 1
-
- def __hash__(self):
- return 0
-
-dict[Machiavelli2()] = Machiavelli2()
-
-try:
- dict[Machiavelli2()]
-except KeyError:
- pass
-
-del dict
-
-##########################################################################
-# And another core-dumper from Michael Hudson.
-
-dict = {}
-
-# let's force dict to malloc its table
-for i in range(1, 10):
- dict[i] = i
-
-class Machiavelli3:
- def __init__(self, id):
- self.id = id
-
- def __eq__(self, other):
- if self.id == other.id:
- dict.clear()
- return 1
- else:
- return 0
-
- def __repr__(self):
- return "%s(%s)"%(self.__class__.__name__, self.id)
-
- def __hash__(self):
- return 0
-
-dict[Machiavelli3(1)] = Machiavelli3(0)
-dict[Machiavelli3(2)] = Machiavelli3(0)
-
-f = open(TESTFN, "w")
-try:
- try:
- print(dict[Machiavelli3(2)], file=f)
- except KeyError:
- pass
-finally:
- f.close()
- os.unlink(TESTFN)
-
-del dict
-del dict1, dict2, dict1keys, dict2keys
diff --git a/Lib/test/test_pickle.py b/Lib/test/test_pickle.py
index 9da2cae..f52d4bd 100644
--- a/Lib/test/test_pickle.py
+++ b/Lib/test/test_pickle.py
@@ -1,5 +1,6 @@
import pickle
import io
+import collections
from test import support
@@ -7,6 +8,7 @@
from test.pickletester import AbstractPickleModuleTests
from test.pickletester import AbstractPersistentPicklerTests
from test.pickletester import AbstractPicklerUnpicklerObjectTests
+from test.pickletester import AbstractDispatchTableTests
from test.pickletester import BigmemPickleTests
try:
@@ -80,6 +82,18 @@
unpickler_class = pickle._Unpickler
+class PyDispatchTableTests(AbstractDispatchTableTests):
+ pickler_class = pickle._Pickler
+ def get_dispatch_table(self):
+ return pickle.dispatch_table.copy()
+
+
+class PyChainDispatchTableTests(AbstractDispatchTableTests):
+ pickler_class = pickle._Pickler
+ def get_dispatch_table(self):
+ return collections.ChainMap({}, pickle.dispatch_table)
+
+
if has_c_implementation:
class CPicklerTests(PyPicklerTests):
pickler = _pickle.Pickler
@@ -101,14 +115,26 @@
pickler_class = _pickle.Pickler
unpickler_class = _pickle.Unpickler
+ class CDispatchTableTests(AbstractDispatchTableTests):
+ pickler_class = pickle.Pickler
+ def get_dispatch_table(self):
+ return pickle.dispatch_table.copy()
+
+ class CChainDispatchTableTests(AbstractDispatchTableTests):
+ pickler_class = pickle.Pickler
+ def get_dispatch_table(self):
+ return collections.ChainMap({}, pickle.dispatch_table)
+
def test_main():
- tests = [PickleTests, PyPicklerTests, PyPersPicklerTests]
+ tests = [PickleTests, PyPicklerTests, PyPersPicklerTests,
+ PyDispatchTableTests, PyChainDispatchTableTests]
if has_c_implementation:
tests.extend([CPicklerTests, CPersPicklerTests,
CDumpPickle_LoadPickle, DumpPickle_CLoadPickle,
PyPicklerUnpicklerObjectTests,
CPicklerUnpicklerObjectTests,
+ CDispatchTableTests, CChainDispatchTableTests,
InMemoryPickleTests])
support.run_unittest(*tests)
support.run_doctest(pickle)
diff --git a/Lib/test/test_pty.py b/Lib/test/test_pty.py
index 4f1251c..ef95268 100644
--- a/Lib/test/test_pty.py
+++ b/Lib/test/test_pty.py
@@ -205,6 +205,7 @@
self.orig_stdout_fileno = pty.STDOUT_FILENO
self.orig_pty_select = pty.select
self.fds = [] # A list of file descriptors to close.
+ self.files = []
self.select_rfds_lengths = []
self.select_rfds_results = []
@@ -212,10 +213,15 @@
pty.STDIN_FILENO = self.orig_stdin_fileno
pty.STDOUT_FILENO = self.orig_stdout_fileno
pty.select = self.orig_pty_select
+ for file in self.files:
+ try:
+ file.close()
+ except OSError:
+ pass
for fd in self.fds:
try:
os.close(fd)
- except:
+ except OSError:
pass
def _pipe(self):
@@ -223,6 +229,11 @@
self.fds.extend(pipe_fds)
return pipe_fds
+ def _socketpair(self):
+ socketpair = socket.socketpair()
+ self.files.extend(socketpair)
+ return socketpair
+
def _mock_select(self, rfds, wfds, xfds):
# This will raise IndexError when no more expected calls exist.
self.assertEqual(self.select_rfds_lengths.pop(0), len(rfds))
@@ -234,9 +245,8 @@
pty.STDOUT_FILENO = mock_stdout_fd
mock_stdin_fd, write_to_stdin_fd = self._pipe()
pty.STDIN_FILENO = mock_stdin_fd
- socketpair = socket.socketpair()
+ socketpair = self._socketpair()
masters = [s.fileno() for s in socketpair]
- self.fds.extend(masters)
# Feed data. Smaller than PIPEBUF. These writes will not block.
os.write(masters[1], b'from master')
@@ -263,9 +273,8 @@
pty.STDOUT_FILENO = mock_stdout_fd
mock_stdin_fd, write_to_stdin_fd = self._pipe()
pty.STDIN_FILENO = mock_stdin_fd
- socketpair = socket.socketpair()
+ socketpair = self._socketpair()
masters = [s.fileno() for s in socketpair]
- self.fds.extend(masters)
os.close(masters[1])
socketpair[1].close()
diff --git a/Lib/test/test_signal.py b/Lib/test/test_signal.py
index fdeb4c2..6be259b 100644
--- a/Lib/test/test_signal.py
+++ b/Lib/test/test_signal.py
@@ -662,7 +662,7 @@
self.wait_helper(signal.SIGALRM, '''
def test(signum):
signal.alarm(1)
- info = signal.sigtimedwait([signum], (10, 1000))
+ info = signal.sigtimedwait([signum], 10.1000)
if info.si_signo != signum:
raise Exception('info.si_signo != %s' % signum)
''')
@@ -675,7 +675,7 @@
def test(signum):
import os
os.kill(os.getpid(), signum)
- info = signal.sigtimedwait([signum], (0, 0))
+ info = signal.sigtimedwait([signum], 0)
if info.si_signo != signum:
raise Exception('info.si_signo != %s' % signum)
''')
@@ -685,7 +685,7 @@
def test_sigtimedwait_timeout(self):
self.wait_helper(signal.SIGALRM, '''
def test(signum):
- received = signal.sigtimedwait([signum], (1, 0))
+ received = signal.sigtimedwait([signum], 1.0)
if received is not None:
raise Exception("received=%r" % (received,))
''')
@@ -694,9 +694,7 @@
'need signal.sigtimedwait()')
def test_sigtimedwait_negative_timeout(self):
signum = signal.SIGALRM
- self.assertRaises(ValueError, signal.sigtimedwait, [signum], (-1, -1))
- self.assertRaises(ValueError, signal.sigtimedwait, [signum], (0, -1))
- self.assertRaises(ValueError, signal.sigtimedwait, [signum], (-1, 0))
+ self.assertRaises(ValueError, signal.sigtimedwait, [signum], -1.0)
@unittest.skipUnless(hasattr(signal, 'sigwaitinfo'),
'need signal.sigwaitinfo()')
diff --git a/Lib/test/test_time.py b/Lib/test/test_time.py
index a89c511..26492c1 100644
--- a/Lib/test/test_time.py
+++ b/Lib/test/test_time.py
@@ -497,12 +497,31 @@
pass
+class TestPytime(unittest.TestCase):
+ def test_timespec(self):
+ from _testcapi import pytime_object_to_timespec
+ for obj, timespec in (
+ (0, (0, 0)),
+ (-1, (-1, 0)),
+ (-1.0, (-1, 0)),
+ (-1e-9, (-1, 999999999)),
+ (-1.2, (-2, 800000000)),
+ (1.123456789, (1, 123456789)),
+ ):
+ self.assertEqual(pytime_object_to_timespec(obj), timespec)
+
+ for invalid in (-(2 ** 100), -(2.0 ** 100.0), 2 ** 100, 2.0 ** 100.0):
+ self.assertRaises(OverflowError, pytime_object_to_timespec, invalid)
+
+
+
def test_main():
support.run_unittest(
TimeTestCase,
TestLocale,
TestAsctime4dyear,
- TestStrftime4dyear)
+ TestStrftime4dyear,
+ TestPytime)
if __name__ == "__main__":
test_main()
diff --git a/Lib/test/test_tokenize.py b/Lib/test/test_tokenize.py
index dce3c6e..db87e11 100644
--- a/Lib/test/test_tokenize.py
+++ b/Lib/test/test_tokenize.py
@@ -563,6 +563,18 @@
NAME 'grün' (2, 0) (2, 4)
OP '=' (2, 5) (2, 6)
STRING "'green'" (2, 7) (2, 14)
+
+Legacy unicode literals:
+
+ >>> dump_tokens("Örter = u'places'\\ngrün = UR'green'")
+ ENCODING 'utf-8' (0, 0) (0, 0)
+ NAME 'Örter' (1, 0) (1, 5)
+ OP '=' (1, 6) (1, 7)
+ STRING "u'places'" (1, 8) (1, 17)
+ NEWLINE '\\n' (1, 17) (1, 18)
+ NAME 'grün' (2, 0) (2, 4)
+ OP '=' (2, 5) (2, 6)
+ STRING "UR'green'" (2, 7) (2, 16)
"""
from test import support
diff --git a/Lib/test/test_weakset.py b/Lib/test/test_weakset.py
index 35db7a6..4d3878f 100644
--- a/Lib/test/test_weakset.py
+++ b/Lib/test/test_weakset.py
@@ -28,6 +28,12 @@
# need to keep references to them
self.items = [ustr(c) for c in ('a', 'b', 'c')]
self.items2 = [ustr(c) for c in ('x', 'y', 'z')]
+ self.ab_items = [ustr(c) for c in 'ab']
+ self.abcde_items = [ustr(c) for c in 'abcde']
+ self.def_items = [ustr(c) for c in 'def']
+ self.ab_weakset = WeakSet(self.ab_items)
+ self.abcde_weakset = WeakSet(self.abcde_items)
+ self.def_weakset = WeakSet(self.def_items)
self.letters = [ustr(c) for c in string.ascii_letters]
self.s = WeakSet(self.items)
self.d = dict.fromkeys(self.items)
@@ -71,6 +77,11 @@
x = WeakSet(self.items + self.items2)
c = C(self.items2)
self.assertEqual(self.s.union(c), x)
+ del c
+ self.assertEqual(len(u), len(self.items) + len(self.items2))
+ self.items2.pop()
+ gc.collect()
+ self.assertEqual(len(u), len(self.items) + len(self.items2))
def test_or(self):
i = self.s.union(self.items2)
@@ -78,14 +89,19 @@
self.assertEqual(self.s | frozenset(self.items2), i)
def test_intersection(self):
- i = self.s.intersection(self.items2)
+ s = WeakSet(self.letters)
+ i = s.intersection(self.items2)
for c in self.letters:
- self.assertEqual(c in i, c in self.d and c in self.items2)
- self.assertEqual(self.s, WeakSet(self.items))
+ self.assertEqual(c in i, c in self.items2 and c in self.letters)
+ self.assertEqual(s, WeakSet(self.letters))
self.assertEqual(type(i), WeakSet)
for C in set, frozenset, dict.fromkeys, list, tuple:
x = WeakSet([])
- self.assertEqual(self.s.intersection(C(self.items2)), x)
+ self.assertEqual(i.intersection(C(self.items)), x)
+ self.assertEqual(len(i), len(self.items2))
+ self.items2.pop()
+ gc.collect()
+ self.assertEqual(len(i), len(self.items2))
def test_isdisjoint(self):
self.assertTrue(self.s.isdisjoint(WeakSet(self.items2)))
@@ -116,6 +132,10 @@
self.assertEqual(self.s, WeakSet(self.items))
self.assertEqual(type(i), WeakSet)
self.assertRaises(TypeError, self.s.symmetric_difference, [[]])
+ self.assertEqual(len(i), len(self.items) + len(self.items2))
+ self.items2.pop()
+ gc.collect()
+ self.assertEqual(len(i), len(self.items) + len(self.items2))
def test_xor(self):
i = self.s.symmetric_difference(self.items2)
@@ -123,22 +143,28 @@
self.assertEqual(self.s ^ frozenset(self.items2), i)
def test_sub_and_super(self):
- pl, ql, rl = map(lambda s: [ustr(c) for c in s], ['ab', 'abcde', 'def'])
- p, q, r = map(WeakSet, (pl, ql, rl))
- self.assertTrue(p < q)
- self.assertTrue(p <= q)
- self.assertTrue(q <= q)
- self.assertTrue(q > p)
- self.assertTrue(q >= p)
- self.assertFalse(q < r)
- self.assertFalse(q <= r)
- self.assertFalse(q > r)
- self.assertFalse(q >= r)
+ self.assertTrue(self.ab_weakset <= self.abcde_weakset)
+ self.assertTrue(self.abcde_weakset <= self.abcde_weakset)
+ self.assertTrue(self.abcde_weakset >= self.ab_weakset)
+ self.assertFalse(self.abcde_weakset <= self.def_weakset)
+ self.assertFalse(self.abcde_weakset >= self.def_weakset)
self.assertTrue(set('a').issubset('abc'))
self.assertTrue(set('abc').issuperset('a'))
self.assertFalse(set('a').issubset('cbs'))
self.assertFalse(set('cbs').issuperset('a'))
+ def test_lt(self):
+ self.assertTrue(self.ab_weakset < self.abcde_weakset)
+ self.assertFalse(self.abcde_weakset < self.def_weakset)
+ self.assertFalse(self.ab_weakset < self.ab_weakset)
+ self.assertFalse(WeakSet() < WeakSet())
+
+ def test_gt(self):
+ self.assertTrue(self.abcde_weakset > self.ab_weakset)
+ self.assertFalse(self.abcde_weakset > self.def_weakset)
+ self.assertFalse(self.ab_weakset > self.ab_weakset)
+ self.assertFalse(WeakSet() > WeakSet())
+
def test_gc(self):
# Create a nest of cycles to exercise overall ref count check
s = WeakSet(Foo() for i in range(1000))
diff --git a/Lib/test/test_xml_etree.py b/Lib/test/test_xml_etree.py
index 58fdcd4..b9230b7 100644
--- a/Lib/test/test_xml_etree.py
+++ b/Lib/test/test_xml_etree.py
@@ -1855,6 +1855,102 @@
# --------------------------------------------------------------------
+class ElementTreeTest(unittest.TestCase):
+
+ def test_istype(self):
+ self.assertIsInstance(ET.ParseError, type)
+ self.assertIsInstance(ET.QName, type)
+ self.assertIsInstance(ET.ElementTree, type)
+ self.assertIsInstance(ET.Element, type)
+ # XXX issue 14128 with C ElementTree
+ # self.assertIsInstance(ET.TreeBuilder, type)
+ # self.assertIsInstance(ET.XMLParser, type)
+
+ def test_Element_subclass_trivial(self):
+ class MyElement(ET.Element):
+ pass
+
+ mye = MyElement('foo')
+ self.assertIsInstance(mye, ET.Element)
+ self.assertIsInstance(mye, MyElement)
+ self.assertEqual(mye.tag, 'foo')
+
+ def test_Element_subclass_constructor(self):
+ class MyElement(ET.Element):
+ def __init__(self, tag, attrib={}, **extra):
+ super(MyElement, self).__init__(tag + '__', attrib, **extra)
+
+ mye = MyElement('foo', {'a': 1, 'b': 2}, c=3, d=4)
+ self.assertEqual(mye.tag, 'foo__')
+ self.assertEqual(sorted(mye.items()),
+ [('a', 1), ('b', 2), ('c', 3), ('d', 4)])
+
+ def test_Element_subclass_new_method(self):
+ class MyElement(ET.Element):
+ def newmethod(self):
+ return self.tag
+
+ mye = MyElement('joe')
+ self.assertEqual(mye.newmethod(), 'joe')
+
+
+class TreeBuilderTest(unittest.TestCase):
+
+ sample1 = ('<!DOCTYPE html PUBLIC'
+ ' "-//W3C//DTD XHTML 1.0 Transitional//EN"'
+ ' "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">'
+ '<html>text</html>')
+
+ def test_dummy_builder(self):
+ class BaseDummyBuilder:
+ def close(self):
+ return 42
+
+ class DummyBuilder(BaseDummyBuilder):
+ data = start = end = lambda *a: None
+
+ parser = ET.XMLParser(target=DummyBuilder())
+ parser.feed(self.sample1)
+ self.assertEqual(parser.close(), 42)
+
+ parser = ET.XMLParser(target=BaseDummyBuilder())
+ parser.feed(self.sample1)
+ self.assertEqual(parser.close(), 42)
+
+ parser = ET.XMLParser(target=object())
+ parser.feed(self.sample1)
+ self.assertIsNone(parser.close())
+
+
+ @unittest.expectedFailure # XXX issue 14007 with C ElementTree
+ def test_doctype(self):
+ class DoctypeParser:
+ _doctype = None
+
+ def doctype(self, name, pubid, system):
+ self._doctype = (name, pubid, system)
+
+ def close(self):
+ return self._doctype
+
+ parser = ET.XMLParser(target=DoctypeParser())
+ parser.feed(self.sample1)
+
+ self.assertEqual(parser.close(),
+ ('html', '-//W3C//DTD XHTML 1.0 Transitional//EN',
+ 'http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd'))
+
+
+class NoAcceleratorTest(unittest.TestCase):
+
+ # Test that the C accelerator was not imported for pyET
+ def test_correct_import_pyET(self):
+ self.assertEqual(pyET.Element.__module__, 'xml.etree.ElementTree')
+ self.assertEqual(pyET.SubElement.__module__, 'xml.etree.ElementTree')
+
+# --------------------------------------------------------------------
+
+
class CleanContext(object):
"""Provide default namespace mapping and path cache."""
checkwarnings = None
@@ -1873,10 +1969,7 @@
("This method will be removed in future versions. "
"Use .+ instead.", DeprecationWarning),
("This method will be removed in future versions. "
- "Use .+ instead.", PendingDeprecationWarning),
- # XMLParser.doctype() is deprecated.
- ("This method of XMLParser is deprecated. Define doctype.. "
- "method on the TreeBuilder target.", DeprecationWarning))
+ "Use .+ instead.", PendingDeprecationWarning))
self.checkwarnings = support.check_warnings(*deprecations, quiet=quiet)
def __enter__(self):
@@ -1898,19 +1991,18 @@
self.checkwarnings.__exit__(*args)
-class TestAcceleratorNotImported(unittest.TestCase):
- # Test that the C accelerator was not imported for pyET
- def test_correct_import_pyET(self):
- self.assertEqual(pyET.Element.__module__, 'xml.etree.ElementTree')
-
-
def test_main(module=pyET):
from test import test_xml_etree
# The same doctests are used for both the Python and the C implementations
test_xml_etree.ET = module
- support.run_unittest(TestAcceleratorNotImported)
+ test_classes = [ElementTreeTest, TreeBuilderTest]
+ if module is pyET:
+ # Run the tests specific to the Python implementation
+ test_classes += [NoAcceleratorTest]
+
+ support.run_unittest(*test_classes)
# XXX the C module should give the same warnings as the Python module
with CleanContext(quiet=(module is not pyET)):
diff --git a/Lib/test/test_xml_etree_c.py b/Lib/test/test_xml_etree_c.py
index a73d0c4..10416d2 100644
--- a/Lib/test/test_xml_etree_c.py
+++ b/Lib/test/test_xml_etree_c.py
@@ -47,13 +47,20 @@
data = None
@unittest.skipUnless(cET, 'requires _elementtree')
+class TestAliasWorking(unittest.TestCase):
+ # Test that the cET alias module is alive
+ def test_alias_working(self):
+ e = cET_alias.Element('foo')
+ self.assertEqual(e.tag, 'foo')
+
+@unittest.skipUnless(cET, 'requires _elementtree')
class TestAcceleratorImported(unittest.TestCase):
# Test that the C accelerator was imported, as expected
def test_correct_import_cET(self):
- self.assertEqual(cET.Element.__module__, '_elementtree')
+ self.assertEqual(cET.SubElement.__module__, '_elementtree')
def test_correct_import_cET_alias(self):
- self.assertEqual(cET_alias.Element.__module__, '_elementtree')
+ self.assertEqual(cET_alias.SubElement.__module__, '_elementtree')
def test_main():
@@ -61,13 +68,15 @@
# Run the tests specific to the C implementation
support.run_doctest(test_xml_etree_c, verbosity=True)
-
- support.run_unittest(MiscTests, TestAcceleratorImported)
+ support.run_unittest(
+ MiscTests,
+ TestAliasWorking,
+ TestAcceleratorImported
+ )
# Run the same test suite as the Python module
test_xml_etree.test_main(module=cET)
- # Exercise the deprecated alias
- test_xml_etree.test_main(module=cET_alias)
+
if __name__ == '__main__':
test_main()
diff --git a/Lib/threading.py b/Lib/threading.py
index 2a0d8ad..441c7bd 100644
--- a/Lib/threading.py
+++ b/Lib/threading.py
@@ -34,40 +34,6 @@
del _thread
-# Debug support (adapted from ihooks.py).
-
-_VERBOSE = False
-
-if __debug__:
-
- class _Verbose(object):
-
- def __init__(self, verbose=None):
- if verbose is None:
- verbose = _VERBOSE
- self._verbose = verbose
-
- def _note(self, format, *args):
- if self._verbose:
- format = format % args
- # Issue #4188: calling current_thread() can incur an infinite
- # recursion if it has to create a DummyThread on the fly.
- ident = get_ident()
- try:
- name = _active[ident].name
- except KeyError:
- name = "<OS thread %d>" % ident
- format = "%s: %s\n" % (name, format)
- _sys.stderr.write(format)
-
-else:
- # Disable this when using "python -O"
- class _Verbose(object):
- def __init__(self, verbose=None):
- pass
- def _note(self, *args):
- pass
-
# Support for profile and trace hooks
_profile_hook = None
@@ -85,17 +51,14 @@
Lock = _allocate_lock
-def RLock(verbose=None, *args, **kwargs):
- if verbose is None:
- verbose = _VERBOSE
- if (__debug__ and verbose) or _CRLock is None:
- return _PyRLock(verbose, *args, **kwargs)
+def RLock(*args, **kwargs):
+ if _CRLock is None:
+ return _PyRLock(*args, **kwargs)
return _CRLock(*args, **kwargs)
-class _RLock(_Verbose):
+class _RLock:
- def __init__(self, verbose=None):
- _Verbose.__init__(self, verbose)
+ def __init__(self):
self._block = _allocate_lock()
self._owner = None
self._count = 0
@@ -113,18 +76,11 @@
me = get_ident()
if self._owner == me:
self._count = self._count + 1
- if __debug__:
- self._note("%s.acquire(%s): recursive success", self, blocking)
return 1
rc = self._block.acquire(blocking, timeout)
if rc:
self._owner = me
self._count = 1
- if __debug__:
- self._note("%s.acquire(%s): initial success", self, blocking)
- else:
- if __debug__:
- self._note("%s.acquire(%s): failure", self, blocking)
return rc
__enter__ = acquire
@@ -136,11 +92,6 @@
if not count:
self._owner = None
self._block.release()
- if __debug__:
- self._note("%s.release(): final release", self)
- else:
- if __debug__:
- self._note("%s.release(): non-final release", self)
def __exit__(self, t, v, tb):
self.release()
@@ -150,12 +101,8 @@
def _acquire_restore(self, state):
self._block.acquire()
self._count, self._owner = state
- if __debug__:
- self._note("%s._acquire_restore()", self)
def _release_save(self):
- if __debug__:
- self._note("%s._release_save()", self)
if self._count == 0:
raise RuntimeError("cannot release un-acquired lock")
count = self._count
@@ -171,10 +118,9 @@
_PyRLock = _RLock
-class Condition(_Verbose):
+class Condition:
- def __init__(self, lock=None, verbose=None):
- _Verbose.__init__(self, verbose)
+ def __init__(self, lock=None):
if lock is None:
lock = RLock()
self._lock = lock
@@ -233,23 +179,16 @@
if timeout is None:
waiter.acquire()
gotit = True
- if __debug__:
- self._note("%s.wait(): got it", self)
else:
if timeout > 0:
gotit = waiter.acquire(True, timeout)
else:
gotit = waiter.acquire(False)
if not gotit:
- if __debug__:
- self._note("%s.wait(%s): timed out", self, timeout)
try:
self._waiters.remove(waiter)
except ValueError:
pass
- else:
- if __debug__:
- self._note("%s.wait(%s): got it", self, timeout)
return gotit
finally:
self._acquire_restore(saved_state)
@@ -265,19 +204,9 @@
else:
waittime = endtime - _time()
if waittime <= 0:
- if __debug__:
- self._note("%s.wait_for(%r, %r): Timed out.",
- self, predicate, timeout)
break
- if __debug__:
- self._note("%s.wait_for(%r, %r): Waiting with timeout=%s.",
- self, predicate, timeout, waittime)
self.wait(waittime)
result = predicate()
- else:
- if __debug__:
- self._note("%s.wait_for(%r, %r): Success.",
- self, predicate, timeout)
return result
def notify(self, n=1):
@@ -286,11 +215,7 @@
__waiters = self._waiters
waiters = __waiters[:n]
if not waiters:
- if __debug__:
- self._note("%s.notify(): no waiters", self)
return
- self._note("%s.notify(): notifying %d waiter%s", self, n,
- n!=1 and "s" or "")
for waiter in waiters:
waiter.release()
try:
@@ -304,14 +229,13 @@
notifyAll = notify_all
-class Semaphore(_Verbose):
+class Semaphore:
# After Tim Peters' semaphore class, but not quite the same (no maximum)
- def __init__(self, value=1, verbose=None):
+ def __init__(self, value=1):
if value < 0:
raise ValueError("semaphore initial value must be >= 0")
- _Verbose.__init__(self, verbose)
self._cond = Condition(Lock())
self._value = value
@@ -324,9 +248,6 @@
while self._value == 0:
if not blocking:
break
- if __debug__:
- self._note("%s.acquire(%s): blocked waiting, value=%s",
- self, blocking, self._value)
if timeout is not None:
if endtime is None:
endtime = _time() + timeout
@@ -337,9 +258,6 @@
self._cond.wait(timeout)
else:
self._value = self._value - 1
- if __debug__:
- self._note("%s.acquire: success, value=%s",
- self, self._value)
rc = True
self._cond.release()
return rc
@@ -349,9 +267,6 @@
def release(self):
self._cond.acquire()
self._value = self._value + 1
- if __debug__:
- self._note("%s.release: success, value=%s",
- self, self._value)
self._cond.notify()
self._cond.release()
@@ -361,8 +276,8 @@
class BoundedSemaphore(Semaphore):
"""Semaphore that checks that # releases is <= # acquires"""
- def __init__(self, value=1, verbose=None):
- Semaphore.__init__(self, value, verbose)
+ def __init__(self, value=1):
+ Semaphore.__init__(self, value)
self._initial_value = value
def release(self):
@@ -371,12 +286,11 @@
return Semaphore.release(self)
-class Event(_Verbose):
+class Event:
# After Tim Peters' event class (without is_posted())
- def __init__(self, verbose=None):
- _Verbose.__init__(self, verbose)
+ def __init__(self):
self._cond = Condition(Lock())
self._flag = False
@@ -426,13 +340,13 @@
# since the previous cycle. In addition, a 'resetting' state exists which is
# similar to 'draining' except that threads leave with a BrokenBarrierError,
# and a 'broken' state in which all threads get the exception.
-class Barrier(_Verbose):
+class Barrier:
"""
Barrier. Useful for synchronizing a fixed number of threads
at known synchronization points. Threads block on 'wait()' and are
simultaneously once they have all made that call.
"""
- def __init__(self, parties, action=None, timeout=None, verbose=None):
+ def __init__(self, parties, action=None, timeout=None):
"""
Create a barrier, initialised to 'parties' threads.
'action' is a callable which, when supplied, will be called
@@ -441,7 +355,6 @@
If a 'timeout' is provided, it is uses as the default for
all subsequent 'wait()' calls.
"""
- _Verbose.__init__(self, verbose)
self._cond = Condition(Lock())
self._action = action
self._timeout = timeout
@@ -602,7 +515,7 @@
# Main class for threads
-class Thread(_Verbose):
+class Thread:
__initialized = False
# Need to store a reference to sys.exc_info for printing
@@ -615,9 +528,8 @@
#XXX __exc_clear = _sys.exc_clear
def __init__(self, group=None, target=None, name=None,
- args=(), kwargs=None, verbose=None, *, daemon=None):
+ args=(), kwargs=None, *, daemon=None):
assert group is None, "group argument must be None for now"
- _Verbose.__init__(self, verbose)
if kwargs is None:
kwargs = {}
self._target = target
@@ -664,8 +576,6 @@
if self._started.is_set():
raise RuntimeError("threads can only be started once")
- if __debug__:
- self._note("%s.start(): starting thread", self)
with _active_limbo_lock:
_limbo[self] = self
try:
@@ -715,24 +625,17 @@
with _active_limbo_lock:
_active[self._ident] = self
del _limbo[self]
- if __debug__:
- self._note("%s._bootstrap(): thread started", self)
if _trace_hook:
- self._note("%s._bootstrap(): registering trace hook", self)
_sys.settrace(_trace_hook)
if _profile_hook:
- self._note("%s._bootstrap(): registering profile hook", self)
_sys.setprofile(_profile_hook)
try:
self.run()
except SystemExit:
- if __debug__:
- self._note("%s._bootstrap(): raised SystemExit", self)
+ pass
except:
- if __debug__:
- self._note("%s._bootstrap(): unhandled exception", self)
# If sys.stderr is no more (most likely from interpreter
# shutdown) use self._stderr. Otherwise still use sys (as in
# _sys) in case sys.stderr was redefined since the creation of
@@ -763,9 +666,6 @@
# hog; deleting everything else is just for thoroughness
finally:
del exc_type, exc_value, exc_tb
- else:
- if __debug__:
- self._note("%s._bootstrap(): normal return", self)
finally:
# Prevent a race in
# test_threading.test_no_refcycle_through_target when
@@ -832,29 +732,18 @@
if self is current_thread():
raise RuntimeError("cannot join current thread")
- if __debug__:
- if not self._stopped:
- self._note("%s.join(): waiting until thread stops", self)
-
self._block.acquire()
try:
if timeout is None:
while not self._stopped:
self._block.wait()
- if __debug__:
- self._note("%s.join(): thread stopped", self)
else:
deadline = _time() + timeout
while not self._stopped:
delay = deadline - _time()
if delay <= 0:
- if __debug__:
- self._note("%s.join(): timed out", self)
break
self._block.wait(delay)
- else:
- if __debug__:
- self._note("%s.join(): thread stopped", self)
finally:
self._block.release()
@@ -947,14 +836,9 @@
def _exitfunc(self):
self._stop()
t = _pickSomeNonDaemonThread()
- if t:
- if __debug__:
- self._note("%s: waiting for other threads", self)
while t:
t.join()
t = _pickSomeNonDaemonThread()
- if __debug__:
- self._note("%s: exiting", self)
self._delete()
def _pickSomeNonDaemonThread():
diff --git a/Lib/tokenize.py b/Lib/tokenize.py
index 4c42bbc..741417a 100644
--- a/Lib/tokenize.py
+++ b/Lib/tokenize.py
@@ -127,6 +127,8 @@
Imagnumber = group(r'[0-9]+[jJ]', Floatnumber + r'[jJ]')
Number = group(Imagnumber, Floatnumber, Intnumber)
+StringPrefix = r'(?:[uU][rR]?|[bB][rR]|[rR][bB]|[rR]|[uU])?'
+
# Tail end of ' string.
Single = r"[^'\\]*(?:\\.[^'\\]*)*'"
# Tail end of " string.
@@ -135,10 +137,10 @@
Single3 = r"[^'\\]*(?:(?:\\.|'(?!''))[^'\\]*)*'''"
# Tail end of """ string.
Double3 = r'[^"\\]*(?:(?:\\.|"(?!""))[^"\\]*)*"""'
-Triple = group("[bB]?[rR]?'''", '[bB]?[rR]?"""')
+Triple = group(StringPrefix + "'''", StringPrefix + '"""')
# Single-line ' or " string.
-String = group(r"[bB]?[rR]?'[^\n'\\]*(?:\\.[^\n'\\]*)*'",
- r'[bB]?[rR]?"[^\n"\\]*(?:\\.[^\n"\\]*)*"')
+String = group(StringPrefix + r"'[^\n'\\]*(?:\\.[^\n'\\]*)*'",
+ StringPrefix + r'"[^\n"\\]*(?:\\.[^\n"\\]*)*"')
# Because of leftmost-then-longest match semantics, be sure to put the
# longest operators first (e.g., if = came before ==, == would get
@@ -156,9 +158,9 @@
Token = Ignore + PlainToken
# First (or only) line of ' or " string.
-ContStr = group(r"[bB]?[rR]?'[^\n'\\]*(?:\\.[^\n'\\]*)*" +
+ContStr = group(StringPrefix + r"'[^\n'\\]*(?:\\.[^\n'\\]*)*" +
group("'", r'\\\r?\n'),
- r'[bB]?[rR]?"[^\n"\\]*(?:\\.[^\n"\\]*)*' +
+ StringPrefix + r'"[^\n"\\]*(?:\\.[^\n"\\]*)*' +
group('"', r'\\\r?\n'))
PseudoExtras = group(r'\\\r?\n', Comment, Triple)
PseudoToken = Whitespace + group(PseudoExtras, Number, Funny, ContStr, Name)
@@ -170,27 +172,49 @@
"'''": Single3, '"""': Double3,
"r'''": Single3, 'r"""': Double3,
"b'''": Single3, 'b"""': Double3,
- "br'''": Single3, 'br"""': Double3,
"R'''": Single3, 'R"""': Double3,
"B'''": Single3, 'B"""': Double3,
+ "br'''": Single3, 'br"""': Double3,
"bR'''": Single3, 'bR"""': Double3,
"Br'''": Single3, 'Br"""': Double3,
"BR'''": Single3, 'BR"""': Double3,
- 'r': None, 'R': None, 'b': None, 'B': None}
+ "rb'''": Single3, 'rb"""': Double3,
+ "Rb'''": Single3, 'Rb"""': Double3,
+ "rB'''": Single3, 'rB"""': Double3,
+ "RB'''": Single3, 'RB"""': Double3,
+ "u'''": Single3, 'u"""': Double3,
+ "ur'''": Single3, 'ur"""': Double3,
+ "R'''": Single3, 'R"""': Double3,
+ "U'''": Single3, 'U"""': Double3,
+ "uR'''": Single3, 'uR"""': Double3,
+ "Ur'''": Single3, 'Ur"""': Double3,
+ "UR'''": Single3, 'UR"""': Double3,
+ 'r': None, 'R': None, 'b': None, 'B': None,
+ 'u': None, 'U': None}
triple_quoted = {}
for t in ("'''", '"""',
"r'''", 'r"""', "R'''", 'R"""',
"b'''", 'b"""', "B'''", 'B"""',
"br'''", 'br"""', "Br'''", 'Br"""',
- "bR'''", 'bR"""', "BR'''", 'BR"""'):
+ "bR'''", 'bR"""', "BR'''", 'BR"""',
+ "rb'''", 'rb"""', "rB'''", 'rB"""',
+ "Rb'''", 'Rb"""', "RB'''", 'RB"""',
+ "u'''", 'u"""', "U'''", 'U"""',
+ "ur'''", 'ur"""', "Ur'''", 'Ur"""',
+ "uR'''", 'uR"""', "UR'''", 'UR"""'):
triple_quoted[t] = t
single_quoted = {}
for t in ("'", '"',
"r'", 'r"', "R'", 'R"',
"b'", 'b"', "B'", 'B"',
"br'", 'br"', "Br'", 'Br"',
- "bR'", 'bR"', "BR'", 'BR"' ):
+ "bR'", 'bR"', "BR'", 'BR"' ,
+ "rb'", 'rb"', "rB'", 'rB"',
+ "Rb'", 'Rb"', "RB'", 'RB"' ,
+ "u'", 'u"', "U'", 'U"',
+ "ur'", 'ur"', "Ur'", 'Ur"',
+ "uR'", 'uR"', "UR'", 'UR"' ):
single_quoted[t] = t
tabsize = 8
diff --git a/Lib/xml/dom/__init__.py b/Lib/xml/dom/__init__.py
index 4401bdf..97cf9a6 100644
--- a/Lib/xml/dom/__init__.py
+++ b/Lib/xml/dom/__init__.py
@@ -17,6 +17,7 @@
class Node:
"""Class giving the NodeType constants."""
+ __slots__ = ()
# DOM implementations may use this as a base class for their own
# Node implementations. If they don't, the constants defined here
diff --git a/Lib/xml/dom/domreg.py b/Lib/xml/dom/domreg.py
index cb35bb0..8c3d901 100644
--- a/Lib/xml/dom/domreg.py
+++ b/Lib/xml/dom/domreg.py
@@ -2,8 +2,6 @@
directly. Instead, the functions getDOMImplementation and
registerDOMImplementation should be imported from xml.dom."""
-from xml.dom.minicompat import * # isinstance, StringTypes
-
# This is a list of well-known implementations. Well-known names
# should be published by posting to xml-sig@python.org, and are
# subsequently recorded in this file.
diff --git a/Lib/xml/dom/expatbuilder.py b/Lib/xml/dom/expatbuilder.py
index ff9c1f1..f074ab9 100644
--- a/Lib/xml/dom/expatbuilder.py
+++ b/Lib/xml/dom/expatbuilder.py
@@ -33,8 +33,6 @@
from xml.dom.minidom import _append_child, _set_attribute_node
from xml.dom.NodeFilter import NodeFilter
-from xml.dom.minicompat import *
-
TEXT_NODE = Node.TEXT_NODE
CDATA_SECTION_NODE = Node.CDATA_SECTION_NODE
DOCUMENT_NODE = Node.DOCUMENT_NODE
@@ -755,7 +753,7 @@
a = minidom.Attr("xmlns", XMLNS_NAMESPACE,
"xmlns", EMPTY_PREFIX)
a.value = uri
- a.ownerDocuemnt = self.document
+ a.ownerDocument = self.document
_set_attribute_node(node, a)
del self._ns_ordered_prefixes[:]
diff --git a/Lib/xml/dom/minidom.py b/Lib/xml/dom/minidom.py
index 7e2f88e..275e20c 100644
--- a/Lib/xml/dom/minidom.py
+++ b/Lib/xml/dom/minidom.py
@@ -62,10 +62,7 @@
return writer.stream.getvalue()
def hasChildNodes(self):
- if self.childNodes:
- return True
- else:
- return False
+ return bool(self.childNodes)
def _get_childNodes(self):
return self.childNodes
@@ -723,12 +720,16 @@
Node.unlink(self)
def getAttribute(self, attname):
+ if self._attrs is None:
+ return ""
try:
return self._attrs[attname].value
except KeyError:
return ""
def getAttributeNS(self, namespaceURI, localName):
+ if self._attrsNS is None:
+ return ""
try:
return self._attrsNS[(namespaceURI, localName)].value
except KeyError:
@@ -926,6 +927,7 @@
"""Mixin that makes childless-ness easy to implement and avoids
the complexity of the Node methods that deal with children.
"""
+ __slots__ = ()
attributes = None
childNodes = EmptyNodeList()
@@ -1063,6 +1065,8 @@
class Text(CharacterData):
+ __slots__ = ()
+
nodeType = Node.TEXT_NODE
nodeName = "#text"
attributes = None
@@ -1184,6 +1188,8 @@
class CDATASection(Text):
+ __slots__ = ()
+
nodeType = Node.CDATA_SECTION_NODE
nodeName = "#cdata-section"
@@ -1262,8 +1268,7 @@
class Identified:
"""Mix-in class that supports the publicId and systemId attributes."""
- # XXX this does not work, this is an old-style class
- # __slots__ = 'publicId', 'systemId'
+ __slots__ = 'publicId', 'systemId'
def _identified_mixin_init(self, publicId, systemId):
self.publicId = publicId
diff --git a/Lib/xml/etree/ElementTree.py b/Lib/xml/etree/ElementTree.py
index defef0d..10ee896 100644
--- a/Lib/xml/etree/ElementTree.py
+++ b/Lib/xml/etree/ElementTree.py
@@ -101,7 +101,6 @@
import re
import warnings
-
class _SimpleElementPath:
# emulate pre-1.2 find/findtext/findall behaviour
def find(self, element, tag, namespaces=None):
@@ -1512,24 +1511,30 @@
self.target = self._target = target
self._error = expat.error
self._names = {} # name memo cache
- # callbacks
+ # main callbacks
parser.DefaultHandlerExpand = self._default
- parser.StartElementHandler = self._start
- parser.EndElementHandler = self._end
- parser.CharacterDataHandler = self._data
- # optional callbacks
- parser.CommentHandler = self._comment
- parser.ProcessingInstructionHandler = self._pi
+ if hasattr(target, 'start'):
+ parser.StartElementHandler = self._start
+ if hasattr(target, 'end'):
+ parser.EndElementHandler = self._end
+ if hasattr(target, 'data'):
+ parser.CharacterDataHandler = target.data
+ # miscellaneous callbacks
+ if hasattr(target, 'comment'):
+ parser.CommentHandler = target.comment
+ if hasattr(target, 'pi'):
+ parser.ProcessingInstructionHandler = target.pi
# let expat do the buffering, if supported
try:
- self._parser.buffer_text = 1
+ parser.buffer_text = 1
except AttributeError:
pass
# use new-style attribute handling, if supported
try:
- self._parser.ordered_attributes = 1
- self._parser.specified_attributes = 1
- parser.StartElementHandler = self._start_list
+ parser.ordered_attributes = 1
+ parser.specified_attributes = 1
+ if hasattr(target, 'start'):
+ parser.StartElementHandler = self._start_list
except AttributeError:
pass
self._doctype = None
@@ -1573,44 +1578,29 @@
attrib[fixname(attrib_in[i])] = attrib_in[i+1]
return self.target.start(tag, attrib)
- def _data(self, text):
- return self.target.data(text)
-
def _end(self, tag):
return self.target.end(self._fixname(tag))
- def _comment(self, data):
- try:
- comment = self.target.comment
- except AttributeError:
- pass
- else:
- return comment(data)
-
- def _pi(self, target, data):
- try:
- pi = self.target.pi
- except AttributeError:
- pass
- else:
- return pi(target, data)
-
def _default(self, text):
prefix = text[:1]
if prefix == "&":
# deal with undefined entities
try:
- self.target.data(self.entity[text[1:-1]])
+ data_handler = self.target.data
+ except AttributeError:
+ return
+ try:
+ data_handler(self.entity[text[1:-1]])
except KeyError:
from xml.parsers import expat
err = expat.error(
"undefined entity %s: line %d, column %d" %
- (text, self._parser.ErrorLineNumber,
- self._parser.ErrorColumnNumber)
+ (text, self.parser.ErrorLineNumber,
+ self.parser.ErrorColumnNumber)
)
err.code = 11 # XML_ERROR_UNDEFINED_ENTITY
- err.lineno = self._parser.ErrorLineNumber
- err.offset = self._parser.ErrorColumnNumber
+ err.lineno = self.parser.ErrorLineNumber
+ err.offset = self.parser.ErrorColumnNumber
raise err
elif prefix == "<" and text[:9] == "<!DOCTYPE":
self._doctype = [] # inside a doctype declaration
@@ -1637,7 +1627,7 @@
pubid = pubid[1:-1]
if hasattr(self.target, "doctype"):
self.target.doctype(name, pubid, system[1:-1])
- elif self.doctype is not self._XMLParser__doctype:
+ elif self.doctype != self._XMLParser__doctype:
# warn about deprecated call
self._XMLParser__doctype(name, pubid, system[1:-1])
self.doctype(name, pubid, system[1:-1])
@@ -1668,7 +1658,7 @@
def feed(self, data):
try:
- self._parser.Parse(data, 0)
+ self.parser.Parse(data, 0)
except self._error as v:
self._raiseerror(v)
@@ -1680,12 +1670,19 @@
def close(self):
try:
- self._parser.Parse("", 1) # end of data
+ self.parser.Parse("", 1) # end of data
except self._error as v:
self._raiseerror(v)
- tree = self.target.close()
- del self.target, self._parser # get rid of circular references
- return tree
+ try:
+ close_handler = self.target.close
+ except AttributeError:
+ pass
+ else:
+ return close_handler()
+ finally:
+ # get rid of circular references
+ del self.parser, self._parser
+ del self.target, self._target
# Import the C accelerators
diff --git a/Lib/xmlrpc/server.py b/Lib/xmlrpc/server.py
index fc3fa4b..54e1726 100644
--- a/Lib/xmlrpc/server.py
+++ b/Lib/xmlrpc/server.py
@@ -1,4 +1,4 @@
-"""XML-RPC Servers.
+r"""XML-RPC Servers.
This module can be used to create simple XML-RPC servers
by creating a server and either installing functions, a
diff --git a/Misc/ACKS b/Misc/ACKS
index 57b6110..17ea919 100644
--- a/Misc/ACKS
+++ b/Misc/ACKS
@@ -371,6 +371,7 @@
Michael Goderbauer
Christoph Gohlke
Tim Golden
+Guilherme Gonçalves
Tiago Gonçalves
Chris Gonnerman
David Goodger
diff --git a/Misc/NEWS b/Misc/NEWS
index 6258bc4..2cf22cb 100644
--- a/Misc/NEWS
+++ b/Misc/NEWS
@@ -2,14 +2,46 @@
Python News
+++++++++++
-What's New in Python 3.3 Alpha 1?
-=================================
+What's New in Python 3.3.0 Alpha 2?
+===================================
-*Release date: XX-XXX-20XX*
+*Release date: XXXX-XX-XX*
Core and Builtins
-----------------
+- Issue #14205: dict lookup raises a RuntimeError if the dict is modified
+ during a lookup.
+
+Library
+-------
+
+- Issue #14168: Check for presence of Element._attrs in minidom before
+ accessing it.
+
+- Issue #12328: Fix multiprocessing's use of overlapped I/O on Windows.
+ Also, add a multiprocessing.connection.wait(rlist, timeout=None) function
+ for polling multiple objects at once. Patch by sbt.
+
+- Issue #13719: Make the distutils and packaging upload commands aware of
+ bdist_msi products.
+
+- Issue #14007: Accept incomplete TreeBuilder objects (missing start, end,
+ data or close method) for the Python implementation as well.
+ Drop the no-op TreeBuilder().xml() method from the C implementation.
+
+
+What's New in Python 3.3.0 Alpha 1?
+===================================
+
+*Release date: 05-Mar-2012*
+
+Core and Builtins
+-----------------
+
+- Issue #14172: Fix reference leak when marshalling a buffer-like object
+ (other than a bytes object).
+
- Issue #13521: dict.setdefault() now does only one lookup for the given key,
making it "atomic" for many purposes. Patch by Filip Gruszczyński.
@@ -508,6 +540,20 @@
Library
-------
+- Issue #14195: An issue that caused weakref.WeakSet instances to incorrectly
+ return True for a WeakSet instance 'a' in both 'a < a' and 'a > a' has been
+ fixed.
+
+- Issue #14166: Pickler objects now have an optional ``dispatch_table``
+ attribute which allows to set custom per-pickler reduction functions.
+ Patch by sbt.
+
+- Issue #14177: marshal.loads() now raises TypeError when given an unicode
+ string. Patch by Guilherme Gonçalves.
+
+- Issue #13550: Remove the debug machinery from the threading module: remove
+ verbose arguments from all threading classes and functions.
+
- Issue #14159: Fix the len() of weak containers (WeakSet, WeakKeyDictionary,
WeakValueDictionary) to return a better approximation when some objects
are dead or dying. Moreover, the implementation is now O(1) rather than
diff --git a/Misc/RPM/python-3.3.spec b/Misc/RPM/python-3.3.spec
index 4882fbb..70ae7fe 100644
--- a/Misc/RPM/python-3.3.spec
+++ b/Misc/RPM/python-3.3.spec
@@ -39,7 +39,7 @@
%define name python
#--start constants--
-%define version 3.3a0
+%define version 3.3.0a1
%define libvers 3.3
#--end constants--
%define release 1pydotorg
diff --git a/Misc/valgrind-python.supp b/Misc/valgrind-python.supp
index 20dbf1e..95e1b9e 100644
--- a/Misc/valgrind-python.supp
+++ b/Misc/valgrind-python.supp
@@ -310,6 +310,38 @@
### fun:MD5_Update
###}
+# Fedora's package "openssl-1.0.1-0.1.beta2.fc17.x86_64" on x86_64
+# See http://bugs.python.org/issue14171
+{
+ openssl 1.0.1 prng 1
+ Memcheck:Cond
+ fun:bcmp
+ fun:fips_get_entropy
+ fun:FIPS_drbg_instantiate
+ fun:RAND_init_fips
+ fun:OPENSSL_init_library
+ fun:SSL_library_init
+ fun:init_hashlib
+}
+
+{
+ openssl 1.0.1 prng 2
+ Memcheck:Cond
+ fun:fips_get_entropy
+ fun:FIPS_drbg_instantiate
+ fun:RAND_init_fips
+ fun:OPENSSL_init_library
+ fun:SSL_library_init
+ fun:init_hashlib
+}
+
+{
+ openssl 1.0.1 prng 3
+ Memcheck:Value8
+ fun:_x86_64_AES_encrypt_compact
+ fun:AES_encrypt
+}
+
#
# All of these problems come from using test_socket_ssl
#
diff --git a/Modules/_elementtree.c b/Modules/_elementtree.c
index 78d8177..348fefc 100644
--- a/Modules/_elementtree.c
+++ b/Modules/_elementtree.c
@@ -191,7 +191,7 @@
}
/* -------------------------------------------------------------------- */
-/* the element type */
+/* the Element type */
typedef struct {
@@ -236,10 +236,10 @@
#define Element_CheckExact(op) (Py_TYPE(op) == &Element_Type)
/* -------------------------------------------------------------------- */
-/* element constructor and destructor */
+/* Element constructors and destructor */
LOCAL(int)
-element_new_extra(ElementObject* self, PyObject* attrib)
+create_extra(ElementObject* self, PyObject* attrib)
{
self->extra = PyObject_Malloc(sizeof(ElementObjectExtra));
if (!self->extra)
@@ -259,7 +259,7 @@
}
LOCAL(void)
-element_dealloc_extra(ElementObject* self)
+dealloc_extra(ElementObject* self)
{
int i;
@@ -274,8 +274,11 @@
PyObject_Free(self->extra);
}
+/* Convenience internal function to create new Element objects with the given
+ * tag and attributes.
+*/
LOCAL(PyObject*)
-element_new(PyObject* tag, PyObject* attrib)
+create_new_element(PyObject* tag, PyObject* attrib)
{
ElementObject* self;
@@ -290,16 +293,10 @@
self->extra = NULL;
if (attrib != Py_None) {
-
- if (element_new_extra(self, attrib) < 0) {
+ if (create_extra(self, attrib) < 0) {
PyObject_Del(self);
return NULL;
}
-
- self->extra->length = 0;
- self->extra->allocated = STATIC_CHILDREN;
- self->extra->children = self->extra->_children;
-
}
Py_INCREF(tag);
@@ -316,6 +313,86 @@
return (PyObject*) self;
}
+static PyObject *
+element_new(PyTypeObject *type, PyObject *args, PyObject *kwds)
+{
+ ElementObject *e = (ElementObject *)type->tp_alloc(type, 0);
+ if (e != NULL) {
+ Py_INCREF(Py_None);
+ e->tag = Py_None;
+
+ Py_INCREF(Py_None);
+ e->text = Py_None;
+
+ Py_INCREF(Py_None);
+ e->tail = Py_None;
+
+ e->extra = NULL;
+ }
+ return (PyObject *)e;
+}
+
+static int
+element_init(PyObject *self, PyObject *args, PyObject *kwds)
+{
+ PyObject *tag;
+ PyObject *tmp;
+ PyObject *attrib = NULL;
+ ElementObject *self_elem;
+
+ if (!PyArg_ParseTuple(args, "O|O!:Element", &tag, &PyDict_Type, &attrib))
+ return -1;
+
+ if (attrib || kwds) {
+ attrib = (attrib) ? PyDict_Copy(attrib) : PyDict_New();
+ if (!attrib)
+ return -1;
+ if (kwds)
+ PyDict_Update(attrib, kwds);
+ } else {
+ Py_INCREF(Py_None);
+ attrib = Py_None;
+ }
+
+ self_elem = (ElementObject *)self;
+
+ /* Use None for empty dictionaries */
+ if (PyDict_CheckExact(attrib) && PyDict_Size(attrib) == 0) {
+ Py_INCREF(Py_None);
+ attrib = Py_None;
+ }
+
+ if (attrib != Py_None) {
+ if (create_extra(self_elem, attrib) < 0) {
+ PyObject_Del(self_elem);
+ return -1;
+ }
+ }
+
+ /* If create_extra needed attrib, it took a reference to it, so we can
+ * release ours anyway.
+ */
+ Py_DECREF(attrib);
+
+ /* Replace the objects already pointed to by tag, text and tail. */
+ tmp = self_elem->tag;
+ self_elem->tag = tag;
+ Py_INCREF(tag);
+ Py_DECREF(tmp);
+
+ tmp = self_elem->text;
+ self_elem->text = Py_None;
+ Py_INCREF(Py_None);
+ Py_DECREF(JOIN_OBJ(tmp));
+
+ tmp = self_elem->tail;
+ self_elem->tail = Py_None;
+ Py_INCREF(Py_None);
+ Py_DECREF(JOIN_OBJ(tmp));
+
+ return 0;
+}
+
LOCAL(int)
element_resize(ElementObject* self, int extra)
{
@@ -326,7 +403,7 @@
elements. set an exception and return -1 if allocation failed */
if (!self->extra)
- element_new_extra(self, NULL);
+ create_extra(self, NULL);
size = self->extra->length + extra;
@@ -444,35 +521,6 @@
}
static PyObject*
-element(PyObject* self, PyObject* args, PyObject* kw)
-{
- PyObject* elem;
-
- PyObject* tag;
- PyObject* attrib = NULL;
- if (!PyArg_ParseTuple(args, "O|O!:Element", &tag,
- &PyDict_Type, &attrib))
- return NULL;
-
- if (attrib || kw) {
- attrib = (attrib) ? PyDict_Copy(attrib) : PyDict_New();
- if (!attrib)
- return NULL;
- if (kw)
- PyDict_Update(attrib, kw);
- } else {
- Py_INCREF(Py_None);
- attrib = Py_None;
- }
-
- elem = element_new(tag, attrib);
-
- Py_DECREF(attrib);
-
- return elem;
-}
-
-static PyObject*
subelement(PyObject* self, PyObject* args, PyObject* kw)
{
PyObject* elem;
@@ -496,7 +544,7 @@
attrib = Py_None;
}
- elem = element_new(tag, attrib);
+ elem = create_new_element(tag, attrib);
Py_DECREF(attrib);
@@ -512,7 +560,7 @@
element_dealloc(ElementObject* self)
{
if (self->extra)
- element_dealloc_extra(self);
+ dealloc_extra(self);
/* discard attributes */
Py_DECREF(self->tag);
@@ -521,7 +569,7 @@
RELEASE(sizeof(ElementObject), "destroy element");
- PyObject_Del(self);
+ Py_TYPE(self)->tp_free((PyObject *)self);
}
/* -------------------------------------------------------------------- */
@@ -547,7 +595,7 @@
return NULL;
if (self->extra) {
- element_dealloc_extra(self);
+ dealloc_extra(self);
self->extra = NULL;
}
@@ -571,7 +619,7 @@
if (!PyArg_ParseTuple(args, ":__copy__"))
return NULL;
- element = (ElementObject*) element_new(
+ element = (ElementObject*) create_new_element(
self->tag, (self->extra) ? self->extra->attrib : Py_None
);
if (!element)
@@ -634,7 +682,7 @@
attrib = Py_None;
}
- element = (ElementObject*) element_new(tag, attrib);
+ element = (ElementObject*) create_new_element(tag, attrib);
Py_DECREF(tag);
Py_DECREF(attrib);
@@ -1029,7 +1077,7 @@
return NULL;
if (!self->extra)
- element_new_extra(self, NULL);
+ create_extra(self, NULL);
if (index < 0) {
index += self->extra->length;
@@ -1100,7 +1148,7 @@
if (!attrib)
return NULL;
- elem = element_new(tag, attrib);
+ elem = create_new_element(tag, attrib);
Py_DECREF(attrib);
@@ -1154,7 +1202,10 @@
static PyObject*
element_repr(ElementObject* self)
{
- return PyUnicode_FromFormat("<Element %R at %p>", self->tag, self);
+ if (self->tag)
+ return PyUnicode_FromFormat("<Element %R at %p>", self->tag, self);
+ else
+ return PyUnicode_FromFormat("<Element at %p>", self);
}
static PyObject*
@@ -1168,7 +1219,7 @@
return NULL;
if (!self->extra)
- element_new_extra(self, NULL);
+ create_extra(self, NULL);
attrib = element_get_attrib(self);
if (!attrib)
@@ -1284,7 +1335,7 @@
PyObject* seq = NULL;
if (!self->extra)
- element_new_extra(self, NULL);
+ create_extra(self, NULL);
if (PySlice_GetIndicesEx(item,
self->extra->length,
@@ -1448,7 +1499,7 @@
} else if (strcmp(name, "attrib") == 0) {
PyErr_Clear();
if (!self->extra)
- element_new_extra(self, NULL);
+ create_extra(self, NULL);
res = element_get_attrib(self);
}
@@ -1484,7 +1535,7 @@
Py_INCREF(self->tail);
} else if (strcmp(name, "attrib") == 0) {
if (!self->extra)
- element_new_extra(self, NULL);
+ create_extra(self, NULL);
Py_DECREF(self->extra->attrib);
self->extra->attrib = value;
Py_INCREF(self->extra->attrib);
@@ -1516,31 +1567,41 @@
PyVarObject_HEAD_INIT(NULL, 0)
"Element", sizeof(ElementObject), 0,
/* methods */
- (destructor)element_dealloc, /* tp_dealloc */
- 0, /* tp_print */
- 0, /* tp_getattr */
- (setattrfunc)element_setattr, /* tp_setattr */
- 0, /* tp_reserved */
- (reprfunc)element_repr, /* tp_repr */
- 0, /* tp_as_number */
- &element_as_sequence, /* tp_as_sequence */
- &element_as_mapping, /* tp_as_mapping */
- 0, /* tp_hash */
- 0, /* tp_call */
- 0, /* tp_str */
- (getattrofunc)element_getattro, /* tp_getattro */
- 0, /* tp_setattro */
- 0, /* tp_as_buffer */
- Py_TPFLAGS_DEFAULT, /* tp_flags */
- 0, /* tp_doc */
- 0, /* tp_traverse */
- 0, /* tp_clear */
- 0, /* tp_richcompare */
- 0, /* tp_weaklistoffset */
- 0, /* tp_iter */
- 0, /* tp_iternext */
- element_methods, /* tp_methods */
- 0, /* tp_members */
+ (destructor)element_dealloc, /* tp_dealloc */
+ 0, /* tp_print */
+ 0, /* tp_getattr */
+ (setattrfunc)element_setattr, /* tp_setattr */
+ 0, /* tp_reserved */
+ (reprfunc)element_repr, /* tp_repr */
+ 0, /* tp_as_number */
+ &element_as_sequence, /* tp_as_sequence */
+ &element_as_mapping, /* tp_as_mapping */
+ 0, /* tp_hash */
+ 0, /* tp_call */
+ 0, /* tp_str */
+ (getattrofunc)element_getattro, /* tp_getattro */
+ 0, /* tp_setattro */
+ 0, /* tp_as_buffer */
+ Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /* tp_flags */
+ 0, /* tp_doc */
+ 0, /* tp_traverse */
+ 0, /* tp_clear */
+ 0, /* tp_richcompare */
+ 0, /* tp_weaklistoffset */
+ 0, /* tp_iter */
+ 0, /* tp_iternext */
+ element_methods, /* tp_methods */
+ 0, /* tp_members */
+ 0, /* tp_getset */
+ 0, /* tp_base */
+ 0, /* tp_dict */
+ 0, /* tp_descr_get */
+ 0, /* tp_descr_set */
+ 0, /* tp_dictoffset */
+ (initproc)element_init, /* tp_init */
+ PyType_GenericAlloc, /* tp_alloc */
+ element_new, /* tp_new */
+ 0, /* tp_free */
};
/* ==================================================================== */
@@ -1638,13 +1699,6 @@
/* handlers */
LOCAL(PyObject*)
-treebuilder_handle_xml(TreeBuilderObject* self, PyObject* encoding,
- PyObject* standalone)
-{
- Py_RETURN_NONE;
-}
-
-LOCAL(PyObject*)
treebuilder_handle_start(TreeBuilderObject* self, PyObject* tag,
PyObject* attrib)
{
@@ -1666,7 +1720,7 @@
self->data = NULL;
}
- node = element_new(tag, attrib);
+ node = create_new_element(tag, attrib);
if (!node)
return NULL;
@@ -1915,22 +1969,10 @@
return treebuilder_handle_start(self, tag, attrib);
}
-static PyObject*
-treebuilder_xml(TreeBuilderObject* self, PyObject* args)
-{
- PyObject* encoding;
- PyObject* standalone;
- if (!PyArg_ParseTuple(args, "OO:xml", &encoding, &standalone))
- return NULL;
-
- return treebuilder_handle_xml(self, encoding, standalone);
-}
-
static PyMethodDef treebuilder_methods[] = {
{"data", (PyCFunction) treebuilder_data, METH_VARARGS},
{"start", (PyCFunction) treebuilder_start, METH_VARARGS},
{"end", (PyCFunction) treebuilder_end, METH_VARARGS},
- {"xml", (PyCFunction) treebuilder_xml, METH_VARARGS},
{"close", (PyCFunction) treebuilder_close, METH_VARARGS},
{NULL, NULL}
};
@@ -1991,8 +2033,6 @@
PyObject* names;
- PyObject* handle_xml;
-
PyObject* handle_start;
PyObject* handle_data;
PyObject* handle_end;
@@ -2445,7 +2485,6 @@
Py_INCREF(target);
self->target = target;
- self->handle_xml = PyObject_GetAttrString(target, "xml");
self->handle_start = PyObject_GetAttrString(target, "start");
self->handle_data = PyObject_GetAttrString(target, "data");
self->handle_end = PyObject_GetAttrString(target, "end");
@@ -2501,7 +2540,6 @@
Py_XDECREF(self->handle_end);
Py_XDECREF(self->handle_data);
Py_XDECREF(self->handle_start);
- Py_XDECREF(self->handle_xml);
Py_DECREF(self->target);
Py_DECREF(self->entity);
@@ -2801,7 +2839,6 @@
/* python module interface */
static PyMethodDef _functions[] = {
- {"Element", (PyCFunction) element, METH_VARARGS|METH_KEYWORDS},
{"SubElement", (PyCFunction) subelement, METH_VARARGS|METH_KEYWORDS},
{"TreeBuilder", (PyCFunction) treebuilder, METH_VARARGS},
#if defined(USE_EXPAT)
@@ -2911,5 +2948,8 @@
Py_INCREF(elementtree_parseerror_obj);
PyModule_AddObject(m, "ParseError", elementtree_parseerror_obj);
+ Py_INCREF((PyObject *)&Element_Type);
+ PyModule_AddObject(m, "Element", (PyObject *)&Element_Type);
+
return m;
}
diff --git a/Modules/_multiprocessing/win32_functions.c b/Modules/_multiprocessing/win32_functions.c
index 15aeeda..93c8fc9 100644
--- a/Modules/_multiprocessing/win32_functions.c
+++ b/Modules/_multiprocessing/win32_functions.c
@@ -60,16 +60,18 @@
static void
overlapped_dealloc(OverlappedObject *self)
{
+ DWORD bytes;
int err = GetLastError();
if (self->pending) {
- if (check_CancelIoEx())
- Py_CancelIoEx(self->handle, &self->overlapped);
- else {
- PyErr_SetString(PyExc_RuntimeError,
- "I/O operations still in flight while destroying "
- "Overlapped object, the process may crash");
- PyErr_WriteUnraisable(NULL);
- }
+ /* make it a programming error to deallocate while operation
+ is pending, even if we can safely cancel it */
+ if (check_CancelIoEx() &&
+ Py_CancelIoEx(self->handle, &self->overlapped))
+ GetOverlappedResult(self->handle, &self->overlapped, &bytes, TRUE);
+ PyErr_SetString(PyExc_RuntimeError,
+ "I/O operations still in flight while destroying "
+ "Overlapped object, the process may crash");
+ PyErr_WriteUnraisable(NULL);
}
CloseHandle(self->overlapped.hEvent);
SetLastError(err);
@@ -85,6 +87,7 @@
int wait;
BOOL res;
DWORD transferred = 0;
+ DWORD err;
wait = PyObject_IsTrue(waitobj);
if (wait < 0)
@@ -94,23 +97,27 @@
wait != 0);
Py_END_ALLOW_THREADS
- if (!res) {
- int err = GetLastError();
- if (err == ERROR_IO_INCOMPLETE)
- Py_RETURN_NONE;
- if (err != ERROR_MORE_DATA) {
+ err = res ? ERROR_SUCCESS : GetLastError();
+ switch (err) {
+ case ERROR_SUCCESS:
+ case ERROR_MORE_DATA:
+ case ERROR_OPERATION_ABORTED:
+ self->completed = 1;
+ self->pending = 0;
+ break;
+ case ERROR_IO_INCOMPLETE:
+ break;
+ default:
self->pending = 0;
return PyErr_SetExcFromWindowsErr(PyExc_IOError, err);
- }
}
- self->pending = 0;
- self->completed = 1;
- if (self->read_buffer) {
+ if (self->completed && self->read_buffer != NULL) {
assert(PyBytes_CheckExact(self->read_buffer));
- if (_PyBytes_Resize(&self->read_buffer, transferred))
+ if (transferred != PyBytes_GET_SIZE(self->read_buffer) &&
+ _PyBytes_Resize(&self->read_buffer, transferred))
return NULL;
}
- return Py_BuildValue("lN", (long) transferred, PyBool_FromLong(res));
+ return Py_BuildValue("II", (unsigned) transferred, (unsigned) err);
}
static PyObject *
@@ -522,9 +529,10 @@
HANDLE handle;
Py_buffer _buf, *buf;
PyObject *bufobj;
- int written;
+ DWORD written;
BOOL ret;
int use_overlapped = 0;
+ DWORD err;
OverlappedObject *overlapped = NULL;
static char *kwlist[] = {"handle", "buffer", "overlapped", NULL};
@@ -553,8 +561,9 @@
overlapped ? &overlapped->overlapped : NULL);
Py_END_ALLOW_THREADS
+ err = ret ? 0 : GetLastError();
+
if (overlapped) {
- int err = GetLastError();
if (!ret) {
if (err == ERROR_IO_PENDING)
overlapped->pending = 1;
@@ -563,13 +572,13 @@
return PyErr_SetExcFromWindowsErr(PyExc_IOError, 0);
}
}
- return (PyObject *) overlapped;
+ return Py_BuildValue("NI", (PyObject *) overlapped, err);
}
PyBuffer_Release(buf);
if (!ret)
return PyErr_SetExcFromWindowsErr(PyExc_IOError, 0);
- return PyLong_FromLong(written);
+ return Py_BuildValue("II", written, err);
}
static PyObject *
@@ -581,6 +590,7 @@
PyObject *buf;
BOOL ret;
int use_overlapped = 0;
+ DWORD err;
OverlappedObject *overlapped = NULL;
static char *kwlist[] = {"handle", "size", "overlapped", NULL};
@@ -607,8 +617,9 @@
overlapped ? &overlapped->overlapped : NULL);
Py_END_ALLOW_THREADS
+ err = ret ? 0 : GetLastError();
+
if (overlapped) {
- int err = GetLastError();
if (!ret) {
if (err == ERROR_IO_PENDING)
overlapped->pending = 1;
@@ -617,16 +628,16 @@
return PyErr_SetExcFromWindowsErr(PyExc_IOError, 0);
}
}
- return (PyObject *) overlapped;
+ return Py_BuildValue("NI", (PyObject *) overlapped, err);
}
- if (!ret && GetLastError() != ERROR_MORE_DATA) {
+ if (!ret && err != ERROR_MORE_DATA) {
Py_DECREF(buf);
return PyErr_SetExcFromWindowsErr(PyExc_IOError, 0);
}
if (_PyBytes_Resize(&buf, nread))
return NULL;
- return Py_BuildValue("NN", buf, PyBool_FromLong(ret));
+ return Py_BuildValue("NI", buf, err);
}
static PyObject *
@@ -783,7 +794,11 @@
WIN32_CONSTANT(F_DWORD, ERROR_ALREADY_EXISTS);
WIN32_CONSTANT(F_DWORD, ERROR_BROKEN_PIPE);
+ WIN32_CONSTANT(F_DWORD, ERROR_IO_PENDING);
+ WIN32_CONSTANT(F_DWORD, ERROR_MORE_DATA);
+ WIN32_CONSTANT(F_DWORD, ERROR_NETNAME_DELETED);
WIN32_CONSTANT(F_DWORD, ERROR_NO_SYSTEM_RESOURCES);
+ WIN32_CONSTANT(F_DWORD, ERROR_OPERATION_ABORTED);
WIN32_CONSTANT(F_DWORD, ERROR_PIPE_BUSY);
WIN32_CONSTANT(F_DWORD, ERROR_PIPE_CONNECTED);
WIN32_CONSTANT(F_DWORD, ERROR_SEM_TIMEOUT);
diff --git a/Modules/_pickle.c b/Modules/_pickle.c
index a0c1029..2dc3a41 100644
--- a/Modules/_pickle.c
+++ b/Modules/_pickle.c
@@ -319,6 +319,7 @@
objects to support self-referential objects
pickling. */
PyObject *pers_func; /* persistent_id() method, can be NULL */
+ PyObject *dispatch_table; /* private dispatch_table, can be NULL */
PyObject *arg;
PyObject *write; /* write() method of the output stream. */
@@ -764,6 +765,7 @@
return NULL;
self->pers_func = NULL;
+ self->dispatch_table = NULL;
self->arg = NULL;
self->write = NULL;
self->proto = 0;
@@ -3176,17 +3178,24 @@
/* XXX: This part needs some unit tests. */
/* Get a reduction callable, and call it. This may come from
- * copyreg.dispatch_table, the object's __reduce_ex__ method,
- * or the object's __reduce__ method.
+ * self.dispatch_table, copyreg.dispatch_table, the object's
+ * __reduce_ex__ method, or the object's __reduce__ method.
*/
- reduce_func = PyDict_GetItem(dispatch_table, (PyObject *)type);
+ if (self->dispatch_table == NULL) {
+ reduce_func = PyDict_GetItem(dispatch_table, (PyObject *)type);
+ /* PyDict_GetItem() unlike PyObject_GetItem() and
+ PyObject_GetAttr() returns a borrowed ref */
+ Py_XINCREF(reduce_func);
+ } else {
+ reduce_func = PyObject_GetItem(self->dispatch_table, (PyObject *)type);
+ if (reduce_func == NULL) {
+ if (PyErr_ExceptionMatches(PyExc_KeyError))
+ PyErr_Clear();
+ else
+ goto error;
+ }
+ }
if (reduce_func != NULL) {
- /* Here, the reference count of the reduce_func object returned by
- PyDict_GetItem needs to be increased to be consistent with the one
- returned by PyObject_GetAttr. This is allow us to blindly DECREF
- reduce_func at the end of the save() routine.
- */
- Py_INCREF(reduce_func);
Py_INCREF(obj);
reduce_value = _Pickler_FastCall(self, reduce_func, obj);
}
@@ -3359,6 +3368,7 @@
Py_XDECREF(self->output_buffer);
Py_XDECREF(self->write);
Py_XDECREF(self->pers_func);
+ Py_XDECREF(self->dispatch_table);
Py_XDECREF(self->arg);
Py_XDECREF(self->fast_memo);
@@ -3372,6 +3382,7 @@
{
Py_VISIT(self->write);
Py_VISIT(self->pers_func);
+ Py_VISIT(self->dispatch_table);
Py_VISIT(self->arg);
Py_VISIT(self->fast_memo);
return 0;
@@ -3383,6 +3394,7 @@
Py_CLEAR(self->output_buffer);
Py_CLEAR(self->write);
Py_CLEAR(self->pers_func);
+ Py_CLEAR(self->dispatch_table);
Py_CLEAR(self->arg);
Py_CLEAR(self->fast_memo);
@@ -3427,6 +3439,7 @@
PyObject *proto_obj = NULL;
PyObject *fix_imports = Py_True;
_Py_IDENTIFIER(persistent_id);
+ _Py_IDENTIFIER(dispatch_table);
if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|OO:Pickler",
kwlist, &file, &proto_obj, &fix_imports))
@@ -3468,6 +3481,13 @@
if (self->pers_func == NULL)
return -1;
}
+ self->dispatch_table = NULL;
+ if (_PyObject_HasAttrId((PyObject *)self, &PyId_dispatch_table)) {
+ self->dispatch_table = _PyObject_GetAttrId((PyObject *)self,
+ &PyId_dispatch_table);
+ if (self->dispatch_table == NULL)
+ return -1;
+ }
return 0;
}
@@ -3749,6 +3769,7 @@
static PyMemberDef Pickler_members[] = {
{"bin", T_INT, offsetof(PicklerObject, bin)},
{"fast", T_INT, offsetof(PicklerObject, fast)},
+ {"dispatch_table", T_OBJECT_EX, offsetof(PicklerObject, dispatch_table)},
{NULL}
};
diff --git a/Modules/_testbuffer.c b/Modules/_testbuffer.c
index 39a7bcc..cc4aea8 100644
--- a/Modules/_testbuffer.c
+++ b/Modules/_testbuffer.c
@@ -44,23 +44,21 @@
#define ADJUST_PTR(ptr, suboffsets) \
(HAVE_PTR(suboffsets) ? *((char**)ptr) + suboffsets[0] : ptr)
-/* User configurable flags for the ndarray */
-#define ND_VAREXPORT 0x001 /* change layout while buffers are exported */
-
-/* User configurable flags for each base buffer */
-#define ND_WRITABLE 0x002 /* mark base buffer as writable */
-#define ND_FORTRAN 0x004 /* Fortran contiguous layout */
-#define ND_SCALAR 0x008 /* scalar: ndim = 0 */
-#define ND_PIL 0x010 /* convert to PIL-style array (suboffsets) */
-#define ND_GETBUF_FAIL 0x020 /* test issue 7385 */
-
/* Default: NumPy style (strides), read-only, no var-export, C-style layout */
-#define ND_DEFAULT 0x0
-
+#define ND_DEFAULT 0x000
+/* User configurable flags for the ndarray */
+#define ND_VAREXPORT 0x001 /* change layout while buffers are exported */
+/* User configurable flags for each base buffer */
+#define ND_WRITABLE 0x002 /* mark base buffer as writable */
+#define ND_FORTRAN 0x004 /* Fortran contiguous layout */
+#define ND_SCALAR 0x008 /* scalar: ndim = 0 */
+#define ND_PIL 0x010 /* convert to PIL-style array (suboffsets) */
+#define ND_REDIRECT 0x020 /* redirect buffer requests */
+#define ND_GETBUF_FAIL 0x040 /* trigger getbuffer failure */
+#define ND_GETBUF_UNDEFINED 0x080 /* undefined view.obj */
/* Internal flags for the base buffer */
-#define ND_C 0x040 /* C contiguous layout (default) */
-#define ND_OWN_ARRAYS 0x080 /* consumer owns arrays */
-#define ND_UNUSED 0x100 /* initializer */
+#define ND_C 0x100 /* C contiguous layout (default) */
+#define ND_OWN_ARRAYS 0x200 /* consumer owns arrays */
/* ndarray properties */
#define ND_IS_CONSUMER(nd) \
@@ -1290,7 +1288,7 @@
PyObject *strides = NULL; /* number of bytes to the next elt in each dim */
Py_ssize_t offset = 0; /* buffer offset */
PyObject *format = simple_format; /* struct module specifier: "B" */
- int flags = ND_UNUSED; /* base buffer and ndarray flags */
+ int flags = ND_DEFAULT; /* base buffer and ndarray flags */
int getbuf = PyBUF_UNUSED; /* re-exporter: getbuffer request flags */
@@ -1302,10 +1300,10 @@
/* NDArrayObject is re-exporter */
if (PyObject_CheckBuffer(v) && shape == NULL) {
if (strides || offset || format != simple_format ||
- flags != ND_UNUSED) {
+ !(flags == ND_DEFAULT || flags == ND_REDIRECT)) {
PyErr_SetString(PyExc_TypeError,
- "construction from exporter object only takes a single "
- "additional getbuf argument");
+ "construction from exporter object only takes 'obj', 'getbuf' "
+ "and 'flags' arguments");
return -1;
}
@@ -1315,6 +1313,7 @@
return -1;
init_flags(nd->head);
+ nd->head->flags |= flags;
return 0;
}
@@ -1333,8 +1332,6 @@
return -1;
}
- if (flags == ND_UNUSED)
- flags = ND_DEFAULT;
if (flags & ND_VAREXPORT) {
nd->flags |= ND_VAREXPORT;
flags &= ~ND_VAREXPORT;
@@ -1357,7 +1354,7 @@
PyObject *strides = NULL; /* number of bytes to the next elt in each dim */
PyObject *format = simple_format; /* struct module specifier: "B" */
Py_ssize_t offset = 0; /* buffer offset */
- int flags = ND_UNUSED; /* base buffer flags */
+ int flags = ND_DEFAULT; /* base buffer flags */
if (!PyArg_ParseTupleAndKeywords(args, kwds, "OO|OnOi", kwlist,
&items, &shape, &strides, &offset, &format, &flags))
@@ -1423,6 +1420,11 @@
Py_buffer *base = &ndbuf->base;
int baseflags = ndbuf->flags;
+ /* redirect mode */
+ if (base->obj != NULL && (baseflags&ND_REDIRECT)) {
+ return PyObject_GetBuffer(base->obj, view, flags);
+ }
+
/* start with complete information */
*view = *base;
view->obj = NULL;
@@ -1445,6 +1447,8 @@
if (baseflags & ND_GETBUF_FAIL) {
PyErr_SetString(PyExc_BufferError,
"ND_GETBUF_FAIL: forced test exception");
+ if (baseflags & ND_GETBUF_UNDEFINED)
+ view->obj = (PyObject *)0x1; /* wrong but permitted in <= 3.2 */
return -1;
}
@@ -2598,6 +2602,126 @@
ndarray_new, /* tp_new */
};
+/**************************************************************************/
+/* StaticArray Object */
+/**************************************************************************/
+
+static PyTypeObject StaticArray_Type;
+
+typedef struct {
+ PyObject_HEAD
+ int legacy_mode; /* if true, use the view.obj==NULL hack */
+} StaticArrayObject;
+
+static char static_mem[12] = {0,1,2,3,4,5,6,7,8,9,10,11};
+static Py_ssize_t static_shape[1] = {12};
+static Py_ssize_t static_strides[1] = {1};
+static Py_buffer static_buffer = {
+ static_mem, /* buf */
+ NULL, /* obj */
+ 12, /* len */
+ 1, /* itemsize */
+ 1, /* readonly */
+ 1, /* ndim */
+ "B", /* format */
+ static_shape, /* shape */
+ static_strides, /* strides */
+ NULL, /* suboffsets */
+ NULL /* internal */
+};
+
+static PyObject *
+staticarray_new(PyTypeObject *type, PyObject *args, PyObject *kwds)
+{
+ return (PyObject *)PyObject_New(StaticArrayObject, &StaticArray_Type);
+}
+
+static int
+staticarray_init(PyObject *self, PyObject *args, PyObject *kwds)
+{
+ StaticArrayObject *a = (StaticArrayObject *)self;
+ static char *kwlist[] = {
+ "legacy_mode", NULL
+ };
+ PyObject *legacy_mode = Py_False;
+
+ if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O", kwlist, &legacy_mode))
+ return -1;
+
+ a->legacy_mode = (legacy_mode != Py_False);
+ return 0;
+}
+
+static void
+staticarray_dealloc(StaticArrayObject *self)
+{
+ PyObject_Del(self);
+}
+
+/* Return a buffer for a PyBUF_FULL_RO request. Flags are not checked,
+ which makes this object a non-compliant exporter! */
+static int
+staticarray_getbuf(StaticArrayObject *self, Py_buffer *view, int flags)
+{
+ *view = static_buffer;
+
+ if (self->legacy_mode) {
+ view->obj = NULL; /* Don't use this in new code. */
+ }
+ else {
+ view->obj = (PyObject *)self;
+ Py_INCREF(view->obj);
+ }
+
+ return 0;
+}
+
+static PyBufferProcs staticarray_as_buffer = {
+ (getbufferproc)staticarray_getbuf, /* bf_getbuffer */
+ NULL, /* bf_releasebuffer */
+};
+
+static PyTypeObject StaticArray_Type = {
+ PyVarObject_HEAD_INIT(NULL, 0)
+ "staticarray", /* Name of this type */
+ sizeof(StaticArrayObject), /* Basic object size */
+ 0, /* Item size for varobject */
+ (destructor)staticarray_dealloc, /* tp_dealloc */
+ 0, /* tp_print */
+ 0, /* tp_getattr */
+ 0, /* tp_setattr */
+ 0, /* tp_compare */
+ 0, /* tp_repr */
+ 0, /* tp_as_number */
+ 0, /* tp_as_sequence */
+ 0, /* tp_as_mapping */
+ 0, /* tp_hash */
+ 0, /* tp_call */
+ 0, /* tp_str */
+ 0, /* tp_getattro */
+ 0, /* tp_setattro */
+ &staticarray_as_buffer, /* tp_as_buffer */
+ Py_TPFLAGS_DEFAULT, /* tp_flags */
+ 0, /* tp_doc */
+ 0, /* tp_traverse */
+ 0, /* tp_clear */
+ 0, /* tp_richcompare */
+ 0, /* tp_weaklistoffset */
+ 0, /* tp_iter */
+ 0, /* tp_iternext */
+ 0, /* tp_methods */
+ 0, /* tp_members */
+ 0, /* tp_getset */
+ 0, /* tp_base */
+ 0, /* tp_dict */
+ 0, /* tp_descr_get */
+ 0, /* tp_descr_set */
+ 0, /* tp_dictoffset */
+ staticarray_init, /* tp_init */
+ 0, /* tp_alloc */
+ staticarray_new, /* tp_new */
+};
+
static struct PyMethodDef _testbuffer_functions[] = {
{"slice_indices", slice_indices, METH_VARARGS, NULL},
@@ -2630,10 +2754,14 @@
if (m == NULL)
return NULL;
- Py_TYPE(&NDArray_Type)=&PyType_Type;
+ Py_TYPE(&NDArray_Type) = &PyType_Type;
Py_INCREF(&NDArray_Type);
PyModule_AddObject(m, "ndarray", (PyObject *)&NDArray_Type);
+ Py_TYPE(&StaticArray_Type) = &PyType_Type;
+ Py_INCREF(&StaticArray_Type);
+ PyModule_AddObject(m, "staticarray", (PyObject *)&StaticArray_Type);
+
structmodule = PyImport_ImportModule("struct");
if (structmodule == NULL)
return NULL;
@@ -2654,6 +2782,8 @@
PyModule_AddIntConstant(m, "ND_SCALAR", ND_SCALAR);
PyModule_AddIntConstant(m, "ND_PIL", ND_PIL);
PyModule_AddIntConstant(m, "ND_GETBUF_FAIL", ND_GETBUF_FAIL);
+ PyModule_AddIntConstant(m, "ND_GETBUF_UNDEFINED", ND_GETBUF_UNDEFINED);
+ PyModule_AddIntConstant(m, "ND_REDIRECT", ND_REDIRECT);
PyModule_AddIntConstant(m, "PyBUF_SIMPLE", PyBUF_SIMPLE);
PyModule_AddIntConstant(m, "PyBUF_WRITABLE", PyBUF_WRITABLE);
diff --git a/Modules/_testcapimodule.c b/Modules/_testcapimodule.c
index 23a4d5ac..9294df3 100644
--- a/Modules/_testcapimodule.c
+++ b/Modules/_testcapimodule.c
@@ -2323,6 +2323,24 @@
return PyLong_FromLong(r);
}
+static PyObject *
+test_pytime_object_to_timespec(PyObject *self, PyObject *args)
+{
+ PyObject *obj;
+ time_t sec;
+ long nsec;
+ if (!PyArg_ParseTuple(args, "O:pytime_object_to_timespec", &obj))
+ return NULL;
+ if (_PyTime_ObjectToTimespec(obj, &sec, &nsec) == -1)
+ return NULL;
+#if defined(HAVE_LONG_LONG) && SIZEOF_TIME_T == SIZEOF_LONG_LONG
+ return Py_BuildValue("Ll", (PY_LONG_LONG)sec, nsec);
+#else
+ assert(sizeof(time_t) <= sizeof(long));
+ return Py_BuildValue("ll", (long)sec, nsec);
+#endif
+}
+
static PyMethodDef TestMethods[] = {
{"raise_exception", raise_exception, METH_VARARGS},
@@ -2412,6 +2430,7 @@
METH_NOARGS},
{"crash_no_current_thread", (PyCFunction)crash_no_current_thread, METH_NOARGS},
{"run_in_subinterp", run_in_subinterp, METH_VARARGS},
+ {"pytime_object_to_timespec", test_pytime_object_to_timespec, METH_VARARGS},
{NULL, NULL} /* sentinel */
};
diff --git a/Modules/mmapmodule.c b/Modules/mmapmodule.c
index cf0b687..f52dce5 100644
--- a/Modules/mmapmodule.c
+++ b/Modules/mmapmodule.c
@@ -959,13 +959,13 @@
}
static PySequenceMethods mmap_as_sequence = {
- (lenfunc)mmap_length, /*sq_length*/
- (binaryfunc)mmap_concat, /*sq_concat*/
- (ssizeargfunc)mmap_repeat, /*sq_repeat*/
- (ssizeargfunc)mmap_item, /*sq_item*/
- 0, /*sq_slice*/
- (ssizeobjargproc)mmap_ass_item, /*sq_ass_item*/
- 0, /*sq_ass_slice*/
+ (lenfunc)mmap_length, /*sq_length*/
+ (binaryfunc)mmap_concat, /*sq_concat*/
+ (ssizeargfunc)mmap_repeat, /*sq_repeat*/
+ (ssizeargfunc)mmap_item, /*sq_item*/
+ 0, /*sq_slice*/
+ (ssizeobjargproc)mmap_ass_item, /*sq_ass_item*/
+ 0, /*sq_ass_slice*/
};
static PyMappingMethods mmap_as_mapping = {
@@ -1027,7 +1027,7 @@
PyObject_GenericGetAttr, /*tp_getattro*/
0, /*tp_setattro*/
&mmap_as_buffer, /*tp_as_buffer*/
- Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /*tp_flags*/
+ Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /*tp_flags*/
mmap_doc, /*tp_doc*/
0, /* tp_traverse */
0, /* tp_clear */
@@ -1043,10 +1043,10 @@
0, /* tp_descr_get */
0, /* tp_descr_set */
0, /* tp_dictoffset */
- 0, /* tp_init */
+ 0, /* tp_init */
PyType_GenericAlloc, /* tp_alloc */
new_mmap_object, /* tp_new */
- PyObject_Del, /* tp_free */
+ PyObject_Del, /* tp_free */
};
@@ -1097,8 +1097,8 @@
int devzero = -1;
int access = (int)ACCESS_DEFAULT;
static char *keywords[] = {"fileno", "length",
- "flags", "prot",
- "access", "offset", NULL};
+ "flags", "prot",
+ "access", "offset", NULL};
if (!PyArg_ParseTupleAndKeywords(args, kwdict, "iO|iii" _Py_PARSE_OFF_T, keywords,
&fd, &map_size_obj, &flags, &prot,
@@ -1260,8 +1260,8 @@
int access = (access_mode)ACCESS_DEFAULT;
DWORD flProtect, dwDesiredAccess;
static char *keywords[] = { "fileno", "length",
- "tagname",
- "access", "offset", NULL };
+ "tagname",
+ "access", "offset", NULL };
if (!PyArg_ParseTupleAndKeywords(args, kwdict, "iO|ziL", keywords,
&fileno, &map_size_obj,
diff --git a/Modules/signalmodule.c b/Modules/signalmodule.c
index e46f8cf..2eb7f29 100644
--- a/Modules/signalmodule.c
+++ b/Modules/signalmodule.c
@@ -783,16 +783,11 @@
siginfo_t si;
int err;
- if (!PyArg_ParseTuple(args, "OO:sigtimedwait", &signals, &timeout))
+ if (!PyArg_ParseTuple(args, "OO:sigtimedwait",
+ &signals, &timeout))
return NULL;
- if (!PyTuple_Check(timeout) || PyTuple_Size(timeout) != 2) {
- PyErr_SetString(PyExc_TypeError,
- "sigtimedwait() arg 2 must be a tuple "
- "(timeout_sec, timeout_nsec)");
- return NULL;
- } else if (!PyArg_ParseTuple(timeout, "ll:sigtimedwait",
- &(buf.tv_sec), &(buf.tv_nsec)))
+ if (_PyTime_ObjectToTimespec(timeout, &buf.tv_sec, &buf.tv_nsec) == -1)
return NULL;
if (buf.tv_sec < 0 || buf.tv_nsec < 0) {
diff --git a/Objects/abstract.c b/Objects/abstract.c
index 62fccdc..39dffac 100644
--- a/Objects/abstract.c
+++ b/Objects/abstract.c
@@ -649,7 +649,7 @@
int
PyBuffer_FillInfo(Py_buffer *view, PyObject *obj, void *buf, Py_ssize_t len,
- int readonly, int flags)
+ int readonly, int flags)
{
if (view == NULL) return 0; /* XXX why not -1? */
if (((flags & PyBUF_WRITABLE) == PyBUF_WRITABLE) &&
diff --git a/Objects/dictobject.c b/Objects/dictobject.c
index 83957ac..23ca442 100644
--- a/Objects/dictobject.c
+++ b/Objects/dictobject.c
@@ -347,12 +347,9 @@
return ep;
}
else {
- /* The compare did major nasty stuff to the
- * dict: start over.
- * XXX A clever adversary could prevent this
- * XXX from terminating.
- */
- return lookdict(mp, key, hash);
+ PyErr_SetString(PyExc_RuntimeError,
+ "dictionary changed size during lookup");
+ return NULL;
}
}
freeslot = NULL;
@@ -379,12 +376,9 @@
return ep;
}
else {
- /* The compare did major nasty stuff to the
- * dict: start over.
- * XXX A clever adversary could prevent this
- * XXX from terminating.
- */
- return lookdict(mp, key, hash);
+ PyErr_SetString(PyExc_RuntimeError,
+ "dictionary changed size during lookup");
+ return NULL;
}
}
else if (ep->me_key == dummy && freeslot == NULL)
diff --git a/Objects/frameobject.c b/Objects/frameobject.c
index 9b05b9d..c1ec811 100644
--- a/Objects/frameobject.c
+++ b/Objects/frameobject.c
@@ -20,7 +20,6 @@
{"f_builtins", T_OBJECT, OFF(f_builtins), READONLY},
{"f_globals", T_OBJECT, OFF(f_globals), READONLY},
{"f_lasti", T_INT, OFF(f_lasti), READONLY},
- {"f_yieldfrom", T_OBJECT, OFF(f_yieldfrom), READONLY},
{NULL} /* Sentinel */
};
diff --git a/Objects/memoryobject.c b/Objects/memoryobject.c
index e87abf5..67f7e01 100644
--- a/Objects/memoryobject.c
+++ b/Objects/memoryobject.c
@@ -86,14 +86,11 @@
return NULL;
if (PyObject_GetBuffer(base, &mbuf->master, PyBUF_FULL_RO) < 0) {
- /* mbuf->master.obj must be NULL. */
+ mbuf->master.obj = NULL;
Py_DECREF(mbuf);
return NULL;
}
- /* Assume that master.obj is a new reference to base. */
- assert(mbuf->master.obj == base);
-
return (PyObject *)mbuf;
}
diff --git a/Objects/unicodeobject.c b/Objects/unicodeobject.c
index a4dcdf6..5c10713 100644
--- a/Objects/unicodeobject.c
+++ b/Objects/unicodeobject.c
@@ -998,7 +998,11 @@
is_sharing = 1;
}
else {
- assert(maxchar <= MAX_UNICODE);
+ if (maxchar > MAX_UNICODE) {
+ PyErr_SetString(PyExc_SystemError,
+ "invalid maximum character passed to PyUnicode_New");
+ return NULL;
+ }
kind_state = PyUnicode_4BYTE_KIND;
char_size = 4;
if (sizeof(wchar_t) == 4)
@@ -3942,6 +3946,10 @@
}
if (unicode_check_modifiable(unicode))
return -1;
+ if (ch > PyUnicode_MAX_CHAR_VALUE(unicode)) {
+ PyErr_SetString(PyExc_ValueError, "character out of range");
+ return -1;
+ }
PyUnicode_WRITE(PyUnicode_KIND(unicode), PyUnicode_DATA(unicode),
index, ch);
return 0;
diff --git a/PC/python_nt.rc b/PC/python_nt.rc
index 5295610..5010baa 100644
--- a/PC/python_nt.rc
+++ b/PC/python_nt.rc
@@ -12,7 +12,7 @@
# include "pythonnt_rc.h"
#endif
-/* e.g., 2.1a2
+/* e.g., 3.3.0a1
* PY_VERSION comes from patchevel.h
*/
#define PYTHON_VERSION PY_VERSION "\0"
diff --git a/PCbuild/pcbuild.sln b/PCbuild/pcbuild.sln
index 992e66a..ac6f224 100644
--- a/PCbuild/pcbuild.sln
+++ b/PCbuild/pcbuild.sln
@@ -584,16 +584,16 @@
{6DE10744-E396-40A5-B4E2-1B69AA7C8D31}.Release|x64.ActiveCfg = Release|x64
{6DE10744-E396-40A5-B4E2-1B69AA7C8D31}.Release|x64.Build.0 = Release|x64
{885D4898-D08D-4091-9C40-C700CFE3FC5A}.Debug|Win32.ActiveCfg = PGInstrument|Win32
- {885D4898-D08D-4091-9C40-C700CFE3FC5A}.Debug|x64.ActiveCfg = Debug|x64
- {885D4898-D08D-4091-9C40-C700CFE3FC5A}.Debug|x64.Build.0 = Debug|x64
+ {885D4898-D08D-4091-9C40-C700CFE3FC5A}.Debug|x64.ActiveCfg = PGUpdate|x64
+ {885D4898-D08D-4091-9C40-C700CFE3FC5A}.Debug|x64.Build.0 = PGUpdate|x64
{885D4898-D08D-4091-9C40-C700CFE3FC5A}.PGInstrument|Win32.ActiveCfg = PGInstrument|Win32
{885D4898-D08D-4091-9C40-C700CFE3FC5A}.PGInstrument|Win32.Build.0 = PGInstrument|Win32
- {885D4898-D08D-4091-9C40-C700CFE3FC5A}.PGInstrument|x64.ActiveCfg = Release|x64
- {885D4898-D08D-4091-9C40-C700CFE3FC5A}.PGInstrument|x64.Build.0 = Release|x64
+ {885D4898-D08D-4091-9C40-C700CFE3FC5A}.PGInstrument|x64.ActiveCfg = PGInstrument|x64
+ {885D4898-D08D-4091-9C40-C700CFE3FC5A}.PGInstrument|x64.Build.0 = PGInstrument|x64
{885D4898-D08D-4091-9C40-C700CFE3FC5A}.PGUpdate|Win32.ActiveCfg = PGUpdate|Win32
{885D4898-D08D-4091-9C40-C700CFE3FC5A}.PGUpdate|Win32.Build.0 = PGUpdate|Win32
- {885D4898-D08D-4091-9C40-C700CFE3FC5A}.PGUpdate|x64.ActiveCfg = Release|x64
- {885D4898-D08D-4091-9C40-C700CFE3FC5A}.PGUpdate|x64.Build.0 = Release|x64
+ {885D4898-D08D-4091-9C40-C700CFE3FC5A}.PGUpdate|x64.ActiveCfg = PGUpdate|x64
+ {885D4898-D08D-4091-9C40-C700CFE3FC5A}.PGUpdate|x64.Build.0 = PGUpdate|x64
{885D4898-D08D-4091-9C40-C700CFE3FC5A}.Release|Win32.ActiveCfg = Release|Win32
{885D4898-D08D-4091-9C40-C700CFE3FC5A}.Release|Win32.Build.0 = Release|Win32
{885D4898-D08D-4091-9C40-C700CFE3FC5A}.Release|x64.ActiveCfg = Release|x64
diff --git a/Parser/tokenizer.c b/Parser/tokenizer.c
index 55f4313..36ca079 100644
--- a/Parser/tokenizer.c
+++ b/Parser/tokenizer.c
@@ -1412,11 +1412,15 @@
/* Identifier (most frequent token!) */
nonascii = 0;
if (is_potential_identifier_start(c)) {
- /* Process b"", r"", br"" and rb"" */
- int saw_b = 0, saw_r = 0;
+ /* Process b"", r"", u"", br"", rb"" and ur"" */
+ int saw_b = 0, saw_r = 0, saw_u = 0;
while (1) {
- if (!saw_b && (c == 'b' || c == 'B'))
+ if (!(saw_b || saw_u) && (c == 'b' || c == 'B'))
saw_b = 1;
+ /* Since this is a backwards compatibility support literal we don't
+ want to support it in arbitrary order like byte literals. */
+ else if (!(saw_b || saw_u || saw_r) && (c == 'u' || c == 'U'))
+ saw_u = 1;
else if (!saw_r && (c == 'r' || c == 'R'))
saw_r = 1;
else
diff --git a/Python/ast.c b/Python/ast.c
index c565642..0f93098 100644
--- a/Python/ast.c
+++ b/Python/ast.c
@@ -3796,6 +3796,9 @@
quote = *++s;
*bytesmode = 1;
}
+ else if (quote == 'u' || quote == 'U') {
+ quote = *++s;
+ }
else if (quote == 'r' || quote == 'R') {
quote = *++s;
rawmode = 1;
diff --git a/Python/getcopyright.c b/Python/getcopyright.c
index d1e2578..d83c6da 100644
--- a/Python/getcopyright.c
+++ b/Python/getcopyright.c
@@ -19,5 +19,5 @@
const char *
Py_GetCopyright(void)
{
- return cprt;
+ return cprt;
}
diff --git a/Python/marshal.c b/Python/marshal.c
index 98bbbaf..b94e8d8 100644
--- a/Python/marshal.c
+++ b/Python/marshal.c
@@ -409,11 +409,12 @@
else if (PyObject_CheckBuffer(v)) {
/* Write unknown buffer-style objects as a string */
char *s;
- PyBufferProcs *pb = v->ob_type->tp_as_buffer;
Py_buffer view;
- if ((*pb->bf_getbuffer)(v, &view, PyBUF_SIMPLE) != 0) {
+ if (PyObject_GetBuffer(v, &view, PyBUF_SIMPLE) != 0) {
w_byte(TYPE_UNKNOWN, p);
+ p->depth--;
p->error = WFERR_UNMARSHALLABLE;
+ return;
}
w_byte(TYPE_STRING, p);
n = view.len;
@@ -425,8 +426,7 @@
}
w_long((long)n, p);
w_string(s, (int)n, p);
- if (pb->bf_releasebuffer != NULL)
- (*pb->bf_releasebuffer)(v, &view);
+ PyBuffer_Release(&view);
}
else {
w_byte(TYPE_UNKNOWN, p);
@@ -1239,7 +1239,6 @@
PyMarshal_WriteObjectToString(PyObject *x, int version)
{
WFILE wf;
- PyObject *res = NULL;
wf.fp = NULL;
wf.readable = NULL;
@@ -1273,12 +1272,7 @@
:"object too deeply nested to marshal");
return NULL;
}
- if (wf.str != NULL) {
- /* XXX Quick hack -- need to do this differently */
- res = PyBytes_FromObject(wf.str);
- Py_DECREF(wf.str);
- }
- return res;
+ return wf.str;
}
/* And an interface for Python programs... */
@@ -1390,7 +1384,7 @@
char *s;
Py_ssize_t n;
PyObject* result;
- if (!PyArg_ParseTuple(args, "s*:loads", &p))
+ if (!PyArg_ParseTuple(args, "y*:loads", &p))
return NULL;
s = p.buf;
n = p.len;
@@ -1406,10 +1400,10 @@
}
PyDoc_STRVAR(loads_doc,
-"loads(string)\n\
+"loads(bytes)\n\
\n\
-Convert the string to a value. If no valid value is found, raise\n\
-EOFError, ValueError or TypeError. Extra characters in the string are\n\
+Convert the bytes object to a value. If no valid value is found, raise\n\
+EOFError, ValueError or TypeError. Extra characters in the input are\n\
ignored.");
static PyMethodDef marshal_methods[] = {
diff --git a/Python/pytime.c b/Python/pytime.c
index bec1c71..d23ce75 100644
--- a/Python/pytime.c
+++ b/Python/pytime.c
@@ -70,6 +70,51 @@
#endif /* MS_WINDOWS */
}
+int
+_PyTime_ObjectToTimespec(PyObject *obj, time_t *sec, long *nsec)
+{
+ if (PyFloat_Check(obj)) {
+ double d, intpart, floatpart, err;
+
+ d = PyFloat_AsDouble(obj);
+ floatpart = modf(d, &intpart);
+ if (floatpart < 0) {
+ floatpart = 1.0 + floatpart;
+ intpart -= 1.0;
+ }
+
+ *sec = (time_t)intpart;
+ err = intpart - (double)*sec;
+ if (err <= -1.0 || err >= 1.0)
+ goto overflow;
+
+ floatpart *= 1e9;
+ *nsec = (long)floatpart;
+ return 0;
+ }
+ else {
+#if defined(HAVE_LONG_LONG) && SIZEOF_TIME_T == SIZEOF_LONG_LONG
+ *sec = PyLong_AsLongLong(obj);
+#else
+ assert(sizeof(time_t) <= sizeof(long));
+ *sec = PyLong_AsLong(obj);
+#endif
+ if (*sec == -1 && PyErr_Occurred()) {
+ if (PyErr_ExceptionMatches(PyExc_OverflowError))
+ goto overflow;
+ else
+ return -1;
+ }
+ *nsec = 0;
+ return 0;
+ }
+
+overflow:
+ PyErr_SetString(PyExc_OverflowError,
+ "timestamp out of range for platform time_t");
+ return -1;
+}
+
void
_PyTime_Init()
{
diff --git a/README b/README
index 3df3292..181d78f 100644
--- a/README
+++ b/README
@@ -1,5 +1,5 @@
-This is Python version 3.3 alpha 0
-==================================
+This is Python version 3.3.0 alpha 1
+====================================
Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011,
2012 Python Software Foundation. All rights reserved.
diff --git a/Tools/msi/msi.py b/Tools/msi/msi.py
index cbdf227..a18debc 100644
--- a/Tools/msi/msi.py
+++ b/Tools/msi/msi.py
@@ -2,12 +2,11 @@
# (C) 2003 Martin v. Loewis
# See "FOO" in comments refers to MSDN sections with the title FOO.
import msilib, schema, sequence, os, glob, time, re, shutil, zipfile
+import subprocess, tempfile
from msilib import Feature, CAB, Directory, Dialog, Binary, add_data
import uisample
from win32com.client import constants
from distutils.spawn import find_executable
-from uuids import product_codes
-import tempfile
# Settings can be overridden in config.py below
# 0 for official python.org releases
@@ -77,9 +76,6 @@
if snapshot:
current_version = "%s.%s.%s" % (major, minor, int(time.time()/3600/24))
- product_code = msilib.gen_uuid()
-else:
- product_code = product_codes[current_version]
if full_current_version is None:
full_current_version = current_version
@@ -187,12 +183,19 @@
msilib.set_arch_from_file(dll_path)
if msilib.pe_type(dll_path) != msilib.pe_type("msisupport.dll"):
raise SystemError("msisupport.dll for incorrect architecture")
+
if msilib.Win64:
upgrade_code = upgrade_code_64
- # Bump the last digit of the code by one, so that 32-bit and 64-bit
- # releases get separate product codes
- digit = hex((int(product_code[-2],16)+1)%16)[-1]
- product_code = product_code[:-2] + digit + '}'
+
+if snapshot:
+ product_code = msilib.gen_uuid()
+else:
+ # official release: generate UUID from the download link that the file will have
+ import uuid
+ product_code = uuid.uuid3(uuid.NAMESPACE_URL,
+ 'http://www.python.org/ftp/python/%s.%s.%s/python-%s%s.msi' %
+ (major, minor, micro, full_current_version, msilib.arch_ext))
+ product_code = '{%s}' % product_code
if testpackage:
ext = 'px'
@@ -906,31 +909,27 @@
kw['componentflags'] = 2 #msidbComponentAttributesOptional
Directory.__init__(self, *args, **kw)
- def check_unpackaged(self):
- self.unpackaged_files.discard('__pycache__')
- self.unpackaged_files.discard('.svn')
- if self.unpackaged_files:
- print "Warning: Unpackaged files in %s" % self.absolute
- print self.unpackaged_files
+def hgmanifest():
+ # Fetch file list from Mercurial
+ process = subprocess.Popen(['hg', 'manifest'], stdout=subprocess.PIPE)
+ stdout, stderr = process.communicate()
+ # Create nested directories for file tree
+ result = {}
+ for line in stdout.splitlines():
+ components = line.split('/')
+ d = result
+ while len(components) > 1:
+ d1 = d.setdefault(components[0], {})
+ d = d1
+ del components[0]
+ d[components[0]] = None
+ return result
-def inside_test(dir):
- if dir.physical in ('test', 'tests'):
- return True
- if dir.basedir:
- return inside_test(dir.basedir)
- return False
-
-def in_packaging_tests(dir):
- if dir.physical == 'tests' and dir.basedir.physical == 'packaging':
- return True
- if dir.basedir:
- return in_packaging_tests(dir.basedir)
- return False
-
# See "File Table", "Component Table", "Directory Table",
# "FeatureComponents Table"
def add_files(db):
+ hgfiles = hgmanifest()
cab = CAB("python")
tmpfiles = []
# Add all executables, icons, text files into the TARGETDIR component
@@ -992,123 +991,40 @@
# Add all .py files in Lib, except tkinter, test
dirs = []
- pydirs = [(root,"Lib")]
+ pydirs = [(root, "Lib", hgfiles["Lib"], default_feature)]
while pydirs:
# Commit every now and then, or else installer will complain
db.Commit()
- parent, dir = pydirs.pop()
- if dir == ".svn" or dir == '__pycache__' or dir.startswith("plat-"):
+ parent, dir, files, feature = pydirs.pop()
+ if dir.startswith("plat-"):
continue
- elif dir in ["tkinter", "idlelib", "Icons"]:
+ if dir in ["tkinter", "idlelib", "turtledemo"]:
if not have_tcl:
continue
+ feature = tcltk
tcltk.set_current()
- elif dir in ('test', 'tests') or inside_test(parent):
- testsuite.set_current()
+ elif dir in ('test', 'tests'):
+ feature = testsuite
elif not have_ctypes and dir == "ctypes":
continue
- else:
- default_feature.set_current()
+ feature.set_current()
lib = PyDirectory(db, cab, parent, dir, dir, "%s|%s" % (parent.make_short(dir), dir))
- # Add additional files
dirs.append(lib)
- lib.glob("*.txt")
- if dir=='site-packages':
- lib.add_file("README.txt", src="README")
- continue
- files = lib.glob("*.py")
- files += lib.glob("*.pyw")
- if files:
- # Add an entry to the RemoveFile table to remove bytecode files.
- lib.remove_pyc()
- # package READMEs if present
- lib.glob("README")
- if dir=='Lib':
- lib.add_file("sysconfig.cfg")
- if dir=='test' and parent.physical=='Lib':
- lib.add_file("185test.db")
- lib.add_file("audiotest.au")
- lib.add_file("sgml_input.html")
- lib.add_file("testtar.tar")
- lib.add_file("test_difflib_expect.html")
- lib.add_file("check_soundcard.vbs")
- lib.add_file("empty.vbs")
- lib.add_file("Sine-1000Hz-300ms.aif")
- lib.glob("*.uue")
- lib.glob("*.pem")
- lib.glob("*.pck")
- lib.glob("cfgparser.*")
- lib.add_file("zip_cp437_header.zip")
- lib.add_file("zipdir.zip")
- lib.add_file("mime.types")
- if dir=='capath':
- lib.glob("*.0")
- if dir=='tests' and parent.physical=='distutils':
- lib.add_file("Setup.sample")
- if dir=='decimaltestdata':
- lib.glob("*.decTest")
- if dir=='xmltestdata':
- lib.glob("*.xml")
- lib.add_file("test.xml.out")
- if dir=='output':
- lib.glob("test_*")
- if dir=='sndhdrdata':
- lib.glob("sndhdr.*")
- if dir=='idlelib':
- lib.glob("*.def")
- lib.add_file("idle.bat")
- lib.add_file("ChangeLog")
- if dir=="Icons":
- lib.glob("*.gif")
- lib.add_file("idle.icns")
- if dir=="command" and parent.physical in ("distutils", "packaging"):
- lib.glob("wininst*.exe")
- lib.add_file("command_template")
- if dir=="lib2to3":
- lib.removefile("pickle", "*.pickle")
- if dir=="macholib":
- lib.add_file("README.ctypes")
- lib.glob("fetch_macholib*")
- if dir=='turtledemo':
- lib.add_file("turtle.cfg")
- if dir=="pydoc_data":
- lib.add_file("_pydoc.css")
- if dir.endswith('.dist-info'):
- lib.add_file('INSTALLER')
- lib.add_file('REQUESTED')
- lib.add_file('RECORD')
- lib.add_file('METADATA')
- lib.glob('RESOURCES')
- if dir.endswith('.egg-info') or dir == 'EGG-INFO':
- lib.add_file('PKG-INFO')
- if in_packaging_tests(parent):
- lib.glob('*.html')
- lib.glob('*.tar.gz')
- if dir=='fake_dists':
- # cannot use glob since there are also egg-info directories here
- lib.add_file('cheese-2.0.2.egg-info')
- lib.add_file('nut-funkyversion.egg-info')
- lib.add_file('strawberry-0.6.egg')
- lib.add_file('truffles-5.0.egg-info')
- lib.add_file('babar.cfg')
- lib.add_file('babar.png')
- if dir=="data" and parent.physical=="test_email":
- # This should contain all non-.svn files listed in subversion
- for f in os.listdir(lib.absolute):
- if f.endswith(".txt") or f==".svn":continue
- if f.endswith(".au") or f.endswith(".gif"):
- lib.add_file(f)
+ has_py = False
+ for name, subdir in files.items():
+ if subdir is None:
+ assert os.path.isfile(os.path.join(lib.absolute, name))
+ if name == 'README':
+ lib.add_file("README.txt", src="README")
else:
- print("WARNING: New file %s in test/test_email/data" % f)
- if dir=='tests' and parent.physical == 'packaging':
- lib.add_file('SETUPTOOLS-PKG-INFO2')
- lib.add_file('SETUPTOOLS-PKG-INFO')
- lib.add_file('PKG-INFO')
- for f in os.listdir(lib.absolute):
- if os.path.isdir(os.path.join(lib.absolute, f)):
- pydirs.append((lib, f))
- for d in dirs:
- d.check_unpackaged()
+ lib.add_file(name)
+ has_py = has_py or name.endswith(".py") or name.endswith(".pyw")
+ else:
+ assert os.path.isdir(os.path.join(lib.absolute, name))
+ pydirs.append((lib, name, subdir, feature))
+
+ if has_py:
+ lib.remove_pyc()
# Add DLLs
default_feature.set_current()
lib = DLLs
diff --git a/Tools/msi/uuids.py b/Tools/msi/uuids.py
deleted file mode 100644
index b401b29..0000000
--- a/Tools/msi/uuids.py
+++ /dev/null
@@ -1,38 +0,0 @@
-# This should be extended for each Python release.
-# The product code must change whenever the name of the MSI file
-# changes, and when new component codes are issued for existing
-# components. See "Changing the Product Code". As we change the
-# component codes with every build, we need a new product code
-# each time. For intermediate (snapshot) releases, they are automatically
-# generated. For official releases, we record the product codes,
-# so people can refer to them.
-product_codes = {
- '3.1.101': '{c423eada-c498-4d51-9eb4-bfeae647e0a0}', # 3.1a1
- '3.1.102': '{f6e199bf-dc64-42f3-87d4-1525991a013e}', # 3.1a2
- '3.1.111': '{c3c82893-69b2-4676-8554-1b6ee6c191e9}', # 3.1b1
- '3.1.121': '{da2b5170-12f3-4d99-8a1f-54926cca7acd}', # 3.1c1
- '3.1.122': '{bceb5133-e2ee-4109-951f-ac7e941a1692}', # 3.1c2
- '3.1.150': '{3ad61ee5-81d2-4d7e-adef-da1dd37277d1}', # 3.1.0
- '3.1.1121':'{5782f957-6d49-41d4-bad0-668715dfd638}', # 3.1.1c1
- '3.1.1150':'{7ff90460-89b7-435b-b583-b37b2815ccc7}', # 3.1.1
- '3.1.2121':'{ec45624a-378c-43be-91f3-3f7a59b0d90c}', # 3.1.2c1
- '3.1.2150':'{d40af016-506c-43fb-a738-bd54fa8c1e85}', # 3.1.2
- '3.2.101' :'{b411f168-7a36-4fff-902c-a554d1c78a4f}', # 3.2a1
- '3.2.102' :'{79ff73b7-8359-410f-b9c5-152d2026f8c8}', # 3.2a2
- '3.2.103' :'{e7635c65-c221-4b9b-b70a-5611b8369d77}', # 3.2a3
- '3.2.104' :'{748cd139-75b8-4ca8-98a7-58262298181e}', # 3.2a4
- '3.2.111' :'{20bfc16f-c7cd-4fc0-8f96-9914614a3c50}', # 3.2b1
- '3.2.112' :'{0e350c98-8d73-4993-b686-cfe87160046e}', # 3.2b2
- '3.2.121' :'{2094968d-7583-47f6-a7fd-22304532e09f}', # 3.2rc1
- '3.2.122' :'{4f3edfa6-cf70-469a-825f-e1206aa7f412}', # 3.2rc2
- '3.2.123' :'{90c673d7-8cfd-4969-9816-f7d70bad87f3}', # 3.2rc3
- '3.2.150' :'{b2042d5e-986d-44ec-aee3-afe4108ccc93}', # 3.2.0
- '3.2.1121':'{4f90de4a-83dd-4443-b625-ca130ff361dd}', # 3.2.1rc1
- '3.2.1122':'{dc5eb04d-ff8a-4bed-8f96-23942fd59e5f}', # 3.2.1rc2
- '3.2.1150':'{34b2530c-6349-4292-9dc3-60bda4aed93c}', # 3.2.1
- '3.2.2121':'{DFB29A53-ACC4-44e6-85A6-D0DA26FE8E4E}', # 3.2.2rc1
- '3.2.2150':'{4CDE3168-D060-4b7c-BC74-4D8F9BB01AFD}', # 3.2.2
- '3.2.3121':'{B8E8CFF7-E4C6-4a7c-9F06-BB3A8B75DDA8}', # 3.2.3rc1
- '3.2.3150':'{789C9644-9F82-44d3-B4CA-AC31F46F5882}', # 3.2.3
-
-}