merge 3.5 (#25060)
diff --git a/Doc/library/collections.rst b/Doc/library/collections.rst
index 8121cc4..f820748 100644
--- a/Doc/library/collections.rst
+++ b/Doc/library/collections.rst
@@ -962,6 +962,9 @@
constructor that is convenient for use cases where named tuples are being
subclassed.
+ * :meth:`types.SimpleNamespace` for a mutable namespace based on an underlying
+ dictionary instead of a tuple.
+
:class:`OrderedDict` objects
----------------------------
diff --git a/Doc/library/datetime.rst b/Doc/library/datetime.rst
index 976cd49..5c659e7 100644
--- a/Doc/library/datetime.rst
+++ b/Doc/library/datetime.rst
@@ -1734,10 +1734,7 @@
otherwise :exc:`ValueError` is raised.
The *name* argument is optional. If specified it must be a string that
- is used as the value returned by the ``tzname(dt)`` method. Otherwise,
- ``tzname(dt)`` returns a string 'UTCsHH:MM', where s is the sign of
- *offset*, HH and MM are two digits of ``offset.hours`` and
- ``offset.minutes`` respectively.
+ will be used as the value returned by the :meth:`datetime.tzname` method.
.. versionadded:: 3.2
@@ -1750,11 +1747,19 @@
.. method:: timezone.tzname(dt)
- Return the fixed value specified when the :class:`timezone` instance is
- constructed or a string 'UTCsHH:MM', where s is the sign of
- *offset*, HH and MM are two digits of ``offset.hours`` and
+ Return the fixed value specified when the :class:`timezone` instance
+ is constructed. If *name* is not provided in the constructor, the
+ name returned by ``tzname(dt)`` is generated from the value of the
+ ``offset`` as follows. If *offset* is ``timedelta(0)``, the name
+ is "UTC", otherwise it is a string 'UTC±HH:MM', where ± is the sign
+ of ``offset``, HH and MM are two digits of ``offset.hours`` and
``offset.minutes`` respectively.
+ .. versionchanged:: 3.6
+ Name generated from ``offset=timedelta(0)`` is now plain 'UTC', not
+ 'UTC+00:00'.
+
+
.. method:: timezone.dst(dt)
Always returns ``None``.
diff --git a/Doc/library/inspect.rst b/Doc/library/inspect.rst
index 26a2913..af0422f 100644
--- a/Doc/library/inspect.rst
+++ b/Doc/library/inspect.rst
@@ -228,24 +228,6 @@
listed in the metaclass' custom :meth:`__dir__`.
-.. function:: getmoduleinfo(path)
-
- Returns a :term:`named tuple` ``ModuleInfo(name, suffix, mode, module_type)``
- of values that describe how Python will interpret the file identified by
- *path* if it is a module, or ``None`` if it would not be identified as a
- module. In that tuple, *name* is the name of the module without the name of
- any enclosing package, *suffix* is the trailing part of the file name (which
- may not be a dot-delimited extension), *mode* is the :func:`open` mode that
- would be used (``'r'`` or ``'rb'``), and *module_type* is an integer giving
- the type of the module. *module_type* will have a value which can be
- compared to the constants defined in the :mod:`imp` module; see the
- documentation for that module for more information on module types.
-
- .. deprecated:: 3.3
- You may check the file path's suffix against the supported suffixes
- listed in :mod:`importlib.machinery` to infer the same information.
-
-
.. function:: getmodulename(path)
Return the name of the module named by the file *path*, without including the
@@ -259,8 +241,7 @@
still return ``None``.
.. versionchanged:: 3.3
- This function is now based directly on :mod:`importlib` rather than the
- deprecated :func:`getmoduleinfo`.
+ The function is based directly on :mod:`importlib`.
.. function:: ismodule(object)
@@ -809,24 +790,6 @@
classes using multiple inheritance and their descendants will appear multiple
times.
-
-.. function:: getargspec(func)
-
- Get the names and default values of a Python function's arguments. A
- :term:`named tuple` ``ArgSpec(args, varargs, keywords, defaults)`` is
- returned. *args* is a list of the argument names. *varargs* and *keywords*
- are the names of the ``*`` and ``**`` arguments or ``None``. *defaults* is a
- tuple of default argument values or ``None`` if there are no default
- arguments; if this tuple has *n* elements, they correspond to the last
- *n* elements listed in *args*.
-
- .. deprecated:: 3.0
- Use :func:`signature` and
- :ref:`Signature Object <inspect-signature-object>`, which provide a
- better introspecting API for callables. This function will be removed
- in Python 3.6.
-
-
.. function:: getfullargspec(func)
Get the names and default values of a Python function's arguments. A
@@ -843,8 +806,6 @@
from kwonlyargs to defaults. *annotations* is a dictionary mapping argument
names to annotations.
- The first four items in the tuple correspond to :func:`getargspec`.
-
.. versionchanged:: 3.4
This function is now based on :func:`signature`, but still ignores
``__wrapped__`` attributes and includes the already bound first
@@ -873,7 +834,7 @@
.. function:: formatargspec(args[, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, annotations[, formatarg, formatvarargs, formatvarkw, formatvalue, formatreturns, formatannotations]])
Format a pretty argument spec from the values returned by
- :func:`getargspec` or :func:`getfullargspec`.
+ :func:`getfullargspec`.
The first seven arguments are (``args``, ``varargs``, ``varkw``,
``defaults``, ``kwonlyargs``, ``kwonlydefaults``, ``annotations``).
diff --git a/Doc/library/multiprocessing.rst b/Doc/library/multiprocessing.rst
index 8703f8f..e74430d 100644
--- a/Doc/library/multiprocessing.rst
+++ b/Doc/library/multiprocessing.rst
@@ -869,8 +869,13 @@
.. function:: cpu_count()
- Return the number of CPUs in the system. May raise
- :exc:`NotImplementedError`.
+ Return the number of CPUs in the system.
+
+ This number is not equivalent to the number of CPUs the current process can
+ use. The number of usable CPUs can be obtained with
+ ``len(os.sched_getaffinity(0))``
+
+ May raise :exc:`NotImplementedError`.
.. seealso::
:func:`os.cpu_count`
diff --git a/Doc/library/operator.rst b/Doc/library/operator.rst
index c01e63b..0695391 100644
--- a/Doc/library/operator.rst
+++ b/Doc/library/operator.rst
@@ -333,6 +333,21 @@
[('orange', 1), ('banana', 2), ('apple', 3), ('pear', 5)]
+.. data:: subscript
+
+ A helper to turn subscript notation into indexing objects. This can be
+ used to create item access patterns ahead of time to pass them into
+ various subscriptable objects.
+
+ For example:
+
+ * ``subscript[5] == 5``
+ * ``subscript[3:7:2] == slice(3, 7, 2)``
+ * ``subscript[5, 8] == (5, 8)``
+
+ .. versionadded:: 3.6
+
+
.. function:: methodcaller(name[, args...])
Return a callable object that calls the method *name* on its operand. If
diff --git a/Doc/library/os.rst b/Doc/library/os.rst
index 13f83c6..1e4bcb8 100644
--- a/Doc/library/os.rst
+++ b/Doc/library/os.rst
@@ -3597,6 +3597,11 @@
Return the number of CPUs in the system. Returns None if undetermined.
+ This number is not equivalent to the number of CPUs the current process can
+ use. The number of usable CPUs can be obtained with
+ ``len(os.sched_getaffinity(0))``
+
+
.. versionadded:: 3.4
diff --git a/Doc/library/time.rst b/Doc/library/time.rst
index 3d335c8..73436ca 100644
--- a/Doc/library/time.rst
+++ b/Doc/library/time.rst
@@ -634,11 +634,11 @@
it is possible to refer to February 29.
:samp:`M{m}.{n}.{d}`
- The *d*'th day (0 <= *d* <= 6) or week *n* of month *m* of the year (1
+ The *d*'th day (0 <= *d* <= 6) of week *n* of month *m* of the year (1
<= *n* <= 5, 1 <= *m* <= 12, where week 5 means "the last *d* day in
month *m*" which may occur in either the fourth or the fifth
week). Week 1 is the first week in which the *d*'th day occurs. Day
- zero is Sunday.
+ zero is a Sunday.
``time`` has the same format as ``offset`` except that no leading sign
('-' or '+') is allowed. The default, if time is not given, is 02:00:00.
diff --git a/Doc/library/urllib.parse.rst b/Doc/library/urllib.parse.rst
index 40098d0..7c075ad 100644
--- a/Doc/library/urllib.parse.rst
+++ b/Doc/library/urllib.parse.rst
@@ -115,8 +115,9 @@
| | | if present | |
+------------------+-------+--------------------------+----------------------+
- See section :ref:`urlparse-result-object` for more information on the result
- object.
+ Reading the :attr:`port` attribute will raise a :exc:`ValueError` if
+ an invalid port is specified in the URL. See section
+ :ref:`urlparse-result-object` for more information on the result object.
.. versionchanged:: 3.2
Added IPv6 URL parsing capabilities.
@@ -126,6 +127,10 @@
false), in accordance with :rfc:`3986`. Previously, a whitelist of
schemes that support fragments existed.
+ .. versionchanged:: 3.6
+ Out-of-range port numbers now raise :exc:`ValueError`, instead of
+ returning :const:`None`.
+
.. function:: parse_qs(qs, keep_blank_values=False, strict_parsing=False, encoding='utf-8', errors='replace')
@@ -228,8 +233,13 @@
| | | if present | |
+------------------+-------+-------------------------+----------------------+
- See section :ref:`urlparse-result-object` for more information on the result
- object.
+ Reading the :attr:`port` attribute will raise a :exc:`ValueError` if
+ an invalid port is specified in the URL. See section
+ :ref:`urlparse-result-object` for more information on the result object.
+
+ .. versionchanged:: 3.6
+ Out-of-range port numbers now raise :exc:`ValueError`, instead of
+ returning :const:`None`.
.. function:: urlunsplit(parts)
diff --git a/Doc/reference/compound_stmts.rst b/Doc/reference/compound_stmts.rst
index 01cfd6d..00e6476 100644
--- a/Doc/reference/compound_stmts.rst
+++ b/Doc/reference/compound_stmts.rst
@@ -471,10 +471,10 @@
decorators: `decorator`+
decorator: "@" `dotted_name` ["(" [`parameter_list` [","]] ")"] NEWLINE
dotted_name: `identifier` ("." `identifier`)*
- parameter_list: (`defparameter` ",")*
- : | "*" [`parameter`] ("," `defparameter`)* ["," "**" `parameter`]
- : | "**" `parameter`
- : | `defparameter` [","] )
+ parameter_list: `defparameter` ("," `defparameter`)* ["," [`parameter_list_starargs`]]
+ : | `parameter_list_starargs`
+ parameter_list_starargs: "*" [`parameter`] ("," `defparameter`)* ["," ["**" `parameter` [","]]]
+ : | "**" `parameter` [","]
parameter: `identifier` [":" `expression`]
defparameter: `parameter` ["=" `expression`]
funcname: `identifier`
diff --git a/Doc/tools/extensions/pyspecific.py b/Doc/tools/extensions/pyspecific.py
index d44b052..9b78184 100644
--- a/Doc/tools/extensions/pyspecific.py
+++ b/Doc/tools/extensions/pyspecific.py
@@ -34,7 +34,7 @@
ISSUE_URI = 'https://bugs.python.org/issue%s'
-SOURCE_URI = 'https://hg.python.org/cpython/file/3.5/%s'
+SOURCE_URI = 'https://hg.python.org/cpython/file/default/%s'
# monkey-patch reST parser to disable alphabetic and roman enumerated lists
from docutils.parsers.rst.states import Body
diff --git a/Doc/tutorial/interpreter.rst b/Doc/tutorial/interpreter.rst
index d5789a6..db0be32 100644
--- a/Doc/tutorial/interpreter.rst
+++ b/Doc/tutorial/interpreter.rst
@@ -1,4 +1,4 @@
-.. _tut-using:
+3.6.. _tut-using:
****************************
Using the Python Interpreter
@@ -10,13 +10,13 @@
Invoking the Interpreter
========================
-The Python interpreter is usually installed as :file:`/usr/local/bin/python3.5`
+The Python interpreter is usually installed as :file:`/usr/local/bin/python3.6`
on those machines where it is available; putting :file:`/usr/local/bin` in your
Unix shell's search path makes it possible to start it by typing the command:
.. code-block:: text
- python3.5
+ python3.6
to the shell. [#]_ Since the choice of the directory where the interpreter lives
is an installation option, other places are possible; check with your local
@@ -24,11 +24,11 @@
popular alternative location.)
On Windows machines, the Python installation is usually placed in
-:file:`C:\\Python35`, though you can change this when you're running the
+:file:`C:\\Python36`, though you can change this when you're running the
installer. To add this directory to your path, you can type the following
command into the command prompt in a DOS box::
- set path=%path%;C:\python35
+ set path=%path%;C:\python36
Typing an end-of-file character (:kbd:`Control-D` on Unix, :kbd:`Control-Z` on
Windows) at the primary prompt causes the interpreter to exit with a zero exit
@@ -96,8 +96,8 @@
prints a welcome message stating its version number and a copyright notice
before printing the first prompt::
- $ python3.5
- Python 3.5 (default, Sep 16 2015, 09:25:04)
+ $ python3.6
+ Python 3.6 (default, Sep 16 2015, 09:25:04)
[GCC 4.8.2] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>
diff --git a/Doc/tutorial/stdlib.rst b/Doc/tutorial/stdlib.rst
index 0954eba..f9ed46d 100644
--- a/Doc/tutorial/stdlib.rst
+++ b/Doc/tutorial/stdlib.rst
@@ -15,7 +15,7 @@
>>> import os
>>> os.getcwd() # Return the current working directory
- 'C:\\Python35'
+ 'C:\\Python36'
>>> os.chdir('/server/accesslogs') # Change current working directory
>>> os.system('mkdir today') # Run the command mkdir in the system shell
0
diff --git a/Doc/tutorial/stdlib2.rst b/Doc/tutorial/stdlib2.rst
index f7d2a0a..71194b0 100644
--- a/Doc/tutorial/stdlib2.rst
+++ b/Doc/tutorial/stdlib2.rst
@@ -277,7 +277,7 @@
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
d['primary'] # entry was automatically removed
- File "C:/python35/lib/weakref.py", line 46, in __getitem__
+ File "C:/python36/lib/weakref.py", line 46, in __getitem__
o = self.data[key]()
KeyError: 'primary'
diff --git a/Doc/whatsnew/3.6.rst b/Doc/whatsnew/3.6.rst
new file mode 100644
index 0000000..48ff38a
--- /dev/null
+++ b/Doc/whatsnew/3.6.rst
@@ -0,0 +1,179 @@
+****************************
+ What's New In Python 3.6
+****************************
+
+:Release: |release|
+:Date: |today|
+
+.. Rules for maintenance:
+
+ * Anyone can add text to this document. Do not spend very much time
+ on the wording of your changes, because your text will probably
+ get rewritten to some degree.
+
+ * The maintainer will go through Misc/NEWS periodically and add
+ changes; it's therefore more important to add your changes to
+ Misc/NEWS than to this file.
+
+ * This is not a complete list of every single change; completeness
+ is the purpose of Misc/NEWS. Some changes I consider too small
+ or esoteric to include. If such a change is added to the text,
+ I'll just remove it. (This is another reason you shouldn't spend
+ too much time on writing your addition.)
+
+ * If you want to draw your new text to the attention of the
+ maintainer, add 'XXX' to the beginning of the paragraph or
+ section.
+
+ * It's OK to just add a fragmentary note about a change. For
+ example: "XXX Describe the transmogrify() function added to the
+ socket module." The maintainer will research the change and
+ write the necessary text.
+
+ * You can comment out your additions if you like, but it's not
+ necessary (especially when a final release is some months away).
+
+ * Credit the author of a patch or bugfix. Just the name is
+ sufficient; the e-mail address isn't necessary.
+
+ * It's helpful to add the bug/patch number as a comment:
+
+ XXX Describe the transmogrify() function added to the socket
+ module.
+ (Contributed by P.Y. Developer in :issue:`12345`.)
+
+ This saves the maintainer the effort of going through the Mercurial log
+ when researching a change.
+
+This article explains the new features in Python 3.6, compared to 3.5.
+
+For full details, see the :source:`Misc/NEWS` file.
+
+.. note::
+
+ Prerelease users should be aware that this document is currently in draft
+ form. It will be updated substantially as Python 3.6 moves towards release,
+ so it's worth checking back even after reading earlier versions.
+
+
+Summary -- Release highlights
+=============================
+
+.. This section singles out the most important changes in Python 3.6.
+ Brevity is key.
+
+* None yet.
+
+.. PEP-sized items next.
+
+.. _pep-4XX:
+
+.. PEP 4XX: Virtual Environments
+.. =============================
+
+
+.. (Implemented by Foo Bar.)
+
+.. .. seealso::
+
+ :pep:`4XX` - Python Virtual Environments
+ PEP written by Carl Meyer
+
+
+Other Language Changes
+======================
+
+* None yet.
+
+
+New Modules
+===========
+
+* None yet.
+
+
+Improved Modules
+================
+
+operator
+--------
+
+* New object :data:`operator.subscript` makes it easier to create complex
+ indexers. For example: ``subscript[0:10:2] == slice(0, 10, 2)``
+ (Contributed by Joe Jevnik in :issue:`24379`.)
+
+
+Optimizations
+=============
+
+* None yet.
+
+
+Build and C API Changes
+=======================
+
+* None yet.
+
+
+Deprecated
+==========
+
+New Keywords
+------------
+
+``async`` and ``await`` are not recommended to be used as variable, class,
+function or module names. Introduced by :pep:`492` in Python 3.5, they will
+become proper keywords in Python 3.7.
+
+
+Deprecated Python modules, functions and methods
+------------------------------------------------
+
+* None yet.
+
+
+Deprecated functions and types of the C API
+-------------------------------------------
+
+* None yet.
+
+
+Deprecated features
+-------------------
+
+* None yet.
+
+
+Removed
+=======
+
+API and Feature Removals
+------------------------
+
+* ``inspect.getargspec()`` was removed (was deprecated since CPython 3.0).
+ :func:`inspect.getfullargspec` is an almost drop in replacement.
+
+* ``inspect.getmoduleinfo()`` was removed (was deprecated since CPython 3.3).
+ :func:`inspect.getmodulename` should be used for obtaining the module
+ name for a given path.
+
+
+Porting to Python 3.6
+=====================
+
+This section lists previously described changes and other bugfixes
+that may require changes to your code.
+
+Changes in the Python API
+-------------------------
+
+* Reading the :attr:`~urllib.parse.SplitResult.port` attribute of
+ :func:`urllib.parse.urlsplit` and :func:`~urllib.parse.urlparse` results
+ now raises :exc:`ValueError` for out-of-range values, rather than
+ returning :const:`None`. See :issue:`20059`.
+
+
+Changes in the C API
+--------------------
+
+* None yet.
diff --git a/Doc/whatsnew/index.rst b/Doc/whatsnew/index.rst
index edb5502..7c92524 100644
--- a/Doc/whatsnew/index.rst
+++ b/Doc/whatsnew/index.rst
@@ -11,6 +11,7 @@
.. toctree::
:maxdepth: 2
+ 3.6.rst
3.5.rst
3.4.rst
3.3.rst
diff --git a/Grammar/Grammar b/Grammar/Grammar
index 99fcea0..14bdecd 100644
--- a/Grammar/Grammar
+++ b/Grammar/Grammar
@@ -27,13 +27,18 @@
funcdef: 'def' NAME parameters ['->' test] ':' suite
parameters: '(' [typedargslist] ')'
-typedargslist: (tfpdef ['=' test] (',' tfpdef ['=' test])* [','
- ['*' [tfpdef] (',' tfpdef ['=' test])* [',' '**' tfpdef] | '**' tfpdef]]
- | '*' [tfpdef] (',' tfpdef ['=' test])* [',' '**' tfpdef] | '**' tfpdef)
+typedargslist: (tfpdef ['=' test] (',' tfpdef ['=' test])* [',' [
+ '*' [tfpdef] (',' tfpdef ['=' test])* [',' ['**' tfpdef [',']]]
+ | '**' tfpdef [',']]]
+ | '*' [tfpdef] (',' tfpdef ['=' test])* [',' ['**' tfpdef [',']]]
+ | '**' tfpdef [','])
tfpdef: NAME [':' test]
-varargslist: (vfpdef ['=' test] (',' vfpdef ['=' test])* [','
- ['*' [vfpdef] (',' vfpdef ['=' test])* [',' '**' vfpdef] | '**' vfpdef]]
- | '*' [vfpdef] (',' vfpdef ['=' test])* [',' '**' vfpdef] | '**' vfpdef)
+varargslist: (vfpdef ['=' test] (',' vfpdef ['=' test])* [',' [
+ '*' [vfpdef] (',' vfpdef ['=' test])* [',' ['**' vfpdef [',']]]
+ | '**' vfpdef [',']]]
+ | '*' [vfpdef] (',' vfpdef ['=' test])* [',' ['**' vfpdef [',']]]
+ | '**' vfpdef [',']
+)
vfpdef: NAME
stmt: simple_stmt | compound_stmt
diff --git a/Include/patchlevel.h b/Include/patchlevel.h
index f0ca3a1..246eba8 100644
--- a/Include/patchlevel.h
+++ b/Include/patchlevel.h
@@ -17,13 +17,13 @@
/* Version parsed out into numeric values */
/*--start constants--*/
#define PY_MAJOR_VERSION 3
-#define PY_MINOR_VERSION 5
+#define PY_MINOR_VERSION 6
#define PY_MICRO_VERSION 0
-#define PY_RELEASE_LEVEL PY_RELEASE_LEVEL_GAMMA
-#define PY_RELEASE_SERIAL 4
+#define PY_RELEASE_LEVEL PY_RELEASE_LEVEL_ALPHA
+#define PY_RELEASE_SERIAL 0
/* Version as a string */
-#define PY_VERSION "3.5.0rc4+"
+#define PY_VERSION "3.6.0a0"
/*--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 027c3d8..5de756a 100644
--- a/Include/pytime.h
+++ b/Include/pytime.h
@@ -30,7 +30,10 @@
_PyTime_ROUND_FLOOR=0,
/* Round towards infinity (+inf).
For example, used for timeout to wait "at least" N seconds. */
- _PyTime_ROUND_CEILING
+ _PyTime_ROUND_CEILING=1,
+ /* Round to nearest with ties going to nearest even integer.
+ For example, used to round from a Python float. */
+ _PyTime_ROUND_HALF_EVEN
} _PyTime_round_t;
/* Convert a time_t to a PyLong. */
diff --git a/Include/setobject.h b/Include/setobject.h
index f17bc1b..87ec1c8 100644
--- a/Include/setobject.h
+++ b/Include/setobject.h
@@ -10,12 +10,13 @@
/* There are three kinds of entries in the table:
-1. Unused: key == NULL
-2. Active: key != NULL and key != dummy
-3. Dummy: key == dummy
+1. Unused: key == NULL and hash == 0
+2. Dummy: key == dummy and hash == -1
+3. Active: key != NULL and key != dummy and hash != -1
-The hash field of Unused slots have no meaning.
-The hash field of Dummny slots are set to -1
+The hash field of Unused slots is always zero.
+
+The hash field of Dummy slots are set to -1
meaning that dummy entries can be detected by
either entry->key==dummy or by entry->hash==-1.
*/
diff --git a/Include/unicodeobject.h b/Include/unicodeobject.h
index 4ba6328..33e8f19 100644
--- a/Include/unicodeobject.h
+++ b/Include/unicodeobject.h
@@ -2261,6 +2261,10 @@
/* Clear all static strings. */
PyAPI_FUNC(void) _PyUnicode_ClearStaticStrings(void);
+/* Fast equality check when the inputs are known to be exact unicode types
+ and where the hash values are equal (i.e. a very probable match) */
+PyAPI_FUNC(int) _PyUnicode_EQ(PyObject *, PyObject *);
+
#ifdef __cplusplus
}
#endif
diff --git a/Lib/_pyio.py b/Lib/_pyio.py
index f47df91..f472256 100644
--- a/Lib/_pyio.py
+++ b/Lib/_pyio.py
@@ -182,8 +182,8 @@
text = "t" in modes
binary = "b" in modes
if "U" in modes:
- if creating or writing or appending:
- raise ValueError("can't use U and writing mode at once")
+ if creating or writing or appending or updating:
+ raise ValueError("mode U cannot be combined with 'x', 'w', 'a', or '+'")
import warnings
warnings.warn("'U' mode is deprecated",
DeprecationWarning, 2)
diff --git a/Lib/aifc.py b/Lib/aifc.py
index 7ebdbeb..692d0bf 100644
--- a/Lib/aifc.py
+++ b/Lib/aifc.py
@@ -257,6 +257,15 @@
_aifc_params = namedtuple('_aifc_params',
'nchannels sampwidth framerate nframes comptype compname')
+_aifc_params.nchannels.__doc__ = 'Number of audio channels (1 for mono, 2 for stereo)'
+_aifc_params.sampwidth.__doc__ = 'Sample width in bytes'
+_aifc_params.framerate.__doc__ = 'Sampling frequency'
+_aifc_params.nframes.__doc__ = 'Number of audio frames'
+_aifc_params.comptype.__doc__ = 'Compression type ("NONE" for AIFF files)'
+_aifc_params.compname.__doc__ = ("""\
+A human-readable version of the compression type
+('not compressed' for AIFF files)""")
+
class Aifc_read:
# Variables used in this class:
diff --git a/Lib/argparse.py b/Lib/argparse.py
index 9a06719..cc53841 100644
--- a/Lib/argparse.py
+++ b/Lib/argparse.py
@@ -118,10 +118,16 @@
def __repr__(self):
type_name = type(self).__name__
arg_strings = []
+ star_args = {}
for arg in self._get_args():
arg_strings.append(repr(arg))
for name, value in self._get_kwargs():
- arg_strings.append('%s=%r' % (name, value))
+ if name.isidentifier():
+ arg_strings.append('%s=%r' % (name, value))
+ else:
+ star_args[name] = value
+ if star_args:
+ arg_strings.append('**%s' % repr(star_args))
return '%s(%s)' % (type_name, ', '.join(arg_strings))
def _get_kwargs(self):
diff --git a/Lib/datetime.py b/Lib/datetime.py
index db13b12..b734a74 100644
--- a/Lib/datetime.py
+++ b/Lib/datetime.py
@@ -316,6 +316,7 @@
return q
+
class timedelta:
"""Represent the difference between two datetime objects.
@@ -1366,6 +1367,26 @@
return self._tzinfo
@classmethod
+ def _fromtimestamp(cls, t, utc, tz):
+ """Construct a datetime from a POSIX timestamp (like time.time()).
+
+ A timezone info object may be passed in as well.
+ """
+ frac, t = _math.modf(t)
+ us = round(frac * 1e6)
+ if us >= 1000000:
+ t += 1
+ us -= 1000000
+ elif us < 0:
+ t -= 1
+ us += 1000000
+
+ converter = _time.gmtime if utc else _time.localtime
+ y, m, d, hh, mm, ss, weekday, jday, dst = converter(t)
+ ss = min(ss, 59) # clamp out leap seconds if the platform has them
+ return cls(y, m, d, hh, mm, ss, us, tz)
+
+ @classmethod
def fromtimestamp(cls, t, tz=None):
"""Construct a datetime from a POSIX timestamp (like time.time()).
@@ -1373,21 +1394,7 @@
"""
_check_tzinfo_arg(tz)
- converter = _time.localtime if tz is None else _time.gmtime
-
- t, frac = divmod(t, 1.0)
- us = int(frac * 1e6)
-
- # If timestamp is less than one microsecond smaller than a
- # full second, us can be rounded up to 1000000. In this case,
- # roll over to seconds, otherwise, ValueError is raised
- # by the constructor.
- if us == 1000000:
- t += 1
- us = 0
- y, m, d, hh, mm, ss, weekday, jday, dst = converter(t)
- ss = min(ss, 59) # clamp out leap seconds if the platform has them
- result = cls(y, m, d, hh, mm, ss, us, tz)
+ result = cls._fromtimestamp(t, tz is not None, tz)
if tz is not None:
result = tz.fromutc(result)
return result
@@ -1395,19 +1402,7 @@
@classmethod
def utcfromtimestamp(cls, t):
"""Construct a naive UTC datetime from a POSIX timestamp."""
- t, frac = divmod(t, 1.0)
- us = int(frac * 1e6)
-
- # If timestamp is less than one microsecond smaller than a
- # full second, us can be rounded up to 1000000. In this case,
- # roll over to seconds, otherwise, ValueError is raised
- # by the constructor.
- if us == 1000000:
- t += 1
- us = 0
- y, m, d, hh, mm, ss, weekday, jday, dst = _time.gmtime(t)
- ss = min(ss, 59) # clamp out leap seconds if the platform has them
- return cls(y, m, d, hh, mm, ss, us)
+ return cls._fromtimestamp(t, True, None)
@classmethod
def now(cls, tz=None):
@@ -1918,6 +1913,8 @@
@staticmethod
def _name_from_offset(delta):
+ if not delta:
+ return 'UTC'
if delta < timedelta(0):
sign = '-'
delta = -delta
diff --git a/Lib/dis.py b/Lib/dis.py
index af37cdf..3540b47 100644
--- a/Lib/dis.py
+++ b/Lib/dis.py
@@ -162,6 +162,15 @@
_Instruction = collections.namedtuple("_Instruction",
"opname opcode arg argval argrepr offset starts_line is_jump_target")
+_Instruction.opname.__doc__ = "Human readable name for operation"
+_Instruction.opcode.__doc__ = "Numeric code for operation"
+_Instruction.arg.__doc__ = "Numeric argument to operation (if any), otherwise None"
+_Instruction.argval.__doc__ = "Resolved arg value (if known), otherwise same as arg"
+_Instruction.argrepr.__doc__ = "Human readable description of operation argument"
+_Instruction.offset.__doc__ = "Start index of operation within bytecode sequence"
+_Instruction.starts_line.__doc__ = "Line started by this opcode (if any), otherwise None"
+_Instruction.is_jump_target.__doc__ = "True if other code jumps to here, otherwise False"
+
class Instruction(_Instruction):
"""Details for a bytecode operation
diff --git a/Lib/distutils/core.py b/Lib/distutils/core.py
index f05b34b..d603d4a 100644
--- a/Lib/distutils/core.py
+++ b/Lib/distutils/core.py
@@ -204,16 +204,15 @@
global _setup_stop_after, _setup_distribution
_setup_stop_after = stop_after
- save_argv = sys.argv
+ save_argv = sys.argv.copy()
g = {'__file__': script_name}
- l = {}
try:
try:
sys.argv[0] = script_name
if script_args is not None:
sys.argv[1:] = script_args
with open(script_name, 'rb') as f:
- exec(f.read(), g, l)
+ exec(f.read(), g)
finally:
sys.argv = save_argv
_setup_stop_after = None
diff --git a/Lib/distutils/tests/test_core.py b/Lib/distutils/tests/test_core.py
index 41321f7..57856f1 100644
--- a/Lib/distutils/tests/test_core.py
+++ b/Lib/distutils/tests/test_core.py
@@ -28,6 +28,21 @@
setup()
"""
+setup_does_nothing = """\
+from distutils.core import setup
+setup()
+"""
+
+
+setup_defines_subclass = """\
+from distutils.core import setup
+from distutils.command.install import install as _install
+
+class install(_install):
+ sub_commands = _install.sub_commands + ['cmd']
+
+setup(cmdclass={'install': install})
+"""
class CoreTestCase(support.EnvironGuard, unittest.TestCase):
@@ -65,6 +80,21 @@
distutils.core.run_setup(
self.write_setup(setup_using___file__))
+ def test_run_setup_preserves_sys_argv(self):
+ # Make sure run_setup does not clobber sys.argv
+ argv_copy = sys.argv.copy()
+ distutils.core.run_setup(
+ self.write_setup(setup_does_nothing))
+ self.assertEqual(sys.argv, argv_copy)
+
+ def test_run_setup_defines_subclass(self):
+ # Make sure the script can use __file__; if that's missing, the test
+ # setup.py script will raise NameError.
+ dist = distutils.core.run_setup(
+ self.write_setup(setup_defines_subclass))
+ install = dist.get_command_obj('install')
+ self.assertIn('cmd', install.sub_commands)
+
def test_run_setup_uses_current_dir(self):
# This tests that the setup script is run with the current directory
# as its own current directory; this was temporarily broken by a
diff --git a/Lib/http/client.py b/Lib/http/client.py
index 80c80cf..155c2e3 100644
--- a/Lib/http/client.py
+++ b/Lib/http/client.py
@@ -405,6 +405,7 @@
self.fp.flush()
def readable(self):
+ """Always returns True"""
return True
# End of "raw stream" methods
@@ -452,6 +453,10 @@
return s
def readinto(self, b):
+ """Read up to len(b) bytes into bytearray b and return the number
+ of bytes read.
+ """
+
if self.fp is None:
return 0
@@ -683,6 +688,17 @@
return self.fp.fileno()
def getheader(self, name, default=None):
+ '''Returns the value of the header matching *name*.
+
+ If there are multiple matching headers, the values are
+ combined into a single string separated by commas and spaces.
+
+ If no matching header is found, returns *default* or None if
+ the *default* is not specified.
+
+ If the headers are unknown, raises http.client.ResponseNotReady.
+
+ '''
if self.headers is None:
raise ResponseNotReady()
headers = self.headers.get_all(name) or default
@@ -705,12 +721,45 @@
# For compatibility with old-style urllib responses.
def info(self):
+ '''Returns an instance of the class mimetools.Message containing
+ meta-information associated with the URL.
+
+ When the method is HTTP, these headers are those returned by
+ the server at the head of the retrieved HTML page (including
+ Content-Length and Content-Type).
+
+ When the method is FTP, a Content-Length header will be
+ present if (as is now usual) the server passed back a file
+ length in response to the FTP retrieval request. A
+ Content-Type header will be present if the MIME type can be
+ guessed.
+
+ When the method is local-file, returned headers will include
+ a Date representing the file’s last-modified time, a
+ Content-Length giving file size, and a Content-Type
+ containing a guess at the file’s type. See also the
+ description of the mimetools module.
+
+ '''
return self.headers
def geturl(self):
+ '''Return the real URL of the page.
+
+ In some cases, the HTTP server redirects a client to another
+ URL. The urlopen() function handles this transparently, but in
+ some cases the caller needs to know which URL the client was
+ redirected to. The geturl() method can be used to get at this
+ redirected URL.
+
+ '''
return self.url
def getcode(self):
+ '''Return the HTTP status code that was sent with the response,
+ or None if the URL is not an HTTP URL.
+
+ '''
return self.status
class HTTPConnection:
diff --git a/Lib/inspect.py b/Lib/inspect.py
index bf4f87d..a089be6 100644
--- a/Lib/inspect.py
+++ b/Lib/inspect.py
@@ -16,7 +16,7 @@
getmodule() - determine the module that an object came from
getclasstree() - arrange classes so as to represent their hierarchy
- getargspec(), getargvalues(), getcallargs() - get info about function arguments
+ getargvalues(), getcallargs() - get info about function arguments
getfullargspec() - same, with support for Python 3 features
formatargspec(), formatargvalues() - format an argument spec
getouterframes(), getinnerframes() - get info about frames
@@ -623,23 +623,6 @@
raise TypeError('{!r} is not a module, class, method, '
'function, traceback, frame, or code object'.format(object))
-ModuleInfo = namedtuple('ModuleInfo', 'name suffix mode module_type')
-
-def getmoduleinfo(path):
- """Get the module name, suffix, mode, and module type for a given file."""
- warnings.warn('inspect.getmoduleinfo() is deprecated', DeprecationWarning,
- 2)
- with warnings.catch_warnings():
- warnings.simplefilter('ignore', PendingDeprecationWarning)
- import imp
- filename = os.path.basename(path)
- suffixes = [(-len(suffix), suffix, mode, mtype)
- for suffix, mode, mtype in imp.get_suffixes()]
- suffixes.sort() # try longest suffixes first, in case they overlap
- for neglen, suffix, mode, mtype in suffixes:
- if filename[neglen:] == suffix:
- return ModuleInfo(filename[:neglen], suffix, mode, mtype)
-
def getmodulename(path):
"""Return the module name for a given file, or None."""
fname = os.path.basename(path)
@@ -1020,31 +1003,6 @@
varkw = co.co_varnames[nargs]
return args, varargs, kwonlyargs, varkw
-
-ArgSpec = namedtuple('ArgSpec', 'args varargs keywords defaults')
-
-def getargspec(func):
- """Get the names and default values of a function's arguments.
-
- A tuple of four things is returned: (args, varargs, keywords, defaults).
- 'args' is a list of the argument names, including keyword-only argument names.
- 'varargs' and 'keywords' are the names of the * and ** arguments or None.
- 'defaults' is an n-tuple of the default values of the last n arguments.
-
- Use the getfullargspec() API for Python 3 code, as annotations
- and keyword arguments are supported. getargspec() will raise ValueError
- if the func has either annotations or keyword arguments.
- """
- warnings.warn("inspect.getargspec() is deprecated, "
- "use inspect.signature() instead", DeprecationWarning,
- stacklevel=2)
- args, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, ann = \
- getfullargspec(func)
- if kwonlyargs or ann:
- raise ValueError("Function has keyword-only arguments or annotations"
- ", use getfullargspec() API which can support them")
- return ArgSpec(args, varargs, varkw, defaults)
-
FullArgSpec = namedtuple('FullArgSpec',
'args, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, annotations')
@@ -1060,8 +1018,6 @@
'kwonlydefaults' is a dictionary mapping names from kwonlyargs to defaults.
'annotations' is a dictionary mapping argument names to annotations.
- The first four items in the tuple correspond to getargspec().
-
This function is deprecated, use inspect.signature() instead.
"""
@@ -1172,8 +1128,7 @@
formatvalue=lambda value: '=' + repr(value),
formatreturns=lambda text: ' -> ' + text,
formatannotation=formatannotation):
- """Format an argument spec from the values returned by getargspec
- or getfullargspec.
+ """Format an argument spec from the values returned by getfullargspec.
The first seven arguments are (args, varargs, varkw, defaults,
kwonlyargs, kwonlydefaults, annotations). The other five arguments
diff --git a/Lib/lib2to3/fixes/fix_types.py b/Lib/lib2to3/fixes/fix_types.py
index db34104..00327a7 100644
--- a/Lib/lib2to3/fixes/fix_types.py
+++ b/Lib/lib2to3/fixes/fix_types.py
@@ -42,7 +42,7 @@
'NotImplementedType' : 'type(NotImplemented)',
'SliceType' : 'slice',
'StringType': 'bytes', # XXX ?
- 'StringTypes' : 'str', # XXX ?
+ 'StringTypes' : '(str,)', # XXX ?
'TupleType': 'tuple',
'TypeType' : 'type',
'UnicodeType': 'str',
diff --git a/Lib/lib2to3/tests/test_fixers.py b/Lib/lib2to3/tests/test_fixers.py
index 06b0033..def9b0e 100644
--- a/Lib/lib2to3/tests/test_fixers.py
+++ b/Lib/lib2to3/tests/test_fixers.py
@@ -3322,6 +3322,10 @@
a = """type(None)"""
self.check(b, a)
+ b = "types.StringTypes"
+ a = "(str,)"
+ self.check(b, a)
+
class Test_idioms(FixerTestCase):
fixer = "idioms"
diff --git a/Lib/operator.py b/Lib/operator.py
index 0e2e53e..bc2a947 100644
--- a/Lib/operator.py
+++ b/Lib/operator.py
@@ -17,7 +17,7 @@
'is_', 'is_not', 'isub', 'itemgetter', 'itruediv', 'ixor', 'le',
'length_hint', 'lshift', 'lt', 'matmul', 'methodcaller', 'mod',
'mul', 'ne', 'neg', 'not_', 'or_', 'pos', 'pow', 'rshift',
- 'setitem', 'sub', 'truediv', 'truth', 'xor']
+ 'setitem', 'sub', 'subscript', 'truediv', 'truth', 'xor']
from builtins import abs as _abs
@@ -408,6 +408,32 @@
return a
+@object.__new__ # create a singleton instance
+class subscript:
+ """
+ A helper to turn subscript notation into indexing objects. This can be
+ used to create item access patterns ahead of time to pass them into
+ various subscriptable objects.
+
+ For example:
+ subscript[5] == 5
+ subscript[3:7:2] == slice(3, 7, 2)
+ subscript[5, 8] == (5, 8)
+ """
+ __slots__ = ()
+
+ def __new__(cls):
+ raise TypeError("cannot create '{}' instances".format(cls.__name__))
+
+ @staticmethod
+ def __getitem__(key):
+ return key
+
+ @staticmethod
+ def __reduce__():
+ return 'subscript'
+
+
try:
from _operator import *
except ImportError:
diff --git a/Lib/pydoc.py b/Lib/pydoc.py
index ee558bf..f4f2530 100755
--- a/Lib/pydoc.py
+++ b/Lib/pydoc.py
@@ -209,6 +209,18 @@
results.append((name, kind, cls, value))
return results
+def sort_attributes(attrs, object):
+ 'Sort the attrs list in-place by _fields and then alphabetically by name'
+ # This allows data descriptors to be ordered according
+ # to a _fields attribute if present.
+ fields = getattr(object, '_fields', [])
+ try:
+ field_order = {name : i-len(fields) for (i, name) in enumerate(fields)}
+ except TypeError:
+ field_order = {}
+ keyfunc = lambda attr: (field_order.get(attr[0], 0), attr[0])
+ attrs.sort(key=keyfunc)
+
# ----------------------------------------------------- module manipulation
def ispackage(path):
@@ -867,8 +879,7 @@
object.__module__)
tag += ':<br>\n'
- # Sort attrs by name.
- attrs.sort(key=lambda t: t[0])
+ sort_attributes(attrs, object)
# Pump out the attrs, segregated by kind.
attrs = spill('Methods %s' % tag, attrs,
@@ -1286,8 +1297,8 @@
else:
tag = "inherited from %s" % classname(thisclass,
object.__module__)
- # Sort attrs by name.
- attrs.sort()
+
+ sort_attributes(attrs, object)
# Pump out the attrs, segregated by kind.
attrs = spill("Methods %s:\n" % tag, attrs,
diff --git a/Lib/pydoc_data/topics.py b/Lib/pydoc_data/topics.py
index 9dad2af..38857d2 100644
--- a/Lib/pydoc_data/topics.py
+++ b/Lib/pydoc_data/topics.py
@@ -1,5 +1,5 @@
# -*- coding: utf-8 -*-
-# Autogenerated by Sphinx on Mon Sep 7 05:10:25 2015
+# Autogenerated by Sphinx on Sat May 23 17:38:41 2015
topics = {'assert': u'\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 to\n\n if __debug__:\n if not expression1: raise AssertionError(expression2)\n\nThese equivalences assume that "__debug__" and "AssertionError" refer\nto 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 (command\nline option -O). The current code generator emits no code for an\nassert statement when optimization is requested at compile time. Note\nthat it is unnecessary to include the source code for the expression\nthat failed in the error message; it will be displayed as part of the\nstack trace.\n\nAssignments to "__debug__" are illegal. The value for the built-in\nvariable is determined when the interpreter starts.\n',
'assignment': u'\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\n*attributeref*, *subscription*, and *slicing*.)\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\n object must be an iterable with the same number of items as there\n are targets in the target list, and the items are assigned, from\n left to right, to the corresponding targets.\n\n * If the target list contains one target prefixed with an\n asterisk, called a "starred" target: The object must be a sequence\n with at least as many items as there are targets in the target\n list, minus one. The first items of the sequence are assigned,\n from left to right, to the targets before the starred target. The\n final items of the sequence are assigned to the targets after the\n starred target. A list of the remaining items in the sequence is\n then assigned to the starred target (the list can be empty).\n\n * Else: The object must be a sequence with the same number of\n items 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" statement\n in the current code block: the name is bound to the object in the\n current local namespace.\n\n * Otherwise: the name is bound to the object in the global\n namespace or the outer namespace determined by "nonlocal",\n 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\n square brackets: The object must be an iterable with the same number\n of 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 always\n set as an instance attribute, creating it if necessary. Thus, the\n two occurrences of "a.x" do not necessarily refer to the same\n attribute: if the RHS expression refers to a class attribute, the\n 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 with\n appropriate arguments.\n\n* If the target is a slicing: The primary expression in the\n reference is evaluated. It should yield a mutable sequence object\n (such as a list). The assigned object should be a sequence object\n of the same type. Next, the lower and upper bound expressions are\n evaluated, insofar they are present; defaults are zero and the\n sequence\'s length. The bounds should evaluate to integers. If\n either bound is negative, the sequence\'s length is added to it. The\n resulting bounds are clipped to lie between zero and the sequence\'s\n length, inclusive. Finally, the sequence object is asked to replace\n the slice with the items of the assigned sequence. The length of\n the slice may be different from the length of the assigned sequence,\n thus changing the length of the target sequence, if the target\n sequence 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\nAlthough the definition of assignment implies that overlaps between\nthe left-hand side and the right-hand side are \'simultanenous\' (for\nexample "a, b = b, a" swaps two variables), overlaps *within* the\ncollection of assigned-to variables occur left-to-right, sometimes\nresulting in confusion. For instance, the following program prints\n"[0, 2]":\n\n x = [0, 1]\n i = 0\n i, x[i] = 1, 2 # i is updated, then x[i] is updated\n print(x)\n\nSee also: **PEP 3132** - Extended Iterable Unpacking\n\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 of 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 the\naugmented version, "x" is only evaluated once. Also, when possible,\nthe actual operation is performed *in-place*, meaning that rather than\ncreating a new object and assigning that to the target, the old object\nis modified instead.\n\nUnlike normal assignments, augmented assignments evaluate the left-\nhand side *before* evaluating the right-hand side. For example, "a[i]\n+= f(x)" first looks-up "a[i]", then it evaluates "f(x)" and performs\nthe addition, and lastly, it writes the result back to "a[i]".\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': u'\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, with leading underscores removed and a single underscore\ninserted, in front of the name. For example, the identifier "__spam"\noccurring in a class named "Ham" will be transformed to "_Ham__spam".\nThis transformation is independent of the syntactical context in which\nthe identifier is used. If the transformed name is extremely long\n(longer than 255 characters), implementation defined truncation may\nhappen. If the class name consists only of underscores, no\ntransformation is done.\n',
@@ -18,19 +18,19 @@
'callable-types': u'\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': u'\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\nAn optional trailing comma may be present after the positional and\nkeyword arguments 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 "TypeError"\nexception is raised. Otherwise, the list of filled slots is used as\nthe 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 parse\ntheir 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 formal\nparameter 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, "expression"\nmust evaluate to an iterable. Elements from this iterable are treated\nas if they were additional positional arguments; if there are\npositional arguments *x1*, ..., *xN*, and "expression" evaluates to a\nsequence *y1*, ..., *yM*, this is equivalent to a call with M+N\npositional 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" syntax\nto be used in the same call, so in practice this confusion does not\narise.\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, a\n"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 an\nexception. 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 the\n same as if that method was called.\n',
'class': u'\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 ""self.name"",\nand an instance attribute hides a class attribute with the same name\nwhen accessed in this way. Class attributes can be used as defaults\nfor instance attributes, but using mutable values there can lead to\nunexpected results. *Descriptors* can be used to create instance\nvariables with different implementation details.\n\nSee also: **PEP 3115** - Metaclasses in Python 3 **PEP 3129** -\n Class Decorators\n',
- 'comparisons': u'\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 only\nonce (but in both cases "z" is not evaluated at all when "x < y" is\nfound 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", except\nthat each expression is evaluated at most once.\n\nNote that "a op1 b op2 c" doesn\'t imply any kind of comparison between\n*a* and *c*, so that, e.g., "x < y > z" is perfectly legal (though\nperhaps not pretty).\n\nThe operators "<", ">", "==", ">=", "<=", and "!=" compare the values\nof two objects. The objects need not have the same type. If both are\nnumbers, they are converted to a common type. Otherwise, the "==" and\n"!=" operators *always* consider objects of different types to be\nunequal, while the "<", ">", ">=" and "<=" operators raise a\n"TypeError" when comparing objects of different types that do not\nimplement these operators for the given pair of types. You can\ncontrol comparison behavior of objects of non-built-in types by\ndefining rich comparison methods like "__gt__()", described in section\n*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. They\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\n equivalents (the result of the built-in function "ord()") of their\n characters. [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison\n of 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 same\n value as "x <= y". If the corresponding element does not exist, the\n shorter sequence is ordered first (for example, "[1,2] < [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 undefined\n results given a list of sets as inputs.\n\n* Most other objects of built-in types compare unequal unless they\n are the same object; the choice whether one object is considered\n smaller or larger than another one is made arbitrarily but\n consistently within one execution of a program.\n\nComparison of objects of differing types depends on whether either of\nthe types provide explicit support for the comparison. Most numeric\ntypes can be compared with one another. When cross-type comparison is\nnot supported, the comparison method returns "NotImplemented".\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" tests\nwhether the dictionary has a given key. For container types such as\nlist, 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* is\na substring of *y*. An equivalent test is "y.find(x) != -1". Empty\nstrings are always considered to be a substring of any other string,\nso """ in "abc"" will return "True".\n\nFor user-defined classes which define the "__contains__()" method, "x\nin 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 == z"\nis produced while iterating over "y". If an exception is raised\nduring 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 y" is\ntrue if and only if *x* and *y* are the same object. "x is not y"\nyields the inverse truth value. [4]\n',
- 'compound': u'\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 control\nflow constructs. "try" specifies exception handlers and/or cleanup\ncode for a group of statements, while the "with" statement allows the\nexecution of initialization and finalization code around a block of\ncode. Function and class definitions are also syntactically compound\nstatements.\n\nA compound statement consists 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 a 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 | async_with_stmt\n | async_for_stmt\n | async_funcdef\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 a\n"DEDENT". Also note that optional continuation clauses always begin\nwith 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 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" statement\nexecuted in the first suite skips the rest of the suite and goes back\nto testing the expression.\n\n\nThe "for" statement\n===================\n\nThe "for" statement is used to iterate over the elements of a sequence\n(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 returned by the iterator. 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" exception),\nthe suite in the "else" clause, if present, is executed, and the loop\nterminates.\n\nA "break" statement executed in the first suite terminates the loop\nwithout executing the "else" clause\'s suite. A "continue" statement\nexecuted in the first suite skips the rest of the suite and continues\nwith the next item, or with the "else" clause if there is no next\nitem.\n\nThe for-loop makes assignments to the variables(s) in the target list.\nThis overwrites all previous assignments to those variables including\nthose made in the suite of the for-loop:\n\n for i in range(10):\n print(i)\n i = 5 # this will not affect the for-loop\n # because i will be overwritten with the next\n # index in the range\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, they will not have been assigned to at\nall by the loop. Hint: the built-in function "range()" returns an\niterator of integers suitable to emulate the effect of Pascal\'s "for i\n:= a to b do"; e.g., "list(range(3))" returns the list "[0, 1, 2]".\n\nNote: There is a subtlety when the sequence is being modified by the\n loop (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" identifier]] ":" 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 no\nexception occurs in the "try" clause, no exception handler is\nexecuted. When an exception occurs in the "try" suite, a search for an\nexception handler is started. This search inspects the except clauses\nin turn until one is found that matches the exception. An expression-\nless except clause, if present, must be last; it matches any\nexception. For an except clause with an expression, that expression\nis evaluated, and the clause matches the exception if the resulting\nobject is "compatible" with the exception. An object is compatible\nwith an exception if it is the class or a base class of the exception\nobject or a tuple containing an item compatible with the exception.\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 raised\nthe 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, if\npresent, 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 accessed via\n"sys.exc_info()". "sys.exc_info()" returns a 3-tuple consisting of the\nexception class, the exception instance and a traceback object (see\nsection *The standard type hierarchy*) identifying the point in the\nprogram where the exception occurred. "sys.exc_info()" values are\nrestored 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 are\nnot handled by the preceding "except" clauses.\n\nIf "finally" is present, it specifies a \'cleanup\' handler. The "try"\nclause is executed, including any "except" and "else" clauses. If an\nexception occurs in any of the clauses and is not handled, the\nexception is temporarily saved. The "finally" clause is executed. If\nthere is a saved exception it is re-raised at the end of the "finally"\nclause. If the "finally" clause raises another exception, the saved\nexception is set as the context of the new exception. If the "finally"\nclause executes a "return" or "break" statement, the saved exception\nis discarded:\n\n >>> def f():\n ... try:\n ... 1/0\n ... finally:\n ... return 42\n ...\n >>> f()\n 42\n\nThe exception information is not available to the program during\nexecution of the "finally" clause.\n\nWhen a "return", "break" or "continue" statement is executed in the\n"try" suite of a "try"..."finally" statement, the "finally" clause is\nalso executed \'on the way out.\' A "continue" statement is illegal in\nthe "finally" clause. (The reason is a problem with the current\nimplementation --- this restriction may be lifted in the future).\n\nThe return value of a function is determined by the last "return"\nstatement executed. Since the "finally" clause always executes, a\n"return" statement executed in the "finally" clause will always be the\nlast one executed:\n\n >>> def foo():\n ... try:\n ... return \'try\'\n ... finally:\n ... return \'finally\'\n ...\n >>> foo()\n \'finally\'\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 "try"..."except"..."finally"\nusage patterns to be encapsulated for 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 be\n 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, three\n "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 reraised.\n If the return value was true, the exception is suppressed, and\n execution continues with the statement following the "with"\n 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: **PEP 0343** - The "with" statement\n\n The specification, background, and examples for the Python "with"\n 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)* ["," "**" 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 --- this\nis a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated from left to right when the\nfunction definition is executed.** This means that the expression is\nevaluated once, when the function is defined, and that the same "pre-\ncomputed" value is used for each call. This is especially important\nto understand when a default parameter is a mutable object, such as a\nlist or a dictionary: if the function modifies the object (e.g. by\nappending an item to a list), the default value is in effect modified.\nThis is generally not what was intended. A way around this is to use\n"None" as the default, and explicitly test for it in the body of the\nfunction, 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 any\nexcess positional parameters, defaulting to the empty tuple. If the\nform ""**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"" following\nthe parameter name. Any parameter may have an annotation even those\nof the form "*identifier" or "**identifier". Functions may have\n"return" annotation of the form ""-> expression"" after the parameter\nlist. These annotations can be any valid Python expression and are\nevaluated when the function definition is executed. Annotations may\nbe evaluated in a different order than they appear in the source code.\nThe presence of annotations does not change the semantics of a\nfunction. The annotation values are available as values of a\ndictionary keyed by the parameters\' names in the "__annotations__"\nattribute 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\nexpressions, described in section *Lambdas*. Note that the lambda\nexpression is merely a shorthand for a simplified function definition;\na function defined in a ""def"" statement can be passed around or\nassigned to another name just like a function defined by a lambda\nexpression. The ""def"" form is actually more powerful since it\nallows the execution of multiple statements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A ""def""\nstatement executed inside a function definition defines a local\nfunction that can be returned or passed around. Free variables used\nin the nested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n\nSee also: **PEP 3107** - Function Annotations\n\n The original specification for function annotations.\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 ""self.name"",\nand an instance attribute hides a class attribute with the same name\nwhen accessed in this way. Class attributes can be used as defaults\nfor instance attributes, but using mutable values there can lead to\nunexpected results. *Descriptors* can be used to create instance\nvariables with different implementation details.\n\nSee also: **PEP 3115** - Metaclasses in Python 3 **PEP 3129** -\n Class Decorators\n\n\nCoroutines\n==========\n\nNew in version 3.5.\n\n\nCoroutine function definition\n-----------------------------\n\n async_funcdef ::= [decorators] "async" "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n\nExecution of Python coroutines can be suspended and resumed at many\npoints (see *coroutine*). In the body of a coroutine, any "await" and\n"async" identifiers become reserved keywords; "await" expressions,\n"async for" and "async with" can only be used in coroutine bodies.\n\nFunctions defined with "async def" syntax are always coroutine\nfunctions, even if they do not contain "await" or "async" keywords.\n\nIt is a "SyntaxError" to use "yield" expressions in "async def"\ncoroutines.\n\nAn example of a coroutine function:\n\n async def func(param1, param2):\n do_stuff()\n await some_coroutine()\n\n\nThe "async for" statement\n-------------------------\n\n async_for_stmt ::= "async" for_stmt\n\nAn *asynchronous iterable* is able to call asynchronous code in its\n*iter* implementation, and *asynchronous iterator* can call\nasynchronous code in its *next* method.\n\nThe "async for" statement allows convenient iteration over\nasynchronous iterators.\n\nThe following code:\n\n async for TARGET in ITER:\n BLOCK\n else:\n BLOCK2\n\nIs semantically equivalent to:\n\n iter = (ITER)\n iter = await type(iter).__aiter__(iter)\n running = True\n while running:\n try:\n TARGET = await type(iter).__anext__(iter)\n except StopAsyncIteration:\n running = False\n else:\n BLOCK\n else:\n BLOCK2\n\nSee also "__aiter__()" and "__anext__()" for details.\n\nIt is a "SyntaxError" to use "async for" statement outside of an\n"async def" function.\n\n\nThe "async with" statement\n--------------------------\n\n async_with_stmt ::= "async" with_stmt\n\nAn *asynchronous context manager* is a *context manager* that is able\nto suspend execution in its *enter* and *exit* methods.\n\nThe following code:\n\n async with EXPR as VAR:\n BLOCK\n\nIs semantically equivalent to:\n\n mgr = (EXPR)\n aexit = type(mgr).__aexit__\n aenter = type(mgr).__aenter__(mgr)\n exc = True\n\n VAR = await aenter\n try:\n BLOCK\n except:\n if not await aexit(mgr, *sys.exc_info()):\n raise\n else:\n await aexit(mgr, None, None, None)\n\nSee also "__aenter__()" and "__aexit__()" for details.\n\nIt is a "SyntaxError" to use "async with" statement outside of an\n"async def" function.\n\nSee also: **PEP 492** - Coroutines with async and await syntax\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack unless\n there is a "finally" clause which happens to raise another\n exception. That new exception causes the old one to be lost.\n\n[2] Currently, control "flows off the end" except in the case of\n an 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\n function body is transformed into the function\'s "__doc__"\n attribute and 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': u'\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 only\nonce (but in both cases "z" is not evaluated at all when "x < y" is\nfound 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", except\nthat each expression is evaluated at most once.\n\nNote that "a op1 b op2 c" doesn\'t imply any kind of comparison between\n*a* and *c*, so that, e.g., "x < y > z" is perfectly legal (though\nperhaps not pretty).\n\nThe operators "<", ">", "==", ">=", "<=", and "!=" compare the values\nof two objects. The objects need not have the same type. If both are\nnumbers, they are converted to a common type. Otherwise, the "==" and\n"!=" operators *always* consider objects of different types to be\nunequal, while the "<", ">", ">=" and "<=" operators raise a\n"TypeError" when comparing objects of different types that do not\nimplement these operators for the given pair of types. You can\ncontrol comparison behavior of objects of non-built-in types by\ndefining rich comparison methods like "__gt__()", described in section\n*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. They\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\n equivalents (the result of the built-in function "ord()") of their\n characters. [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison\n of 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 same\n value as "x <= y". If the corresponding element does not exist, the\n shorter sequence is ordered first (for example, "[1,2] < [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 undefined\n results given a list of sets as inputs.\n\n* Most other objects of built-in types compare unequal unless they\n are the same object; the choice whether one object is considered\n smaller or larger than another one is made arbitrarily but\n consistently within one execution of a program.\n\nComparison of objects of differing types depends on whether either of\nthe types provide explicit support for the comparison. Most numeric\ntypes can be compared with one another. When cross-type comparison is\nnot supported, the comparison method returns "NotImplemented".\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" tests\nwhether the dictionary has a given key. For container types such as\nlist, 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* is\na substring of *y*. An equivalent test is "y.find(x) != -1". Empty\nstrings are always considered to be a substring of any other string,\nso """ in "abc"" will return "True".\n\nFor user-defined classes which define the "__contains__()" method, "x\nin 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 == z"\nis produced while iterating over "y". If an exception is raised\nduring 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 y" is\ntrue if and only if *x* and *y* are the same object. "x is not y"\nyields the inverse truth value. [4]\n',
+ 'compound': u'\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 control\nflow constructs. "try" specifies exception handlers and/or cleanup\ncode for a group of statements, while the "with" statement allows the\nexecution of initialization and finalization code around a block of\ncode. Function and class definitions are also syntactically compound\nstatements.\n\nA compound statement consists 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 a 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 | async_with_stmt\n | async_for_stmt\n | async_funcdef\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 a\n"DEDENT". Also note that optional continuation clauses always begin\nwith 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 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" statement\nexecuted in the first suite skips the rest of the suite and goes back\nto testing the expression.\n\n\nThe "for" statement\n===================\n\nThe "for" statement is used to iterate over the elements of a sequence\n(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 returned by the iterator. 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" exception),\nthe suite in the "else" clause, if present, is executed, and the loop\nterminates.\n\nA "break" statement executed in the first suite terminates the loop\nwithout executing the "else" clause\'s suite. A "continue" statement\nexecuted in the first suite skips the rest of the suite and continues\nwith the next item, or with the "else" clause if there is no next\nitem.\n\nThe for-loop makes assignments to the variables(s) in the target list.\nThis overwrites all previous assignments to those variables including\nthose made in the suite of the for-loop:\n\n for i in range(10):\n print(i)\n i = 5 # this will not affect the for-loop\n # because i will be overwritten with the next\n # index in the range\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, they will not have been assigned to at\nall by the loop. Hint: the built-in function "range()" returns an\niterator of integers suitable to emulate the effect of Pascal\'s "for i\n:= a to b do"; e.g., "list(range(3))" returns the list "[0, 1, 2]".\n\nNote: There is a subtlety when the sequence is being modified by the\n loop (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" identifier]] ":" 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 no\nexception occurs in the "try" clause, no exception handler is\nexecuted. When an exception occurs in the "try" suite, a search for an\nexception handler is started. This search inspects the except clauses\nin turn until one is found that matches the exception. An expression-\nless except clause, if present, must be last; it matches any\nexception. For an except clause with an expression, that expression\nis evaluated, and the clause matches the exception if the resulting\nobject is "compatible" with the exception. An object is compatible\nwith an exception if it is the class or a base class of the exception\nobject or a tuple containing an item compatible with the exception.\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 raised\nthe 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, if\npresent, 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 accessed via\n"sys.exc_info()". "sys.exc_info()" returns a 3-tuple consisting of the\nexception class, the exception instance and a traceback object (see\nsection *The standard type hierarchy*) identifying the point in the\nprogram where the exception occurred. "sys.exc_info()" values are\nrestored 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 are\nnot handled by the preceding "except" clauses.\n\nIf "finally" is present, it specifies a \'cleanup\' handler. The "try"\nclause is executed, including any "except" and "else" clauses. If an\nexception occurs in any of the clauses and is not handled, the\nexception is temporarily saved. The "finally" clause is executed. If\nthere is a saved exception it is re-raised at the end of the "finally"\nclause. If the "finally" clause raises another exception, the saved\nexception is set as the context of the new exception. If the "finally"\nclause executes a "return" or "break" statement, the saved exception\nis discarded:\n\n >>> def f():\n ... try:\n ... 1/0\n ... finally:\n ... return 42\n ...\n >>> f()\n 42\n\nThe exception information is not available to the program during\nexecution of the "finally" clause.\n\nWhen a "return", "break" or "continue" statement is executed in the\n"try" suite of a "try"..."finally" statement, the "finally" clause is\nalso executed \'on the way out.\' A "continue" statement is illegal in\nthe "finally" clause. (The reason is a problem with the current\nimplementation --- this restriction may be lifted in the future).\n\nThe return value of a function is determined by the last "return"\nstatement executed. Since the "finally" clause always executes, a\n"return" statement executed in the "finally" clause will always be the\nlast one executed:\n\n >>> def foo():\n ... try:\n ... return \'try\'\n ... finally:\n ... return \'finally\'\n ...\n >>> foo()\n \'finally\'\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 "try"..."except"..."finally"\nusage patterns to be encapsulated for 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 be\n 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, three\n "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 reraised.\n If the return value was true, the exception is suppressed, and\n execution continues with the statement following the "with"\n 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: **PEP 0343** - The "with" statement\n\n The specification, background, and examples for the Python "with"\n 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)* ["," "**" 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 --- this\nis a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated from left to right when the\nfunction definition is executed.** This means that the expression is\nevaluated once, when the function is defined, and that the same "pre-\ncomputed" value is used for each call. This is especially important\nto understand when a default parameter is a mutable object, such as a\nlist or a dictionary: if the function modifies the object (e.g. by\nappending an item to a list), the default value is in effect modified.\nThis is generally not what was intended. A way around this is to use\n"None" as the default, and explicitly test for it in the body of the\nfunction, 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 any\nexcess positional parameters, defaulting to the empty tuple. If the\nform ""**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"" following\nthe parameter name. Any parameter may have an annotation even those\nof the form "*identifier" or "**identifier". Functions may have\n"return" annotation of the form ""-> expression"" after the parameter\nlist. These annotations can be any valid Python expression and are\nevaluated when the function definition is executed. Annotations may\nbe evaluated in a different order than they appear in the source code.\nThe presence of annotations does not change the semantics of a\nfunction. The annotation values are available as values of a\ndictionary keyed by the parameters\' names in the "__annotations__"\nattribute 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\nexpressions, described in section *Lambdas*. Note that the lambda\nexpression is merely a shorthand for a simplified function definition;\na function defined in a ""def"" statement can be passed around or\nassigned to another name just like a function defined by a lambda\nexpression. The ""def"" form is actually more powerful since it\nallows the execution of multiple statements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A ""def""\nstatement executed inside a function definition defines a local\nfunction that can be returned or passed around. Free variables used\nin the nested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n\nSee also: **PEP 3107** - Function Annotations\n\n The original specification for function annotations.\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 ""self.name"",\nand an instance attribute hides a class attribute with the same name\nwhen accessed in this way. Class attributes can be used as defaults\nfor instance attributes, but using mutable values there can lead to\nunexpected results. *Descriptors* can be used to create instance\nvariables with different implementation details.\n\nSee also: **PEP 3115** - Metaclasses in Python 3 **PEP 3129** -\n Class Decorators\n\n\nCoroutines\n==========\n\n\nCoroutine function definition\n-----------------------------\n\n async_funcdef ::= "async" funcdef\n\nExecution of Python coroutines can be suspended and resumed at many\npoints (see *coroutine*.) "await" expressions, "async for" and "async\nwith" can only be used in their bodies.\n\nFunctions defined with "async def" syntax are always coroutine\nfunctions, even if they do not contain "await" or "async" keywords.\n\nIt is a "SyntaxError" to use "yield" expressions in coroutines.\n\nNew in version 3.5.\n\n\nThe "async for" statement\n-------------------------\n\n async_for_stmt ::= "async" for_stmt\n\nAn *asynchronous iterable* is able to call asynchronous code in its\n*iter* implementation, and *asynchronous iterator* can call\nasynchronous code in its *next* method.\n\nThe "async for" statement allows convenient iteration over\nasynchronous iterators.\n\nThe following code:\n\n async for TARGET in ITER:\n BLOCK\n else:\n BLOCK2\n\nIs semantically equivalent to:\n\n iter = (ITER)\n iter = await type(iter).__aiter__(iter)\n running = True\n while running:\n try:\n TARGET = await type(iter).__anext__(iter)\n except StopAsyncIteration:\n running = False\n else:\n BLOCK\n else:\n BLOCK2\n\nSee also "__aiter__()" and "__anext__()" for details.\n\nNew in version 3.5.\n\n\nThe "async with" statement\n--------------------------\n\n async_with_stmt ::= "async" with_stmt\n\nAn *asynchronous context manager* is a *context manager* that is able\nto suspend execution in its *enter* and *exit* methods.\n\nThe following code:\n\n async with EXPR as VAR:\n BLOCK\n\nIs semantically equivalent to:\n\n mgr = (EXPR)\n aexit = type(mgr).__aexit__\n aenter = type(mgr).__aenter__(mgr)\n exc = True\n\n VAR = await aenter\n try:\n BLOCK\n except:\n if not await aexit(mgr, *sys.exc_info()):\n raise\n else:\n await aexit(mgr, None, None, None)\n\nSee also "__aenter__()" and "__aexit__()" for details.\n\nNew in version 3.5.\n\nSee also: **PEP 492** - Coroutines with async and await syntax\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack unless\n there is a "finally" clause which happens to raise another\n exception. That new exception causes the old one to be lost.\n\n[2] Currently, control "flows off the end" except in the case of\n an 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\n function body is transformed into the function\'s "__doc__"\n attribute and 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': u'\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 manager\nhandles the entry into, and the exit from, the desired runtime context\nfor the execution of the block of code. Context managers are normally\ninvoked using the "with" statement (described in section *The with\nstatement*), but can also be used by directly invoking their methods.\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: **PEP 0343** - The "with" statement\n\n The specification, background, and examples for the Python "with"\n statement.\n',
'continue': u'\nThe "continue" statement\n************************\n\n continue_stmt ::= "continue"\n\n"continue" may only occur syntactically nested in a "for" or "while"\nloop, but not nested in a function or class definition or "finally"\nclause within that loop. It continues with the next cycle of the\nnearest 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': u'\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 as follows:\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\n other 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 as a\nleft argument to the \'%\' operator). Extensions must define their own\nconversion behavior.\n',
- 'customization': u'\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 an\n 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 after the instance has been created (by "__new__()"), but\n before it is returned to the caller. 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, if\n any, must explicitly call it to ensure proper initialization of the\n base class part of the instance; for example:\n "BaseClass.__init__(self, [args...])".\n\n Because "__new__()" and "__init__()" work together in constructing\n objects ("__new__()" to create it, and "__init__()" to customise\n it), no non-"None" value may be returned by "__init__()"; doing so\n will cause a "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, the\n derived class\'s "__del__()" method, if any, must explicitly call it\n to ensure proper deletion of the base class part of the instance.\n Note that it is possible (though not recommended!) for the\n "__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 is\n only called when "x"\'s reference count reaches zero. Some common\n situations that may prevent the reference count of an object from\n going to zero include: circular references between objects (e.g.,\n a doubly-linked list or a tree data structure with parent and\n child pointers); a reference to the object on the stack frame of\n a function that caught an exception (the traceback stored in\n "sys.exc_info()[2]" keeps the stack frame alive); or a reference\n to the object on the stack frame that raised an unhandled\n 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 second can be resolved by freeing the reference to the\n traceback object when it is no longer useful, and the third can\n be resolved by storing "None" in "sys.last_traceback". Circular\n references which are garbage are detected and cleaned up when the\n cyclic garbage collector is enabled (it\'s on by default). Refer\n to the documentation for the "gc" module for more information\n about this topic.\n\n Warning: Due to the precarious circumstances under which\n "__del__()" methods are invoked, exceptions that occur during\n their execution are ignored, and a warning is printed to\n "sys.stderr" instead. Also, when "__del__()" is invoked in\n response to a module being deleted (e.g., when execution of the\n program is done), other globals referenced by the "__del__()"\n method may already have been deleted or in the process of being\n torn down (e.g. the import machinery shutting down). For this\n reason, "__del__()" methods should do the absolute minimum needed\n to maintain external invariants. Starting with version 1.5,\n Python 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 "official"\n string representation of an object. If at all possible, this\n should look like a valid Python expression that could be used to\n 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__()" but\n not "__str__()", then "__repr__()" is also used when an "informal"\n string representation of instances of that class is 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 "str(object)" and the built-in functions "format()" and\n "print()" to compute the "informal" or nicely printable string\n representation of an object. The return value must be a *string*\n object.\n\n This method differs from "object.__repr__()" in that there is no\n expectation that "__str__()" return a valid Python expression: a\n more convenient or concise representation can be used.\n\n The default implementation defined by the built-in type "object"\n calls "object.__repr__()".\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 "str.format()" method of class "str") to produce a "formatted"\n string representation of an object. The "format_spec" argument is a\n string that contains a description of the formatting options\n desired. The interpretation of the "format_spec" argument is up to\n the type implementing "__format__()", however most classes will\n either delegate formatting to one of the built-in types, or use a\n 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\n Changed in version 3.4: The __format__ method of "object" itself\n raises a "TypeError" if passed any non-empty string.\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 "x.__le__(y)",\n "x==y" calls "x.__eq__(y)", "x!=y" calls "x.__ne__(y)", "x>y" calls\n "x.__gt__(y)", and "x>=y" calls "x.__ge__(y)".\n\n A rich comparison method may return the singleton "NotImplemented"\n if it does not implement the operation for a given pair of\n arguments. By convention, "False" and "True" are returned for a\n successful comparison. However, these methods can return any value,\n so if the comparison operator is used in a Boolean context (e.g.,\n in the condition of an "if" statement), Python will call "bool()"\n on the value to determine if the result is true or false.\n\n By default, "__ne__()" delegates to "__eq__()" and inverts the\n result unless it is "NotImplemented". There are no other implied\n relationships among the comparison operators, for example, the\n truth of "(x<y or x==y)" does not imply "x<=y". To automatically\n generate ordering operations from a single root operation, see\n "functools.total_ordering()".\n\n See 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 other\'s\n reflection, "__le__()" and "__ge__()" are each other\'s reflection,\n and "__eq__()" and "__ne__()" are their own reflection. If the\n operands are of different types, and right operand\'s type is a\n direct or indirect subclass of the left operand\'s type, the\n reflected method of the right operand has priority, otherwise the\n left operand\'s method has priority. Virtual subclassing is not\n considered.\n\nobject.__hash__(self)\n\n Called by built-in function "hash()" and for operations on members\n of hashed collections including "set", "frozenset", and "dict".\n "__hash__()" should return an integer. The only required property\n is that objects which compare equal have the same hash value; it is\n advised to somehow mix together (e.g. using exclusive or) the hash\n values for the components of the object that also play a part in\n comparison of objects.\n\n Note: "hash()" truncates the value returned from an object\'s\n custom "__hash__()" method to the size of a "Py_ssize_t". This\n is typically 8 bytes on 64-bit builds and 4 bytes on 32-bit\n builds. If an object\'s "__hash__()" must interoperate on builds\n of different bit sizes, be sure to check the width on all\n supported builds. An easy way to do this is with "python -c\n "import sys; print(sys.hash_info.width)""\n\n If a class does not define an "__eq__()" method it should not\n define a "__hash__()" operation either; if it defines "__eq__()"\n but not "__hash__()", its instances will not be usable as items in\n hashable collections. If a class defines mutable objects and\n implements an "__eq__()" method, it should not implement\n "__hash__()", since the implementation of hashable collections\n requires that a key\'s hash value is immutable (if the object\'s hash\n value changes, it will be in the wrong hash bucket).\n\n User-defined classes have "__eq__()" and "__hash__()" methods by\n default; with them, all objects compare unequal (except with\n themselves) and "x.__hash__()" returns an appropriate value such\n that "x == y" implies both that "x is y" and "hash(x) == hash(y)".\n\n A class that overrides "__eq__()" and does not define "__hash__()"\n will have its "__hash__()" implicitly set to "None". When the\n "__hash__()" method of a class is "None", instances of the class\n will raise an appropriate "TypeError" when a program attempts to\n retrieve their hash value, and will also be correctly identified as\n unhashable when checking "isinstance(obj, collections.Hashable").\n\n If a class that overrides "__eq__()" needs to retain the\n implementation of "__hash__()" from a parent class, the interpreter\n must be told this explicitly by setting "__hash__ =\n <ParentClass>.__hash__".\n\n If a class that does not override "__eq__()" wishes to suppress\n hash support, it should include "__hash__ = None" in the class\n definition. A class which defines its own "__hash__()" that\n explicitly raises a "TypeError" would be incorrectly identified as\n hashable by an "isinstance(obj, collections.Hashable)" call.\n\n 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 iteration order of\n dicts, sets and other mappings. 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 is not\n defined, "__len__()" is called, if it is defined, and the object is\n considered true if its result is nonzero. If a class defines\n neither "__len__()" nor "__bool__()", all its instances are\n considered true.\n',
+ 'customization': u'\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 an\n 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 after the instance has been created (by "__new__()"), but\n before it is returned to the caller. 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, if\n any, must explicitly call it to ensure proper initialization of the\n base class part of the instance; for example:\n "BaseClass.__init__(self, [args...])".\n\n Because "__new__()" and "__init__()" work together in constructing\n objects ("__new__()" to create it, and "__init__()" to customise\n it), no non-"None" value may be returned by "__init__()"; doing so\n will cause a "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, the\n derived class\'s "__del__()" method, if any, must explicitly call it\n to ensure proper deletion of the base class part of the instance.\n Note that it is possible (though not recommended!) for the\n "__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 is\n only called when "x"\'s reference count reaches zero. Some common\n situations that may prevent the reference count of an object from\n going to zero include: circular references between objects (e.g.,\n a doubly-linked list or a tree data structure with parent and\n child pointers); a reference to the object on the stack frame of\n a function that caught an exception (the traceback stored in\n "sys.exc_info()[2]" keeps the stack frame alive); or a reference\n to the object on the stack frame that raised an unhandled\n 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 second can be resolved by freeing the reference to the\n traceback object when it is no longer useful, and the third can\n be resolved by storing "None" in "sys.last_traceback". Circular\n references which are garbage are detected and cleaned up when the\n cyclic garbage collector is enabled (it\'s on by default). Refer\n to the documentation for the "gc" module for more information\n about this topic.\n\n Warning: Due to the precarious circumstances under which\n "__del__()" methods are invoked, exceptions that occur during\n their execution are ignored, and a warning is printed to\n "sys.stderr" instead. Also, when "__del__()" is invoked in\n response to a module being deleted (e.g., when execution of the\n program is done), other globals referenced by the "__del__()"\n method may already have been deleted or in the process of being\n torn down (e.g. the import machinery shutting down). For this\n reason, "__del__()" methods should do the absolute minimum needed\n to maintain external invariants. Starting with version 1.5,\n Python 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 "official"\n string representation of an object. If at all possible, this\n should look like a valid Python expression that could be used to\n 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__()" but\n not "__str__()", then "__repr__()" is also used when an "informal"\n string representation of instances of that class is 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 "str(object)" and the built-in functions "format()" and\n "print()" to compute the "informal" or nicely printable string\n representation of an object. The return value must be a *string*\n object.\n\n This method differs from "object.__repr__()" in that there is no\n expectation that "__str__()" return a valid Python expression: a\n more convenient or concise representation can be used.\n\n The default implementation defined by the built-in type "object"\n calls "object.__repr__()".\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 "str.format()" method of class "str") to produce a "formatted"\n string representation of an object. The "format_spec" argument is a\n string that contains a description of the formatting options\n desired. The interpretation of the "format_spec" argument is up to\n the type implementing "__format__()", however most classes will\n either delegate formatting to one of the built-in types, or use a\n 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\n Changed in version 3.4: The __format__ method of "object" itself\n raises a "TypeError" if passed any non-empty string.\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 "x.__le__(y)",\n "x==y" calls "x.__eq__(y)", "x!=y" calls "x.__ne__(y)", "x>y" calls\n "x.__gt__(y)", and "x>=y" calls "x.__ge__(y)".\n\n A rich comparison method may return the singleton "NotImplemented"\n if it does not implement the operation for a given pair of\n arguments. By convention, "False" and "True" are returned for a\n successful comparison. However, these methods can return any value,\n so if the comparison operator is used in a Boolean context (e.g.,\n in the condition of an "if" statement), Python will call "bool()"\n on the value to determine if the result 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 the\n paragraph on "__hash__()" for some important notes on creating\n *hashable* objects which support custom comparison operations and\n 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 other\'s\n reflection, "__le__()" and "__ge__()" are each other\'s reflection,\n and "__eq__()" and "__ne__()" are their own 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 members\n of hashed collections including "set", "frozenset", and "dict".\n "__hash__()" should return an integer. The only required property\n is that objects which compare equal have the same hash value; it is\n advised to somehow mix together (e.g. using exclusive or) the hash\n values for the components of the object that also play a part in\n comparison of objects.\n\n Note: "hash()" truncates the value returned from an object\'s\n custom "__hash__()" method to the size of a "Py_ssize_t". This\n is typically 8 bytes on 64-bit builds and 4 bytes on 32-bit\n builds. If an object\'s "__hash__()" must interoperate on builds\n of different bit sizes, be sure to check the width on all\n supported builds. An easy way to do this is with "python -c\n "import sys; print(sys.hash_info.width)""\n\n If a class does not define an "__eq__()" method it should not\n define a "__hash__()" operation either; if it defines "__eq__()"\n but not "__hash__()", its instances will not be usable as items in\n hashable collections. If a class defines mutable objects and\n implements an "__eq__()" method, it should not implement\n "__hash__()", since the implementation of hashable collections\n requires that a key\'s hash value is immutable (if the object\'s hash\n value changes, it will be in the wrong hash bucket).\n\n User-defined classes have "__eq__()" and "__hash__()" methods by\n default; with them, all objects compare unequal (except with\n themselves) and "x.__hash__()" returns an appropriate value such\n that "x == y" implies both that "x is y" and "hash(x) == hash(y)".\n\n A class that overrides "__eq__()" and does not define "__hash__()"\n will have its "__hash__()" implicitly set to "None". When the\n "__hash__()" method of a class is "None", instances of the class\n will raise an appropriate "TypeError" when a program attempts to\n retrieve their hash value, and will also be correctly identified as\n unhashable when checking "isinstance(obj, collections.Hashable").\n\n If a class that overrides "__eq__()" needs to retain the\n implementation of "__hash__()" from a parent class, the interpreter\n must be told this explicitly by setting "__hash__ =\n <ParentClass>.__hash__".\n\n If a class that does not override "__eq__()" wishes to suppress\n hash support, it should include "__hash__ = None" in the class\n definition. A class which defines its own "__hash__()" that\n explicitly raises a "TypeError" would be incorrectly identified as\n hashable by an "isinstance(obj, collections.Hashable)" call.\n\n 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 iteration order of\n dicts, sets and other mappings. 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 is not\n defined, "__len__()" is called, if it is defined, and the object is\n considered true if its result is nonzero. If a class defines\n neither "__len__()" nor "__bool__()", all its instances are\n considered true.\n',
'debugger': u'\n"pdb" --- The Python Debugger\n*****************************\n\n**Source code:** Lib/pdb.py\n\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 reading\nthe source. The extension interface uses the modules "bdb" and "cmd".\n\nThe debugger\'s prompt is "(Pdb)". Typical usage to run a program under\ncontrol 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\nChanged in version 3.3: Tab-completion via the "readline" module is\navailable for commands and command arguments, e.g. the current global\nand local names are offered as arguments of the "p" command.\n\n"pdb.py" can also be invoked as a script to debug other scripts. For\nexample:\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 executes\ncommands as if given in a ".pdbrc" file, see *Debugger Commands*.\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 the\n explanation of the built-in "exec()" or "eval()" 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 instantiating\nthe "Pdb" class and calling the method of the same name. If you want\nto access further features, you have to do this yourself:\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 the help\ncommand (but not "he" or "hel", nor "H" or "Help" or "HELP").\nArguments to commands must be separated by whitespace (spaces or\ntabs). Optional arguments are enclosed in square brackets ("[]") in\nthe 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 multiple commands\nin a line that is passed to the Python parser.) No intelligence is\napplied to separating the commands; the input is split at the first\n";;" pair, even if it is in the middle of a quoted string.\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, these\ncommands 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, "help\n 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) p 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 "step"\n is that "step" stops inside a called function, while "next"\n executes called functions at (nearly) full speed, only stopping at\n 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. With\n 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 an\n exception is being debugged, the line where the exception was\n originally raised or propagated is indicated by ">>", if it differs\n 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 expression\n\n Evaluate the *expression* in the current context and print its\n value.\n\n Note: "print()" can also be used, but is not a debugger command\n --- this executes the Python "print()" function.\n\npp expression\n\n Like the "p" command, except the value of the expression is pretty-\n 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 all\n 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 are\n 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\n is determined by the "__name__" in the frame globals.\n',
'del': u'\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: Previously it was illegal to delete a name\nfrom the local namespace if it occurs as a free variable in a nested\nblock.\n',
'dict': u'\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': u'\nInteraction with dynamic features\n*********************************\n\nName resolution of free variables occurs at runtime, not at compile\ntime. This means that the following code will print 42:\n\n i = 10\n def f():\n print(i)\n i = 42\n f()\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\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',
+ 'dynamic-features': u'\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\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': u'\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',
'exceptions': u'\nExceptions\n**********\n\nExceptions are a means of breaking out of the normal flow of control\nof a code block in order to handle errors or other exceptional\nconditions. An exception is *raised* at the point where the error is\ndetected; it may be *handled* by the surrounding code block or by any\ncode block that directly or indirectly invoked the code block where\nthe error occurred.\n\nThe Python interpreter raises an exception when it detects a run-time\nerror (such as division by zero). A Python program can also\nexplicitly raise an exception with the "raise" statement. Exception\nhandlers are specified with the "try" ... "except" statement. The\n"finally" clause of such a statement can be used to specify cleanup\ncode which does not handle the exception, but is executed whether an\nexception occurred or not in the preceding code.\n\nPython uses the "termination" model of error handling: an exception\nhandler can find out what happened and continue execution at an outer\nlevel, but it cannot repair the cause of the error and retry the\nfailing operation (except by re-entering the offending piece of code\nfrom the top).\n\nWhen an exception is not handled at all, the interpreter terminates\nexecution of the program, or returns to its interactive main loop. In\neither case, it prints a stack backtrace, except when the exception is\n"SystemExit".\n\nExceptions are identified by class instances. The "except" clause is\nselected depending on the class of the instance: it must reference the\nclass of the instance or a base class thereof. The instance can be\nreceived by the handler and can carry additional information about the\nexceptional condition.\n\nNote: Exception messages are not part of the Python API. Their\n contents may change from one version of Python to the next without\n warning and should not be relied on by code which will run under\n multiple versions of the interpreter.\n\nSee also the description of the "try" statement in section *The try\nstatement* and "raise" statement in section *The raise statement*.\n\n-[ Footnotes ]-\n\n[1] This limitation occurs because the code that is executed by\n these operations is not available at the time the module is\n compiled.\n',
- 'execmodel': u'\nExecution model\n***************\n\n\nStructure of a programm\n=======================\n\nA Python program is constructed from code blocks. A *block* is a piece\nof Python program text that is executed as a unit. The following are\nblocks: a module, a function body, and a class definition. Each\ncommand typed interactively is a block. A script file (a file given\nas standard input to the interpreter or specified as a command line\nargument to the interpreter) is a code block. A script command (a\ncommand specified on the interpreter command line with the \'**-c**\'\noption) is a code block. The string argument passed to the built-in\nfunctions "eval()" and "exec()" is a code block.\n\nA code block is executed in an *execution frame*. A frame contains\nsome administrative information (used for debugging) and determines\nwhere and how execution continues after the code block\'s execution has\ncompleted.\n\n\nNaming and binding\n==================\n\n\nBinding of names\n----------------\n\n*Names* refer to objects. Names are introduced by name binding\noperations.\n\nThe following constructs bind names: formal parameters to functions,\n"import" statements, class and function definitions (these bind the\nclass or function name in the defining block), and targets that are\nidentifiers if occurring in an assignment, "for" loop header, or after\n"as" in a "with" statement or "except" clause. The "import" statement\nof the form "from ... import *" binds all names defined in the\nimported module, except those beginning with an underscore. This form\nmay only be used at the module level.\n\nA target occurring in a "del" statement is also considered bound for\nthis purpose (though the actual semantics are to unbind the name).\n\nEach assignment or import statement occurs within a block defined by a\nclass or function definition or at the module level (the top-level\ncode block).\n\nIf a name is bound in a block, it is a local variable of that block,\nunless declared as "nonlocal" or "global". If a name is bound at the\nmodule level, it is a global variable. (The variables of the module\ncode block are local and global.) If a variable is used in a code\nblock but not defined there, it is a *free variable*.\n\nEach occurrence of a name in the program text refers to the *binding*\nof that name established by the following name resolution rules.\n\n\nResolution of names\n-------------------\n\nA *scope* defines the visibility of a name within a block. If a local\nvariable is defined in a block, its scope includes that block. If the\ndefinition occurs in a function block, the scope extends to any blocks\ncontained within the defining one, unless a contained block introduces\na different binding for the name.\n\nWhen a name is used in a code block, it is resolved using the nearest\nenclosing scope. The set of all such scopes visible to a code block\nis called the block\'s *environment*.\n\nWhen a name is not found at all, a "NameError" exception is raised. If\nthe current scope is a function scope, and the name refers to a local\nvariable that has not yet been bound to a value at the point where the\nname is used, an "UnboundLocalError" exception is raised.\n"UnboundLocalError" is a subclass of "NameError".\n\nIf a name binding operation occurs anywhere within a code block, all\nuses of the name within the block are treated as references to the\ncurrent block. This can lead to errors when a name is used within a\nblock before it is bound. This rule is subtle. Python lacks\ndeclarations and allows name binding operations to occur anywhere\nwithin a code block. The local variables of a code block can be\ndetermined by scanning the entire text of the block for name binding\noperations.\n\nIf the "global" statement occurs within a block, all uses of the name\nspecified in the statement refer to the binding of that name in the\ntop-level namespace. Names are resolved in the top-level namespace by\nsearching the global namespace, i.e. the namespace of the module\ncontaining the code block, and the builtins namespace, the namespace\nof the module "builtins". The global namespace is searched first. If\nthe name is not found there, the builtins namespace is searched. The\n"global" statement must precede all uses of the name.\n\nThe "global" statement has the same scope as a name binding operation\nin the same block. If the nearest enclosing scope for a free variable\ncontains a global statement, the free variable is treated as a global.\n\nThe "nonlocal" statement causes corresponding names to refer to\npreviously bound variables in the nearest enclosing function scope.\n"SyntaxError" is raised at compile time if the given name does not\nexist in any enclosing function scope.\n\nThe namespace for a module is automatically created the first time a\nmodule is imported. The main module for a script is always called\n"__main__".\n\nClass definition blocks and arguments to "exec()" and "eval()" are\nspecial in the context of name resolution. A class definition is an\nexecutable statement that may use and define names. These references\nfollow the normal rules for name resolution with an exception that\nunbound local variables are looked up in the global namespace. The\nnamespace of the class definition becomes the attribute dictionary of\nthe class. The scope of names defined in a class block is limited to\nthe class block; it does not extend to the code blocks of methods --\nthis includes comprehensions and generator expressions since they are\nimplemented using a function scope. This means that the following\nwill fail:\n\n class A:\n a = 42\n b = list(a + i for i in range(10))\n\n\nBuiltins and restricted execution\n---------------------------------\n\nThe builtins namespace associated with the execution of a code block\nis actually found by looking up the name "__builtins__" in its global\nnamespace; this should be a dictionary or a module (in the latter case\nthe module\'s dictionary is used). By default, when in the "__main__"\nmodule, "__builtins__" is the built-in module "builtins"; when in any\nother module, "__builtins__" is an alias for the dictionary of the\n"builtins" module itself. "__builtins__" can be set to a user-created\ndictionary to create a weak form of restricted execution.\n\n**CPython implementation detail:** Users should not touch\n"__builtins__"; it is strictly an implementation detail. Users\nwanting to override values in the builtins namespace should "import"\nthe "builtins" module and modify its attributes appropriately.\n\n\nInteraction with dynamic features\n---------------------------------\n\nName resolution of free variables occurs at runtime, not at compile\ntime. This means that the following code will print 42:\n\n i = 10\n def f():\n print(i)\n i = 42\n f()\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\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\n\nExceptions\n==========\n\nExceptions are a means of breaking out of the normal flow of control\nof a code block in order to handle errors or other exceptional\nconditions. An exception is *raised* at the point where the error is\ndetected; it may be *handled* by the surrounding code block or by any\ncode block that directly or indirectly invoked the code block where\nthe error occurred.\n\nThe Python interpreter raises an exception when it detects a run-time\nerror (such as division by zero). A Python program can also\nexplicitly raise an exception with the "raise" statement. Exception\nhandlers are specified with the "try" ... "except" statement. The\n"finally" clause of such a statement can be used to specify cleanup\ncode which does not handle the exception, but is executed whether an\nexception occurred or not in the preceding code.\n\nPython uses the "termination" model of error handling: an exception\nhandler can find out what happened and continue execution at an outer\nlevel, but it cannot repair the cause of the error and retry the\nfailing operation (except by re-entering the offending piece of code\nfrom the top).\n\nWhen an exception is not handled at all, the interpreter terminates\nexecution of the program, or returns to its interactive main loop. In\neither case, it prints a stack backtrace, except when the exception is\n"SystemExit".\n\nExceptions are identified by class instances. The "except" clause is\nselected depending on the class of the instance: it must reference the\nclass of the instance or a base class thereof. The instance can be\nreceived by the handler and can carry additional information about the\nexceptional condition.\n\nNote: Exception messages are not part of the Python API. Their\n contents may change from one version of Python to the next without\n warning and should not be relied on by code which will run under\n multiple versions of the interpreter.\n\nSee also the description of the "try" statement in section *The try\nstatement* and "raise" statement in section *The raise statement*.\n\n-[ Footnotes ]-\n\n[1] This limitation occurs because the code that is executed by\n these operations is not available at the time the module is\n compiled.\n',
+ 'execmodel': u'\nExecution model\n***************\n\n\nNaming and binding\n==================\n\n*Names* refer to objects. Names are introduced by name binding\noperations. Each occurrence of a name in the program text refers to\nthe *binding* of that name established in the innermost function block\ncontaining the use.\n\nA *block* is a piece of Python program text that is executed as a\nunit. The following are blocks: a module, a function body, and a class\ndefinition. Each command typed interactively is a block. A script\nfile (a file given as standard input to the interpreter or specified\nas a command line argument to the interpreter) is a code block. A\nscript command (a command specified on the interpreter command line\nwith the \'**-c**\' option) is a code block. The string argument passed\nto the built-in functions "eval()" and "exec()" is a code block.\n\nA code block is executed in an *execution frame*. A frame contains\nsome administrative information (used for debugging) and determines\nwhere and how execution continues after the code block\'s execution has\ncompleted.\n\nA *scope* defines the visibility of a name within a block. If a local\nvariable is defined in a block, its scope includes that block. If the\ndefinition occurs in a function block, the scope extends to any blocks\ncontained within the defining one, unless a contained block introduces\na different binding for the name. The scope of names defined in a\nclass block is limited to the class block; it does not extend to the\ncode blocks of methods -- this includes comprehensions and generator\nexpressions since they are implemented using a function scope. This\nmeans that the following will fail:\n\n class A:\n a = 42\n b = list(a + i for i in range(10))\n\nWhen a name is used in a code block, it is resolved using the nearest\nenclosing scope. The set of all such scopes visible to a code block\nis called the block\'s *environment*.\n\nIf a name is bound in a block, it is a local variable of that block,\nunless declared as "nonlocal". If a name is bound at the module\nlevel, it is a global variable. (The variables of the module code\nblock are local and global.) If a variable is used in a code block\nbut not defined there, it is a *free variable*.\n\nWhen a name is not found at all, a "NameError" exception is raised.\nIf the name refers to a local variable that has not been bound, an\n"UnboundLocalError" exception is raised. "UnboundLocalError" is a\nsubclass of "NameError".\n\nThe following constructs bind names: formal parameters to functions,\n"import" statements, class and function definitions (these bind the\nclass or function name in the defining block), and targets that are\nidentifiers if occurring in an assignment, "for" loop header, or after\n"as" in a "with" statement or "except" clause. The "import" statement\nof the form "from ... import *" binds all names defined in the\nimported module, except those beginning with an underscore. This form\nmay only be used at the module level.\n\nA target occurring in a "del" statement is also considered bound for\nthis purpose (though the actual semantics are to unbind the name).\n\nEach assignment or import statement occurs within a block defined by a\nclass or function definition or at the module level (the top-level\ncode block).\n\nIf a name binding operation occurs anywhere within a code block, all\nuses of the name within the block are treated as references to the\ncurrent block. This can lead to errors when a name is used within a\nblock before it is bound. This rule is subtle. Python lacks\ndeclarations and allows name binding operations to occur anywhere\nwithin a code block. The local variables of a code block can be\ndetermined by scanning the entire text of the block for name binding\noperations.\n\nIf the "global" statement occurs within a block, all uses of the name\nspecified in the statement refer to the binding of that name in the\ntop-level namespace. Names are resolved in the top-level namespace by\nsearching the global namespace, i.e. the namespace of the module\ncontaining the code block, and the builtins namespace, the namespace\nof the module "builtins". The global namespace is searched first. If\nthe name is not found there, the builtins namespace is searched. The\n"global" statement must precede all uses of the name.\n\nThe builtins namespace associated with the execution of a code block\nis actually found by looking up the name "__builtins__" in its global\nnamespace; this should be a dictionary or a module (in the latter case\nthe module\'s dictionary is used). By default, when in the "__main__"\nmodule, "__builtins__" is the built-in module "builtins"; when in any\nother module, "__builtins__" is an alias for the dictionary of the\n"builtins" module itself. "__builtins__" can be set to a user-created\ndictionary to create a weak form of restricted execution.\n\n**CPython implementation detail:** Users should not touch\n"__builtins__"; it is strictly an implementation detail. Users\nwanting to override values in the builtins namespace should "import"\nthe "builtins" module and modify its attributes appropriately.\n\nThe namespace for a module is automatically created the first time a\nmodule is imported. The main module for a script is always called\n"__main__".\n\nThe "global" statement has the same scope as a name binding operation\nin the same block. If the nearest enclosing scope for a free variable\ncontains a global statement, the free variable is treated as a global.\n\nA class definition is an executable statement that may use and define\nnames. These references follow the normal rules for name resolution.\nThe namespace of the class definition becomes the attribute dictionary\nof the class. Names defined at the class scope are not visible in\nmethods.\n\n\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\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\n\nExceptions\n==========\n\nExceptions are a means of breaking out of the normal flow of control\nof a code block in order to handle errors or other exceptional\nconditions. An exception is *raised* at the point where the error is\ndetected; it may be *handled* by the surrounding code block or by any\ncode block that directly or indirectly invoked the code block where\nthe error occurred.\n\nThe Python interpreter raises an exception when it detects a run-time\nerror (such as division by zero). A Python program can also\nexplicitly raise an exception with the "raise" statement. Exception\nhandlers are specified with the "try" ... "except" statement. The\n"finally" clause of such a statement can be used to specify cleanup\ncode which does not handle the exception, but is executed whether an\nexception occurred or not in the preceding code.\n\nPython uses the "termination" model of error handling: an exception\nhandler can find out what happened and continue execution at an outer\nlevel, but it cannot repair the cause of the error and retry the\nfailing operation (except by re-entering the offending piece of code\nfrom the top).\n\nWhen an exception is not handled at all, the interpreter terminates\nexecution of the program, or returns to its interactive main loop. In\neither case, it prints a stack backtrace, except when the exception is\n"SystemExit".\n\nExceptions are identified by class instances. The "except" clause is\nselected depending on the class of the instance: it must reference the\nclass of the instance or a base class thereof. The instance can be\nreceived by the handler and can carry additional information about the\nexceptional condition.\n\nNote: Exception messages are not part of the Python API. Their\n contents may change from one version of Python to the next without\n warning and should not be relied on by code which will run under\n multiple versions of the interpreter.\n\nSee also the description of the "try" statement in section *The try\nstatement* and "raise" statement in section *The raise statement*.\n\n-[ Footnotes ]-\n\n[1] This limitation occurs because the code that is executed by\n these operations is not available at the time the module is\n compiled.\n',
'exprlists': u'\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': u'\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 number\nas "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': u'\nThe "for" statement\n*******************\n\nThe "for" statement is used to iterate over the elements of a sequence\n(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 returned by the iterator. 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" exception),\nthe suite in the "else" clause, if present, is executed, and the loop\nterminates.\n\nA "break" statement executed in the first suite terminates the loop\nwithout executing the "else" clause\'s suite. A "continue" statement\nexecuted in the first suite skips the rest of the suite and continues\nwith the next item, or with the "else" clause if there is no next\nitem.\n\nThe for-loop makes assignments to the variables(s) in the target list.\nThis overwrites all previous assignments to those variables including\nthose made in the suite of the for-loop:\n\n for i in range(10):\n print(i)\n i = 5 # this will not affect the for-loop\n # because i will be overwritten with the next\n # index in the range\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, they will not have been assigned to at\nall by the loop. Hint: the built-in function "range()" returns an\niterator of integers suitable to emulate the effect of Pascal\'s "for i\n:= a to b do"; e.g., "list(range(3))" returns the list "[0, 1, 2]".\n\nNote: There is a subtlety when the sequence is being modified by the\n loop (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',
@@ -42,16 +42,16 @@
'if': u'\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',
'imaginary': u'\nImaginary literals\n******************\n\nImaginary literals are described by the following lexical definitions:\n\n imagnumber ::= (floatnumber | intpart) ("j" | "J")\n\nAn imaginary literal yields a complex number with a real part of 0.0.\nComplex numbers are represented as a pair of floating point numbers\nand have the same restrictions on their range. To create a complex\nnumber with a nonzero real part, add a floating point number to it,\ne.g., "(3+4j)". Some examples of imaginary literals:\n\n 3.14j 10.j 10j .001j 1e100j 3.14e-10j\n',
'import': u'\nThe "import" statement\n**********************\n\n import_stmt ::= "import" module ["as" name] ( "," module ["as" name] )*\n | "from" relative_module "import" identifier ["as" name]\n ( "," identifier ["as" name] )*\n | "from" relative_module "import" "(" identifier ["as" name]\n ( "," identifier ["as" name] )* [","] ")"\n | "from" module "import" "*"\n module ::= (identifier ".")* identifier\n relative_module ::= "."* module | "."+\n name ::= identifier\n\nThe basic import statement (no "from" clause) is executed in two\nsteps:\n\n1. find a module, loading and initializing it if necessary\n\n2. define a name or names in the local namespace for the scope\n where the "import" statement occurs.\n\nWhen the statement contains multiple clauses (separated by commas) the\ntwo steps are carried out separately for each clause, just as though\nthe clauses had been separated out into individiual import statements.\n\nThe details of the first step, finding and loading modules are\ndescribed in greater detail in the section on the *import system*,\nwhich also describes the various types of packages and modules that\ncan be imported, as well as all the hooks that can be used to\ncustomize the import system. Note that failures in this step may\nindicate either that the module could not be located, *or* that an\nerror occurred while initializing the module, which includes execution\nof the module\'s code.\n\nIf the requested module is retrieved successfully, it will be made\navailable in the local namespace in one of three ways:\n\n* If the module name is followed by "as", then the name following\n "as" is bound directly to the imported module.\n\n* If no other name is specified, and the module being imported is a\n top level module, the module\'s name is bound in the local namespace\n as a reference to the imported module\n\n* If the module being imported is *not* a top level module, then the\n name of the top level package that contains the module is bound in\n the local namespace as a reference to the top level package. The\n imported module must be accessed using its full qualified name\n rather than directly\n\nThe "from" form uses a slightly more complex process:\n\n1. find the module specified in the "from" clause, loading and\n initializing it if necessary;\n\n2. for each of the identifiers specified in the "import" clauses:\n\n 1. check if the imported module has an attribute by that name\n\n 2. if not, attempt to import a submodule with that name and then\n check the imported module again for that attribute\n\n 3. if the attribute is not found, "ImportError" is raised.\n\n 4. otherwise, a reference to that value is stored in the local\n namespace, using the name in the "as" clause if it is present,\n otherwise using the attribute name\n\nExamples:\n\n import foo # foo imported and bound locally\n import foo.bar.baz # foo.bar.baz imported, foo bound locally\n import foo.bar.baz as fbb # foo.bar.baz imported and bound as fbb\n from foo.bar import baz # foo.bar.baz imported and bound as baz\n from foo import attr # foo imported and foo.attr bound as attr\n\nIf the list of identifiers is replaced by a star ("\'*\'"), all public\nnames defined in the module are bound in the local namespace for the\nscope where the "import" statement occurs.\n\nThe *public names* defined by a module are determined by checking the\nmodule\'s namespace for a variable named "__all__"; if defined, it must\nbe a sequence of strings which are names defined or imported by that\nmodule. The names given in "__all__" are all considered public and\nare required to exist. If "__all__" is not defined, the set of public\nnames includes all names found in the module\'s namespace which do not\nbegin with an underscore character ("\'_\'"). "__all__" should contain\nthe entire public API. It is intended to avoid accidentally exporting\nitems that are not part of the API (such as library modules which were\nimported and used within the module).\n\nThe wild card form of import --- "from module import *" --- is only\nallowed at the module level. Attempting to use it in class or\nfunction definitions will raise a "SyntaxError".\n\nWhen specifying what module to import you do not have to specify the\nabsolute name of the module. When a module or package is contained\nwithin another package it is possible to make a relative import within\nthe same top package without having to mention the package name. By\nusing leading dots in the specified module or package after "from" you\ncan specify how high to traverse up the current package hierarchy\nwithout specifying exact names. One leading dot means the current\npackage where the module making the import exists. Two dots means up\none package level. Three dots is up two levels, etc. So if you execute\n"from . import mod" from a module in the "pkg" package then you will\nend up importing "pkg.mod". If you execute "from ..subpkg2 import mod"\nfrom within "pkg.subpkg1" you will import "pkg.subpkg2.mod". The\nspecification for relative imports is contained within **PEP 328**.\n\n"importlib.import_module()" is provided to support applications that\ndetermine dynamically the modules to be loaded.\n\n\nFuture statements\n=================\n\nA *future statement* is a directive to the compiler that a particular\nmodule should be compiled using syntax or semantics that will be\navailable in a specified future release of Python where the feature\nbecomes standard.\n\nThe future statement is intended to ease migration to future versions\nof Python that introduce incompatible changes to the language. It\nallows use of the new features on a per-module basis before the\nrelease in which the feature becomes standard.\n\n future_statement ::= "from" "__future__" "import" feature ["as" name]\n ("," feature ["as" name])*\n | "from" "__future__" "import" "(" feature ["as" name]\n ("," feature ["as" name])* [","] ")"\n feature ::= identifier\n name ::= identifier\n\nA future statement must appear near the top of the module. The only\nlines that can appear before a future statement are:\n\n* the module docstring (if any),\n\n* comments,\n\n* blank lines, and\n\n* other future statements.\n\nThe features recognized by Python 3.0 are "absolute_import",\n"division", "generators", "unicode_literals", "print_function",\n"nested_scopes" and "with_statement". They are all redundant because\nthey are always enabled, and only kept for backwards compatibility.\n\nA future statement is recognized and treated specially at compile\ntime: Changes to the semantics of core constructs are often\nimplemented by generating different code. It may even be the case\nthat a new feature introduces new incompatible syntax (such as a new\nreserved word), in which case the compiler may need to parse the\nmodule differently. Such decisions cannot be pushed off until\nruntime.\n\nFor any given release, the compiler knows which feature names have\nbeen defined, and raises a compile-time error if a future statement\ncontains a feature not known to it.\n\nThe direct runtime semantics are the same as for any import statement:\nthere is a standard module "__future__", described later, and it will\nbe imported in the usual way at the time the future statement is\nexecuted.\n\nThe interesting runtime semantics depend on the specific feature\nenabled by the future statement.\n\nNote that there is nothing special about the statement:\n\n import __future__ [as name]\n\nThat is not a future statement; it\'s an ordinary import statement with\nno special semantics or syntax restrictions.\n\nCode compiled by calls to the built-in functions "exec()" and\n"compile()" that occur in a module "M" containing a future statement\nwill, by default, use the new syntax or semantics associated with the\nfuture statement. This can be controlled by optional arguments to\n"compile()" --- see the documentation of that function for details.\n\nA future statement typed at an interactive interpreter prompt will\ntake effect for the rest of the interpreter session. If an\ninterpreter is started with the *-i* option, is passed a script name\nto execute, and the script includes a future statement, it will be in\neffect in the interactive session started after the script is\nexecuted.\n\nSee also: **PEP 236** - Back to the __future__\n\n The original proposal for the __future__ mechanism.\n',
- 'in': u'\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 only\nonce (but in both cases "z" is not evaluated at all when "x < y" is\nfound 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", except\nthat each expression is evaluated at most once.\n\nNote that "a op1 b op2 c" doesn\'t imply any kind of comparison between\n*a* and *c*, so that, e.g., "x < y > z" is perfectly legal (though\nperhaps not pretty).\n\nThe operators "<", ">", "==", ">=", "<=", and "!=" compare the values\nof two objects. The objects need not have the same type. If both are\nnumbers, they are converted to a common type. Otherwise, the "==" and\n"!=" operators *always* consider objects of different types to be\nunequal, while the "<", ">", ">=" and "<=" operators raise a\n"TypeError" when comparing objects of different types that do not\nimplement these operators for the given pair of types. You can\ncontrol comparison behavior of objects of non-built-in types by\ndefining rich comparison methods like "__gt__()", described in section\n*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. They\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\n equivalents (the result of the built-in function "ord()") of their\n characters. [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison\n of 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 same\n value as "x <= y". If the corresponding element does not exist, the\n shorter sequence is ordered first (for example, "[1,2] < [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 undefined\n results given a list of sets as inputs.\n\n* Most other objects of built-in types compare unequal unless they\n are the same object; the choice whether one object is considered\n smaller or larger than another one is made arbitrarily but\n consistently within one execution of a program.\n\nComparison of objects of differing types depends on whether either of\nthe types provide explicit support for the comparison. Most numeric\ntypes can be compared with one another. When cross-type comparison is\nnot supported, the comparison method returns "NotImplemented".\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" tests\nwhether the dictionary has a given key. For container types such as\nlist, 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* is\na substring of *y*. An equivalent test is "y.find(x) != -1". Empty\nstrings are always considered to be a substring of any other string,\nso """ in "abc"" will return "True".\n\nFor user-defined classes which define the "__contains__()" method, "x\nin 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 == z"\nis produced while iterating over "y". If an exception is raised\nduring 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 y" is\ntrue if and only if *x* and *y* are the same object. "x is not y"\nyields the inverse truth value. [4]\n',
+ 'in': u'\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 only\nonce (but in both cases "z" is not evaluated at all when "x < y" is\nfound 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", except\nthat each expression is evaluated at most once.\n\nNote that "a op1 b op2 c" doesn\'t imply any kind of comparison between\n*a* and *c*, so that, e.g., "x < y > z" is perfectly legal (though\nperhaps not pretty).\n\nThe operators "<", ">", "==", ">=", "<=", and "!=" compare the values\nof two objects. The objects need not have the same type. If both are\nnumbers, they are converted to a common type. Otherwise, the "==" and\n"!=" operators *always* consider objects of different types to be\nunequal, while the "<", ">", ">=" and "<=" operators raise a\n"TypeError" when comparing objects of different types that do not\nimplement these operators for the given pair of types. You can\ncontrol comparison behavior of objects of non-built-in types by\ndefining rich comparison methods like "__gt__()", described in section\n*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. They\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\n equivalents (the result of the built-in function "ord()") of their\n characters. [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison\n of 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 same\n value as "x <= y". If the corresponding element does not exist, the\n shorter sequence is ordered first (for example, "[1,2] < [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 undefined\n results given a list of sets as inputs.\n\n* Most other objects of built-in types compare unequal unless they\n are the same object; the choice whether one object is considered\n smaller or larger than another one is made arbitrarily but\n consistently within one execution of a program.\n\nComparison of objects of differing types depends on whether either of\nthe types provide explicit support for the comparison. Most numeric\ntypes can be compared with one another. When cross-type comparison is\nnot supported, the comparison method returns "NotImplemented".\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" tests\nwhether the dictionary has a given key. For container types such as\nlist, 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* is\na substring of *y*. An equivalent test is "y.find(x) != -1". Empty\nstrings are always considered to be a substring of any other string,\nso """ in "abc"" will return "True".\n\nFor user-defined classes which define the "__contains__()" method, "x\nin 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 == z"\nis produced while iterating over "y". If an exception is raised\nduring 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 y" is\ntrue if and only if *x* and *y* are the same object. "x is not y"\nyields the inverse truth value. [4]\n',
'integers': u'\nInteger literals\n****************\n\nInteger literals are described by the following lexical definitions:\n\n integer ::= decimalinteger | octinteger | hexinteger | bininteger\n decimalinteger ::= nonzerodigit digit* | "0"+\n nonzerodigit ::= "1"..."9"\n digit ::= "0"..."9"\n octinteger ::= "0" ("o" | "O") octdigit+\n hexinteger ::= "0" ("x" | "X") hexdigit+\n bininteger ::= "0" ("b" | "B") bindigit+\n octdigit ::= "0"..."7"\n hexdigit ::= digit | "a"..."f" | "A"..."F"\n bindigit ::= "0" | "1"\n\nThere is no limit for the length of integer literals apart from what\ncan be stored in available memory.\n\nNote that leading zeros in a non-zero decimal number are not allowed.\nThis is for disambiguation with C-style octal literals, which Python\nused before version 3.0.\n\nSome examples of integer literals:\n\n 7 2147483647 0o177 0b100110111\n 3 79228162514264337593543950336 0o377 0xdeadbeef\n',
'lambda': u'\nLambdas\n*******\n\n lambda_expr ::= "lambda" [parameter_list]: expression\n lambda_expr_nocond ::= "lambda" [parameter_list]: expression_nocond\n\nLambda expressions (sometimes called lambda forms) are used to create\nanonymous functions. The expression "lambda arguments: expression"\nyields a function object. The unnamed object behaves like a function\nobject defined with\n\n def <lambda>(arguments):\n return expression\n\nSee section *Function definitions* for the syntax of parameter lists.\nNote that functions created with lambda expressions cannot contain\nstatements or annotations.\n',
'lists': u'\nList displays\n*************\n\nA list display is a possibly empty series of expressions enclosed in\nsquare brackets:\n\n list_display ::= "[" [expression_list | comprehension] "]"\n\nA list display yields a new list object, the contents being specified\nby either a list of expressions or a comprehension. When a comma-\nseparated list of expressions is supplied, its elements are evaluated\nfrom left to right and placed into the list object in that order.\nWhen a comprehension is supplied, the list is constructed from the\nelements resulting from the comprehension.\n',
- 'naming': u'\nNaming and binding\n******************\n\n\nBinding of names\n================\n\n*Names* refer to objects. Names are introduced by name binding\noperations.\n\nThe following constructs bind names: formal parameters to functions,\n"import" statements, class and function definitions (these bind the\nclass or function name in the defining block), and targets that are\nidentifiers if occurring in an assignment, "for" loop header, or after\n"as" in a "with" statement or "except" clause. The "import" statement\nof the form "from ... import *" binds all names defined in the\nimported module, except those beginning with an underscore. This form\nmay only be used at the module level.\n\nA target occurring in a "del" statement is also considered bound for\nthis purpose (though the actual semantics are to unbind the name).\n\nEach assignment or import statement occurs within a block defined by a\nclass or function definition or at the module level (the top-level\ncode block).\n\nIf a name is bound in a block, it is a local variable of that block,\nunless declared as "nonlocal" or "global". If a name is bound at the\nmodule level, it is a global variable. (The variables of the module\ncode block are local and global.) If a variable is used in a code\nblock but not defined there, it is a *free variable*.\n\nEach occurrence of a name in the program text refers to the *binding*\nof that name established by the following name resolution rules.\n\n\nResolution of names\n===================\n\nA *scope* defines the visibility of a name within a block. If a local\nvariable is defined in a block, its scope includes that block. If the\ndefinition occurs in a function block, the scope extends to any blocks\ncontained within the defining one, unless a contained block introduces\na different binding for the name.\n\nWhen a name is used in a code block, it is resolved using the nearest\nenclosing scope. The set of all such scopes visible to a code block\nis called the block\'s *environment*.\n\nWhen a name is not found at all, a "NameError" exception is raised. If\nthe current scope is a function scope, and the name refers to a local\nvariable that has not yet been bound to a value at the point where the\nname is used, an "UnboundLocalError" exception is raised.\n"UnboundLocalError" is a subclass of "NameError".\n\nIf a name binding operation occurs anywhere within a code block, all\nuses of the name within the block are treated as references to the\ncurrent block. This can lead to errors when a name is used within a\nblock before it is bound. This rule is subtle. Python lacks\ndeclarations and allows name binding operations to occur anywhere\nwithin a code block. The local variables of a code block can be\ndetermined by scanning the entire text of the block for name binding\noperations.\n\nIf the "global" statement occurs within a block, all uses of the name\nspecified in the statement refer to the binding of that name in the\ntop-level namespace. Names are resolved in the top-level namespace by\nsearching the global namespace, i.e. the namespace of the module\ncontaining the code block, and the builtins namespace, the namespace\nof the module "builtins". The global namespace is searched first. If\nthe name is not found there, the builtins namespace is searched. The\n"global" statement must precede all uses of the name.\n\nThe "global" statement has the same scope as a name binding operation\nin the same block. If the nearest enclosing scope for a free variable\ncontains a global statement, the free variable is treated as a global.\n\nThe "nonlocal" statement causes corresponding names to refer to\npreviously bound variables in the nearest enclosing function scope.\n"SyntaxError" is raised at compile time if the given name does not\nexist in any enclosing function scope.\n\nThe namespace for a module is automatically created the first time a\nmodule is imported. The main module for a script is always called\n"__main__".\n\nClass definition blocks and arguments to "exec()" and "eval()" are\nspecial in the context of name resolution. A class definition is an\nexecutable statement that may use and define names. These references\nfollow the normal rules for name resolution with an exception that\nunbound local variables are looked up in the global namespace. The\nnamespace of the class definition becomes the attribute dictionary of\nthe class. The scope of names defined in a class block is limited to\nthe class block; it does not extend to the code blocks of methods --\nthis includes comprehensions and generator expressions since they are\nimplemented using a function scope. This means that the following\nwill fail:\n\n class A:\n a = 42\n b = list(a + i for i in range(10))\n\n\nBuiltins and restricted execution\n=================================\n\nThe builtins namespace associated with the execution of a code block\nis actually found by looking up the name "__builtins__" in its global\nnamespace; this should be a dictionary or a module (in the latter case\nthe module\'s dictionary is used). By default, when in the "__main__"\nmodule, "__builtins__" is the built-in module "builtins"; when in any\nother module, "__builtins__" is an alias for the dictionary of the\n"builtins" module itself. "__builtins__" can be set to a user-created\ndictionary to create a weak form of restricted execution.\n\n**CPython implementation detail:** Users should not touch\n"__builtins__"; it is strictly an implementation detail. Users\nwanting to override values in the builtins namespace should "import"\nthe "builtins" module and modify its attributes appropriately.\n\n\nInteraction with dynamic features\n=================================\n\nName resolution of free variables occurs at runtime, not at compile\ntime. This means that the following code will print 42:\n\n i = 10\n def f():\n print(i)\n i = 42\n f()\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\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',
+ 'naming': u'\nNaming and binding\n******************\n\n*Names* refer to objects. Names are introduced by name binding\noperations. Each occurrence of a name in the program text refers to\nthe *binding* of that name established in the innermost function block\ncontaining the use.\n\nA *block* is a piece of Python program text that is executed as a\nunit. The following are blocks: a module, a function body, and a class\ndefinition. Each command typed interactively is a block. A script\nfile (a file given as standard input to the interpreter or specified\nas a command line argument to the interpreter) is a code block. A\nscript command (a command specified on the interpreter command line\nwith the \'**-c**\' option) is a code block. The string argument passed\nto the built-in functions "eval()" and "exec()" is a code block.\n\nA code block is executed in an *execution frame*. A frame contains\nsome administrative information (used for debugging) and determines\nwhere and how execution continues after the code block\'s execution has\ncompleted.\n\nA *scope* defines the visibility of a name within a block. If a local\nvariable is defined in a block, its scope includes that block. If the\ndefinition occurs in a function block, the scope extends to any blocks\ncontained within the defining one, unless a contained block introduces\na different binding for the name. The scope of names defined in a\nclass block is limited to the class block; it does not extend to the\ncode blocks of methods -- this includes comprehensions and generator\nexpressions since they are implemented using a function scope. This\nmeans that the following will fail:\n\n class A:\n a = 42\n b = list(a + i for i in range(10))\n\nWhen a name is used in a code block, it is resolved using the nearest\nenclosing scope. The set of all such scopes visible to a code block\nis called the block\'s *environment*.\n\nIf a name is bound in a block, it is a local variable of that block,\nunless declared as "nonlocal". If a name is bound at the module\nlevel, it is a global variable. (The variables of the module code\nblock are local and global.) If a variable is used in a code block\nbut not defined there, it is a *free variable*.\n\nWhen a name is not found at all, a "NameError" exception is raised.\nIf the name refers to a local variable that has not been bound, an\n"UnboundLocalError" exception is raised. "UnboundLocalError" is a\nsubclass of "NameError".\n\nThe following constructs bind names: formal parameters to functions,\n"import" statements, class and function definitions (these bind the\nclass or function name in the defining block), and targets that are\nidentifiers if occurring in an assignment, "for" loop header, or after\n"as" in a "with" statement or "except" clause. The "import" statement\nof the form "from ... import *" binds all names defined in the\nimported module, except those beginning with an underscore. This form\nmay only be used at the module level.\n\nA target occurring in a "del" statement is also considered bound for\nthis purpose (though the actual semantics are to unbind the name).\n\nEach assignment or import statement occurs within a block defined by a\nclass or function definition or at the module level (the top-level\ncode block).\n\nIf a name binding operation occurs anywhere within a code block, all\nuses of the name within the block are treated as references to the\ncurrent block. This can lead to errors when a name is used within a\nblock before it is bound. This rule is subtle. Python lacks\ndeclarations and allows name binding operations to occur anywhere\nwithin a code block. The local variables of a code block can be\ndetermined by scanning the entire text of the block for name binding\noperations.\n\nIf the "global" statement occurs within a block, all uses of the name\nspecified in the statement refer to the binding of that name in the\ntop-level namespace. Names are resolved in the top-level namespace by\nsearching the global namespace, i.e. the namespace of the module\ncontaining the code block, and the builtins namespace, the namespace\nof the module "builtins". The global namespace is searched first. If\nthe name is not found there, the builtins namespace is searched. The\n"global" statement must precede all uses of the name.\n\nThe builtins namespace associated with the execution of a code block\nis actually found by looking up the name "__builtins__" in its global\nnamespace; this should be a dictionary or a module (in the latter case\nthe module\'s dictionary is used). By default, when in the "__main__"\nmodule, "__builtins__" is the built-in module "builtins"; when in any\nother module, "__builtins__" is an alias for the dictionary of the\n"builtins" module itself. "__builtins__" can be set to a user-created\ndictionary to create a weak form of restricted execution.\n\n**CPython implementation detail:** Users should not touch\n"__builtins__"; it is strictly an implementation detail. Users\nwanting to override values in the builtins namespace should "import"\nthe "builtins" module and modify its attributes appropriately.\n\nThe namespace for a module is automatically created the first time a\nmodule is imported. The main module for a script is always called\n"__main__".\n\nThe "global" statement has the same scope as a name binding operation\nin the same block. If the nearest enclosing scope for a free variable\ncontains a global statement, the free variable is treated as a global.\n\nA class definition is an executable statement that may use and define\nnames. These references follow the normal rules for name resolution.\nThe namespace of the class definition becomes the attribute dictionary\nof the class. Names defined at the class scope are not visible in\nmethods.\n\n\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\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',
'nonlocal': u'\nThe "nonlocal" statement\n************************\n\n nonlocal_stmt ::= "nonlocal" identifier ("," identifier)*\n\nThe "nonlocal" statement causes the listed identifiers to refer to\npreviously bound variables in the nearest enclosing scope excluding\nglobals. This is important because the default behavior for binding is\nto search the local namespace first. The statement allows\nencapsulated code to rebind variables outside of the local scope\nbesides the global (module) scope.\n\nNames listed in a "nonlocal" statement, unlike those listed in a\n"global" statement, must refer to pre-existing bindings in an\nenclosing scope (the scope in which a new binding should be created\ncannot be determined unambiguously).\n\nNames listed in a "nonlocal" statement must not collide with pre-\nexisting bindings in the local scope.\n\nSee also: **PEP 3104** - Access to Names in Outer Scopes\n\n The specification for the "nonlocal" statement.\n',
'numbers': u'\nNumeric literals\n****************\n\nThere are three types of numeric literals: integers, floating point\nnumbers, and imaginary numbers. There are no complex literals\n(complex numbers can be formed by adding a real number and an\nimaginary number).\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',
'numeric-types': u'\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.__matmul__(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 ("+", "-", "*", "@", "/", "//", "%", "divmod()",\n "pow()", "**", "<<", ">>", "&", "^", "|"). For instance, to\n evaluate the expression "x + y", where *x* is an instance of a\n class that has an "__add__()" method, "x.__add__(y)" is called.\n The "__divmod__()" method should be the equivalent to using\n "__floordiv__()" and "__mod__()"; it should not be related to\n "__truediv__()". Note that "__pow__()" should be defined to accept\n an optional third argument if the ternary version of the built-in\n "pow()" function 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.__rmatmul__(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 ("+", "-", "*", "@", "/", "//", "%", "divmod()",\n "pow()", "**", "<<", ">>", "&", "^", "|") with reflected (swapped)\n operands. These functions are only called if the left operand does\n not support the corresponding operation and the operands are of\n different types. [2] For instance, to evaluate the expression "x -\n y", where *y* is an instance of a class that has an "__rsub__()"\n method, "y.__rsub__(x)" is called if "x.__sub__(y)" returns\n *NotImplemented*.\n\n Note that ternary "pow()" will not try calling "__rpow__()" (the\n coercion rules would become too complicated).\n\n Note: If the right operand\'s type is a subclass of the left\n operand\'s type and that subclass provides the reflected method\n for the operation, this method will be called before the left\n operand\'s non-reflected method. This behavior allows subclasses\n to override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__imatmul__(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 should attempt to\n do the operation in-place (modifying *self*) and return the result\n (which could be, but does not have to be, *self*). If a specific\n method is not defined, the augmented assignment falls back to the\n normal methods. For instance, if *x* is an instance of a class\n with an "__iadd__()" method, "x += y" is equivalent to "x =\n x.__iadd__(y)" . Otherwise, "x.__add__(y)" and "y.__radd__(x)" are\n considered, as with the evaluation of "x + y". In certain\n situations, augmented assignment can result in unexpected errors\n (see *Why does a_tuple[i] += [\'item\'] raise an exception when the\n addition works?*), but this behavior is in fact part of the data\n model.\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()", "int()",\n "float()" and "round()". Should return a value of the appropriate\n type.\n\nobject.__index__(self)\n\n Called to implement "operator.index()", and whenever Python needs\n to losslessly convert the numeric object to an integer object (such\n as in slicing, or in the built-in "bin()", "hex()" and "oct()"\n functions). Presence of this method indicates that the numeric\n object is an integer type. Must return an integer.\n\n Note: In order to have a coherent integer type class, when\n "__index__()" is defined "__int__()" should also be defined, and\n both should return the same value.\n',
'objects': u'\nObjects, values and types\n*************************\n\n*Objects* are Python\'s abstraction for data. All data in a Python\nprogram is represented by objects or by relations between objects. (In\na sense, and in conformance to Von Neumann\'s model of a "stored\nprogram computer," code is also represented by objects.)\n\nEvery object has an identity, a type and a value. An object\'s\n*identity* never changes once it has been created; you may think of it\nas the object\'s address in memory. The \'"is"\' operator compares the\nidentity of two objects; the "id()" function returns an integer\nrepresenting its identity.\n\n**CPython implementation detail:** For CPython, "id(x)" is the memory\naddress where "x" is stored.\n\nAn object\'s type determines the operations that the object supports\n(e.g., "does it have a length?") and also defines the possible values\nfor objects of that type. The "type()" function returns an object\'s\ntype (which is an object itself). Like its identity, an object\'s\n*type* is also unchangeable. [1]\n\nThe *value* of some objects can change. Objects whose value can\nchange are said to be *mutable*; objects whose value is unchangeable\nonce they are created are called *immutable*. (The value of an\nimmutable container object that contains a reference to a mutable\nobject can change when the latter\'s value is changed; however the\ncontainer is still considered immutable, because the collection of\nobjects it contains cannot be changed. So, immutability is not\nstrictly the same as having an unchangeable value, it is more subtle.)\nAn object\'s mutability is determined by its type; for instance,\nnumbers, strings and tuples are immutable, while dictionaries and\nlists are mutable.\n\nObjects are never explicitly destroyed; however, when they become\nunreachable they may be garbage-collected. An implementation is\nallowed to postpone garbage collection or omit it altogether --- it is\na matter of implementation quality how garbage collection is\nimplemented, as long as no objects are collected that are still\nreachable.\n\n**CPython implementation detail:** CPython currently uses a reference-\ncounting scheme with (optional) delayed detection of cyclically linked\ngarbage, which collects most objects as soon as they become\nunreachable, but is not guaranteed to collect garbage containing\ncircular references. See the documentation of the "gc" module for\ninformation on controlling the collection of cyclic garbage. Other\nimplementations act differently and CPython may change. Do not depend\non immediate finalization of objects when they become unreachable (so\nyou should always close files explicitly).\n\nNote that the use of the implementation\'s tracing or debugging\nfacilities may keep objects alive that would normally be collectable.\nAlso note that catching an exception with a \'"try"..."except"\'\nstatement may keep objects alive.\n\nSome objects contain references to "external" resources such as open\nfiles or windows. It is understood that these resources are freed\nwhen the object is garbage-collected, but since garbage collection is\nnot guaranteed to happen, such objects also provide an explicit way to\nrelease the external resource, usually a "close()" method. Programs\nare strongly recommended to explicitly close such objects. The\n\'"try"..."finally"\' statement and the \'"with"\' statement provide\nconvenient ways to do this.\n\nSome objects contain references to other objects; these are called\n*containers*. Examples of containers are tuples, lists and\ndictionaries. The references are part of a container\'s value. In\nmost cases, when we talk about the value of a container, we imply the\nvalues, not the identities of the contained objects; however, when we\ntalk about the mutability of a container, only the identities of the\nimmediately contained objects are implied. So, if an immutable\ncontainer (like a tuple) contains a reference to a mutable object, its\nvalue changes if that mutable object is changed.\n\nTypes affect almost all aspects of object behavior. Even the\nimportance of object identity is affected in some sense: for immutable\ntypes, operations that compute new values may actually return a\nreference to any existing object with the same type and value, while\nfor mutable objects this is not allowed. E.g., after "a = 1; b = 1",\n"a" and "b" may or may not refer to the same object with the value\none, depending on the implementation, but after "c = []; d = []", "c"\nand "d" are guaranteed to refer to two different, unique, newly\ncreated empty lists. (Note that "c = d = []" assigns the same object\nto both "c" and "d".)\n',
- 'operator-summary': u'\nOperator precedence\n*******************\n\nThe following table summarizes the operator precedence in Python, from\nlowest 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 exponentiation, which\ngroups from right to left).\n\nNote that comparisons, membership tests, and identity tests, all have\nthe same precedence and have a left-to-right chaining feature as\ndescribed in the *Comparisons* section.\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, matrix multiplication |\n| | division, remainder [5] |\n+-------------------------------------------------+---------------------------------------+\n| "+x", "-x", "~x" | Positive, negative, bitwise NOT |\n+-------------------------------------------------+---------------------------------------+\n| "**" | Exponentiation [6] |\n+-------------------------------------------------+---------------------------------------+\n| "await" "x" | Await expression |\n+-------------------------------------------------+---------------------------------------+\n| "x[index]", "x[index:index]", | Subscription, slicing, call, |\n| "x(arguments...)", "x.attribute" | attribute reference |\n+-------------------------------------------------+---------------------------------------+\n| "(expressions...)", "[expressions...]", "{key: | Binding or tuple display, list |\n| value...}", "{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\n it 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", which\n is numerically exactly equal to "1e100". The function\n "math.fmod()" returns a result whose sign matches the sign of the\n first argument instead, and so returns "-1e-100" in this case.\n Which approach is more appropriate depends on the 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 close\n to "x".\n\n[3] While comparisons between strings make sense at the byte\n level, they may be counter-intuitive to users. For example, the\n strings ""\\u00C7"" and ""\\u0043\\u0327"" 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\n dynamic nature of descriptors, you may notice seemingly unusual\n behaviour in certain uses of the "is" operator, like those\n involving comparisons between instance methods, or constants.\n Check their 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\n or bitwise unary operator on its right, that is, "2**-1" is "0.5".\n',
+ 'operator-summary': u'\nOperator precedence\n*******************\n\nThe following table summarizes the operator precedence in Python, from\nlowest 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 exponentiation, which\ngroups from right to left).\n\nNote that comparisons, membership tests, and identity tests, all have\nthe same precedence and have a left-to-right chaining feature as\ndescribed in the *Comparisons* section.\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, matrix multiplication |\n| | division, remainder [5] |\n+-------------------------------------------------+---------------------------------------+\n| "+x", "-x", "~x" | Positive, negative, bitwise NOT |\n+-------------------------------------------------+---------------------------------------+\n| "**" | Exponentiation [6] |\n+-------------------------------------------------+---------------------------------------+\n| "await" "x" | Await expression |\n+-------------------------------------------------+---------------------------------------+\n| "x[index]", "x[index:index]", | Subscription, slicing, call, |\n| "x(arguments...)", "x.attribute" | attribute reference |\n+-------------------------------------------------+---------------------------------------+\n| "(expressions...)", "[expressions...]", "{key: | Binding or tuple display, list |\n| value...}", "{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\n it 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", which\n is numerically exactly equal to "1e100". The function\n "math.fmod()" returns a result whose sign matches the sign of the\n first argument instead, and so returns "-1e-100" in this case.\n Which approach is more appropriate depends on the 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 close\n to "x".\n\n[3] While comparisons between strings make sense at the byte\n level, they may be counter-intuitive to users. For example, the\n strings ""\\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\n dynamic nature of descriptors, you may notice seemingly unusual\n behaviour in certain uses of the "is" operator, like those\n involving comparisons between instance methods, or constants.\n Check their 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\n or bitwise unary operator on its right, that is, "2**-1" is "0.5".\n',
'pass': u'\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': u'\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 ::= await ["**" 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 "ZeroDivisionError".\nRaising a negative number to a fractional power results in a "complex"\nnumber. (In earlier versions it raised a "ValueError".)\n',
'raise': u'\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 returns\nthe same exception instance, with its traceback set to its argument),\nlike so:\n\n raise Exception("foo occurred").with_traceback(tracebackobj)\n\nThe "from" clause is used for exception chaining: if given, the second\n*expression* must be another exception class or instance, which will\nthen be attached to the raised exception as the "__cause__" attribute\n(which is writable). If the raised exception is not handled, both\nexceptions 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 or a "finally" clause: the previous exception is\nthen attached as the new 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',
@@ -60,15 +60,15 @@
'shifting': u'\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 floor division by "pow(2,n)".\nA left shift by *n* bits is defined as multiplication with "pow(2,n)".\n\nNote: In the current implementation, the right-hand operand is\n required to be at most "sys.maxsize". If the right-hand operand is\n larger than "sys.maxsize" an "OverflowError" exception is raised.\n',
'slicings': u'\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 slicing:\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 is indexed\n(using the same "__getitem__()" method as normal subscription) with a\nkey that is constructed from the slice list, as follows. If the slice\nlist contains 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': u'\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\n in 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\n being one of "Lu" (Letter, uppercase), "Ll" (Letter, lowercase),\n or "Lt" (Letter, titlecase).\n\n[5] To format only a tuple you should therefore provide a\n singleton tuple whose only element is the tuple to be formatted.\n',
- 'specialnames': u'\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 class,\nthen "x[i]" is roughly equivalent to "type(x).__getitem__(x, i)".\nExcept where mentioned, attempts to execute an operation raise an\nexception 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 an\n 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 after the instance has been created (by "__new__()"), but\n before it is returned to the caller. 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, if\n any, must explicitly call it to ensure proper initialization of the\n base class part of the instance; for example:\n "BaseClass.__init__(self, [args...])".\n\n Because "__new__()" and "__init__()" work together in constructing\n objects ("__new__()" to create it, and "__init__()" to customise\n it), no non-"None" value may be returned by "__init__()"; doing so\n will cause a "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, the\n derived class\'s "__del__()" method, if any, must explicitly call it\n to ensure proper deletion of the base class part of the instance.\n Note that it is possible (though not recommended!) for the\n "__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 is\n only called when "x"\'s reference count reaches zero. Some common\n situations that may prevent the reference count of an object from\n going to zero include: circular references between objects (e.g.,\n a doubly-linked list or a tree data structure with parent and\n child pointers); a reference to the object on the stack frame of\n a function that caught an exception (the traceback stored in\n "sys.exc_info()[2]" keeps the stack frame alive); or a reference\n to the object on the stack frame that raised an unhandled\n 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 second can be resolved by freeing the reference to the\n traceback object when it is no longer useful, and the third can\n be resolved by storing "None" in "sys.last_traceback". Circular\n references which are garbage are detected and cleaned up when the\n cyclic garbage collector is enabled (it\'s on by default). Refer\n to the documentation for the "gc" module for more information\n about this topic.\n\n Warning: Due to the precarious circumstances under which\n "__del__()" methods are invoked, exceptions that occur during\n their execution are ignored, and a warning is printed to\n "sys.stderr" instead. Also, when "__del__()" is invoked in\n response to a module being deleted (e.g., when execution of the\n program is done), other globals referenced by the "__del__()"\n method may already have been deleted or in the process of being\n torn down (e.g. the import machinery shutting down). For this\n reason, "__del__()" methods should do the absolute minimum needed\n to maintain external invariants. Starting with version 1.5,\n Python 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 "official"\n string representation of an object. If at all possible, this\n should look like a valid Python expression that could be used to\n 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__()" but\n not "__str__()", then "__repr__()" is also used when an "informal"\n string representation of instances of that class is 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 "str(object)" and the built-in functions "format()" and\n "print()" to compute the "informal" or nicely printable string\n representation of an object. The return value must be a *string*\n object.\n\n This method differs from "object.__repr__()" in that there is no\n expectation that "__str__()" return a valid Python expression: a\n more convenient or concise representation can be used.\n\n The default implementation defined by the built-in type "object"\n calls "object.__repr__()".\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 "str.format()" method of class "str") to produce a "formatted"\n string representation of an object. The "format_spec" argument is a\n string that contains a description of the formatting options\n desired. The interpretation of the "format_spec" argument is up to\n the type implementing "__format__()", however most classes will\n either delegate formatting to one of the built-in types, or use a\n 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\n Changed in version 3.4: The __format__ method of "object" itself\n raises a "TypeError" if passed any non-empty string.\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 "x.__le__(y)",\n "x==y" calls "x.__eq__(y)", "x!=y" calls "x.__ne__(y)", "x>y" calls\n "x.__gt__(y)", and "x>=y" calls "x.__ge__(y)".\n\n A rich comparison method may return the singleton "NotImplemented"\n if it does not implement the operation for a given pair of\n arguments. By convention, "False" and "True" are returned for a\n successful comparison. However, these methods can return any value,\n so if the comparison operator is used in a Boolean context (e.g.,\n in the condition of an "if" statement), Python will call "bool()"\n on the value to determine if the result is true or false.\n\n By default, "__ne__()" delegates to "__eq__()" and inverts the\n result unless it is "NotImplemented". There are no other implied\n relationships among the comparison operators, for example, the\n truth of "(x<y or x==y)" does not imply "x<=y". To automatically\n generate ordering operations from a single root operation, see\n "functools.total_ordering()".\n\n See 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 other\'s\n reflection, "__le__()" and "__ge__()" are each other\'s reflection,\n and "__eq__()" and "__ne__()" are their own reflection. If the\n operands are of different types, and right operand\'s type is a\n direct or indirect subclass of the left operand\'s type, the\n reflected method of the right operand has priority, otherwise the\n left operand\'s method has priority. Virtual subclassing is not\n considered.\n\nobject.__hash__(self)\n\n Called by built-in function "hash()" and for operations on members\n of hashed collections including "set", "frozenset", and "dict".\n "__hash__()" should return an integer. The only required property\n is that objects which compare equal have the same hash value; it is\n advised to somehow mix together (e.g. using exclusive or) the hash\n values for the components of the object that also play a part in\n comparison of objects.\n\n Note: "hash()" truncates the value returned from an object\'s\n custom "__hash__()" method to the size of a "Py_ssize_t". This\n is typically 8 bytes on 64-bit builds and 4 bytes on 32-bit\n builds. If an object\'s "__hash__()" must interoperate on builds\n of different bit sizes, be sure to check the width on all\n supported builds. An easy way to do this is with "python -c\n "import sys; print(sys.hash_info.width)""\n\n If a class does not define an "__eq__()" method it should not\n define a "__hash__()" operation either; if it defines "__eq__()"\n but not "__hash__()", its instances will not be usable as items in\n hashable collections. If a class defines mutable objects and\n implements an "__eq__()" method, it should not implement\n "__hash__()", since the implementation of hashable collections\n requires that a key\'s hash value is immutable (if the object\'s hash\n value changes, it will be in the wrong hash bucket).\n\n User-defined classes have "__eq__()" and "__hash__()" methods by\n default; with them, all objects compare unequal (except with\n themselves) and "x.__hash__()" returns an appropriate value such\n that "x == y" implies both that "x is y" and "hash(x) == hash(y)".\n\n A class that overrides "__eq__()" and does not define "__hash__()"\n will have its "__hash__()" implicitly set to "None". When the\n "__hash__()" method of a class is "None", instances of the class\n will raise an appropriate "TypeError" when a program attempts to\n retrieve their hash value, and will also be correctly identified as\n unhashable when checking "isinstance(obj, collections.Hashable").\n\n If a class that overrides "__eq__()" needs to retain the\n implementation of "__hash__()" from a parent class, the interpreter\n must be told this explicitly by setting "__hash__ =\n <ParentClass>.__hash__".\n\n If a class that does not override "__eq__()" wishes to suppress\n hash support, it should include "__hash__ = None" in the class\n definition. A class which defines its own "__hash__()" that\n explicitly raises a "TypeError" would be incorrectly identified as\n hashable by an "isinstance(obj, collections.Hashable)" call.\n\n 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 iteration order of\n dicts, sets and other mappings. 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 is not\n defined, "__len__()" is called, if it is defined, and the object is\n considered true if its result is nonzero. If a class defines\n neither "__len__()" nor "__bool__()", all its instances are\n 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") for\nclass 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. This\n method should return the (computed) attribute value or raise an\n "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 for\n efficiency reasons and because otherwise "__getattr__()" would have\n no way to access other attributes of the instance. Note that at\n least for instance variables, you can fake total control by not\n 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 "__getattr__()",\n the latter will not be called unless "__getattribute__()" either\n calls it explicitly or raises an "AttributeError". This method\n should return the (computed) attribute value or raise an\n "AttributeError" exception. In order to avoid infinite recursion in\n this method, its implementation should always call the base class\n method with the same name to access any attributes it needs, for\n example, "object.__getattribute__(self, name)".\n\n Note: This method may still be bypassed when looking up special\n methods as the result of implicit invocation via language syntax\n or 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 "AttributeError"\n 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\nThe attribute "__objclass__" is interpreted by the "inspect" module as\nspecifying the class where this object was defined (setting this\nappropriately can assist in runtime introspection of dynamic class\nattributes). For callables, it may indicate that an instance of the\ngiven type (or a subclass) is expected or required as the first\npositional argument (for example, CPython sets this attribute for\nunbound methods that are implemented in C).\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, it\nis 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". How\nthe 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 "A"\n immediately preceding "B" and then invokes the descriptor with the\n 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__()". If it\ndoes not define "__get__()", then accessing the attribute will return\nthe descriptor object itself unless there is a value in the object\'s\ninstance dictionary. If the descriptor defines "__set__()" and/or\n"__delete__()", it is a data descriptor; if it defines neither, it is\na non-data descriptor. Normally, data descriptors define both\n"__get__()" and "__set__()", while non-data descriptors have just the\n"__get__()" method. Data descriptors with "__set__()" and "__get__()"\ndefined always override a redefinition in an instance dictionary. In\ncontrast, non-data descriptors can be overridden by instances.\n\nPython methods (including "staticmethod()" and "classmethod()") are\nimplemented 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. *__slots__*\n reserves space for the declared variables and prevents the\n automatic creation of *__dict__* and *__weakref__* for each\n 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\n defining *__slots__* do not support weak references to its\n instances. If weak reference support is needed, then add\n "\'__weakref__\'" to the sequence of strings in the *__slots__*\n 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\n instance variable defined by the base class slot is inaccessible\n (except by retrieving its descriptor directly from the base class).\n This 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", "bytes" and "tuple".\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings\n may 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()". The class body is\nexecuted in a new namespace and the class name is bound locally to the\nresult of "type(name, bases, namespace)".\n\nThe class creation process can be customised by passing the\n"metaclass" keyword argument in the class definition line, or by\ninheriting from an existing class that included such an argument. In\nthe following example, both "MyClass" and "MySubclass" are instances\nof "Meta":\n\n class Meta(type):\n pass\n\n class MyClass(metaclass=Meta):\n pass\n\n class MySubclass(MyClass):\n pass\n\nAny other keyword arguments that are specified in the class definition\nare passed through to all metaclass operations described below.\n\nWhen a class definition is executed, the following steps occur:\n\n* the appropriate metaclass is determined\n\n* the class namespace is prepared\n\n* the class body is executed\n\n* the class object is created\n\n\nDetermining the appropriate metaclass\n-------------------------------------\n\nThe appropriate metaclass for a class definition is determined as\nfollows:\n\n* if no bases and no explicit metaclass are given, then "type()" is\n used\n\n* if an explicit metaclass is given and it is *not* an instance of\n "type()", then it is used directly as the metaclass\n\n* if an instance of "type()" is given as the explicit metaclass, or\n bases are defined, then the most derived metaclass is used\n\nThe most derived metaclass is selected from the explicitly specified\nmetaclass (if any) and the metaclasses (i.e. "type(cls)") of all\nspecified base classes. The most derived metaclass is one which is a\nsubtype of *all* of these candidate metaclasses. If none of the\ncandidate metaclasses meets that criterion, then the class definition\nwill fail with "TypeError".\n\n\nPreparing the class namespace\n-----------------------------\n\nOnce the appropriate metaclass has been identified, then the class\nnamespace is prepared. If the metaclass has a "__prepare__" attribute,\nit is called as "namespace = metaclass.__prepare__(name, bases,\n**kwds)" (where the additional keyword arguments, if any, come from\nthe class definition).\n\nIf the metaclass has no "__prepare__" attribute, then the class\nnamespace is initialised as an empty "dict()" instance.\n\nSee also: **PEP 3115** - Metaclasses in Python 3000\n\n Introduced the "__prepare__" namespace hook\n\n\nExecuting the class body\n------------------------\n\nThe class body is executed (approximately) as "exec(body, globals(),\nnamespace)". The key difference from a normal call to "exec()" is that\nlexical scoping allows the class body (including any methods) to\nreference names from the current and outer scopes when the class\ndefinition occurs inside a function.\n\nHowever, even when the class definition occurs inside the function,\nmethods defined inside the class still cannot see names defined at the\nclass scope. Class variables must be accessed through the first\nparameter of instance or class methods, and cannot be accessed at all\nfrom static methods.\n\n\nCreating the class object\n-------------------------\n\nOnce the class namespace has been populated by executing the class\nbody, the class object is created by calling "metaclass(name, bases,\nnamespace, **kwds)" (the additional keywords passed here are the same\nas those passed to "__prepare__").\n\nThis class object is the one that will be referenced by the zero-\nargument form of "super()". "__class__" is an implicit closure\nreference created by the compiler if any methods in a class body refer\nto either "__class__" or "super". This allows the zero argument form\nof "super()" to correctly identify the class being defined based on\nlexical scoping, while the class or instance that was used to make the\ncurrent call is identified based on the first argument passed to the\nmethod.\n\nAfter the class object is created, it is passed to the class\ndecorators included in the class definition (if any) and the resulting\nobject is bound in the local namespace as the defined class.\n\nSee also: **PEP 3135** - New super\n\n Describes the implicit "__class__" closure reference\n\n\nMetaclass example\n-----------------\n\nThe potential uses for metaclasses are boundless. Some ideas that have\nbeen explored include 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 variables\nare 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, namespace, **kwds):\n result = type.__new__(cls, name, bases, dict(namespace))\n result.members = tuple(namespace)\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 and\nattributes 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 in\norder 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: **PEP 3119** - Introducing Abstract Base Classes\n\n Includes the specification for customizing "isinstance()" and\n "issubclass()" behavior through "__instancecheck__()" and\n "__subclasscheck__()", with motivation for this functionality in\n 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" where\n*N* is the length of the sequence, or slice objects, which define a\nrange of items. It is also recommended that mappings provide the\nmethods "keys()", "values()", "items()", "get()", "clear()",\n"setdefault()", "pop()", "popitem()", "copy()", and "update()"\nbehaving similar to those for Python\'s standard dictionary objects.\nThe "collections" module provides a "MutableMapping" abstract base\nclass to help create those methods from a base set of "__getitem__()",\n"__setitem__()", "__delitem__()", and "keys()". Mutable sequences\nshould provide methods "append()", "count()", "index()", "extend()",\n"insert()", "pop()", "remove()", "reverse()" and "sort()", like Python\nstandard list objects. Finally, sequence types should implement\naddition (meaning concatenation) and multiplication (meaning\nrepetition) by defining the methods "__add__()", "__radd__()",\n"__iadd__()", "__mul__()", "__rmul__()" and "__imul__()" described\nbelow; they should not define other numerical operators. It is\nrecommended that both mappings and sequences implement the\n"__contains__()" method to allow efficient use of the "in" operator;\nfor mappings, "in" should search the mapping\'s keys; for sequences, it\nshould search through the values. It is further recommended that both\nmappings and sequences implement the "__iter__()" method to allow\nefficient iteration through the container; for mappings, "__iter__()"\nshould be the same as "keys()"; for sequences, it should iterate\nthrough 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 that\n doesn\'t define a "__bool__()" method and whose "__len__()" method\n returns zero is considered to be false in a Boolean context.\n\nobject.__length_hint__(self)\n\n Called to implement "operator.length_hint()". Should return an\n estimated length for the object (which may be greater or less than\n the actual length). The length must be an integer ">=" 0. This\n method is purely an optimization and is never required for\n correctness.\n\n New in version 3.4.\n\nNote: Slicing is done exclusively with the following three methods.\n A 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 "None".\n\nobject.__getitem__(self, key)\n\n Called to implement evaluation of "self[key]". For sequence types,\n the accepted keys should be integers and slice objects. Note that\n the special interpretation of negative indexes (if the class wishes\n to emulate a sequence type) is up to the "__getitem__()" method. If\n *key* is of an inappropriate type, "TypeError" may be raised; if of\n a value outside the set of indexes for the sequence (after any\n special interpretation of negative values), "IndexError" should be\n raised. For mapping types, if *key* is missing (not in the\n container), "KeyError" 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.__missing__(self, key)\n\n Called by "dict"."__getitem__()" to implement "self[key]" for dict\n subclasses when key is not in the dictionary.\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__()" 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.\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 "reversed()"\n built-in will fall back to using the sequence protocol ("__len__()"\n and "__getitem__()"). Objects that support the sequence protocol\n should only provide "__reversed__()" if they can provide an\n implementation that is more efficient than the one provided by\n "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 test\n first tries iteration via "__iter__()", then the old sequence\n iteration protocol via "__getitem__()", see *this section in the\n 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.__matmul__(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 ("+", "-", "*", "@", "/", "//", "%", "divmod()",\n "pow()", "**", "<<", ">>", "&", "^", "|"). For instance, to\n evaluate the expression "x + y", where *x* is an instance of a\n class that has an "__add__()" method, "x.__add__(y)" is called.\n The "__divmod__()" method should be the equivalent to using\n "__floordiv__()" and "__mod__()"; it should not be related to\n "__truediv__()". Note that "__pow__()" should be defined to accept\n an optional third argument if the ternary version of the built-in\n "pow()" function 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.__rmatmul__(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 ("+", "-", "*", "@", "/", "//", "%", "divmod()",\n "pow()", "**", "<<", ">>", "&", "^", "|") with reflected (swapped)\n operands. These functions are only called if the left operand does\n not support the corresponding operation and the operands are of\n different types. [2] For instance, to evaluate the expression "x -\n y", where *y* is an instance of a class that has an "__rsub__()"\n method, "y.__rsub__(x)" is called if "x.__sub__(y)" returns\n *NotImplemented*.\n\n Note that ternary "pow()" will not try calling "__rpow__()" (the\n coercion rules would become too complicated).\n\n Note: If the right operand\'s type is a subclass of the left\n operand\'s type and that subclass provides the reflected method\n for the operation, this method will be called before the left\n operand\'s non-reflected method. This behavior allows subclasses\n to override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__imatmul__(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 should attempt to\n do the operation in-place (modifying *self*) and return the result\n (which could be, but does not have to be, *self*). If a specific\n method is not defined, the augmented assignment falls back to the\n normal methods. For instance, if *x* is an instance of a class\n with an "__iadd__()" method, "x += y" is equivalent to "x =\n x.__iadd__(y)" . Otherwise, "x.__add__(y)" and "y.__radd__(x)" are\n considered, as with the evaluation of "x + y". In certain\n situations, augmented assignment can result in unexpected errors\n (see *Why does a_tuple[i] += [\'item\'] raise an exception when the\n addition works?*), but this behavior is in fact part of the data\n model.\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()", "int()",\n "float()" and "round()". Should return a value of the appropriate\n type.\n\nobject.__index__(self)\n\n Called to implement "operator.index()", and whenever Python needs\n to losslessly convert the numeric object to an integer object (such\n as in slicing, or in the built-in "bin()", "hex()" and "oct()"\n functions). Presence of this method indicates that the numeric\n object is an integer type. Must return an integer.\n\n Note: In order to have a coherent integer type class, when\n "__index__()" is defined "__int__()" should also be defined, and\n both should return the same value.\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 manager\nhandles the entry into, and the exit from, the desired runtime context\nfor the execution of the block of code. Context managers are normally\ninvoked using the "with" statement (described in section *The with\nstatement*), but can also be used by directly invoking their methods.\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: **PEP 0343** - The "with" statement\n\n The specification, background, and examples for the Python "with"\n 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 by\nall objects, including type objects. If the implicit lookup of these\nmethods used the conventional lookup process, they would fail when\ninvoked 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 provides\nsignificant scope for speed optimisations within the interpreter, at\nthe cost of some flexibility in the handling of special methods (the\nspecial method *must* be set on the class object itself in order to be\nconsistently invoked by the interpreter).\n',
- 'string-methods': u'\nString Methods\n**************\n\nStrings implement all of the *common* sequence operations, along with\nthe additional methods described below.\n\nStrings also support two styles of string formatting, one providing a\nlarge degree of flexibility and customization (see "str.format()",\n*Format String Syntax* and *String Formatting*) and the other based on\nC "printf" style formatting that handles a narrower range of types and\nis slightly harder to use correctly, but is often faster for the cases\nit can handle (*printf-style String Formatting*).\n\nThe *Text Processing Services* section of the standard library covers\na number of other modules that provide various text related utilities\n(including regular expression support in the "re" module).\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 "\'\xdf\'" is equivalent to ""ss"".\n Since it is already lowercase, "lower()" would do nothing to "\'\xdf\'";\n "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 an ASCII space). The\n original string is returned if *width* is less than or equal to\n "len(s)".\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 possible\n values are "\'ignore\'", "\'replace\'", "\'xmlcharrefreplace\'",\n "\'backslashreplace\'" and any other name registered via\n "codecs.register_error()", see section *Error Handlers*. For a list\n of possible encodings, see section *Standard 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 suffixes\n to look for. With optional *start*, test beginning at that\n position. With optional *end*, stop comparing at that position.\n\nstr.expandtabs(tabsize=8)\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. Tab positions occur every *tabsize* characters\n (default is 8, giving tab positions at columns 0, 8, 16 and so on).\n To expand the string, the current column is set to zero and the\n string is examined character by character. If the character is a\n tab ("\\t"), one or more space characters are inserted in the result\n until the current column is equal to the next tab position. (The\n tab character itself is not copied.) If the character is a newline\n ("\\n") or return ("\\r"), it is copied and the current column is\n reset to zero. Any other character is copied unchanged and the\n current column is incremented by one regardless of how the\n character is represented when printed.\n\n >>> \'01\\t012\\t0123\\t01234\'.expandtabs()\n \'01 012 0123 01234\'\n >>> \'01\\t012\\t0123\\t01234\'.expandtabs(4)\n \'01 012 0123 01234\'\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\n the position of *sub*. To check if *sub* is a substring or not,\n use 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 used\n directly and not copied to a "dict". This is useful if for example\n "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 "c"\n is alphanumeric if one of the following returns "True":\n "c.isalpha()", "c.isdecimal()", "c.isdigit()", or "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\n Use "keyword.iskeyword()" to test for reserved identifiers such as\n "def" and "class".\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 an ASCII\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* is\n 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 an ASCII\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 splitting\n from the right, "rsplit()" behaves like "split()" which is\n 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 or "-1", then there is\n no limit 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* argument\n may consist of multiple characters (for example,\n "\'1<>2<>3\'.split(\'<>\')" returns "[\'1\', \'2\', \'3\']"). Splitting an\n empty string with a specified separator returns "[\'\']".\n\n For example:\n\n >>> \'1,2,3\'.split(\',\')\n [\'1\', \'2\', \'3\']\n >>> \'1,2,3\'.split(\',\', maxsplit=1)\n [\'1\', \'2,3\']\n >>> \'1,2,,3,\'.split(\',\')\n [\'1\', \'2\', \'\', \'3\', \'\']\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 For example:\n\n >>> \'1 2 3\'.split()\n [\'1\', \'2\', \'3\']\n >>> \'1 2 3\'.split(maxsplit=1)\n [\'1\', \'2 3\']\n >>> \' 1 2 3 \'.split()\n [\'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\n This method splits on the following line boundaries. In\n particular, the boundaries are a superset of *universal newlines*.\n\n +-------------------------+-------------------------------+\n | Representation | Description |\n +=========================+===============================+\n | "\\n" | Line Feed |\n +-------------------------+-------------------------------+\n | "\\r" | Carriage Return |\n +-------------------------+-------------------------------+\n | "\\r\\n" | Carriage Return + Line Feed |\n +-------------------------+-------------------------------+\n | "\\v" or "\\x0b" | Line Tabulation |\n +-------------------------+-------------------------------+\n | "\\f" or "\\x0c" | Form Feed |\n +-------------------------+-------------------------------+\n | "\\x1c" | File Separator |\n +-------------------------+-------------------------------+\n | "\\x1d" | Group Separator |\n +-------------------------+-------------------------------+\n | "\\x1e" | Record Separator |\n +-------------------------+-------------------------------+\n | "\\x85" | Next Line (C1 Control Code) |\n +-------------------------+-------------------------------+\n | "\\u2028" | Line Separator |\n +-------------------------+-------------------------------+\n | "\\u2029" | Paragraph Separator |\n +-------------------------+-------------------------------+\n\n Changed in version 3.2: "\\v" and "\\f" added to list of line\n boundaries.\n\n For example:\n\n >>> \'ab c\\n\\nde fg\\rkl\\r\\n\'.splitlines()\n [\'ab c\', \'\', \'de fg\', \'kl\']\n >>> \'ab c\\n\\nde fg\\rkl\\r\\n\'.splitlines(keepends=True)\n [\'ab c\\n\', \'\\n\', \'de fg\\r\', \'kl\\r\\n\']\n\n Unlike "split()" when a delimiter string *sep* is given, this\n method returns an empty list for the empty string, and a terminal\n line break does not result in an extra line:\n\n >>> "".splitlines()\n []\n >>> "One line\\n".splitlines()\n [\'One line\']\n\n For comparison, "split(\'\\n\')" gives:\n\n >>> \'\'.split(\'\\n\')\n [\'\']\n >>> \'Two lines\\n\'.split(\'\\n\')\n [\'Two lines\', \'\']\n\nstr.startswith(prefix[, start[, end]])\n\n Return "True" if string starts with the *prefix*, otherwise return\n "False". *prefix* can also be a tuple of prefixes to look for.\n With optional *start*, test string beginning at that position.\n With optional *end*, stop comparing string at that 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 *chars*\n argument defaults to removing whitespace. The *chars* argument is\n not a prefix or suffix; rather, all combinations of its values are\n stripped:\n\n >>> \' spacious \'.strip()\n \'spacious\'\n >>> \'www.example.com\'.strip(\'cmowz.\')\n \'example\'\n\n The outermost leading and trailing *chars* argument values are\n stripped from the string. Characters are removed from the leading\n end until reaching a string character that is not contained in the\n set of characters in *chars*. A similar action takes place on the\n trailing end. For example:\n\n >>> comment_string = \'#....... Section 3.2.1 Issue #32 .......\'\n >>> comment_string.strip(\'.#! \')\n \'Section 3.2.1 Issue #32\'\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 For example:\n\n >>> \'Hello world\'.title()\n \'Hello World\'\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(table)\n\n Return a copy of the string in which each character has been mapped\n through the given translation table. The table must be an object\n that implements indexing via "__getitem__()", typically a *mapping*\n or *sequence*. When indexed by a Unicode ordinal (an integer), the\n table object can do any of the following: return a Unicode ordinal\n or a string, to map the character to one or more other characters;\n return "None", to delete the character from the return string; or\n raise a "LookupError" exception, to map the character to itself.\n\n You can use "str.maketrans()" to create a translation map from\n character-to-character mappings in different formats.\n\n See also the "codecs" module for a more flexible approach to custom\n character mappings.\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 be\n "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 a copy of the string left filled with ASCII "\'0\'" digits to\n make a string of length *width*. A leading sign prefix\n ("\'+\'"/"\'-\'") is handled by inserting the padding *after* the sign\n character rather than before. The original string is returned if\n *width* is less than or equal to "len(s)".\n\n For example:\n\n >>> "42".zfill(5)\n \'00042\'\n >>> "-42".zfill(5)\n \'-0042\'\n',
+ 'specialnames': u'\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 class,\nthen "x[i]" is roughly equivalent to "type(x).__getitem__(x, i)".\nExcept where mentioned, attempts to execute an operation raise an\nexception 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 an\n 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 after the instance has been created (by "__new__()"), but\n before it is returned to the caller. 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, if\n any, must explicitly call it to ensure proper initialization of the\n base class part of the instance; for example:\n "BaseClass.__init__(self, [args...])".\n\n Because "__new__()" and "__init__()" work together in constructing\n objects ("__new__()" to create it, and "__init__()" to customise\n it), no non-"None" value may be returned by "__init__()"; doing so\n will cause a "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, the\n derived class\'s "__del__()" method, if any, must explicitly call it\n to ensure proper deletion of the base class part of the instance.\n Note that it is possible (though not recommended!) for the\n "__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 is\n only called when "x"\'s reference count reaches zero. Some common\n situations that may prevent the reference count of an object from\n going to zero include: circular references between objects (e.g.,\n a doubly-linked list or a tree data structure with parent and\n child pointers); a reference to the object on the stack frame of\n a function that caught an exception (the traceback stored in\n "sys.exc_info()[2]" keeps the stack frame alive); or a reference\n to the object on the stack frame that raised an unhandled\n 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 second can be resolved by freeing the reference to the\n traceback object when it is no longer useful, and the third can\n be resolved by storing "None" in "sys.last_traceback". Circular\n references which are garbage are detected and cleaned up when the\n cyclic garbage collector is enabled (it\'s on by default). Refer\n to the documentation for the "gc" module for more information\n about this topic.\n\n Warning: Due to the precarious circumstances under which\n "__del__()" methods are invoked, exceptions that occur during\n their execution are ignored, and a warning is printed to\n "sys.stderr" instead. Also, when "__del__()" is invoked in\n response to a module being deleted (e.g., when execution of the\n program is done), other globals referenced by the "__del__()"\n method may already have been deleted or in the process of being\n torn down (e.g. the import machinery shutting down). For this\n reason, "__del__()" methods should do the absolute minimum needed\n to maintain external invariants. Starting with version 1.5,\n Python 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 "official"\n string representation of an object. If at all possible, this\n should look like a valid Python expression that could be used to\n 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__()" but\n not "__str__()", then "__repr__()" is also used when an "informal"\n string representation of instances of that class is 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 "str(object)" and the built-in functions "format()" and\n "print()" to compute the "informal" or nicely printable string\n representation of an object. The return value must be a *string*\n object.\n\n This method differs from "object.__repr__()" in that there is no\n expectation that "__str__()" return a valid Python expression: a\n more convenient or concise representation can be used.\n\n The default implementation defined by the built-in type "object"\n calls "object.__repr__()".\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 "str.format()" method of class "str") to produce a "formatted"\n string representation of an object. The "format_spec" argument is a\n string that contains a description of the formatting options\n desired. The interpretation of the "format_spec" argument is up to\n the type implementing "__format__()", however most classes will\n either delegate formatting to one of the built-in types, or use a\n 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\n Changed in version 3.4: The __format__ method of "object" itself\n raises a "TypeError" if passed any non-empty string.\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 "x.__le__(y)",\n "x==y" calls "x.__eq__(y)", "x!=y" calls "x.__ne__(y)", "x>y" calls\n "x.__gt__(y)", and "x>=y" calls "x.__ge__(y)".\n\n A rich comparison method may return the singleton "NotImplemented"\n if it does not implement the operation for a given pair of\n arguments. By convention, "False" and "True" are returned for a\n successful comparison. However, these methods can return any value,\n so if the comparison operator is used in a Boolean context (e.g.,\n in the condition of an "if" statement), Python will call "bool()"\n on the value to determine if the result 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 the\n paragraph on "__hash__()" for some important notes on creating\n *hashable* objects which support custom comparison operations and\n 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 other\'s\n reflection, "__le__()" and "__ge__()" are each other\'s reflection,\n and "__eq__()" and "__ne__()" are their own 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 members\n of hashed collections including "set", "frozenset", and "dict".\n "__hash__()" should return an integer. The only required property\n is that objects which compare equal have the same hash value; it is\n advised to somehow mix together (e.g. using exclusive or) the hash\n values for the components of the object that also play a part in\n comparison of objects.\n\n Note: "hash()" truncates the value returned from an object\'s\n custom "__hash__()" method to the size of a "Py_ssize_t". This\n is typically 8 bytes on 64-bit builds and 4 bytes on 32-bit\n builds. If an object\'s "__hash__()" must interoperate on builds\n of different bit sizes, be sure to check the width on all\n supported builds. An easy way to do this is with "python -c\n "import sys; print(sys.hash_info.width)""\n\n If a class does not define an "__eq__()" method it should not\n define a "__hash__()" operation either; if it defines "__eq__()"\n but not "__hash__()", its instances will not be usable as items in\n hashable collections. If a class defines mutable objects and\n implements an "__eq__()" method, it should not implement\n "__hash__()", since the implementation of hashable collections\n requires that a key\'s hash value is immutable (if the object\'s hash\n value changes, it will be in the wrong hash bucket).\n\n User-defined classes have "__eq__()" and "__hash__()" methods by\n default; with them, all objects compare unequal (except with\n themselves) and "x.__hash__()" returns an appropriate value such\n that "x == y" implies both that "x is y" and "hash(x) == hash(y)".\n\n A class that overrides "__eq__()" and does not define "__hash__()"\n will have its "__hash__()" implicitly set to "None". When the\n "__hash__()" method of a class is "None", instances of the class\n will raise an appropriate "TypeError" when a program attempts to\n retrieve their hash value, and will also be correctly identified as\n unhashable when checking "isinstance(obj, collections.Hashable").\n\n If a class that overrides "__eq__()" needs to retain the\n implementation of "__hash__()" from a parent class, the interpreter\n must be told this explicitly by setting "__hash__ =\n <ParentClass>.__hash__".\n\n If a class that does not override "__eq__()" wishes to suppress\n hash support, it should include "__hash__ = None" in the class\n definition. A class which defines its own "__hash__()" that\n explicitly raises a "TypeError" would be incorrectly identified as\n hashable by an "isinstance(obj, collections.Hashable)" call.\n\n 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 iteration order of\n dicts, sets and other mappings. 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 is not\n defined, "__len__()" is called, if it is defined, and the object is\n considered true if its result is nonzero. If a class defines\n neither "__len__()" nor "__bool__()", all its instances are\n 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") for\nclass 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. This\n method should return the (computed) attribute value or raise an\n "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 for\n efficiency reasons and because otherwise "__getattr__()" would have\n no way to access other attributes of the instance. Note that at\n least for instance variables, you can fake total control by not\n 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 "__getattr__()",\n the latter will not be called unless "__getattribute__()" either\n calls it explicitly or raises an "AttributeError". This method\n should return the (computed) attribute value or raise an\n "AttributeError" exception. In order to avoid infinite recursion in\n this method, its implementation should always call the base class\n method with the same name to access any attributes it needs, for\n example, "object.__getattribute__(self, name)".\n\n Note: This method may still be bypassed when looking up special\n methods as the result of implicit invocation via language syntax\n or 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 "AttributeError"\n 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\nThe attribute "__objclass__" is interpreted by the "inspect" module as\nspecifying the class where this object was defined (setting this\nappropriately can assist in runtime introspection of dynamic class\nattributes). For callables, it may indicate that an instance of the\ngiven type (or a subclass) is expected or required as the first\npositional argument (for example, CPython sets this attribute for\nunbound methods that are implemented in C).\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, it\nis 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". How\nthe 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 "A"\n immediately preceding "B" and then invokes the descriptor with the\n 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__()". If it\ndoes not define "__get__()", then accessing the attribute will return\nthe descriptor object itself unless there is a value in the object\'s\ninstance dictionary. If the descriptor defines "__set__()" and/or\n"__delete__()", it is a data descriptor; if it defines neither, it is\na non-data descriptor. Normally, data descriptors define both\n"__get__()" and "__set__()", while non-data descriptors have just the\n"__get__()" method. Data descriptors with "__set__()" and "__get__()"\ndefined always override a redefinition in an instance dictionary. In\ncontrast, non-data descriptors can be overridden by instances.\n\nPython methods (including "staticmethod()" and "classmethod()") are\nimplemented 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. *__slots__*\n reserves space for the declared variables and prevents the\n automatic creation of *__dict__* and *__weakref__* for each\n 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\n defining *__slots__* do not support weak references to its\n instances. If weak reference support is needed, then add\n "\'__weakref__\'" to the sequence of strings in the *__slots__*\n 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\n instance variable defined by the base class slot is inaccessible\n (except by retrieving its descriptor directly from the base class).\n This 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", "bytes" and "tuple".\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings\n may 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()". The class body is\nexecuted in a new namespace and the class name is bound locally to the\nresult of "type(name, bases, namespace)".\n\nThe class creation process can be customised by passing the\n"metaclass" keyword argument in the class definition line, or by\ninheriting from an existing class that included such an argument. In\nthe following example, both "MyClass" and "MySubclass" are instances\nof "Meta":\n\n class Meta(type):\n pass\n\n class MyClass(metaclass=Meta):\n pass\n\n class MySubclass(MyClass):\n pass\n\nAny other keyword arguments that are specified in the class definition\nare passed through to all metaclass operations described below.\n\nWhen a class definition is executed, the following steps occur:\n\n* the appropriate metaclass is determined\n\n* the class namespace is prepared\n\n* the class body is executed\n\n* the class object is created\n\n\nDetermining the appropriate metaclass\n-------------------------------------\n\nThe appropriate metaclass for a class definition is determined as\nfollows:\n\n* if no bases and no explicit metaclass are given, then "type()" is\n used\n\n* if an explicit metaclass is given and it is *not* an instance of\n "type()", then it is used directly as the metaclass\n\n* if an instance of "type()" is given as the explicit metaclass, or\n bases are defined, then the most derived metaclass is used\n\nThe most derived metaclass is selected from the explicitly specified\nmetaclass (if any) and the metaclasses (i.e. "type(cls)") of all\nspecified base classes. The most derived metaclass is one which is a\nsubtype of *all* of these candidate metaclasses. If none of the\ncandidate metaclasses meets that criterion, then the class definition\nwill fail with "TypeError".\n\n\nPreparing the class namespace\n-----------------------------\n\nOnce the appropriate metaclass has been identified, then the class\nnamespace is prepared. If the metaclass has a "__prepare__" attribute,\nit is called as "namespace = metaclass.__prepare__(name, bases,\n**kwds)" (where the additional keyword arguments, if any, come from\nthe class definition).\n\nIf the metaclass has no "__prepare__" attribute, then the class\nnamespace is initialised as an empty "dict()" instance.\n\nSee also: **PEP 3115** - Metaclasses in Python 3000\n\n Introduced the "__prepare__" namespace hook\n\n\nExecuting the class body\n------------------------\n\nThe class body is executed (approximately) as "exec(body, globals(),\nnamespace)". The key difference from a normal call to "exec()" is that\nlexical scoping allows the class body (including any methods) to\nreference names from the current and outer scopes when the class\ndefinition occurs inside a function.\n\nHowever, even when the class definition occurs inside the function,\nmethods defined inside the class still cannot see names defined at the\nclass scope. Class variables must be accessed through the first\nparameter of instance or class methods, and cannot be accessed at all\nfrom static methods.\n\n\nCreating the class object\n-------------------------\n\nOnce the class namespace has been populated by executing the class\nbody, the class object is created by calling "metaclass(name, bases,\nnamespace, **kwds)" (the additional keywords passed here are the same\nas those passed to "__prepare__").\n\nThis class object is the one that will be referenced by the zero-\nargument form of "super()". "__class__" is an implicit closure\nreference created by the compiler if any methods in a class body refer\nto either "__class__" or "super". This allows the zero argument form\nof "super()" to correctly identify the class being defined based on\nlexical scoping, while the class or instance that was used to make the\ncurrent call is identified based on the first argument passed to the\nmethod.\n\nAfter the class object is created, it is passed to the class\ndecorators included in the class definition (if any) and the resulting\nobject is bound in the local namespace as the defined class.\n\nSee also: **PEP 3135** - New super\n\n Describes the implicit "__class__" closure reference\n\n\nMetaclass example\n-----------------\n\nThe potential uses for metaclasses are boundless. Some ideas that have\nbeen explored include 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 variables\nare 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, namespace, **kwds):\n result = type.__new__(cls, name, bases, dict(namespace))\n result.members = tuple(namespace)\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 and\nattributes 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 in\norder 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: **PEP 3119** - Introducing Abstract Base Classes\n\n Includes the specification for customizing "isinstance()" and\n "issubclass()" behavior through "__instancecheck__()" and\n "__subclasscheck__()", with motivation for this functionality in\n 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" where\n*N* is the length of the sequence, or slice objects, which define a\nrange of items. It is also recommended that mappings provide the\nmethods "keys()", "values()", "items()", "get()", "clear()",\n"setdefault()", "pop()", "popitem()", "copy()", and "update()"\nbehaving similar to those for Python\'s standard dictionary objects.\nThe "collections" module provides a "MutableMapping" abstract base\nclass to help create those methods from a base set of "__getitem__()",\n"__setitem__()", "__delitem__()", and "keys()". Mutable sequences\nshould provide methods "append()", "count()", "index()", "extend()",\n"insert()", "pop()", "remove()", "reverse()" and "sort()", like Python\nstandard list objects. Finally, sequence types should implement\naddition (meaning concatenation) and multiplication (meaning\nrepetition) by defining the methods "__add__()", "__radd__()",\n"__iadd__()", "__mul__()", "__rmul__()" and "__imul__()" described\nbelow; they should not define other numerical operators. It is\nrecommended that both mappings and sequences implement the\n"__contains__()" method to allow efficient use of the "in" operator;\nfor mappings, "in" should search the mapping\'s keys; for sequences, it\nshould search through the values. It is further recommended that both\nmappings and sequences implement the "__iter__()" method to allow\nefficient iteration through the container; for mappings, "__iter__()"\nshould be the same as "keys()"; for sequences, it should iterate\nthrough 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 that\n doesn\'t define a "__bool__()" method and whose "__len__()" method\n returns zero is considered to be false in a Boolean context.\n\nobject.__length_hint__(self)\n\n Called to implement "operator.length_hint()". Should return an\n estimated length for the object (which may be greater or less than\n the actual length). The length must be an integer ">=" 0. This\n method is purely an optimization and is never required for\n correctness.\n\n New in version 3.4.\n\nNote: Slicing is done exclusively with the following three methods.\n A 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 "None".\n\nobject.__getitem__(self, key)\n\n Called to implement evaluation of "self[key]". For sequence types,\n the accepted keys should be integers and slice objects. Note that\n the special interpretation of negative indexes (if the class wishes\n to emulate a sequence type) is up to the "__getitem__()" method. If\n *key* is of an inappropriate type, "TypeError" may be raised; if of\n a value outside the set of indexes for the sequence (after any\n special interpretation of negative values), "IndexError" should be\n raised. For mapping types, if *key* is missing (not in the\n container), "KeyError" 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.__missing__(self, key)\n\n Called by "dict"."__getitem__()" to implement "self[key]" for dict\n subclasses when key is not in the dictionary.\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__()" 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.\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 "reversed()"\n built-in will fall back to using the sequence protocol ("__len__()"\n and "__getitem__()"). Objects that support the sequence protocol\n should only provide "__reversed__()" if they can provide an\n implementation that is more efficient than the one provided by\n "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 test\n first tries iteration via "__iter__()", then the old sequence\n iteration protocol via "__getitem__()", see *this section in the\n 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.__matmul__(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 ("+", "-", "*", "@", "/", "//", "%", "divmod()",\n "pow()", "**", "<<", ">>", "&", "^", "|"). For instance, to\n evaluate the expression "x + y", where *x* is an instance of a\n class that has an "__add__()" method, "x.__add__(y)" is called.\n The "__divmod__()" method should be the equivalent to using\n "__floordiv__()" and "__mod__()"; it should not be related to\n "__truediv__()". Note that "__pow__()" should be defined to accept\n an optional third argument if the ternary version of the built-in\n "pow()" function 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.__rmatmul__(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 ("+", "-", "*", "@", "/", "//", "%", "divmod()",\n "pow()", "**", "<<", ">>", "&", "^", "|") with reflected (swapped)\n operands. These functions are only called if the left operand does\n not support the corresponding operation and the operands are of\n different types. [2] For instance, to evaluate the expression "x -\n y", where *y* is an instance of a class that has an "__rsub__()"\n method, "y.__rsub__(x)" is called if "x.__sub__(y)" returns\n *NotImplemented*.\n\n Note that ternary "pow()" will not try calling "__rpow__()" (the\n coercion rules would become too complicated).\n\n Note: If the right operand\'s type is a subclass of the left\n operand\'s type and that subclass provides the reflected method\n for the operation, this method will be called before the left\n operand\'s non-reflected method. This behavior allows subclasses\n to override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__imatmul__(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 should attempt to\n do the operation in-place (modifying *self*) and return the result\n (which could be, but does not have to be, *self*). If a specific\n method is not defined, the augmented assignment falls back to the\n normal methods. For instance, if *x* is an instance of a class\n with an "__iadd__()" method, "x += y" is equivalent to "x =\n x.__iadd__(y)" . Otherwise, "x.__add__(y)" and "y.__radd__(x)" are\n considered, as with the evaluation of "x + y". In certain\n situations, augmented assignment can result in unexpected errors\n (see *Why does a_tuple[i] += [\'item\'] raise an exception when the\n addition works?*), but this behavior is in fact part of the data\n model.\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()", "int()",\n "float()" and "round()". Should return a value of the appropriate\n type.\n\nobject.__index__(self)\n\n Called to implement "operator.index()", and whenever Python needs\n to losslessly convert the numeric object to an integer object (such\n as in slicing, or in the built-in "bin()", "hex()" and "oct()"\n functions). Presence of this method indicates that the numeric\n object is an integer type. Must return an integer.\n\n Note: In order to have a coherent integer type class, when\n "__index__()" is defined "__int__()" should also be defined, and\n both should return the same value.\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 manager\nhandles the entry into, and the exit from, the desired runtime context\nfor the execution of the block of code. Context managers are normally\ninvoked using the "with" statement (described in section *The with\nstatement*), but can also be used by directly invoking their methods.\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: **PEP 0343** - The "with" statement\n\n The specification, background, and examples for the Python "with"\n 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 by\nall objects, including type objects. If the implicit lookup of these\nmethods used the conventional lookup process, they would fail when\ninvoked 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 provides\nsignificant scope for speed optimisations within the interpreter, at\nthe cost of some flexibility in the handling of special methods (the\nspecial method *must* be set on the class object itself in order to be\nconsistently invoked by the interpreter).\n',
+ 'string-methods': u'\nString Methods\n**************\n\nStrings implement all of the *common* sequence operations, along with\nthe additional methods described below.\n\nStrings also support two styles of string formatting, one providing a\nlarge degree of flexibility and customization (see "str.format()",\n*Format String Syntax* and *String Formatting*) and the other based on\nC "printf" style formatting that handles a narrower range of types and\nis slightly harder to use correctly, but is often faster for the cases\nit can handle (*printf-style String Formatting*).\n\nThe *Text Processing Services* section of the standard library covers\na number of other modules that provide various text related utilities\n(including regular expression support in the "re" module).\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 "\'\xdf\'" is equivalent to ""ss"".\n Since it is already lowercase, "lower()" would do nothing to "\'\xdf\'";\n "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 an ASCII space). The\n original string is returned if *width* is less than or equal to\n "len(s)".\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 possible\n values are "\'ignore\'", "\'replace\'", "\'xmlcharrefreplace\'",\n "\'backslashreplace\'" and any other name registered via\n "codecs.register_error()", see section *Error Handlers*. For a list\n of possible encodings, see section *Standard 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 suffixes\n to look for. With optional *start*, test beginning at that\n position. With optional *end*, stop comparing at that position.\n\nstr.expandtabs(tabsize=8)\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. Tab positions occur every *tabsize* characters\n (default is 8, giving tab positions at columns 0, 8, 16 and so on).\n To expand the string, the current column is set to zero and the\n string is examined character by character. If the character is a\n tab ("\\t"), one or more space characters are inserted in the result\n until the current column is equal to the next tab position. (The\n tab character itself is not copied.) If the character is a newline\n ("\\n") or return ("\\r"), it is copied and the current column is\n reset to zero. Any other character is copied unchanged and the\n current column is incremented by one regardless of how the\n character is represented when printed.\n\n >>> \'01\\t012\\t0123\\t01234\'.expandtabs()\n \'01 012 0123 01234\'\n >>> \'01\\t012\\t0123\\t01234\'.expandtabs(4)\n \'01 012 0123 01234\'\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\n the position of *sub*. To check if *sub* is a substring or not,\n use 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 used\n directly and not copied to a "dict". This is useful if for example\n "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 "c"\n is alphanumeric if one of the following returns "True":\n "c.isalpha()", "c.isdecimal()", "c.isdigit()", or "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\n Use "keyword.iskeyword()" to test for reserved identifiers such as\n "def" and "class".\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 an ASCII\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* is\n 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 an ASCII\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 splitting\n from the right, "rsplit()" behaves like "split()" which is\n 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 or "-1", then there is\n no limit 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* argument\n may consist of multiple characters (for example,\n "\'1<>2<>3\'.split(\'<>\')" returns "[\'1\', \'2\', \'3\']"). Splitting an\n empty string with a specified separator returns "[\'\']".\n\n For example:\n\n >>> \'1,2,3\'.split(\',\')\n [\'1\', \'2\', \'3\']\n >>> \'1,2,3\'.split(\',\', maxsplit=1)\n [\'1\', \'2,3\']\n >>> \'1,2,,3,\'.split(\',\')\n [\'1\', \'2\', \'\', \'3\', \'\']\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 For example:\n\n >>> \'1 2 3\'.split()\n [\'1\', \'2\', \'3\']\n >>> \'1 2 3\'.split(maxsplit=1)\n [\'1\', \'2 3\']\n >>> \' 1 2 3 \'.split()\n [\'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\n This method splits on the following line boundaries. In\n particular, the boundaries are a superset of *universal newlines*.\n\n +-------------------------+-------------------------------+\n | Representation | Description |\n +=========================+===============================+\n | "\\n" | Line Feed |\n +-------------------------+-------------------------------+\n | "\\r" | Carriage Return |\n +-------------------------+-------------------------------+\n | "\\r\\n" | Carriage Return + Line Feed |\n +-------------------------+-------------------------------+\n | "\\v" or "\\x0b" | Line Tabulation |\n +-------------------------+-------------------------------+\n | "\\f" or "\\x0c" | Form Feed |\n +-------------------------+-------------------------------+\n | "\\x1c" | File Separator |\n +-------------------------+-------------------------------+\n | "\\x1d" | Group Separator |\n +-------------------------+-------------------------------+\n | "\\x1e" | Record Separator |\n +-------------------------+-------------------------------+\n | "\\x85" | Next Line (C1 Control Code) |\n +-------------------------+-------------------------------+\n | "\\u2028" | Line Separator |\n +-------------------------+-------------------------------+\n | "\\u2029" | Paragraph Separator |\n +-------------------------+-------------------------------+\n\n Changed in version 3.2: "\\v" and "\\f" added to list of line\n boundaries.\n\n For example:\n\n >>> \'ab c\\n\\nde fg\\rkl\\r\\n\'.splitlines()\n [\'ab c\', \'\', \'de fg\', \'kl\']\n >>> \'ab c\\n\\nde fg\\rkl\\r\\n\'.splitlines(keepends=True)\n [\'ab c\\n\', \'\\n\', \'de fg\\r\', \'kl\\r\\n\']\n\n Unlike "split()" when a delimiter string *sep* is given, this\n method returns an empty list for the empty string, and a terminal\n line break does not result in an extra line:\n\n >>> "".splitlines()\n []\n >>> "One line\\n".splitlines()\n [\'One line\']\n\n For comparison, "split(\'\\n\')" gives:\n\n >>> \'\'.split(\'\\n\')\n [\'\']\n >>> \'Two lines\\n\'.split(\'\\n\')\n [\'Two lines\', \'\']\n\nstr.startswith(prefix[, start[, end]])\n\n Return "True" if string starts with the *prefix*, otherwise return\n "False". *prefix* can also be a tuple of prefixes to look for.\n With optional *start*, test string beginning at that position.\n With optional *end*, stop comparing string at that 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 *chars*\n argument defaults to removing whitespace. The *chars* argument is\n not a prefix or suffix; rather, all combinations of its values are\n stripped:\n\n >>> \' spacious \'.strip()\n \'spacious\'\n >>> \'www.example.com\'.strip(\'cmowz.\')\n \'example\'\n\n The outermost leading and trailing *chars* argument values are\n stripped from the string. Characters are removed from the leading\n end until reaching a string character that is not contained in the\n set of characters in *chars*. A similar action takes place on the\n trailing end. For example:\n\n >>> comment_string = \'#....... Section 3.2.1 Issue #32 .......\'\n >>> comment_string.strip(\'.#! \')\n \'Section 3.2.1 Issue #32\'\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 For example:\n\n >>> \'Hello world\'.title()\n \'Hello World\'\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\n character 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 be\n "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 a copy of the string left filled with ASCII "\'0\'" digits to\n make a string of length *width*. A leading sign prefix\n ("\'+\'"/"\'-\'") is handled by inserting the padding *after* the sign\n character rather than before. The original string is returned if\n *width* is less than or equal to "len(s)".\n\n For example:\n\n >>> "42".zfill(5)\n \'00042\'\n >>> "-42".zfill(5)\n \'-0042\'\n',
'strings': u'\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" | "R" | "U"\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 "bytesprefix"\nand the rest of the literal. The source character set is defined by\nthe encoding declaration; it is UTF-8 if no encoding declaration is\ngiven in the source file; see section *Encoding declarations*.\n\nIn plain English: Both types of literals can be enclosed in matching\nsingle quotes ("\'") or double quotes ("""). They can also be enclosed\nin matching groups of three single or double quotes (these are\ngenerally 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 produce\nan instance of the "bytes" type instead of the "str" type. They may\nonly contain ASCII characters; bytes with a numeric value of 128 or\ngreater must be expressed with escapes.\n\nAs of Python 3.3 it is possible again to prefix string literals 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 treat\nbackslashes as literal characters. As a result, in string literals,\n"\'\\U\'" and "\'\\u\'" escapes in raw strings are not treated specially.\nGiven that Python 2.x\'s raw unicode literals behave differently than\nPython 3.x\'s the "\'ur\'" syntax is not supported.\n\nNew in version 3.3: The "\'rb\'" prefix of raw bytes literals has been\nadded as a synonym of "\'br\'".\n\nNew in version 3.3: Support for the unicode legacy literal\n("u\'value\'") was reintroduced to simplify the maintenance of dual\nPython 2.x and 3.x codebases. See **PEP 414** for more information.\n\nIn triple-quoted literals, unescaped newlines and quotes are allowed\n(and are retained), except that three unescaped quotes in a row\nterminate the literal. (A "quote" is the character used to open the\nliteral, i.e. either "\'" or """.)\n\nUnless an "\'r\'" or "\'R\'" prefix is present, escape sequences in string\nand bytes literals are interpreted according to rules similar to those\nused by Standard 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\n byte with the given value. In a string literal, these escapes\n denote a 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\n be encoded using this escape sequence. Exactly four hex digits are\n required.\n\n6. Any Unicode character can be encoded this way. Exactly eight\n 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 result*. (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 literal, quotes can be escaped with a backslash, but the\nbackslash remains in the result; for example, "r"\\""" is a valid\nstring literal consisting of two characters: a backslash and a double\nquote; "r"\\"" is not a valid string literal (even a raw string cannot\nend in an odd number of backslashes). Specifically, *a raw literal\ncannot end in a single backslash* (since the backslash would escape\nthe following quote character). Note also that a single backslash\nfollowed by a newline is interpreted as those two characters as part\nof the literal, *not* as a line continuation.\n',
'subscriptions': u'\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\n(lists or dictionaries for example). 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 "x").\nThe resulting value must be a nonnegative integer less than the number\nof items in the sequence, and the subscription selects the item whose\nindex is that value (counting from zero). Since the support for\nnegative indices and slicing occurs in the object\'s "__getitem__()"\nmethod, subclasses overriding this method will need to explicitly add\nthat 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': u'\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, unless\notherwise stated. (Important exception: the Boolean operations "or"\nand "and" always return one of their operands.)\n',
'try': u'\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" identifier]] ":" 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 no\nexception occurs in the "try" clause, no exception handler is\nexecuted. When an exception occurs in the "try" suite, a search for an\nexception handler is started. This search inspects the except clauses\nin turn until one is found that matches the exception. An expression-\nless except clause, if present, must be last; it matches any\nexception. For an except clause with an expression, that expression\nis evaluated, and the clause matches the exception if the resulting\nobject is "compatible" with the exception. An object is compatible\nwith an exception if it is the class or a base class of the exception\nobject or a tuple containing an item compatible with the exception.\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 raised\nthe 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, if\npresent, 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 accessed via\n"sys.exc_info()". "sys.exc_info()" returns a 3-tuple consisting of the\nexception class, the exception instance and a traceback object (see\nsection *The standard type hierarchy*) identifying the point in the\nprogram where the exception occurred. "sys.exc_info()" values are\nrestored 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 are\nnot handled by the preceding "except" clauses.\n\nIf "finally" is present, it specifies a \'cleanup\' handler. The "try"\nclause is executed, including any "except" and "else" clauses. If an\nexception occurs in any of the clauses and is not handled, the\nexception is temporarily saved. The "finally" clause is executed. If\nthere is a saved exception it is re-raised at the end of the "finally"\nclause. If the "finally" clause raises another exception, the saved\nexception is set as the context of the new exception. If the "finally"\nclause executes a "return" or "break" statement, the saved exception\nis discarded:\n\n >>> def f():\n ... try:\n ... 1/0\n ... finally:\n ... return 42\n ...\n >>> f()\n 42\n\nThe exception information is not available to the program during\nexecution of the "finally" clause.\n\nWhen a "return", "break" or "continue" statement is executed in the\n"try" suite of a "try"..."finally" statement, the "finally" clause is\nalso executed \'on the way out.\' A "continue" statement is illegal in\nthe "finally" clause. (The reason is a problem with the current\nimplementation --- this restriction may be lifted in the future).\n\nThe return value of a function is determined by the last "return"\nstatement executed. Since the "finally" clause always executes, a\n"return" statement executed in the "finally" clause will always be the\nlast one executed:\n\n >>> def foo():\n ... try:\n ... return \'try\'\n ... finally:\n ... return \'finally\'\n ...\n >>> foo()\n \'finally\'\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': u'\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". It\n is used to signify the absence of a value in many situations, e.g.,\n 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\n should return this value if they do not implement the operation for\n the operands provided. (The interpreter will then try the\n reflected operation, or some other fallback, depending on the\n operator.) Its truth value is true.\n\n See *Implementing the arithmetic operations* for more details.\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\n only Boolean objects. The Boolean type is a subtype of the\n integer type, and Boolean values behave like the values 0 and\n 1, 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 are\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 items\n of a sequence. When the length of a sequence is *n*, the index set\n contains the numbers 0, 1, ..., *n*-1. Item *i* of sequence *a* is\n 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* where\n "x = i + n*k", *n* ">=" "0" and *i* "<=" *x* "<" *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 code\n points. All the code points in the range "U+0000 - U+10FFFF"\n can be represented in a string. Python doesn\'t have a "char"\n type; instead, every code point in the string is represented\n as a string object with length "1". The built-in function\n "ord()" converts a code point from its string form to an\n integer in the range "0 - 10FFFF"; "chr()" converts an\n integer in the range "0 - 10FFFF" to the corresponding length\n "1" string object. "str.encode()" can be used to convert a\n "str" to "bytes" using the given text encoding, and\n "bytes.decode()" can be used to achieve the 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 a\n 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 immutable\n and *hashable*, it can be used again as an element of another\n 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 "k"\n from the mapping "a"; this can be used in expressions and as the\n target of assignments or "del" statements. The built-in function\n "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 "1.0")\n 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 "collections"\n 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; not inherited by | |\n | | subclasses | |\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 have | |\n | | 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 that | Read-only |\n | | 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 | | and "\'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__"); "__name__"\n is the method name (same as "__func__.__name__"); "__module__"\n is the name of the module the method was defined in, or "None"\n 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 object\n is said to be bound. The new method\'s "__func__" attribute is\n 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__" attribute\n is the class itself, and its "__func__" attribute is the\n 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, when\n "C" is a class which contains a definition for a function "f()",\n and "x" is an instance of "C", calling "x.f(1)" is equivalent to\n 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 actually\n be the class itself, so that calling either "x.f(1)" or "C.f(1)"\n is equivalent to calling "f(C,1)" where "f" is the underlying\n 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 "iterator.__next__()" method will cause the\n function to execute until it provides a value using the "yield"\n statement. When the function executes a "return" statement or\n falls off 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 Coroutine functions\n A function or method which is defined using "async def" is\n called a *coroutine function*. Such a function, when called,\n returns a *coroutine* object. It may contain "await"\n expressions, as well as "async with" and "async for" statements.\n See also the *Coroutine Objects* section.\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 function\'s\n name; "__self__" is set to "None" (but see the next item);\n "__module__" is the name of the module the function was defined\n 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 a basic organizational unit of Python code, and are\n created by the *import system* as invoked either by the "import"\n statement (see "import"), or by calling functions such as\n "importlib.import_module()" and built-in "__import__()". A module\n object has a namespace implemented by a dictionary object (this is\n the dictionary referenced by the "__globals__" attribute of\n functions defined in the module). Attribute references are\n translated to lookups in this dictionary, e.g., "m.x" is equivalent\n to "m.__dict__["x"]". A module object does not contain the code\n object used to initialize the module (since it isn\'t needed once\n 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 name;\n "__doc__" is the module\'s documentation string, or "None" if\n unavailable; "__file__" is the pathname of the file from which the\n module was loaded, if it was loaded from a file. The "__file__"\n attribute may be missing for certain types of modules, such as C\n modules that are statically linked into the interpreter; for\n extension modules loaded dynamically from a shared library, it is\n the pathname of the 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 allow\n for other means of locating attributes). When the attribute name is\n 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 https://www.python.org/download/releases/2.3/mro/.\n\n When a class attribute reference (for class "C", say) would yield a\n class method object, it is transformed into an instance method\n object whose "__self__" attributes is "C". When it would yield a\n static method object, it is transformed into the object wrapped by\n 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__" is\n the module name in which the class was defined; "__dict__" is the\n dictionary containing the class\'s namespace; "__bases__" is a tuple\n (possibly empty or a singleton) containing the base classes, in the\n order of their occurrence in the base class list; "__doc__" is the\n class\'s documentation string, or None if 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 "__dict__".\n If no class attribute is found, and the object\'s class has a\n "__getattr__()" method, that is called to satisfy the 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 instead\n 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()" method\n 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 name;\n "co_argcount" is the number of positional arguments (including\n arguments with default values); "co_nlocals" is the number of\n local variables used by the function (including arguments);\n "co_varnames" is a tuple containing the names of the local\n variables (starting with the argument names); "co_cellvars" is a\n tuple containing the names of local variables that are\n referenced by nested functions; "co_freevars" is a tuple\n containing the names of free variables; "co_code" is a string\n representing the sequence of bytecode instructions; "co_consts"\n is a tuple containing the literals used by the bytecode;\n "co_names" is a tuple containing the names used by the bytecode;\n "co_filename" is 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 a\n number of flags for the interpreter.\n\n The following flag bits are defined for "co_flags": bit "0x04"\n is set if the function uses the "*arguments" syntax to accept an\n arbitrary number of positional arguments; bit "0x08" is set if\n the function uses the "**keywords" syntax to accept arbitrary\n keyword arguments; bit "0x20" is set if the function is a\n generator.\n\n Future feature declarations ("from __future__ import division")\n also use bits in "co_flags" to indicate whether a code object\n was compiled with a particular feature enabled: bit "0x2000" is\n set if the function was compiled with future division enabled;\n bits "0x10" and "0x1000" were used in earlier versions of\n 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 stack\n frame (towards the caller), or "None" if this is the bottom\n stack frame; "f_code" is the code object being executed in this\n frame; "f_locals" is the dictionary used to look up local\n variables; "f_globals" is used for global variables;\n "f_builtins" is used for built-in (intrinsic) names; "f_lasti"\n gives the precise instruction (this is an index into the\n 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 of\n the frame --- writing to this from within a trace function jumps\n to the given line (only for the bottom-most frame). A debugger\n can implement a Jump command (aka Set Next Statement) by writing\n to f_lineno.\n\n Frame objects support one method:\n\n frame.clear()\n\n This method clears all references to local variables held by\n the frame. Also, if the frame belonged to a generator, the\n generator is finalized. This helps break reference cycles\n involving frame objects (for example when catching an\n exception and storing its traceback for later use).\n\n "RuntimeError" is raised if the frame is currently executing.\n\n New in version 3.4.\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 no\n suitable handler, the stack trace is written (nicely formatted)\n to the standard error stream; if the interpreter is interactive,\n it is also made available to the user as "sys.last_traceback".\n\n Special read-only attributes: "tb_next" is the next level in the\n stack trace (towards the frame where the exception occurred), or\n "None" if there is no next level; "tb_frame" points to the\n execution frame of the current level; "tb_lineno" gives the line\n number where the exception occurred; "tb_lasti" indicates the\n precise instruction. The line number and last instruction in\n the traceback may differ from the line number of its frame\n object if the exception occurred in a "try" statement with no\n matching except clause 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; "stop"\n is the upper bound; "step" is the step value; each is "None" if\n 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',
+ 'types': u'\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". It\n is used to signify the absence of a value in many situations, e.g.,\n 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\n should return this value if they do not implement the operation for\n the operands provided. (The interpreter will then try the\n reflected operation, or some other fallback, depending on the\n operator.) Its truth value is true.\n\n See *Implementing the arithmetic operations* for more details.\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\n only Boolean objects. The Boolean type is a subtype of the\n integer type, and Boolean values behave like the values 0 and\n 1, 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 are\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 items\n of a sequence. When the length of a sequence is *n*, the index set\n contains the numbers 0, 1, ..., *n*-1. Item *i* of sequence *a* is\n 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* where\n "x = i + n*k", *n* ">=" "0" and *i* "<=" *x* "<" *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 code\n points. All the code points in the range "U+0000 - U+10FFFF"\n can be represented in a string. Python doesn\'t have a "char"\n type; instead, every code point in the string is represented\n as a string object with length "1". The built-in function\n "ord()" converts a code point from its string form to an\n integer in the range "0 - 10FFFF"; "chr()" converts an\n integer in the range "0 - 10FFFF" to the corresponding length\n "1" string object. "str.encode()" can be used to convert a\n "str" to "bytes" using the given text encoding, and\n "bytes.decode()" can be used to achieve the 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 a\n 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 immutable\n and *hashable*, it can be used again as an element of another\n 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 "k"\n from the mapping "a"; this can be used in expressions and as the\n target of assignments or "del" statements. The built-in function\n "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 "1.0")\n 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 "collections"\n 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; not inherited by | |\n | | subclasses | |\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 have | |\n | | 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 that | Read-only |\n | | 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 | | and "\'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__"); "__name__"\n is the method name (same as "__func__.__name__"); "__module__"\n is the name of the module the method was defined in, or "None"\n 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 object\n is said to be bound. The new method\'s "__func__" attribute is\n 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__" attribute\n is the class itself, and its "__func__" attribute is the\n 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, when\n "C" is a class which contains a definition for a function "f()",\n and "x" is an instance of "C", calling "x.f(1)" is equivalent to\n 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 actually\n be the class itself, so that calling either "x.f(1)" or "C.f(1)"\n is equivalent to calling "f(C,1)" where "f" is the underlying\n 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 "iterator.__next__()" method will cause the\n function to execute until it provides a value using the "yield"\n statement. When the function executes a "return" statement or\n falls off 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 Coroutine functions\n A function or method which is defined using "async def" is\n called a *coroutine function*. Such a function, when called,\n returns a *coroutine* object. It may contain "await"\n expressions, as well as "async with" and "async for" statements.\n See also *Coroutines* section.\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 function\'s\n name; "__self__" is set to "None" (but see the next item);\n "__module__" is the name of the module the function was defined\n 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 a basic organizational unit of Python code, and are\n created by the *import system* as invoked either by the "import"\n statement (see "import"), or by calling functions such as\n "importlib.import_module()" and built-in "__import__()". A module\n object has a namespace implemented by a dictionary object (this is\n the dictionary referenced by the "__globals__" attribute of\n functions defined in the module). Attribute references are\n translated to lookups in this dictionary, e.g., "m.x" is equivalent\n to "m.__dict__["x"]". A module object does not contain the code\n object used to initialize the module (since it isn\'t needed once\n 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 name;\n "__doc__" is the module\'s documentation string, or "None" if\n unavailable; "__file__" is the pathname of the file from which the\n module was loaded, if it was loaded from a file. The "__file__"\n attribute may be missing for certain types of modules, such as C\n modules that are statically linked into the interpreter; for\n extension modules loaded dynamically from a shared library, it is\n the pathname of the 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 allow\n for other means of locating attributes). When the attribute name is\n 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 https://www.python.org/download/releases/2.3/mro/.\n\n When a class attribute reference (for class "C", say) would yield a\n class method object, it is transformed into an instance method\n object whose "__self__" attributes is "C". When it would yield a\n static method object, it is transformed into the object wrapped by\n 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__" is\n the module name in which the class was defined; "__dict__" is the\n dictionary containing the class\'s namespace; "__bases__" is a tuple\n (possibly empty or a singleton) containing the base classes, in the\n order of their occurrence in the base class list; "__doc__" is the\n class\'s documentation string, or None if 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 "__dict__".\n If no class attribute is found, and the object\'s class has a\n "__getattr__()" method, that is called to satisfy the 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 instead\n 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()" method\n 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 name;\n "co_argcount" is the number of positional arguments (including\n arguments with default values); "co_nlocals" is the number of\n local variables used by the function (including arguments);\n "co_varnames" is a tuple containing the names of the local\n variables (starting with the argument names); "co_cellvars" is a\n tuple containing the names of local variables that are\n referenced by nested functions; "co_freevars" is a tuple\n containing the names of free variables; "co_code" is a string\n representing the sequence of bytecode instructions; "co_consts"\n is a tuple containing the literals used by the bytecode;\n "co_names" is a tuple containing the names used by the bytecode;\n "co_filename" is 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 a\n number of flags for the interpreter.\n\n The following flag bits are defined for "co_flags": bit "0x04"\n is set if the function uses the "*arguments" syntax to accept an\n arbitrary number of positional arguments; bit "0x08" is set if\n the function uses the "**keywords" syntax to accept arbitrary\n keyword arguments; bit "0x20" is set if the function is a\n generator.\n\n Future feature declarations ("from __future__ import division")\n also use bits in "co_flags" to indicate whether a code object\n was compiled with a particular feature enabled: bit "0x2000" is\n set if the function was compiled with future division enabled;\n bits "0x10" and "0x1000" were used in earlier versions of\n 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 stack\n frame (towards the caller), or "None" if this is the bottom\n stack frame; "f_code" is the code object being executed in this\n frame; "f_locals" is the dictionary used to look up local\n variables; "f_globals" is used for global variables;\n "f_builtins" is used for built-in (intrinsic) names; "f_lasti"\n gives the precise instruction (this is an index into the\n 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 of\n the frame --- writing to this from within a trace function jumps\n to the given line (only for the bottom-most frame). A debugger\n can implement a Jump command (aka Set Next Statement) by writing\n to f_lineno.\n\n Frame objects support one method:\n\n frame.clear()\n\n This method clears all references to local variables held by\n the frame. Also, if the frame belonged to a generator, the\n generator is finalized. This helps break reference cycles\n involving frame objects (for example when catching an\n exception and storing its traceback for later use).\n\n "RuntimeError" is raised if the frame is currently executing.\n\n New in version 3.4.\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 no\n suitable handler, the stack trace is written (nicely formatted)\n to the standard error stream; if the interpreter is interactive,\n it is also made available to the user as "sys.last_traceback".\n\n Special read-only attributes: "tb_next" is the next level in the\n stack trace (towards the frame where the exception occurred), or\n "None" if there is no next level; "tb_frame" points to the\n execution frame of the current level; "tb_lineno" gives the line\n number where the exception occurred; "tb_lasti" indicates the\n precise instruction. The line number and last instruction in\n the traceback may differ from the line number of its frame\n object if the exception occurred in a "try" statement with no\n matching except clause 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; "stop"\n is the upper bound; "step" is the step value; each is "None" if\n 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': u'\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': u'\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" module.)\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 index\nthe same dictionary entry. (Note however, that since computers store\nfloating-point numbers as approximations it is usually unwise to use\nthem as dictionary keys.)\n\nDictionaries can be created by placing a comma-separated list of "key:\nvalue" pairs within braces, for example: "{\'jack\': 4098, \'sjoerd\':\n4127}" or "{4098: \'jack\', 4127: \'sjoerd\'}", or by the "dict"\nconstructor.\n\nclass class dict(**kwarg)\nclass class dict(mapping, **kwarg)\nclass class dict(iterable, **kwarg)\n\n Return a new dictionary initialized from an optional positional\n argument and a possibly empty set of keyword arguments.\n\n If no positional argument is given, an empty dictionary is created.\n If a positional argument is given and it is a mapping object, a\n dictionary is created with the same key-value pairs as the mapping\n object. Otherwise, the positional argument must be an *iterable*\n object. Each item in the iterable must itself be an iterable with\n exactly two objects. The first object of each item becomes a key\n in the new dictionary, and the second object the corresponding\n value. If a key occurs more than once, the last value for that key\n becomes the corresponding value in the new dictionary.\n\n If keyword arguments are given, the keyword arguments and their\n values are added to the dictionary created from the positional\n argument. If a key being added is already present, the value from\n the keyword argument replaces the value from the positional\n argument.\n\n To illustrate, the following examples all return a dictionary equal\n to "{"one": 1, "two": 2, "three": 3}":\n\n >>> a = dict(one=1, two=2, three=3)\n >>> b = {\'one\': 1, \'two\': 2, \'three\': 3}\n >>> c = dict(zip([\'one\', \'two\', \'three\'], [1, 2, 3]))\n >>> d = dict([(\'two\', 2), (\'one\', 1), (\'three\', 3)])\n >>> e = dict({\'three\': 3, \'one\': 1, \'two\': 2})\n >>> a == b == c == d == e\n True\n\n Providing keyword arguments as in the first example only works for\n keys that are valid Python identifiers. Otherwise, any valid keys\n can be used.\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__()" and *key*\n is not present, the "d[key]" operation calls that method with\n the key *key* as argument. The "d[key]" operation then returns\n or raises whatever is returned or raised by the\n "__missing__(key)" call. No other operations or methods invoke\n "__missing__()". If "__missing__()" is not defined, "KeyError"\n is raised. "__missing__()" must be a method; it cannot be an\n instance 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 The example above shows part of the implementation of\n "collections.Counter". A different "__missing__" method is used\n by "collections.defaultdict".\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 not\n 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", so\n 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 the *documentation of view objects*.\n\n keys()\n\n Return a new view of the dictionary\'s keys. See the\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 the\n *documentation of view objects*.\n\n Dictionaries compare equal if and only if they have the same "(key,\n value)" pairs. Order comparisons (\'<\', \'<=\', \'>=\', \'>\') raise\n "TypeError".\n\nSee also: "types.MappingProxyType" can be used to create a read-only\n view of a "dict".\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 the\ndictionary\'s entries, which means that when the dictionary changes,\nthe 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 using\n "zip()": "pairs = zip(d.values(), d.keys())". Another way to\n create the same list is "pairs = [(v, k) for (k, v) in 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, values\n or items (in the latter case, *x* should be a "(key, value)"\n 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.abc.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',
+ 'typesmapping': u'\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" module.)\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 index\nthe same dictionary entry. (Note however, that since computers store\nfloating-point numbers as approximations it is usually unwise to use\nthem as dictionary keys.)\n\nDictionaries can be created by placing a comma-separated list of "key:\nvalue" pairs within braces, for example: "{\'jack\': 4098, \'sjoerd\':\n4127}" or "{4098: \'jack\', 4127: \'sjoerd\'}", or by the "dict"\nconstructor.\n\nclass class dict(**kwarg)\nclass class dict(mapping, **kwarg)\nclass class dict(iterable, **kwarg)\n\n Return a new dictionary initialized from an optional positional\n argument and a possibly empty set of keyword arguments.\n\n If no positional argument is given, an empty dictionary is created.\n If a positional argument is given and it is a mapping object, a\n dictionary is created with the same key-value pairs as the mapping\n object. Otherwise, the positional argument must be an *iterable*\n object. Each item in the iterable must itself be an iterable with\n exactly two objects. The first object of each item becomes a key\n in the new dictionary, and the second object the corresponding\n value. If a key occurs more than once, the last value for that key\n becomes the corresponding value in the new dictionary.\n\n If keyword arguments are given, the keyword arguments and their\n values are added to the dictionary created from the positional\n argument. If a key being added is already present, the value from\n the keyword argument replaces the value from the positional\n argument.\n\n To illustrate, the following examples all return a dictionary equal\n to "{"one": 1, "two": 2, "three": 3}":\n\n >>> a = dict(one=1, two=2, three=3)\n >>> b = {\'one\': 1, \'two\': 2, \'three\': 3}\n >>> c = dict(zip([\'one\', \'two\', \'three\'], [1, 2, 3]))\n >>> d = dict([(\'two\', 2), (\'one\', 1), (\'three\', 3)])\n >>> e = dict({\'three\': 3, \'one\': 1, \'two\': 2})\n >>> a == b == c == d == e\n True\n\n Providing keyword arguments as in the first example only works for\n keys that are valid Python identifiers. Otherwise, any valid keys\n can be used.\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__()" and *key*\n is not present, the "d[key]" operation calls that method with\n the key *key* as argument. The "d[key]" operation then returns\n or raises whatever is returned or raised by the\n "__missing__(key)" call. No other operations or methods invoke\n "__missing__()". If "__missing__()" is not defined, "KeyError"\n is raised. "__missing__()" must be a method; it cannot be an\n instance 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 The example above shows part of the implementation of\n "collections.Counter". A different "__missing__" method is used\n by "collections.defaultdict".\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 not\n 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", so\n 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 the *documentation of view objects*.\n\n keys()\n\n Return a new view of the dictionary\'s keys. See the\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 the\n *documentation of view objects*.\n\nSee also: "types.MappingProxyType" can be used to create a read-only\n view of a "dict".\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 the\ndictionary\'s entries, which means that when the dictionary changes,\nthe 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 using\n "zip()": "pairs = zip(d.values(), d.keys())". Another way to\n create the same list is "pairs = [(v, k) for (k, v) in 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, values\n or items (in the latter case, *x* should be a "(key, value)"\n 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.abc.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': u'\nMethods\n*******\n\nMethods are functions that are called using the attribute notation.\nThere are two flavors: built-in methods (such as "append()" on lists)\nand class instance methods. Built-in methods are described with the\ntypes 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 "self"\nargument to the argument list. Bound methods have two special read-\nonly attributes: "m.__self__" is the object on which the method\noperates, and "m.__func__" is the function implementing the method.\nCalling "m(arg-1, arg-2, ..., arg-n)" is completely equivalent to\ncalling "m.__func__(m.__self__, arg-1, arg-2, ..., arg-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 an\nattribute on a method results in an "AttributeError" being raised. In\norder to set a method attribute, you need to explicitly set it on the\nunderlying function object:\n\n >>> class C:\n ... def method(self):\n ... pass\n ...\n >>> c = C()\n >>> c.method.whoami = \'my name is method\' # can\'t set on the method\n Traceback (most recent call last):\n File "<stdin>", line 1, in <module>\n AttributeError: \'method\' object has no attribute \'whoami\'\n >>> c.method.__func__.whoami = \'my name is method\'\n >>> c.method.whoami\n \'my name is method\'\n\nSee *The standard type hierarchy* for more information.\n',
'typesmodules': u'\nModules\n*******\n\nThe only special operation on a module is attribute access: "m.name",\nwhere *m* is a module and *name* accesses a name defined in *m*\'s\nsymbol table. Module attributes can be assigned to. (Note that the\n"import" statement is not, strictly speaking, an operation on a module\nobject; "import foo" does not require a module object named *foo* to\nexist, rather it requires an (external) *definition* for a module\nnamed *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 write\n"m.__dict__[\'a\'] = 1", which defines "m.a" to be "1", but you can\'t\nwrite "m.__dict__ = {}"). Modifying "__dict__" directly is not\nrecommended.\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': u'\nSequence Types --- "list", "tuple", "range"\n*******************************************\n\nThere are three basic sequence types: lists, tuples, and range\nobjects. Additional sequence types tailored for processing of *binary\ndata* and *text strings* are described in dedicated sections.\n\n\nCommon Sequence Operations\n==========================\n\nThe operations in the following table are supported by most sequence\ntypes, both mutable and immutable. The "collections.abc.Sequence" ABC\nis provided to make it easier to correctly implement these operations\non custom sequence types.\n\nThis table lists the sequence operations sorted in ascending priority.\nIn the table, *s* and *t* are sequences of the same type, *n*, *i*,\n*j* and *k* are integers and *x* is an arbitrary object that meets any\ntype and value restrictions imposed by *s*.\n\nThe "in" and "not in" operations have the same priorities as the\ncomparison operations. The "+" (concatenation) and "*" (repetition)\noperations have the same priority as the corresponding numeric\noperations.\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)(7) |\n+----------------------------+----------------------------------+------------+\n| "s * n" or "n * s" | *n* shallow copies of *s* | (2)(7) |\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(x[, i[, j]])" | index of the first occurrence of | (8) |\n| | *x* in *s* (at or after index | |\n| | *i* and before index *j*) | |\n+----------------------------+----------------------------------+------------+\n| "s.count(x)" | total number of occurrences of | |\n| | *x* in *s* | |\n+----------------------------+----------------------------------+------------+\n\nSequences of the same type also support comparisons. In particular,\ntuples and lists are compared lexicographically by comparing\ncorresponding elements. This means that to compare equal, every\nelement must compare equal and the two sequences must be of the same\ntype and have the same length. (For full details see *Comparisons* in\nthe language reference.)\n\nNotes:\n\n1. While the "in" and "not in" operations are used only for simple\n containment testing in the general case, some specialised sequences\n (such as "str", "bytes" and "bytearray") also use them for\n subsequence testing:\n\n >>> "gg" in "eggs"\n True\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\n the 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 "None",\n use "0". If *j* is omitted or "None", use "len(s)". If *i* is\n greater than or equal to *j*, the slice is 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", "i+2*k",\n "i+3*k" and so on, stopping when *j* is reached (but never\n including *j*). If *i* or *j* is greater than "len(s)", use\n "len(s)". If *i* or *j* are omitted or "None", they become "end"\n values (which end depends on the sign of *k*). Note, *k* cannot be\n zero. If *k* is "None", it is treated like "1".\n\n6. Concatenating immutable sequences always results in a new\n object. This means that building up a sequence by repeated\n concatenation will have a quadratic runtime cost in the total\n sequence length. To get a linear runtime cost, you must switch to\n one of the alternatives below:\n\n * if concatenating "str" objects, you can build a list and use\n "str.join()" at the end or else write to a "io.StringIO" instance\n and retrieve its value when complete\n\n * if concatenating "bytes" objects, you can similarly use\n "bytes.join()" or "io.BytesIO", or you can do in-place\n concatenation with a "bytearray" object. "bytearray" objects are\n mutable and have an efficient overallocation mechanism\n\n * if concatenating "tuple" objects, extend a "list" instead\n\n * for other types, investigate the relevant class documentation\n\n7. Some sequence types (such as "range") only support item\n sequences that follow specific patterns, and hence don\'t support\n sequence concatenation or repetition.\n\n8. "index" raises "ValueError" when *x* is not found in *s*. When\n supported, the additional arguments to the index method allow\n efficient searching of subsections of the sequence. Passing the\n extra arguments is roughly equivalent to using "s[i:j].index(x)",\n only without copying any data and with the returned index being\n relative to the start of the sequence rather than the start of the\n slice.\n\n\nImmutable Sequence Types\n========================\n\nThe only operation that immutable sequence types generally implement\nthat is not also implemented by mutable sequence types is support for\nthe "hash()" built-in.\n\nThis support allows immutable sequences, such as "tuple" instances, to\nbe used as "dict" keys and stored in "set" and "frozenset" instances.\n\nAttempting to hash an immutable sequence that contains unhashable\nvalues will result in "TypeError".\n\n\nMutable Sequence Types\n======================\n\nThe operations in the following table are defined on mutable sequence\ntypes. The "collections.abc.MutableSequence" ABC is provided to make\nit easier to correctly implement these operations on custom sequence\ntypes.\n\nIn the table *s* is an instance of a mutable sequence type, *t* is any\niterable object and *x* is an arbitrary object that meets any type and\nvalue restrictions imposed by *s* (for example, "bytearray" only\naccepts integers that meet the value restriction "0 <= x <= 255").\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)" | appends *x* to the end of the | |\n| | sequence (same as | |\n| | "s[len(s):len(s)] = [x]") | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.clear()" | removes all items from "s" (same | (5) |\n| | as "del s[:]") | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.copy()" | creates a shallow copy of "s" | (5) |\n| | (same as "s[:]") | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.extend(t)" | extends *s* with the contents of | |\n| | *t* (same as "s[len(s):len(s)] = | |\n| | t") | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.insert(i, x)" | inserts *x* into *s* at the | |\n| | index given by *i* (same as | |\n| | "s[i:i] = [x]") | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.pop([i])" | retrieves the item at *i* and | (2) |\n| | also removes it from *s* | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.remove(x)" | remove the first item from *s* | (3) |\n| | where "s[i] == x" | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.reverse()" | reverses the items of *s* in | (4) |\n| | place | |\n+--------------------------------+----------------------------------+-----------------------+\n\nNotes:\n\n1. *t* must have the same length as the slice it is replacing.\n\n2. The optional argument *i* defaults to "-1", so that by default\n the last item is removed and returned.\n\n3. "remove" raises "ValueError" when *x* is not found in *s*.\n\n4. The "reverse()" method modifies the sequence in place for\n economy of space when reversing a large sequence. To remind users\n that it operates by side effect, it does not return the reversed\n sequence.\n\n5. "clear()" and "copy()" are included for consistency with the\n interfaces of mutable containers that don\'t support slicing\n operations (such as "dict" and "set")\n\n New in version 3.3: "clear()" and "copy()" methods.\n\n\nLists\n=====\n\nLists are mutable sequences, typically used to store collections of\nhomogeneous items (where the precise degree of similarity will vary by\napplication).\n\nclass class list([iterable])\n\n Lists may be constructed in several ways:\n\n * Using a pair of square brackets to denote the empty list: "[]"\n\n * Using square brackets, separating items with commas: "[a]",\n "[a, b, c]"\n\n * Using a list comprehension: "[x for x in iterable]"\n\n * Using the type constructor: "list()" or "list(iterable)"\n\n The constructor builds a list whose items are the same and in the\n same order as *iterable*\'s items. *iterable* may be either a\n sequence, a container that supports iteration, or an iterator\n object. If *iterable* is already a list, a copy is made and\n returned, similar to "iterable[:]". For example, "list(\'abc\')"\n returns "[\'a\', \'b\', \'c\']" and "list( (1, 2, 3) )" returns "[1, 2,\n 3]". If no argument is given, the constructor creates a new empty\n list, "[]".\n\n Many other operations also produce lists, including the "sorted()"\n built-in.\n\n Lists implement all of the *common* and *mutable* sequence\n operations. Lists also provide the following additional method:\n\n sort(*, key=None, reverse=None)\n\n This method sorts the list in place, using only "<" comparisons\n between items. Exceptions are not suppressed - if any comparison\n operations fail, the entire sort operation will fail (and the\n list will likely be left in a partially modified state).\n\n "sort()" accepts two arguments that can only be passed by\n keyword (*keyword-only arguments*):\n\n *key* specifies a function of one argument that is used to\n extract a comparison key from each list element (for example,\n "key=str.lower"). The key corresponding to each item in the list\n is calculated once and then used for the entire sorting process.\n The default value of "None" means that list items are sorted\n directly without calculating a separate key value.\n\n The "functools.cmp_to_key()" utility is available to convert a\n 2.x 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 This method modifies the sequence in place for economy of space\n when sorting a large sequence. To remind users that it operates\n by side effect, it does not return the sorted sequence (use\n "sorted()" to explicitly request a new sorted list instance).\n\n The "sort()" method is guaranteed to be stable. A sort is\n stable if it guarantees not to change the relative order of\n elements that compare equal --- this is helpful for sorting in\n multiple passes (for example, sort by department, then by salary\n 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\n\nTuples\n======\n\nTuples are immutable sequences, typically used to store collections of\nheterogeneous data (such as the 2-tuples produced by the "enumerate()"\nbuilt-in). Tuples are also used for cases where an immutable sequence\nof homogeneous data is needed (such as allowing storage in a "set" or\n"dict" instance).\n\nclass class tuple([iterable])\n\n Tuples may be constructed in a number of ways:\n\n * Using a pair of parentheses to denote the empty tuple: "()"\n\n * Using a trailing comma for a singleton tuple: "a," or "(a,)"\n\n * Separating items with commas: "a, b, c" or "(a, b, c)"\n\n * Using the "tuple()" built-in: "tuple()" or "tuple(iterable)"\n\n The constructor builds a tuple whose items are the same and in the\n same order as *iterable*\'s items. *iterable* may be either a\n sequence, a container that supports iteration, or an iterator\n object. If *iterable* is already a tuple, it is returned\n unchanged. For example, "tuple(\'abc\')" returns "(\'a\', \'b\', \'c\')"\n and "tuple( [1, 2, 3] )" returns "(1, 2, 3)". If no argument is\n given, the constructor creates a new empty tuple, "()".\n\n Note that it is actually the comma which makes a tuple, not the\n parentheses. The parentheses are optional, except in the empty\n tuple case, or when they are needed to avoid syntactic ambiguity.\n For example, "f(a, b, c)" is a function call with three arguments,\n while "f((a, b, c))" is a function call with a 3-tuple as the sole\n argument.\n\n Tuples implement all of the *common* sequence operations.\n\nFor heterogeneous collections of data where access by name is clearer\nthan access by index, "collections.namedtuple()" may be a more\nappropriate choice than a simple tuple object.\n\n\nRanges\n======\n\nThe "range" type represents an immutable sequence of numbers and is\ncommonly used for looping a specific number of times in "for" loops.\n\nclass class range(stop)\nclass class range(start, stop[, step])\n\n The arguments to the range constructor must be integers (either\n built-in "int" or any object that implements the "__index__"\n special method). If the *step* argument is omitted, it defaults to\n "1". If the *start* argument is omitted, it defaults to "0". If\n *step* is zero, "ValueError" is raised.\n\n For a positive *step*, the contents of a range "r" are determined\n by the formula "r[i] = start + step*i" where "i >= 0" and "r[i] <\n stop".\n\n For a negative *step*, the contents of the range are still\n determined by the formula "r[i] = start + step*i", but the\n constraints are "i >= 0" and "r[i] > stop".\n\n A range object will be empty if "r[0]" does not meet the value\n constraint. Ranges do support negative indices, but these are\n interpreted as indexing from the end of the sequence determined by\n the positive indices.\n\n Ranges containing absolute values larger than "sys.maxsize" are\n permitted but some features (such as "len()") may raise\n "OverflowError".\n\n Range examples:\n\n >>> list(range(10))\n [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n >>> list(range(1, 11))\n [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n >>> list(range(0, 30, 5))\n [0, 5, 10, 15, 20, 25]\n >>> list(range(0, 10, 3))\n [0, 3, 6, 9]\n >>> list(range(0, -10, -1))\n [0, -1, -2, -3, -4, -5, -6, -7, -8, -9]\n >>> list(range(0))\n []\n >>> list(range(1, 0))\n []\n\n Ranges implement all of the *common* sequence operations except\n concatenation and repetition (due to the fact that range objects\n can only represent sequences that follow a strict pattern and\n repetition and concatenation will usually violate that pattern).\n\nThe advantage of the "range" type over a regular "list" or "tuple" is\nthat a "range" object will always take the same (small) amount of\nmemory, no matter the size of the range it represents (as it only\nstores the "start", "stop" and "step" values, calculating individual\nitems and subranges as needed).\n\nRange objects implement the "collections.abc.Sequence" ABC, and\nprovide features such as containment tests, element index lookup,\nslicing and support for negative indices (see *Sequence Types ---\nlist, tuple, range*):\n\n>>> r = range(0, 20, 2)\n>>> r\nrange(0, 20, 2)\n>>> 11 in r\nFalse\n>>> 10 in r\nTrue\n>>> r.index(10)\n5\n>>> r[5]\n10\n>>> r[:5]\nrange(0, 10, 2)\n>>> r[-1]\n18\n\nTesting range objects for equality with "==" and "!=" compares them as\nsequences. That is, two range objects are considered equal if they\nrepresent the same sequence of values. (Note that two range objects\nthat compare equal might have different "start", "stop" and "step"\nattributes, for example "range(0) == range(2, 1, 3)" or "range(0, 3,\n2) == range(0, 4, 2)".)\n\nChanged in version 3.2: Implement the Sequence ABC. Support slicing\nand negative indices. Test "int" objects for membership in constant\ntime instead of iterating through all items.\n\nChanged in version 3.3: Define \'==\' and \'!=\' to compare range objects\nbased on the sequence of values they define (instead of comparing\nbased on object identity).\n\nNew in version 3.3: The "start", "stop" and "step" attributes.\n',
diff --git a/Lib/sched.py b/Lib/sched.py
index b47648d..bd7c0f1 100644
--- a/Lib/sched.py
+++ b/Lib/sched.py
@@ -46,6 +46,17 @@
def __gt__(s, o): return (s.time, s.priority) > (o.time, o.priority)
def __ge__(s, o): return (s.time, s.priority) >= (o.time, o.priority)
+Event.time.__doc__ = ('''Numeric type compatible with the return value of the
+timefunc function passed to the constructor.''')
+Event.priority.__doc__ = ('''Events scheduled for the same time will be executed
+in the order of their priority.''')
+Event.action.__doc__ = ('''Executing the event means executing
+action(*argument, **kwargs)''')
+Event.argument.__doc__ = ('''argument is a sequence holding the positional
+arguments for the action.''')
+Event.kwargs.__doc__ = ('''kwargs is a dictionary holding the keyword
+arguments for the action.''')
+
_sentinel = object()
class scheduler:
diff --git a/Lib/selectors.py b/Lib/selectors.py
index 6d569c3..ecd8632 100644
--- a/Lib/selectors.py
+++ b/Lib/selectors.py
@@ -43,9 +43,17 @@
SelectorKey = namedtuple('SelectorKey', ['fileobj', 'fd', 'events', 'data'])
-"""Object used to associate a file object to its backing file descriptor,
-selected event mask and attached data."""
+SelectorKey.__doc__ = """SelectorKey(fileobj, fd, events, data)
+
+ Object used to associate a file object to its backing
+ file descriptor, selected event mask, and attached data.
+"""
+SelectorKey.fileobj.__doc__ = 'File object registered.'
+SelectorKey.fd.__doc__ = 'Underlying file descriptor.'
+SelectorKey.events.__doc__ = 'Events that must be waited for on this file object.'
+SelectorKey.data.__doc__ = ('''Optional opaque data associated to this file object.
+For example, this could be used to store a per-client session ID.''')
class _SelectorMapping(Mapping):
"""Mapping of file objects to selector keys."""
diff --git a/Lib/shutil.py b/Lib/shutil.py
index 3f4b6bf..f47a763 100644
--- a/Lib/shutil.py
+++ b/Lib/shutil.py
@@ -974,6 +974,9 @@
__all__.append('disk_usage')
_ntuple_diskusage = collections.namedtuple('usage', 'total used free')
+ _ntuple_diskusage.total.__doc__ = 'Total space in bytes'
+ _ntuple_diskusage.used.__doc__ = 'Used space in bytes'
+ _ntuple_diskusage.free.__doc__ = 'Free space in bytes'
def disk_usage(path):
"""Return disk usage statistics about the given path.
diff --git a/Lib/site-packages/README b/Lib/site-packages/README.txt
similarity index 100%
rename from Lib/site-packages/README
rename to Lib/site-packages/README.txt
diff --git a/Lib/sndhdr.py b/Lib/sndhdr.py
index e5901ec..7ecafb4 100644
--- a/Lib/sndhdr.py
+++ b/Lib/sndhdr.py
@@ -37,6 +37,18 @@
SndHeaders = namedtuple('SndHeaders',
'filetype framerate nchannels nframes sampwidth')
+SndHeaders.filetype.__doc__ = ("""The value for type indicates the data type
+and will be one of the strings 'aifc', 'aiff', 'au','hcom',
+'sndr', 'sndt', 'voc', 'wav', '8svx', 'sb', 'ub', or 'ul'.""")
+SndHeaders.framerate.__doc__ = ("""The sampling_rate will be either the actual
+value or 0 if unknown or difficult to decode.""")
+SndHeaders.nchannels.__doc__ = ("""The number of channels or 0 if it cannot be
+determined or if the value is difficult to decode.""")
+SndHeaders.nframes.__doc__ = ("""The value for frames will be either the number
+of frames or -1.""")
+SndHeaders.sampwidth.__doc__ = ("""Either the sample size in bits or
+'A' for A-LAW or 'U' for u-LAW.""")
+
def what(filename):
"""Guess the type of a sound file."""
res = whathdr(filename)
diff --git a/Lib/sre_compile.py b/Lib/sre_compile.py
index 502b061..4edb03f 100644
--- a/Lib/sre_compile.py
+++ b/Lib/sre_compile.py
@@ -409,57 +409,39 @@
table[i] = idx + 1
return table
-def _compile_info(code, pattern, flags):
- # internal: compile an info block. in the current version,
- # this contains min/max pattern width, and an optional literal
- # prefix or a character map
- lo, hi = pattern.getwidth()
- if hi > MAXCODE:
- hi = MAXCODE
- if lo == 0:
- code.extend([INFO, 4, 0, lo, hi])
- return
- # look for a literal prefix
+def _get_literal_prefix(pattern):
+ # look for literal prefix
prefix = []
prefixappend = prefix.append
- prefix_skip = 0
+ prefix_skip = None
+ got_all = True
+ for op, av in pattern.data:
+ if op is LITERAL:
+ prefixappend(av)
+ elif op is SUBPATTERN:
+ prefix1, prefix_skip1, got_all = _get_literal_prefix(av[1])
+ if prefix_skip is None:
+ if av[0] is not None:
+ prefix_skip = len(prefix)
+ elif prefix_skip1 is not None:
+ prefix_skip = len(prefix) + prefix_skip1
+ prefix.extend(prefix1)
+ if not got_all:
+ break
+ else:
+ got_all = False
+ break
+ return prefix, prefix_skip, got_all
+
+def _get_charset_prefix(pattern):
charset = [] # not used
charsetappend = charset.append
- if not (flags & SRE_FLAG_IGNORECASE):
- # look for literal prefix
- for op, av in pattern.data:
+ if pattern.data:
+ op, av = pattern.data[0]
+ if op is SUBPATTERN and av[1]:
+ op, av = av[1][0]
if op is LITERAL:
- if len(prefix) == prefix_skip:
- prefix_skip = prefix_skip + 1
- prefixappend(av)
- elif op is SUBPATTERN and len(av[1]) == 1:
- op, av = av[1][0]
- if op is LITERAL:
- prefixappend(av)
- else:
- break
- else:
- break
- # if no prefix, look for charset prefix
- if not prefix and pattern.data:
- op, av = pattern.data[0]
- if op is SUBPATTERN and av[1]:
- op, av = av[1][0]
- if op is LITERAL:
- charsetappend((op, av))
- elif op is BRANCH:
- c = []
- cappend = c.append
- for p in av[1]:
- if not p:
- break
- op, av = p[0]
- if op is LITERAL:
- cappend((op, av))
- else:
- break
- else:
- charset = c
+ charsetappend((op, av))
elif op is BRANCH:
c = []
cappend = c.append
@@ -473,8 +455,43 @@
break
else:
charset = c
- elif op is IN:
- charset = av
+ elif op is BRANCH:
+ c = []
+ cappend = c.append
+ for p in av[1]:
+ if not p:
+ break
+ op, av = p[0]
+ if op is LITERAL:
+ cappend((op, av))
+ else:
+ break
+ else:
+ charset = c
+ elif op is IN:
+ charset = av
+ return charset
+
+def _compile_info(code, pattern, flags):
+ # internal: compile an info block. in the current version,
+ # this contains min/max pattern width, and an optional literal
+ # prefix or a character map
+ lo, hi = pattern.getwidth()
+ if hi > MAXCODE:
+ hi = MAXCODE
+ if lo == 0:
+ code.extend([INFO, 4, 0, lo, hi])
+ return
+ # look for a literal prefix
+ prefix = []
+ prefix_skip = 0
+ charset = [] # not used
+ if not (flags & SRE_FLAG_IGNORECASE):
+ # look for literal prefix
+ prefix, prefix_skip, got_all = _get_literal_prefix(pattern)
+ # if no prefix, look for charset prefix
+ if not prefix:
+ charset = _get_charset_prefix(pattern)
## if prefix:
## print("*** PREFIX", prefix, prefix_skip)
## if charset:
@@ -487,7 +504,7 @@
mask = 0
if prefix:
mask = SRE_INFO_PREFIX
- if len(prefix) == prefix_skip == len(pattern.data):
+ if prefix_skip is None and got_all:
mask = mask | SRE_INFO_LITERAL
elif charset:
mask = mask | SRE_INFO_CHARSET
@@ -502,6 +519,8 @@
# add literal prefix
if prefix:
emit(len(prefix)) # length
+ if prefix_skip is None:
+ prefix_skip = len(prefix)
emit(prefix_skip) # skip
code.extend(prefix)
# generate overlap table
diff --git a/Lib/string.py b/Lib/string.py
index f3365c6..e7b692d 100644
--- a/Lib/string.py
+++ b/Lib/string.py
@@ -112,10 +112,7 @@
# Check the most common path first.
named = mo.group('named') or mo.group('braced')
if named is not None:
- val = mapping[named]
- # We use this idiom instead of str() because the latter will
- # fail if val is a Unicode containing non-ASCII characters.
- return '%s' % (val,)
+ return str(mapping[named])
if mo.group('escaped') is not None:
return self.delimiter
if mo.group('invalid') is not None:
@@ -142,9 +139,7 @@
named = mo.group('named') or mo.group('braced')
if named is not None:
try:
- # We use this idiom instead of str() because the latter
- # will fail if val is a Unicode containing non-ASCII
- return '%s' % (mapping[named],)
+ return str(mapping[named])
except KeyError:
return mo.group()
if mo.group('escaped') is not None:
diff --git a/Lib/test/datetimetester.py b/Lib/test/datetimetester.py
index babeb44..5d2df32 100644
--- a/Lib/test/datetimetester.py
+++ b/Lib/test/datetimetester.py
@@ -258,7 +258,8 @@
with self.assertRaises(TypeError): self.EST.dst(5)
def test_tzname(self):
- self.assertEqual('UTC+00:00', timezone(ZERO).tzname(None))
+ self.assertEqual('UTC', timezone.utc.tzname(None))
+ self.assertEqual('UTC', timezone(ZERO).tzname(None))
self.assertEqual('UTC-05:00', timezone(-5 * HOUR).tzname(None))
self.assertEqual('UTC+09:30', timezone(9.5 * HOUR).tzname(None))
self.assertEqual('UTC-00:01', timezone(timedelta(minutes=-1)).tzname(None))
@@ -663,11 +664,15 @@
eq(td(milliseconds=0.4/1000), td(0)) # rounds to 0
eq(td(milliseconds=-0.4/1000), td(0)) # rounds to 0
eq(td(milliseconds=0.5/1000), td(microseconds=0))
- eq(td(milliseconds=-0.5/1000), td(microseconds=0))
+ eq(td(milliseconds=-0.5/1000), td(microseconds=-0))
eq(td(milliseconds=0.6/1000), td(microseconds=1))
eq(td(milliseconds=-0.6/1000), td(microseconds=-1))
+ eq(td(milliseconds=1.5/1000), td(microseconds=2))
+ eq(td(milliseconds=-1.5/1000), td(microseconds=-2))
eq(td(seconds=0.5/10**6), td(microseconds=0))
- eq(td(seconds=-0.5/10**6), td(microseconds=0))
+ eq(td(seconds=-0.5/10**6), td(microseconds=-0))
+ eq(td(seconds=1/2**7), td(microseconds=7812))
+ eq(td(seconds=-1/2**7), td(microseconds=-7812))
# Rounding due to contributions from more than one field.
us_per_hour = 3600e6
@@ -1846,11 +1851,12 @@
18000 + 3600 + 2*60 + 3 + 4*1e-6)
def test_microsecond_rounding(self):
- for fts in [self.theclass.fromtimestamp,
- self.theclass.utcfromtimestamp]:
+ for fts in (datetime.fromtimestamp,
+ self.theclass.utcfromtimestamp):
zero = fts(0)
self.assertEqual(zero.second, 0)
self.assertEqual(zero.microsecond, 0)
+ one = fts(1e-6)
try:
minus_one = fts(-1e-6)
except OSError:
@@ -1861,22 +1867,28 @@
self.assertEqual(minus_one.microsecond, 999999)
t = fts(-1e-8)
- self.assertEqual(t, minus_one)
+ self.assertEqual(t, zero)
t = fts(-9e-7)
self.assertEqual(t, minus_one)
t = fts(-1e-7)
- self.assertEqual(t, minus_one)
+ self.assertEqual(t, zero)
+ t = fts(-1/2**7)
+ self.assertEqual(t.second, 59)
+ self.assertEqual(t.microsecond, 992188)
t = fts(1e-7)
self.assertEqual(t, zero)
t = fts(9e-7)
- self.assertEqual(t, zero)
+ self.assertEqual(t, one)
t = fts(0.99999949)
self.assertEqual(t.second, 0)
self.assertEqual(t.microsecond, 999999)
t = fts(0.9999999)
+ self.assertEqual(t.second, 1)
+ self.assertEqual(t.microsecond, 0)
+ t = fts(1/2**7)
self.assertEqual(t.second, 0)
- self.assertEqual(t.microsecond, 999999)
+ self.assertEqual(t.microsecond, 7812)
def test_insane_fromtimestamp(self):
# It's possible that some platform maps time_t to double,
diff --git a/Lib/test/eintrdata/eintr_tester.py b/Lib/test/eintrdata/eintr_tester.py
index f755880..0616df6 100644
--- a/Lib/test/eintrdata/eintr_tester.py
+++ b/Lib/test/eintrdata/eintr_tester.py
@@ -13,6 +13,8 @@
import select
import signal
import socket
+import subprocess
+import sys
import time
import unittest
@@ -28,7 +30,7 @@
# signal delivery periodicity
signal_period = 0.1
# default sleep time for tests - should obviously have:
- # sleep_time > signal_period
+ # sleep_time > signal_period
sleep_time = 0.2
@classmethod
@@ -51,18 +53,22 @@
# default sleep time
time.sleep(cls.sleep_time)
+ def subprocess(self, *args, **kw):
+ cmd_args = (sys.executable, '-c') + args
+ return subprocess.Popen(cmd_args, **kw)
+
@unittest.skipUnless(hasattr(signal, "setitimer"), "requires setitimer()")
class OSEINTRTest(EINTRBaseTest):
""" EINTR tests for the os module. """
+ def new_sleep_process(self):
+ code = 'import time; time.sleep(%r)' % self.sleep_time
+ return self.subprocess(code)
+
def _test_wait_multiple(self, wait_func):
num = 3
- for _ in range(num):
- pid = os.fork()
- if pid == 0:
- self._sleep()
- os._exit(0)
+ processes = [self.new_sleep_process() for _ in range(num)]
for _ in range(num):
wait_func()
@@ -74,12 +80,8 @@
self._test_wait_multiple(lambda: os.wait3(0))
def _test_wait_single(self, wait_func):
- pid = os.fork()
- if pid == 0:
- self._sleep()
- os._exit(0)
- else:
- wait_func(pid)
+ proc = self.new_sleep_process()
+ wait_func(proc.pid)
def test_waitpid(self):
self._test_wait_single(lambda pid: os.waitpid(pid, 0))
@@ -97,19 +99,24 @@
# atomic
datas = [b"hello", b"world", b"spam"]
- pid = os.fork()
- if pid == 0:
- os.close(rd)
- for data in datas:
- # let the parent block on read()
- self._sleep()
- os.write(wr, data)
- os._exit(0)
- else:
- self.addCleanup(os.waitpid, pid, 0)
+ code = '\n'.join((
+ 'import os, sys, time',
+ '',
+ 'wr = int(sys.argv[1])',
+ 'datas = %r' % datas,
+ 'sleep_time = %r' % self.sleep_time,
+ '',
+ 'for data in datas:',
+ ' # let the parent block on read()',
+ ' time.sleep(sleep_time)',
+ ' os.write(wr, data)',
+ ))
+
+ with self.subprocess(code, str(wr), pass_fds=[wr]) as proc:
os.close(wr)
for data in datas:
self.assertEqual(data, os.read(rd, len(data)))
+ self.assertEqual(proc.wait(), 0)
def test_write(self):
rd, wr = os.pipe()
@@ -119,23 +126,34 @@
# we must write enough data for the write() to block
data = b"xyz" * support.PIPE_MAX_SIZE
- pid = os.fork()
- if pid == 0:
- os.close(wr)
- read_data = io.BytesIO()
- # let the parent block on write()
- self._sleep()
- while len(read_data.getvalue()) < len(data):
- chunk = os.read(rd, 2 * len(data))
- read_data.write(chunk)
- self.assertEqual(read_data.getvalue(), data)
- os._exit(0)
- else:
+ code = '\n'.join((
+ 'import io, os, sys, time',
+ '',
+ 'rd = int(sys.argv[1])',
+ 'sleep_time = %r' % self.sleep_time,
+ 'data = b"xyz" * %s' % support.PIPE_MAX_SIZE,
+ 'data_len = len(data)',
+ '',
+ '# let the parent block on write()',
+ 'time.sleep(sleep_time)',
+ '',
+ 'read_data = io.BytesIO()',
+ 'while len(read_data.getvalue()) < data_len:',
+ ' chunk = os.read(rd, 2 * data_len)',
+ ' read_data.write(chunk)',
+ '',
+ 'value = read_data.getvalue()',
+ 'if value != data:',
+ ' raise Exception("read error: %s vs %s bytes"',
+ ' % (len(value), data_len))',
+ ))
+
+ with self.subprocess(code, str(rd), pass_fds=[rd]) as proc:
os.close(rd)
written = 0
while written < len(data):
written += os.write(wr, memoryview(data)[written:])
- self.assertEqual(0, os.waitpid(pid, 0)[1])
+ self.assertEqual(proc.wait(), 0)
@unittest.skipUnless(hasattr(signal, "setitimer"), "requires setitimer()")
@@ -151,19 +169,32 @@
# single-byte payload guard us against partial recv
datas = [b"x", b"y", b"z"]
- pid = os.fork()
- if pid == 0:
- rd.close()
- for data in datas:
- # let the parent block on recv()
- self._sleep()
- wr.sendall(data)
- os._exit(0)
- else:
- self.addCleanup(os.waitpid, pid, 0)
+ code = '\n'.join((
+ 'import os, socket, sys, time',
+ '',
+ 'fd = int(sys.argv[1])',
+ 'family = %s' % int(wr.family),
+ 'sock_type = %s' % int(wr.type),
+ 'datas = %r' % datas,
+ 'sleep_time = %r' % self.sleep_time,
+ '',
+ 'wr = socket.fromfd(fd, family, sock_type)',
+ 'os.close(fd)',
+ '',
+ 'with wr:',
+ ' for data in datas:',
+ ' # let the parent block on recv()',
+ ' time.sleep(sleep_time)',
+ ' wr.sendall(data)',
+ ))
+
+ fd = wr.fileno()
+ proc = self.subprocess(code, str(fd), pass_fds=[fd])
+ with proc:
wr.close()
for data in datas:
self.assertEqual(data, recv_func(rd, len(data)))
+ self.assertEqual(proc.wait(), 0)
def test_recv(self):
self._test_recv(socket.socket.recv)
@@ -180,25 +211,43 @@
# we must send enough data for the send() to block
data = b"xyz" * (support.SOCK_MAX_SIZE // 3)
- pid = os.fork()
- if pid == 0:
- wr.close()
- # let the parent block on send()
- self._sleep()
- received_data = bytearray(len(data))
- n = 0
- while n < len(data):
- n += rd.recv_into(memoryview(received_data)[n:])
- self.assertEqual(received_data, data)
- os._exit(0)
- else:
+ code = '\n'.join((
+ 'import os, socket, sys, time',
+ '',
+ 'fd = int(sys.argv[1])',
+ 'family = %s' % int(rd.family),
+ 'sock_type = %s' % int(rd.type),
+ 'sleep_time = %r' % self.sleep_time,
+ 'data = b"xyz" * %s' % (support.SOCK_MAX_SIZE // 3),
+ 'data_len = len(data)',
+ '',
+ 'rd = socket.fromfd(fd, family, sock_type)',
+ 'os.close(fd)',
+ '',
+ 'with rd:',
+ ' # let the parent block on send()',
+ ' time.sleep(sleep_time)',
+ '',
+ ' received_data = bytearray(data_len)',
+ ' n = 0',
+ ' while n < data_len:',
+ ' n += rd.recv_into(memoryview(received_data)[n:])',
+ '',
+ 'if received_data != data:',
+ ' raise Exception("recv error: %s vs %s bytes"',
+ ' % (len(received_data), data_len))',
+ ))
+
+ fd = rd.fileno()
+ proc = self.subprocess(code, str(fd), pass_fds=[fd])
+ with proc:
rd.close()
written = 0
while written < len(data):
sent = send_func(wr, memoryview(data)[written:])
# sendall() returns None
written += len(data) if sent is None else sent
- self.assertEqual(0, os.waitpid(pid, 0)[1])
+ self.assertEqual(proc.wait(), 0)
def test_send(self):
self._test_send(socket.socket.send)
@@ -215,45 +264,60 @@
self.addCleanup(sock.close)
sock.bind((support.HOST, 0))
- _, port = sock.getsockname()
+ port = sock.getsockname()[1]
sock.listen()
- pid = os.fork()
- if pid == 0:
- # let parent block on accept()
- self._sleep()
- with socket.create_connection((support.HOST, port)):
- self._sleep()
- os._exit(0)
- else:
- self.addCleanup(os.waitpid, pid, 0)
+ code = '\n'.join((
+ 'import socket, time',
+ '',
+ 'host = %r' % support.HOST,
+ 'port = %s' % port,
+ 'sleep_time = %r' % self.sleep_time,
+ '',
+ '# let parent block on accept()',
+ 'time.sleep(sleep_time)',
+ 'with socket.create_connection((host, port)):',
+ ' time.sleep(sleep_time)',
+ ))
+
+ with self.subprocess(code) as proc:
client_sock, _ = sock.accept()
client_sock.close()
+ self.assertEqual(proc.wait(), 0)
@unittest.skipUnless(hasattr(os, 'mkfifo'), 'needs mkfifo()')
def _test_open(self, do_open_close_reader, do_open_close_writer):
+ filename = support.TESTFN
+
# Use a fifo: until the child opens it for reading, the parent will
# block when trying to open it for writing.
- support.unlink(support.TESTFN)
- os.mkfifo(support.TESTFN)
- self.addCleanup(support.unlink, support.TESTFN)
+ support.unlink(filename)
+ os.mkfifo(filename)
+ self.addCleanup(support.unlink, filename)
- pid = os.fork()
- if pid == 0:
- # let the parent block
- self._sleep()
- do_open_close_reader(support.TESTFN)
- os._exit(0)
- else:
- self.addCleanup(os.waitpid, pid, 0)
- do_open_close_writer(support.TESTFN)
+ code = '\n'.join((
+ 'import os, time',
+ '',
+ 'path = %a' % filename,
+ 'sleep_time = %r' % self.sleep_time,
+ '',
+ '# let the parent block',
+ 'time.sleep(sleep_time)',
+ '',
+ do_open_close_reader,
+ ))
+
+ with self.subprocess(code) as proc:
+ do_open_close_writer(filename)
+
+ self.assertEqual(proc.wait(), 0)
def test_open(self):
- self._test_open(lambda path: open(path, 'r').close(),
+ self._test_open("open(path, 'r').close()",
lambda path: open(path, 'w').close())
def test_os_open(self):
- self._test_open(lambda path: os.close(os.open(path, os.O_RDONLY)),
+ self._test_open("os.close(os.open(path, os.O_RDONLY))",
lambda path: os.close(os.open(path, os.O_WRONLY)))
@@ -290,20 +354,21 @@
old_handler = signal.signal(signum, lambda *args: None)
self.addCleanup(signal.signal, signum, old_handler)
+ code = '\n'.join((
+ 'import os, time',
+ 'pid = %s' % os.getpid(),
+ 'signum = %s' % int(signum),
+ 'sleep_time = %r' % self.sleep_time,
+ 'time.sleep(sleep_time)',
+ 'os.kill(pid, signum)',
+ ))
+
t0 = time.monotonic()
- child_pid = os.fork()
- if child_pid == 0:
- # child
- try:
- self._sleep()
- os.kill(pid, signum)
- finally:
- os._exit(0)
- else:
+ with self.subprocess(code) as proc:
# parent
signal.sigwaitinfo([signum])
dt = time.monotonic() - t0
- os.waitpid(child_pid, 0)
+ self.assertEqual(proc.wait(), 0)
self.assertGreaterEqual(dt, self.sleep_time)
diff --git a/Lib/test/test_argparse.py b/Lib/test/test_argparse.py
index 27bfad5..893ec39 100644
--- a/Lib/test/test_argparse.py
+++ b/Lib/test/test_argparse.py
@@ -4512,6 +4512,21 @@
string = "Namespace(bar='spam', foo=42)"
self.assertStringEqual(ns, string)
+ def test_namespace_starkwargs_notidentifier(self):
+ ns = argparse.Namespace(**{'"': 'quote'})
+ string = """Namespace(**{'"': 'quote'})"""
+ self.assertStringEqual(ns, string)
+
+ def test_namespace_kwargs_and_starkwargs_notidentifier(self):
+ ns = argparse.Namespace(a=1, **{'"': 'quote'})
+ string = """Namespace(a=1, **{'"': 'quote'})"""
+ self.assertStringEqual(ns, string)
+
+ def test_namespace_starkwargs_identifier(self):
+ ns = argparse.Namespace(**{'valid': True})
+ string = "Namespace(valid=True)"
+ self.assertStringEqual(ns, string)
+
def test_parser(self):
parser = argparse.ArgumentParser(prog='PROG')
string = (
diff --git a/Lib/test/test_collections.py b/Lib/test/test_collections.py
index 4124f91..cd238bc 100644
--- a/Lib/test/test_collections.py
+++ b/Lib/test/test_collections.py
@@ -2002,6 +2002,14 @@
od = OrderedDict(**d)
self.assertGreater(sys.getsizeof(od), sys.getsizeof(d))
+ def test_views(self):
+ OrderedDict = self.module.OrderedDict
+ # See http://bugs.python.org/issue24286
+ s = 'the quick brown fox jumped over a lazy dog yesterday before dawn'.split()
+ od = OrderedDict.fromkeys(s)
+ self.assertEqual(od.keys(), dict(od).keys())
+ self.assertEqual(od.items(), dict(od).items())
+
def test_override_update(self):
OrderedDict = self.module.OrderedDict
# Verify that subclasses can override update() without breaking __init__()
diff --git a/Lib/test/test_dictviews.py b/Lib/test/test_dictviews.py
index 8d33801..fcb6814 100644
--- a/Lib/test/test_dictviews.py
+++ b/Lib/test/test_dictviews.py
@@ -1,3 +1,4 @@
+import collections
import unittest
class DictSetTest(unittest.TestCase):
@@ -197,6 +198,27 @@
d[42] = d.values()
self.assertRaises(RecursionError, repr, d)
+ def test_abc_registry(self):
+ d = dict(a=1)
+
+ self.assertIsInstance(d.keys(), collections.KeysView)
+ self.assertIsInstance(d.keys(), collections.MappingView)
+ self.assertIsInstance(d.keys(), collections.Set)
+ self.assertIsInstance(d.keys(), collections.Sized)
+ self.assertIsInstance(d.keys(), collections.Iterable)
+ self.assertIsInstance(d.keys(), collections.Container)
+
+ self.assertIsInstance(d.values(), collections.ValuesView)
+ self.assertIsInstance(d.values(), collections.MappingView)
+ self.assertIsInstance(d.values(), collections.Sized)
+
+ self.assertIsInstance(d.items(), collections.ItemsView)
+ self.assertIsInstance(d.items(), collections.MappingView)
+ self.assertIsInstance(d.items(), collections.Set)
+ self.assertIsInstance(d.items(), collections.Sized)
+ self.assertIsInstance(d.items(), collections.Iterable)
+ self.assertIsInstance(d.items(), collections.Container)
+
if __name__ == "__main__":
unittest.main()
diff --git a/Lib/test/test_file.py b/Lib/test/test_file.py
index 4e392b7..67c3d86 100644
--- a/Lib/test/test_file.py
+++ b/Lib/test/test_file.py
@@ -139,7 +139,7 @@
def testModeStrings(self):
# check invalid mode strings
- for mode in ("", "aU", "wU+"):
+ for mode in ("", "aU", "wU+", "U+", "+U", "rU+"):
try:
f = self.open(TESTFN, mode)
except ValueError:
diff --git a/Lib/test/test_grammar.py b/Lib/test/test_grammar.py
index ec3d783..8f8d71c 100644
--- a/Lib/test/test_grammar.py
+++ b/Lib/test/test_grammar.py
@@ -295,6 +295,10 @@
pos2key2dict(1,2,k2=100,tokwarg1=100,tokwarg2=200)
pos2key2dict(1,2,tokwarg1=100,tokwarg2=200, k2=100)
+ self.assertRaises(SyntaxError, eval, "def f(*): pass")
+ self.assertRaises(SyntaxError, eval, "def f(*,): pass")
+ self.assertRaises(SyntaxError, eval, "def f(*, **kwds): pass")
+
# keyword arguments after *arglist
def f(*args, **kwargs):
return args, kwargs
@@ -352,6 +356,23 @@
check_syntax_error(self, "f(*g(1=2))")
check_syntax_error(self, "f(**g(1=2))")
+ # Check trailing commas are permitted in funcdef argument list
+ def f(a,): pass
+ def f(*args,): pass
+ def f(**kwds,): pass
+ def f(a, *args,): pass
+ def f(a, **kwds,): pass
+ def f(*args, b,): pass
+ def f(*, b,): pass
+ def f(*args, **kwds,): pass
+ def f(a, *args, b,): pass
+ def f(a, *, b,): pass
+ def f(a, *args, **kwds,): pass
+ def f(*args, b, **kwds,): pass
+ def f(*, b, **kwds,): pass
+ def f(a, *args, b, **kwds,): pass
+ def f(a, *, b, **kwds,): pass
+
def test_lambdef(self):
### lambdef: 'lambda' [varargslist] ':' test
l1 = lambda : 0
@@ -370,6 +391,23 @@
self.assertEqual(l6(1,2), 1+2+20)
self.assertEqual(l6(1,2,k=10), 1+2+10)
+ # check that trailing commas are permitted
+ l10 = lambda a,: 0
+ l11 = lambda *args,: 0
+ l12 = lambda **kwds,: 0
+ l13 = lambda a, *args,: 0
+ l14 = lambda a, **kwds,: 0
+ l15 = lambda *args, b,: 0
+ l16 = lambda *, b,: 0
+ l17 = lambda *args, **kwds,: 0
+ l18 = lambda a, *args, b,: 0
+ l19 = lambda a, *, b,: 0
+ l20 = lambda a, *args, **kwds,: 0
+ l21 = lambda *args, b, **kwds,: 0
+ l22 = lambda *, b, **kwds,: 0
+ l23 = lambda a, *args, b, **kwds,: 0
+ l24 = lambda a, *, b, **kwds,: 0
+
### stmt: simple_stmt | compound_stmt
# Tested below
diff --git a/Lib/test/test_inspect.py b/Lib/test/test_inspect.py
index 955b2ad..db15b39 100644
--- a/Lib/test/test_inspect.py
+++ b/Lib/test/test_inspect.py
@@ -38,7 +38,7 @@
# ismodule, isclass, ismethod, isfunction, istraceback, isframe, iscode,
# isbuiltin, isroutine, isgenerator, isgeneratorfunction, getmembers,
# getdoc, getfile, getmodule, getsourcefile, getcomments, getsource,
-# getclasstree, getargspec, getargvalues, formatargspec, formatargvalues,
+# getclasstree, getargvalues, formatargspec, formatargvalues,
# currentframe, stack, trace, isdatadescriptor
# NOTE: There are some additional tests relating to interaction with
@@ -628,18 +628,6 @@
got = inspect.getmro(D)
self.assertEqual(expected, got)
- def assertArgSpecEquals(self, routine, args_e, varargs_e=None,
- varkw_e=None, defaults_e=None, formatted=None):
- with self.assertWarns(DeprecationWarning):
- args, varargs, varkw, defaults = inspect.getargspec(routine)
- self.assertEqual(args, args_e)
- self.assertEqual(varargs, varargs_e)
- self.assertEqual(varkw, varkw_e)
- self.assertEqual(defaults, defaults_e)
- if formatted is not None:
- self.assertEqual(inspect.formatargspec(args, varargs, varkw, defaults),
- formatted)
-
def assertFullArgSpecEquals(self, routine, args_e, varargs_e=None,
varkw_e=None, defaults_e=None,
kwonlyargs_e=[], kwonlydefaults_e=None,
@@ -658,23 +646,6 @@
kwonlyargs, kwonlydefaults, ann),
formatted)
- def test_getargspec(self):
- self.assertArgSpecEquals(mod.eggs, ['x', 'y'], formatted='(x, y)')
-
- self.assertArgSpecEquals(mod.spam,
- ['a', 'b', 'c', 'd', 'e', 'f'],
- 'g', 'h', (3, 4, 5),
- '(a, b, c, d=3, e=4, f=5, *g, **h)')
-
- self.assertRaises(ValueError, self.assertArgSpecEquals,
- mod2.keyworded, [])
-
- self.assertRaises(ValueError, self.assertArgSpecEquals,
- mod2.annotated, [])
- self.assertRaises(ValueError, self.assertArgSpecEquals,
- mod2.keyword_only_arg, [])
-
-
def test_getfullargspec(self):
self.assertFullArgSpecEquals(mod2.keyworded, [], varargs_e='arg1',
kwonlyargs_e=['arg2'],
@@ -688,20 +659,19 @@
kwonlyargs_e=['arg'],
formatted='(*, arg)')
- def test_argspec_api_ignores_wrapped(self):
+ def test_fullargspec_api_ignores_wrapped(self):
# Issue 20684: low level introspection API must ignore __wrapped__
@functools.wraps(mod.spam)
def ham(x, y):
pass
# Basic check
- self.assertArgSpecEquals(ham, ['x', 'y'], formatted='(x, y)')
self.assertFullArgSpecEquals(ham, ['x', 'y'], formatted='(x, y)')
self.assertFullArgSpecEquals(functools.partial(ham),
['x', 'y'], formatted='(x, y)')
# Other variants
def check_method(f):
- self.assertArgSpecEquals(f, ['self', 'x', 'y'],
- formatted='(self, x, y)')
+ self.assertFullArgSpecEquals(f, ['self', 'x', 'y'],
+ formatted='(self, x, y)')
class C:
@functools.wraps(mod.spam)
def ham(self, x, y):
@@ -779,11 +749,11 @@
with self.assertRaises(TypeError):
inspect.getfullargspec(builtin)
- def test_getargspec_method(self):
+ def test_getfullargspec_method(self):
class A(object):
def m(self):
pass
- self.assertArgSpecEquals(A.m, ['self'])
+ self.assertFullArgSpecEquals(A.m, ['self'])
def test_classify_newstyle(self):
class A(object):
diff --git a/Lib/test/test_itertools.py b/Lib/test/test_itertools.py
index fcd8869..81e1711 100644
--- a/Lib/test/test_itertools.py
+++ b/Lib/test/test_itertools.py
@@ -613,6 +613,56 @@
for proto in range(pickle.HIGHEST_PROTOCOL + 1):
self.pickletest(proto, cycle('abc'))
+ for proto in range(pickle.HIGHEST_PROTOCOL + 1):
+ # test with partial consumed input iterable
+ it = iter('abcde')
+ c = cycle(it)
+ _ = [next(c) for i in range(2)] # consume 2 of 5 inputs
+ p = pickle.dumps(c, proto)
+ d = pickle.loads(p) # rebuild the cycle object
+ self.assertEqual(take(20, d), list('cdeabcdeabcdeabcdeab'))
+
+ # test with completely consumed input iterable
+ it = iter('abcde')
+ c = cycle(it)
+ _ = [next(c) for i in range(7)] # consume 7 of 5 inputs
+ p = pickle.dumps(c, proto)
+ d = pickle.loads(p) # rebuild the cycle object
+ self.assertEqual(take(20, d), list('cdeabcdeabcdeabcdeab'))
+
+ def test_cycle_setstate(self):
+ # Verify both modes for restoring state
+
+ # Mode 0 is efficient. It uses an incompletely consumed input
+ # iterator to build a cycle object and then passes in state with
+ # a list of previously consumed values. There is no data
+ # overlap bewteen the two.
+ c = cycle('defg')
+ c.__setstate__((list('abc'), 0))
+ self.assertEqual(take(20, c), list('defgabcdefgabcdefgab'))
+
+ # Mode 1 is inefficient. It starts with a cycle object built
+ # from an iterator over the remaining elements in a partial
+ # cycle and then passes in state with all of the previously
+ # seen values (this overlaps values included in the iterator).
+ c = cycle('defg')
+ c.__setstate__((list('abcdefg'), 1))
+ self.assertEqual(take(20, c), list('defgabcdefgabcdefgab'))
+
+ # The first argument to setstate needs to be a tuple
+ with self.assertRaises(SystemError):
+ cycle('defg').__setstate__([list('abcdefg'), 0])
+
+ # The first argument in the setstate tuple must be a list
+ with self.assertRaises(TypeError):
+ c = cycle('defg')
+ c.__setstate__((dict.fromkeys('defg'), 0))
+ take(20, c)
+
+ # The first argument in the setstate tuple must be a list
+ with self.assertRaises(TypeError):
+ cycle('defg').__setstate__((list('abcdefg'), 'x'))
+
def test_groupby(self):
# Check whether it accepts arguments correctly
self.assertEqual([], list(groupby([])))
diff --git a/Lib/test/test_linecache.py b/Lib/test/test_linecache.py
index 21ef738..240db7f 100644
--- a/Lib/test/test_linecache.py
+++ b/Lib/test/test_linecache.py
@@ -3,6 +3,8 @@
import linecache
import unittest
import os.path
+import tempfile
+import tokenize
from test import support
@@ -10,8 +12,6 @@
NONEXISTENT_FILENAME = FILENAME + '.missing'
INVALID_NAME = '!@$)(!@#_1'
EMPTY = ''
-TESTS = 'inspect_fodder inspect_fodder2 mapping_tests'
-TESTS = TESTS.split()
TEST_PATH = os.path.dirname(__file__)
MODULES = "linecache abc".split()
MODULE_PATH = os.path.dirname(FILENAME)
@@ -37,6 +37,65 @@
return 3''' # No ending newline
+class TempFile:
+
+ def setUp(self):
+ super().setUp()
+ with tempfile.NamedTemporaryFile(delete=False) as fp:
+ self.file_name = fp.name
+ fp.write(self.file_byte_string)
+ self.addCleanup(support.unlink, self.file_name)
+
+
+class GetLineTestsGoodData(TempFile):
+ # file_list = ['list\n', 'of\n', 'good\n', 'strings\n']
+
+ def setUp(self):
+ self.file_byte_string = ''.join(self.file_list).encode('utf-8')
+ super().setUp()
+
+ def test_getline(self):
+ with tokenize.open(self.file_name) as fp:
+ for index, line in enumerate(fp):
+ if not line.endswith('\n'):
+ line += '\n'
+
+ cached_line = linecache.getline(self.file_name, index + 1)
+ self.assertEqual(line, cached_line)
+
+ def test_getlines(self):
+ lines = linecache.getlines(self.file_name)
+ self.assertEqual(lines, self.file_list)
+
+
+class GetLineTestsBadData(TempFile):
+ # file_byte_string = b'Bad data goes here'
+
+ def test_getline(self):
+ self.assertRaises((SyntaxError, UnicodeDecodeError),
+ linecache.getline, self.file_name, 1)
+
+ def test_getlines(self):
+ self.assertRaises((SyntaxError, UnicodeDecodeError),
+ linecache.getlines, self.file_name)
+
+
+class EmptyFile(GetLineTestsGoodData, unittest.TestCase):
+ file_list = []
+
+
+class SingleEmptyLine(GetLineTestsGoodData, unittest.TestCase):
+ file_list = ['\n']
+
+
+class GoodUnicode(GetLineTestsGoodData, unittest.TestCase):
+ file_list = ['á\n', 'b\n', 'abcdef\n', 'ááááá\n']
+
+
+class BadUnicode(GetLineTestsBadData, unittest.TestCase):
+ file_byte_string = b'\x80abc'
+
+
class LineCacheTests(unittest.TestCase):
def test_getline(self):
@@ -53,13 +112,6 @@
self.assertEqual(getline(EMPTY, 1), EMPTY)
self.assertEqual(getline(INVALID_NAME, 1), EMPTY)
- # Check whether lines correspond to those from file iteration
- for entry in TESTS:
- filename = os.path.join(TEST_PATH, entry) + '.py'
- with open(filename) as file:
- for index, line in enumerate(file):
- self.assertEqual(line, getline(filename, index + 1))
-
# Check module loading
for entry in MODULES:
filename = os.path.join(MODULE_PATH, entry) + '.py'
@@ -80,12 +132,13 @@
def test_clearcache(self):
cached = []
- for entry in TESTS:
- filename = os.path.join(TEST_PATH, entry) + '.py'
+ for entry in MODULES:
+ filename = os.path.join(MODULE_PATH, entry) + '.py'
cached.append(filename)
linecache.getline(filename, 1)
# Are all files cached?
+ self.assertNotEqual(cached, [])
cached_empty = [fn for fn in cached if fn not in linecache.cache]
self.assertEqual(cached_empty, [])
diff --git a/Lib/test/test_operator.py b/Lib/test/test_operator.py
index da9c8ef..27501c2 100644
--- a/Lib/test/test_operator.py
+++ b/Lib/test/test_operator.py
@@ -120,63 +120,63 @@
operator = self.module
self.assertRaises(TypeError, operator.add)
self.assertRaises(TypeError, operator.add, None, None)
- self.assertTrue(operator.add(3, 4) == 7)
+ self.assertEqual(operator.add(3, 4), 7)
def test_bitwise_and(self):
operator = self.module
self.assertRaises(TypeError, operator.and_)
self.assertRaises(TypeError, operator.and_, None, None)
- self.assertTrue(operator.and_(0xf, 0xa) == 0xa)
+ self.assertEqual(operator.and_(0xf, 0xa), 0xa)
def test_concat(self):
operator = self.module
self.assertRaises(TypeError, operator.concat)
self.assertRaises(TypeError, operator.concat, None, None)
- self.assertTrue(operator.concat('py', 'thon') == 'python')
- self.assertTrue(operator.concat([1, 2], [3, 4]) == [1, 2, 3, 4])
- self.assertTrue(operator.concat(Seq1([5, 6]), Seq1([7])) == [5, 6, 7])
- self.assertTrue(operator.concat(Seq2([5, 6]), Seq2([7])) == [5, 6, 7])
+ self.assertEqual(operator.concat('py', 'thon'), 'python')
+ self.assertEqual(operator.concat([1, 2], [3, 4]), [1, 2, 3, 4])
+ self.assertEqual(operator.concat(Seq1([5, 6]), Seq1([7])), [5, 6, 7])
+ self.assertEqual(operator.concat(Seq2([5, 6]), Seq2([7])), [5, 6, 7])
self.assertRaises(TypeError, operator.concat, 13, 29)
def test_countOf(self):
operator = self.module
self.assertRaises(TypeError, operator.countOf)
self.assertRaises(TypeError, operator.countOf, None, None)
- self.assertTrue(operator.countOf([1, 2, 1, 3, 1, 4], 3) == 1)
- self.assertTrue(operator.countOf([1, 2, 1, 3, 1, 4], 5) == 0)
+ self.assertEqual(operator.countOf([1, 2, 1, 3, 1, 4], 3), 1)
+ self.assertEqual(operator.countOf([1, 2, 1, 3, 1, 4], 5), 0)
def test_delitem(self):
operator = self.module
a = [4, 3, 2, 1]
self.assertRaises(TypeError, operator.delitem, a)
self.assertRaises(TypeError, operator.delitem, a, None)
- self.assertTrue(operator.delitem(a, 1) is None)
- self.assertTrue(a == [4, 2, 1])
+ self.assertIsNone(operator.delitem(a, 1))
+ self.assertEqual(a, [4, 2, 1])
def test_floordiv(self):
operator = self.module
self.assertRaises(TypeError, operator.floordiv, 5)
self.assertRaises(TypeError, operator.floordiv, None, None)
- self.assertTrue(operator.floordiv(5, 2) == 2)
+ self.assertEqual(operator.floordiv(5, 2), 2)
def test_truediv(self):
operator = self.module
self.assertRaises(TypeError, operator.truediv, 5)
self.assertRaises(TypeError, operator.truediv, None, None)
- self.assertTrue(operator.truediv(5, 2) == 2.5)
+ self.assertEqual(operator.truediv(5, 2), 2.5)
def test_getitem(self):
operator = self.module
a = range(10)
self.assertRaises(TypeError, operator.getitem)
self.assertRaises(TypeError, operator.getitem, a, None)
- self.assertTrue(operator.getitem(a, 2) == 2)
+ self.assertEqual(operator.getitem(a, 2), 2)
def test_indexOf(self):
operator = self.module
self.assertRaises(TypeError, operator.indexOf)
self.assertRaises(TypeError, operator.indexOf, None, None)
- self.assertTrue(operator.indexOf([4, 3, 2, 1], 3) == 1)
+ self.assertEqual(operator.indexOf([4, 3, 2, 1], 3), 1)
self.assertRaises(ValueError, operator.indexOf, [4, 3, 2, 1], 0)
def test_invert(self):
@@ -189,21 +189,21 @@
operator = self.module
self.assertRaises(TypeError, operator.lshift)
self.assertRaises(TypeError, operator.lshift, None, 42)
- self.assertTrue(operator.lshift(5, 1) == 10)
- self.assertTrue(operator.lshift(5, 0) == 5)
+ self.assertEqual(operator.lshift(5, 1), 10)
+ self.assertEqual(operator.lshift(5, 0), 5)
self.assertRaises(ValueError, operator.lshift, 2, -1)
def test_mod(self):
operator = self.module
self.assertRaises(TypeError, operator.mod)
self.assertRaises(TypeError, operator.mod, None, 42)
- self.assertTrue(operator.mod(5, 2) == 1)
+ self.assertEqual(operator.mod(5, 2), 1)
def test_mul(self):
operator = self.module
self.assertRaises(TypeError, operator.mul)
self.assertRaises(TypeError, operator.mul, None, None)
- self.assertTrue(operator.mul(5, 2) == 10)
+ self.assertEqual(operator.mul(5, 2), 10)
def test_matmul(self):
operator = self.module
@@ -227,7 +227,7 @@
operator = self.module
self.assertRaises(TypeError, operator.or_)
self.assertRaises(TypeError, operator.or_, None, None)
- self.assertTrue(operator.or_(0xa, 0x5) == 0xf)
+ self.assertEqual(operator.or_(0xa, 0x5), 0xf)
def test_pos(self):
operator = self.module
@@ -250,8 +250,8 @@
operator = self.module
self.assertRaises(TypeError, operator.rshift)
self.assertRaises(TypeError, operator.rshift, None, 42)
- self.assertTrue(operator.rshift(5, 1) == 2)
- self.assertTrue(operator.rshift(5, 0) == 5)
+ self.assertEqual(operator.rshift(5, 1), 2)
+ self.assertEqual(operator.rshift(5, 0), 5)
self.assertRaises(ValueError, operator.rshift, 2, -1)
def test_contains(self):
@@ -266,15 +266,15 @@
a = list(range(3))
self.assertRaises(TypeError, operator.setitem, a)
self.assertRaises(TypeError, operator.setitem, a, None, None)
- self.assertTrue(operator.setitem(a, 0, 2) is None)
- self.assertTrue(a == [2, 1, 2])
+ self.assertIsNone(operator.setitem(a, 0, 2))
+ self.assertEqual(a, [2, 1, 2])
self.assertRaises(IndexError, operator.setitem, a, 4, 2)
def test_sub(self):
operator = self.module
self.assertRaises(TypeError, operator.sub)
self.assertRaises(TypeError, operator.sub, None, None)
- self.assertTrue(operator.sub(5, 2) == 3)
+ self.assertEqual(operator.sub(5, 2), 3)
def test_truth(self):
operator = self.module
@@ -292,7 +292,7 @@
operator = self.module
self.assertRaises(TypeError, operator.xor)
self.assertRaises(TypeError, operator.xor, None, None)
- self.assertTrue(operator.xor(0xb, 0xc) == 0x7)
+ self.assertEqual(operator.xor(0xb, 0xc), 0x7)
def test_is(self):
operator = self.module
@@ -596,5 +596,38 @@
module2 = c_operator
+class SubscriptTestCase:
+ def test_subscript(self):
+ subscript = self.module.subscript
+ self.assertIsNone(subscript[None])
+ self.assertEqual(subscript[0], 0)
+ self.assertEqual(subscript[0:1:2], slice(0, 1, 2))
+ self.assertEqual(
+ subscript[0, ..., :2, ...],
+ (0, Ellipsis, slice(2), Ellipsis),
+ )
+
+ def test_pickle(self):
+ from operator import subscript
+ for proto in range(pickle.HIGHEST_PROTOCOL + 1):
+ with self.subTest(proto=proto):
+ self.assertIs(
+ pickle.loads(pickle.dumps(subscript, proto)),
+ subscript,
+ )
+
+ def test_singleton(self):
+ with self.assertRaises(TypeError):
+ type(self.module.subscript)()
+
+ def test_immutable(self):
+ with self.assertRaises(AttributeError):
+ self.module.subscript.attr = None
+
+
+class PySubscriptTestCase(SubscriptTestCase, PyOperatorTestCase):
+ pass
+
+
if __name__ == "__main__":
unittest.main()
diff --git a/Lib/test/test_os.py b/Lib/test/test_os.py
index 0b77835..c424b57 100644
--- a/Lib/test/test_os.py
+++ b/Lib/test/test_os.py
@@ -226,15 +226,10 @@
# Test attributes on return values from os.*stat* family.
class StatAttributeTests(unittest.TestCase):
def setUp(self):
- os.mkdir(support.TESTFN)
- self.fname = os.path.join(support.TESTFN, "f1")
- f = open(self.fname, 'wb')
- f.write(b"ABC")
- f.close()
-
- def tearDown(self):
- os.unlink(self.fname)
- os.rmdir(support.TESTFN)
+ self.fname = support.TESTFN
+ self.addCleanup(support.unlink, self.fname)
+ with open(self.fname, 'wb') as fp:
+ fp.write(b"ABC")
@unittest.skipUnless(hasattr(os, 'stat'), 'test needs os.stat()')
def check_stat_attributes(self, fname):
@@ -426,7 +421,11 @@
0)
# test directory st_file_attributes (FILE_ATTRIBUTE_DIRECTORY set)
- result = os.stat(support.TESTFN)
+ dirname = support.TESTFN + "dir"
+ os.mkdir(dirname)
+ self.addCleanup(os.rmdir, dirname)
+
+ result = os.stat(dirname)
self.check_file_attributes(result)
self.assertEqual(
result.st_file_attributes & stat.FILE_ATTRIBUTE_DIRECTORY,
diff --git a/Lib/test/test_pydoc.py b/Lib/test/test_pydoc.py
index ec5c31b..0533a03 100644
--- a/Lib/test/test_pydoc.py
+++ b/Lib/test/test_pydoc.py
@@ -811,6 +811,22 @@
self.assertEqual(self._get_summary_line(t.wrap),
"wrap(text) method of textwrap.TextWrapper instance")
+ def test_field_order_for_named_tuples(self):
+ Person = namedtuple('Person', ['nickname', 'firstname', 'agegroup'])
+ s = pydoc.render_doc(Person)
+ self.assertLess(s.index('nickname'), s.index('firstname'))
+ self.assertLess(s.index('firstname'), s.index('agegroup'))
+
+ class NonIterableFields:
+ _fields = None
+
+ class NonHashableFields:
+ _fields = [[]]
+
+ # Make sure these doesn't fail
+ pydoc.render_doc(NonIterableFields)
+ pydoc.render_doc(NonHashableFields)
+
@requires_docstrings
def test_bound_builtin_method(self):
s = StringIO()
diff --git a/Lib/test/test_set.py b/Lib/test/test_set.py
index 54de508..ade39fb 100644
--- a/Lib/test/test_set.py
+++ b/Lib/test/test_set.py
@@ -10,6 +10,8 @@
import warnings
import collections
import collections.abc
+import itertools
+import string
class PassThru(Exception):
pass
@@ -711,6 +713,28 @@
addhashvalue(hash(frozenset([e for e, m in elemmasks if m&i])))
self.assertEqual(len(hashvalues), 2**n)
+ def letter_range(n):
+ return string.ascii_letters[:n]
+
+ def zf_range(n):
+ # https://en.wikipedia.org/wiki/Set-theoretic_definition_of_natural_numbers
+ nums = [frozenset()]
+ for i in range(n-1):
+ num = frozenset(nums)
+ nums.append(num)
+ return nums[:n]
+
+ def powerset(s):
+ for i in range(len(s)+1):
+ yield from map(frozenset, itertools.combinations(s, i))
+
+ for n in range(18):
+ t = 2 ** n
+ mask = t - 1
+ for nums in (range, letter_range, zf_range):
+ u = len({h & mask for h in map(hash, powerset(nums(n)))})
+ self.assertGreater(4*u, t)
+
class FrozenSetSubclass(frozenset):
pass
diff --git a/Lib/test/test_symbol.py b/Lib/test/test_symbol.py
new file mode 100644
index 0000000..2dcb9de
--- /dev/null
+++ b/Lib/test/test_symbol.py
@@ -0,0 +1,55 @@
+import unittest
+from test import support
+import filecmp
+import os
+import sys
+import subprocess
+
+
+SYMBOL_FILE = support.findfile('symbol.py')
+GRAMMAR_FILE = os.path.join(os.path.dirname(__file__),
+ '..', '..', 'Include', 'graminit.h')
+TEST_PY_FILE = 'symbol_test.py'
+
+
+class TestSymbolGeneration(unittest.TestCase):
+
+ def _copy_file_without_generated_symbols(self, source_file, dest_file):
+ with open(source_file) as fp:
+ lines = fp.readlines()
+ with open(dest_file, 'w') as fp:
+ fp.writelines(lines[:lines.index("#--start constants--\n") + 1])
+ fp.writelines(lines[lines.index("#--end constants--\n"):])
+
+ def _generate_symbols(self, grammar_file, target_symbol_py_file):
+ proc = subprocess.Popen([sys.executable,
+ SYMBOL_FILE,
+ grammar_file,
+ target_symbol_py_file], stderr=subprocess.PIPE)
+ stderr = proc.communicate()[1]
+ return proc.returncode, stderr
+
+ def compare_files(self, file1, file2):
+ with open(file1) as fp:
+ lines1 = fp.readlines()
+ with open(file2) as fp:
+ lines2 = fp.readlines()
+ self.assertEqual(lines1, lines2)
+
+ @unittest.skipIf(not os.path.exists(GRAMMAR_FILE),
+ 'test only works from source build directory')
+ def test_real_grammar_and_symbol_file(self):
+ output = support.TESTFN
+ self.addCleanup(support.unlink, output)
+
+ self._copy_file_without_generated_symbols(SYMBOL_FILE, output)
+
+ exitcode, stderr = self._generate_symbols(GRAMMAR_FILE, output)
+ self.assertEqual(b'', stderr)
+ self.assertEqual(0, exitcode)
+
+ self.compare_files(SYMBOL_FILE, output)
+
+
+if __name__ == "__main__":
+ unittest.main()
diff --git a/Lib/test/test_time.py b/Lib/test/test_time.py
index 6bcd212..f883c45 100644
--- a/Lib/test/test_time.py
+++ b/Lib/test/test_time.py
@@ -1,6 +1,8 @@
from test import support
+import decimal
import enum
import locale
+import math
import platform
import sys
import sysconfig
@@ -21,17 +23,27 @@
TIME_MAXYEAR = (1 << 8 * SIZEOF_INT - 1) - 1
TIME_MINYEAR = -TIME_MAXYEAR - 1
+SEC_TO_US = 10 ** 6
US_TO_NS = 10 ** 3
MS_TO_NS = 10 ** 6
SEC_TO_NS = 10 ** 9
+NS_TO_SEC = 10 ** 9
class _PyTime(enum.IntEnum):
# Round towards minus infinity (-inf)
ROUND_FLOOR = 0
# Round towards infinity (+inf)
ROUND_CEILING = 1
+ # Round to nearest with ties going to nearest even integer
+ ROUND_HALF_EVEN = 2
-ALL_ROUNDING_METHODS = (_PyTime.ROUND_FLOOR, _PyTime.ROUND_CEILING)
+# Rounding modes supported by PyTime
+ROUNDING_MODES = (
+ # (PyTime rounding method, decimal rounding method)
+ (_PyTime.ROUND_FLOOR, decimal.ROUND_FLOOR),
+ (_PyTime.ROUND_CEILING, decimal.ROUND_CEILING),
+ (_PyTime.ROUND_HALF_EVEN, decimal.ROUND_HALF_EVEN),
+)
class TimeTestCase(unittest.TestCase):
@@ -607,79 +619,6 @@
class TestPytime(unittest.TestCase):
- def setUp(self):
- self.invalid_values = (
- -(2 ** 100), 2 ** 100,
- -(2.0 ** 100.0), 2.0 ** 100.0,
- )
-
- @support.cpython_only
- def test_time_t(self):
- from _testcapi import pytime_object_to_time_t
- for obj, time_t, rnd in (
- # Round towards minus infinity (-inf)
- (0, 0, _PyTime.ROUND_FLOOR),
- (-1, -1, _PyTime.ROUND_FLOOR),
- (-1.0, -1, _PyTime.ROUND_FLOOR),
- (-1.9, -2, _PyTime.ROUND_FLOOR),
- (1.0, 1, _PyTime.ROUND_FLOOR),
- (1.9, 1, _PyTime.ROUND_FLOOR),
- # Round towards infinity (+inf)
- (0, 0, _PyTime.ROUND_CEILING),
- (-1, -1, _PyTime.ROUND_CEILING),
- (-1.0, -1, _PyTime.ROUND_CEILING),
- (-1.9, -1, _PyTime.ROUND_CEILING),
- (1.0, 1, _PyTime.ROUND_CEILING),
- (1.9, 2, _PyTime.ROUND_CEILING),
- ):
- self.assertEqual(pytime_object_to_time_t(obj, rnd), time_t)
-
- rnd = _PyTime.ROUND_FLOOR
- for invalid in self.invalid_values:
- self.assertRaises(OverflowError,
- pytime_object_to_time_t, invalid, rnd)
-
- @support.cpython_only
- def test_timespec(self):
- from _testcapi import pytime_object_to_timespec
- for obj, timespec, rnd in (
- # Round towards minus infinity (-inf)
- (0, (0, 0), _PyTime.ROUND_FLOOR),
- (-1, (-1, 0), _PyTime.ROUND_FLOOR),
- (-1.0, (-1, 0), _PyTime.ROUND_FLOOR),
- (1e-9, (0, 1), _PyTime.ROUND_FLOOR),
- (1e-10, (0, 0), _PyTime.ROUND_FLOOR),
- (-1e-9, (-1, 999999999), _PyTime.ROUND_FLOOR),
- (-1e-10, (-1, 999999999), _PyTime.ROUND_FLOOR),
- (-1.2, (-2, 800000000), _PyTime.ROUND_FLOOR),
- (0.9999999999, (0, 999999999), _PyTime.ROUND_FLOOR),
- (1.1234567890, (1, 123456789), _PyTime.ROUND_FLOOR),
- (1.1234567899, (1, 123456789), _PyTime.ROUND_FLOOR),
- (-1.1234567890, (-2, 876543211), _PyTime.ROUND_FLOOR),
- (-1.1234567891, (-2, 876543210), _PyTime.ROUND_FLOOR),
- # Round towards infinity (+inf)
- (0, (0, 0), _PyTime.ROUND_CEILING),
- (-1, (-1, 0), _PyTime.ROUND_CEILING),
- (-1.0, (-1, 0), _PyTime.ROUND_CEILING),
- (1e-9, (0, 1), _PyTime.ROUND_CEILING),
- (1e-10, (0, 1), _PyTime.ROUND_CEILING),
- (-1e-9, (-1, 999999999), _PyTime.ROUND_CEILING),
- (-1e-10, (0, 0), _PyTime.ROUND_CEILING),
- (-1.2, (-2, 800000000), _PyTime.ROUND_CEILING),
- (0.9999999999, (1, 0), _PyTime.ROUND_CEILING),
- (1.1234567890, (1, 123456790), _PyTime.ROUND_CEILING),
- (1.1234567899, (1, 123456790), _PyTime.ROUND_CEILING),
- (-1.1234567890, (-2, 876543211), _PyTime.ROUND_CEILING),
- (-1.1234567891, (-2, 876543211), _PyTime.ROUND_CEILING),
- ):
- with self.subTest(obj=obj, round=rnd, timespec=timespec):
- self.assertEqual(pytime_object_to_timespec(obj, rnd), timespec)
-
- rnd = _PyTime.ROUND_FLOOR
- for invalid in self.invalid_values:
- self.assertRaises(OverflowError,
- pytime_object_to_timespec, invalid, rnd)
-
@unittest.skipUnless(time._STRUCT_TM_ITEMS == 11, "needs tm_zone support")
def test_localtime_timezone(self):
@@ -734,266 +673,291 @@
self.assertIs(lt.tm_zone, None)
-@unittest.skipUnless(_testcapi is not None,
- 'need the _testcapi module')
-class TestPyTime_t(unittest.TestCase):
+@unittest.skipIf(_testcapi is None, 'need the _testcapi module')
+class CPyTimeTestCase:
+ """
+ Base class to test the C _PyTime_t API.
+ """
+ OVERFLOW_SECONDS = None
+
+ def setUp(self):
+ from _testcapi import SIZEOF_TIME_T
+ bits = SIZEOF_TIME_T * 8 - 1
+ self.time_t_min = -2 ** bits
+ self.time_t_max = 2 ** bits - 1
+
+ def time_t_filter(self, seconds):
+ return (self.time_t_min <= seconds <= self.time_t_max)
+
+ def _rounding_values(self, use_float):
+ "Build timestamps used to test rounding."
+
+ units = [1, US_TO_NS, MS_TO_NS, SEC_TO_NS]
+ if use_float:
+ # picoseconds are only tested to pytime_converter accepting floats
+ units.append(1e-3)
+
+ values = (
+ # small values
+ 1, 2, 5, 7, 123, 456, 1234,
+ # 10^k - 1
+ 9,
+ 99,
+ 999,
+ 9999,
+ 99999,
+ 999999,
+ # test half even rounding near 0.5, 1.5, 2.5, 3.5, 4.5
+ 499, 500, 501,
+ 1499, 1500, 1501,
+ 2500,
+ 3500,
+ 4500,
+ )
+
+ ns_timestamps = [0]
+ for unit in units:
+ for value in values:
+ ns = value * unit
+ ns_timestamps.extend((-ns, ns))
+ for pow2 in (0, 5, 10, 15, 22, 23, 24, 30, 33):
+ ns = (2 ** pow2) * SEC_TO_NS
+ ns_timestamps.extend((
+ -ns-1, -ns, -ns+1,
+ ns-1, ns, ns+1
+ ))
+ for seconds in (_testcapi.INT_MIN, _testcapi.INT_MAX):
+ ns_timestamps.append(seconds * SEC_TO_NS)
+ if use_float:
+ # numbers with an extract representation in IEEE 754 (base 2)
+ for pow2 in (3, 7, 10, 15):
+ ns = 2.0 ** (-pow2)
+ ns_timestamps.extend((-ns, ns))
+
+ # seconds close to _PyTime_t type limit
+ ns = (2 ** 63 // SEC_TO_NS) * SEC_TO_NS
+ ns_timestamps.extend((-ns, ns))
+
+ return ns_timestamps
+
+ def _check_rounding(self, pytime_converter, expected_func,
+ use_float, unit_to_sec, value_filter=None):
+
+ def convert_values(ns_timestamps):
+ if use_float:
+ unit_to_ns = SEC_TO_NS / float(unit_to_sec)
+ values = [ns / unit_to_ns for ns in ns_timestamps]
+ else:
+ unit_to_ns = SEC_TO_NS // unit_to_sec
+ values = [ns // unit_to_ns for ns in ns_timestamps]
+
+ if value_filter:
+ values = filter(value_filter, values)
+
+ # remove duplicates and sort
+ return sorted(set(values))
+
+ # test rounding
+ ns_timestamps = self._rounding_values(use_float)
+ valid_values = convert_values(ns_timestamps)
+ for time_rnd, decimal_rnd in ROUNDING_MODES :
+ context = decimal.getcontext()
+ context.rounding = decimal_rnd
+
+ for value in valid_values:
+ debug_info = {'value': value, 'rounding': decimal_rnd}
+ try:
+ result = pytime_converter(value, time_rnd)
+ expected = expected_func(value)
+ except Exception as exc:
+ self.fail("Error on timestamp conversion: %s" % debug_info)
+ self.assertEqual(result,
+ expected,
+ debug_info)
+
+ # test overflow
+ ns = self.OVERFLOW_SECONDS * SEC_TO_NS
+ ns_timestamps = (-ns, ns)
+ overflow_values = convert_values(ns_timestamps)
+ for time_rnd, _ in ROUNDING_MODES :
+ for value in overflow_values:
+ debug_info = {'value': value, 'rounding': time_rnd}
+ with self.assertRaises(OverflowError, msg=debug_info):
+ pytime_converter(value, time_rnd)
+
+ def check_int_rounding(self, pytime_converter, expected_func,
+ unit_to_sec=1, value_filter=None):
+ self._check_rounding(pytime_converter, expected_func,
+ False, unit_to_sec, value_filter)
+
+ def check_float_rounding(self, pytime_converter, expected_func,
+ unit_to_sec=1, value_filter=None):
+ self._check_rounding(pytime_converter, expected_func,
+ True, unit_to_sec, value_filter)
+
+ def decimal_round(self, x):
+ d = decimal.Decimal(x)
+ d = d.quantize(1)
+ return int(d)
+
+
+class TestCPyTime(CPyTimeTestCase, unittest.TestCase):
+ """
+ Test the C _PyTime_t API.
+ """
+ # _PyTime_t is a 64-bit signed integer
+ OVERFLOW_SECONDS = math.ceil((2**63 + 1) / SEC_TO_NS)
+
def test_FromSeconds(self):
from _testcapi import PyTime_FromSeconds
- for seconds in (0, 3, -456, _testcapi.INT_MAX, _testcapi.INT_MIN):
- with self.subTest(seconds=seconds):
- self.assertEqual(PyTime_FromSeconds(seconds),
- seconds * SEC_TO_NS)
+
+ # PyTime_FromSeconds() expects a C int, reject values out of range
+ def c_int_filter(secs):
+ return (_testcapi.INT_MIN <= secs <= _testcapi.INT_MAX)
+
+ self.check_int_rounding(lambda secs, rnd: PyTime_FromSeconds(secs),
+ lambda secs: secs * SEC_TO_NS,
+ value_filter=c_int_filter)
def test_FromSecondsObject(self):
from _testcapi import PyTime_FromSecondsObject
- # Conversion giving the same result for all rounding methods
- for rnd in ALL_ROUNDING_METHODS:
- for obj, ts in (
- # integers
- (0, 0),
- (1, SEC_TO_NS),
- (-3, -3 * SEC_TO_NS),
+ self.check_int_rounding(
+ PyTime_FromSecondsObject,
+ lambda secs: secs * SEC_TO_NS)
- # float: subseconds
- (0.0, 0),
- (1e-9, 1),
- (1e-6, 10 ** 3),
- (1e-3, 10 ** 6),
-
- # float: seconds
- (2.0, 2 * SEC_TO_NS),
- (123.0, 123 * SEC_TO_NS),
- (-7.0, -7 * SEC_TO_NS),
-
- # nanosecond are kept for value <= 2^23 seconds
- (2**22 - 1e-9, 4194303999999999),
- (2**22, 4194304000000000),
- (2**22 + 1e-9, 4194304000000001),
- (2**23 - 1e-9, 8388607999999999),
- (2**23, 8388608000000000),
-
- # start loosing precision for value > 2^23 seconds
- (2**23 + 1e-9, 8388608000000002),
-
- # nanoseconds are lost for value > 2^23 seconds
- (2**24 - 1e-9, 16777215999999998),
- (2**24, 16777216000000000),
- (2**24 + 1e-9, 16777216000000000),
- (2**25 - 1e-9, 33554432000000000),
- (2**25 , 33554432000000000),
- (2**25 + 1e-9, 33554432000000000),
-
- # close to 2^63 nanoseconds (_PyTime_t limit)
- (9223372036, 9223372036 * SEC_TO_NS),
- (9223372036.0, 9223372036 * SEC_TO_NS),
- (-9223372036, -9223372036 * SEC_TO_NS),
- (-9223372036.0, -9223372036 * SEC_TO_NS),
- ):
- with self.subTest(obj=obj, round=rnd, timestamp=ts):
- self.assertEqual(PyTime_FromSecondsObject(obj, rnd), ts)
-
- with self.subTest(round=rnd):
- with self.assertRaises(OverflowError):
- PyTime_FromSecondsObject(9223372037, rnd)
- PyTime_FromSecondsObject(9223372037.0, rnd)
- PyTime_FromSecondsObject(-9223372037, rnd)
- PyTime_FromSecondsObject(-9223372037.0, rnd)
-
- # Conversion giving different results depending on the rounding method
- FLOOR = _PyTime.ROUND_FLOOR
- CEILING = _PyTime.ROUND_CEILING
- for obj, ts, rnd in (
- # close to zero
- ( 1e-10, 0, FLOOR),
- ( 1e-10, 1, CEILING),
- (-1e-10, -1, FLOOR),
- (-1e-10, 0, CEILING),
-
- # test rounding of the last nanosecond
- ( 1.1234567899, 1123456789, FLOOR),
- ( 1.1234567899, 1123456790, CEILING),
- (-1.1234567899, -1123456790, FLOOR),
- (-1.1234567899, -1123456789, CEILING),
-
- # close to 1 second
- ( 0.9999999999, 999999999, FLOOR),
- ( 0.9999999999, 1000000000, CEILING),
- (-0.9999999999, -1000000000, FLOOR),
- (-0.9999999999, -999999999, CEILING),
- ):
- with self.subTest(obj=obj, round=rnd, timestamp=ts):
- self.assertEqual(PyTime_FromSecondsObject(obj, rnd), ts)
+ self.check_float_rounding(
+ PyTime_FromSecondsObject,
+ lambda ns: self.decimal_round(ns * SEC_TO_NS))
def test_AsSecondsDouble(self):
from _testcapi import PyTime_AsSecondsDouble
- for nanoseconds, seconds in (
- # near 1 nanosecond
- ( 0, 0.0),
- ( 1, 1e-9),
- (-1, -1e-9),
+ def float_converter(ns):
+ if abs(ns) % SEC_TO_NS == 0:
+ return float(ns // SEC_TO_NS)
+ else:
+ return float(ns) / SEC_TO_NS
- # near 1 second
- (SEC_TO_NS + 1, 1.0 + 1e-9),
- (SEC_TO_NS, 1.0),
- (SEC_TO_NS - 1, 1.0 - 1e-9),
+ self.check_int_rounding(lambda ns, rnd: PyTime_AsSecondsDouble(ns),
+ float_converter,
+ NS_TO_SEC)
- # a few seconds
- (123 * SEC_TO_NS, 123.0),
- (-567 * SEC_TO_NS, -567.0),
+ def create_decimal_converter(self, denominator):
+ denom = decimal.Decimal(denominator)
- # nanosecond are kept for value <= 2^23 seconds
- (4194303999999999, 2**22 - 1e-9),
- (4194304000000000, 2**22),
- (4194304000000001, 2**22 + 1e-9),
+ def converter(value):
+ d = decimal.Decimal(value) / denom
+ return self.decimal_round(d)
- # start loosing precision for value > 2^23 seconds
- (8388608000000002, 2**23 + 1e-9),
+ return converter
- # nanoseconds are lost for value > 2^23 seconds
- (16777215999999998, 2**24 - 1e-9),
- (16777215999999999, 2**24 - 1e-9),
- (16777216000000000, 2**24 ),
- (16777216000000001, 2**24 ),
- (16777216000000002, 2**24 + 2e-9),
-
- (33554432000000000, 2**25 ),
- (33554432000000002, 2**25 ),
- (33554432000000004, 2**25 + 4e-9),
-
- # close to 2^63 nanoseconds (_PyTime_t limit)
- (9223372036 * SEC_TO_NS, 9223372036.0),
- (-9223372036 * SEC_TO_NS, -9223372036.0),
- ):
- with self.subTest(nanoseconds=nanoseconds, seconds=seconds):
- self.assertEqual(PyTime_AsSecondsDouble(nanoseconds),
- seconds)
-
- def test_timeval(self):
+ def test_AsTimeval(self):
from _testcapi import PyTime_AsTimeval
- for rnd in ALL_ROUNDING_METHODS:
- for ns, tv in (
- # microseconds
- (0, (0, 0)),
- (1000, (0, 1)),
- (-1000, (-1, 999999)),
- # seconds
- (2 * SEC_TO_NS, (2, 0)),
- (-3 * SEC_TO_NS, (-3, 0)),
- ):
- with self.subTest(nanoseconds=ns, timeval=tv, round=rnd):
- self.assertEqual(PyTime_AsTimeval(ns, rnd), tv)
+ us_converter = self.create_decimal_converter(US_TO_NS)
- FLOOR = _PyTime.ROUND_FLOOR
- CEILING = _PyTime.ROUND_CEILING
- for ns, tv, rnd in (
- # nanoseconds
- (1, (0, 0), FLOOR),
- (1, (0, 1), CEILING),
- (-1, (-1, 999999), FLOOR),
- (-1, (0, 0), CEILING),
+ def timeval_converter(ns):
+ us = us_converter(ns)
+ return divmod(us, SEC_TO_US)
- # seconds + nanoseconds
- (1234567001, (1, 234567), FLOOR),
- (1234567001, (1, 234568), CEILING),
- (-1234567001, (-2, 765432), FLOOR),
- (-1234567001, (-2, 765433), CEILING),
- ):
- with self.subTest(nanoseconds=ns, timeval=tv, round=rnd):
- self.assertEqual(PyTime_AsTimeval(ns, rnd), tv)
+ if sys.platform == 'win32':
+ from _testcapi import LONG_MIN, LONG_MAX
+
+ # On Windows, timeval.tv_sec type is a C long
+ def seconds_filter(secs):
+ return LONG_MIN <= secs <= LONG_MAX
+ else:
+ seconds_filter = self.time_t_filter
+
+ self.check_int_rounding(PyTime_AsTimeval,
+ timeval_converter,
+ NS_TO_SEC,
+ value_filter=seconds_filter)
@unittest.skipUnless(hasattr(_testcapi, 'PyTime_AsTimespec'),
'need _testcapi.PyTime_AsTimespec')
- def test_timespec(self):
+ def test_AsTimespec(self):
from _testcapi import PyTime_AsTimespec
- for ns, ts in (
- # nanoseconds
- (0, (0, 0)),
- (1, (0, 1)),
- (-1, (-1, 999999999)),
- # seconds
- (2 * SEC_TO_NS, (2, 0)),
- (-3 * SEC_TO_NS, (-3, 0)),
+ def timespec_converter(ns):
+ return divmod(ns, SEC_TO_NS)
- # seconds + nanoseconds
- (1234567890, (1, 234567890)),
- (-1234567890, (-2, 765432110)),
- ):
- with self.subTest(nanoseconds=ns, timespec=ts):
- self.assertEqual(PyTime_AsTimespec(ns), ts)
+ self.check_int_rounding(lambda ns, rnd: PyTime_AsTimespec(ns),
+ timespec_converter,
+ NS_TO_SEC,
+ value_filter=self.time_t_filter)
- def test_milliseconds(self):
+ def test_AsMilliseconds(self):
from _testcapi import PyTime_AsMilliseconds
- for rnd in ALL_ROUNDING_METHODS:
- for ns, tv in (
- # milliseconds
- (1 * MS_TO_NS, 1),
- (-2 * MS_TO_NS, -2),
- # seconds
- (2 * SEC_TO_NS, 2000),
- (-3 * SEC_TO_NS, -3000),
- ):
- with self.subTest(nanoseconds=ns, timeval=tv, round=rnd):
- self.assertEqual(PyTime_AsMilliseconds(ns, rnd), tv)
+ self.check_int_rounding(PyTime_AsMilliseconds,
+ self.create_decimal_converter(MS_TO_NS),
+ NS_TO_SEC)
- FLOOR = _PyTime.ROUND_FLOOR
- CEILING = _PyTime.ROUND_CEILING
- for ns, ms, rnd in (
- # nanoseconds
- (1, 0, FLOOR),
- (1, 1, CEILING),
- (-1, 0, FLOOR),
- (-1, -1, CEILING),
-
- # seconds + nanoseconds
- (1234 * MS_TO_NS + 1, 1234, FLOOR),
- (1234 * MS_TO_NS + 1, 1235, CEILING),
- (-1234 * MS_TO_NS - 1, -1234, FLOOR),
- (-1234 * MS_TO_NS - 1, -1235, CEILING),
- ):
- with self.subTest(nanoseconds=ns, milliseconds=ms, round=rnd):
- self.assertEqual(PyTime_AsMilliseconds(ns, rnd), ms)
-
- def test_microseconds(self):
+ def test_AsMicroseconds(self):
from _testcapi import PyTime_AsMicroseconds
- for rnd in ALL_ROUNDING_METHODS:
- for ns, tv in (
- # microseconds
- (1 * US_TO_NS, 1),
- (-2 * US_TO_NS, -2),
- # milliseconds
- (1 * MS_TO_NS, 1000),
- (-2 * MS_TO_NS, -2000),
+ self.check_int_rounding(PyTime_AsMicroseconds,
+ self.create_decimal_converter(US_TO_NS),
+ NS_TO_SEC)
- # seconds
- (2 * SEC_TO_NS, 2000000),
- (-3 * SEC_TO_NS, -3000000),
- ):
- with self.subTest(nanoseconds=ns, timeval=tv, round=rnd):
- self.assertEqual(PyTime_AsMicroseconds(ns, rnd), tv)
- FLOOR = _PyTime.ROUND_FLOOR
- CEILING = _PyTime.ROUND_CEILING
- for ns, ms, rnd in (
- # nanoseconds
- (1, 0, FLOOR),
- (1, 1, CEILING),
- (-1, 0, FLOOR),
- (-1, -1, CEILING),
+class TestOldPyTime(CPyTimeTestCase, unittest.TestCase):
+ """
+ Test the old C _PyTime_t API: _PyTime_ObjectToXXX() functions.
+ """
- # seconds + nanoseconds
- (1234 * US_TO_NS + 1, 1234, FLOOR),
- (1234 * US_TO_NS + 1, 1235, CEILING),
- (-1234 * US_TO_NS - 1, -1234, FLOOR),
- (-1234 * US_TO_NS - 1, -1235, CEILING),
- ):
- with self.subTest(nanoseconds=ns, milliseconds=ms, round=rnd):
- self.assertEqual(PyTime_AsMicroseconds(ns, rnd), ms)
+ # time_t is a 32-bit or 64-bit signed integer
+ OVERFLOW_SECONDS = 2 ** 64
+
+ def test_object_to_time_t(self):
+ from _testcapi import pytime_object_to_time_t
+
+ self.check_int_rounding(pytime_object_to_time_t,
+ lambda secs: secs,
+ value_filter=self.time_t_filter)
+
+ self.check_float_rounding(pytime_object_to_time_t,
+ self.decimal_round,
+ value_filter=self.time_t_filter)
+
+ def create_converter(self, sec_to_unit):
+ def converter(secs):
+ floatpart, intpart = math.modf(secs)
+ intpart = int(intpart)
+ floatpart *= sec_to_unit
+ floatpart = self.decimal_round(floatpart)
+ if floatpart < 0:
+ floatpart += sec_to_unit
+ intpart -= 1
+ elif floatpart >= sec_to_unit:
+ floatpart -= sec_to_unit
+ intpart += 1
+ return (intpart, floatpart)
+ return converter
+
+ def test_object_to_timeval(self):
+ from _testcapi import pytime_object_to_timeval
+
+ self.check_int_rounding(pytime_object_to_timeval,
+ lambda secs: (secs, 0),
+ value_filter=self.time_t_filter)
+
+ self.check_float_rounding(pytime_object_to_timeval,
+ self.create_converter(SEC_TO_US),
+ value_filter=self.time_t_filter)
+
+ def test_object_to_timespec(self):
+ from _testcapi import pytime_object_to_timespec
+
+ self.check_int_rounding(pytime_object_to_timespec,
+ lambda secs: (secs, 0),
+ value_filter=self.time_t_filter)
+
+ self.check_float_rounding(pytime_object_to_timespec,
+ self.create_converter(SEC_TO_NS),
+ value_filter=self.time_t_filter)
if __name__ == "__main__":
diff --git a/Lib/test/test_urlparse.py b/Lib/test/test_urlparse.py
index 0552f90..fcf5082 100644
--- a/Lib/test/test_urlparse.py
+++ b/Lib/test/test_urlparse.py
@@ -554,29 +554,27 @@
self.assertEqual(p.port, 80)
self.assertEqual(p.geturl(), url)
- # Verify an illegal port is returned as None
+ # Verify an illegal port raises ValueError
url = b"HTTP://WWW.PYTHON.ORG:65536/doc/#frag"
p = urllib.parse.urlsplit(url)
- self.assertEqual(p.port, None)
+ with self.assertRaisesRegex(ValueError, "out of range"):
+ p.port
def test_attributes_bad_port(self):
- """Check handling of non-integer ports."""
- p = urllib.parse.urlsplit("http://www.example.net:foo")
- self.assertEqual(p.netloc, "www.example.net:foo")
- self.assertRaises(ValueError, lambda: p.port)
-
- p = urllib.parse.urlparse("http://www.example.net:foo")
- self.assertEqual(p.netloc, "www.example.net:foo")
- self.assertRaises(ValueError, lambda: p.port)
-
- # Once again, repeat ourselves to test bytes
- p = urllib.parse.urlsplit(b"http://www.example.net:foo")
- self.assertEqual(p.netloc, b"www.example.net:foo")
- self.assertRaises(ValueError, lambda: p.port)
-
- p = urllib.parse.urlparse(b"http://www.example.net:foo")
- self.assertEqual(p.netloc, b"www.example.net:foo")
- self.assertRaises(ValueError, lambda: p.port)
+ """Check handling of invalid ports."""
+ for bytes in (False, True):
+ for parse in (urllib.parse.urlsplit, urllib.parse.urlparse):
+ for port in ("foo", "1.5", "-1", "0x10"):
+ with self.subTest(bytes=bytes, parse=parse, port=port):
+ netloc = "www.example.net:" + port
+ url = "http://" + netloc
+ if bytes:
+ netloc = netloc.encode("ascii")
+ url = url.encode("ascii")
+ p = parse(url)
+ self.assertEqual(p.netloc, netloc)
+ with self.assertRaises(ValueError):
+ p.port
def test_attributes_without_netloc(self):
# This example is straight from RFC 3261. It looks like it
diff --git a/Lib/test/test_warnings/data/import_warning.py b/Lib/test/test_warnings/data/import_warning.py
index d6ea2ce..32daec1 100644
--- a/Lib/test/test_warnings/data/import_warning.py
+++ b/Lib/test/test_warnings/data/import_warning.py
@@ -1,3 +1,3 @@
import warnings
-warnings.warn('module-level warning', DeprecationWarning, stacklevel=2)
\ No newline at end of file
+warnings.warn('module-level warning', DeprecationWarning, stacklevel=2)
diff --git a/Lib/test/test_zipimport.py b/Lib/test/test_zipimport.py
index a97a778..4f19535 100644
--- a/Lib/test/test_zipimport.py
+++ b/Lib/test/test_zipimport.py
@@ -214,7 +214,8 @@
packdir2 = packdir + TESTPACK2 + os.sep
files = {packdir + "__init__" + pyc_ext: (NOW, test_pyc),
packdir2 + "__init__" + pyc_ext: (NOW, test_pyc),
- packdir2 + TESTMOD + pyc_ext: (NOW, test_pyc)}
+ packdir2 + TESTMOD + pyc_ext: (NOW, test_pyc),
+ "spam" + pyc_ext: (NOW, test_pyc)}
z = ZipFile(TEMP_ZIP, "w")
try:
@@ -228,6 +229,14 @@
zi = zipimport.zipimporter(TEMP_ZIP)
self.assertEqual(zi.archive, TEMP_ZIP)
self.assertEqual(zi.is_package(TESTPACK), True)
+
+ find_mod = zi.find_module('spam')
+ self.assertIsNotNone(find_mod)
+ self.assertIsInstance(find_mod, zipimport.zipimporter)
+ self.assertFalse(find_mod.is_package('spam'))
+ load_mod = find_mod.load_module('spam')
+ self.assertEqual(find_mod.get_filename('spam'), load_mod.__file__)
+
mod = zi.load_module(TESTPACK)
self.assertEqual(zi.get_filename(TESTPACK), mod.__file__)
@@ -287,6 +296,16 @@
self.assertEqual(
zi.is_package(TESTPACK2 + os.sep + TESTMOD), False)
+ pkg_path = TEMP_ZIP + os.sep + packdir + TESTPACK2
+ zi2 = zipimport.zipimporter(pkg_path)
+ find_mod_dotted = zi2.find_module(TESTMOD)
+ self.assertIsNotNone(find_mod_dotted)
+ self.assertIsInstance(find_mod_dotted, zipimport.zipimporter)
+ self.assertFalse(zi2.is_package(TESTMOD))
+ load_mod = find_mod_dotted.load_module(TESTMOD)
+ self.assertEqual(
+ find_mod_dotted.get_filename(TESTMOD), load_mod.__file__)
+
mod_path = TESTPACK2 + os.sep + TESTMOD
mod_name = module_path_to_dotted_name(mod_path)
__import__(mod_name)
diff --git a/Lib/timeit.py b/Lib/timeit.py
index 2de88f7..98cb3eb 100755
--- a/Lib/timeit.py
+++ b/Lib/timeit.py
@@ -317,20 +317,26 @@
print("%d loops," % number, end=' ')
usec = best * 1e6 / number
if time_unit is not None:
- print("best of %d: %.*g %s per loop" % (repeat, precision,
- usec/units[time_unit], time_unit))
+ scale = units[time_unit]
else:
- if usec < 1000:
- print("best of %d: %.*g usec per loop" % (repeat, precision, usec))
- else:
- msec = usec / 1000
- if msec < 1000:
- print("best of %d: %.*g msec per loop" % (repeat,
- precision, msec))
- else:
- sec = msec / 1000
- print("best of %d: %.*g sec per loop" % (repeat,
- precision, sec))
+ scales = [(scale, unit) for unit, scale in units.items()]
+ scales.sort(reverse=True)
+ for scale, time_unit in scales:
+ if usec >= scale:
+ break
+ print("best of %d: %.*g %s per loop" % (repeat, precision,
+ usec/scale, time_unit))
+ best = min(r)
+ usec = best * 1e6 / number
+ worst = max(r)
+ if worst >= best * 4:
+ usec = worst * 1e6 / number
+ import warnings
+ warnings.warn_explicit(
+ "The test results are likely unreliable. The worst\n"
+ "time (%.*g %s) was more than four times slower than the best time." %
+ (precision, usec/scale, time_unit),
+ UserWarning, '', 0)
return None
if __name__ == "__main__":
diff --git a/Lib/tkinter/ttk.py b/Lib/tkinter/ttk.py
index b9c57ad..bad9596 100644
--- a/Lib/tkinter/ttk.py
+++ b/Lib/tkinter/ttk.py
@@ -381,7 +381,9 @@
a sequence identifying the value for that option."""
if query_opt is not None:
kw[query_opt] = None
- return _val_or_dict(self.tk, kw, self._name, "configure", style)
+ result = _val_or_dict(self.tk, kw, self._name, "configure", style)
+ if result or query_opt:
+ return result
def map(self, style, query_opt=None, **kw):
@@ -466,12 +468,14 @@
def element_names(self):
"""Returns the list of elements defined in the current theme."""
- return self.tk.splitlist(self.tk.call(self._name, "element", "names"))
+ return tuple(n.lstrip('-') for n in self.tk.splitlist(
+ self.tk.call(self._name, "element", "names")))
def element_options(self, elementname):
"""Return the list of elementname's options."""
- return self.tk.splitlist(self.tk.call(self._name, "element", "options", elementname))
+ return tuple(o.lstrip('-') for o in self.tk.splitlist(
+ self.tk.call(self._name, "element", "options", elementname)))
def theme_create(self, themename, parent=None, settings=None):
diff --git a/Lib/traceback.py b/Lib/traceback.py
index 02edeb6..3d2e5e0 100644
--- a/Lib/traceback.py
+++ b/Lib/traceback.py
@@ -477,10 +477,9 @@
self._load_lines()
@classmethod
- def from_exception(self, exc, *args, **kwargs):
+ def from_exception(cls, exc, *args, **kwargs):
"""Create a TracebackException from an exception."""
- return TracebackException(
- type(exc), exc, exc.__traceback__, *args, **kwargs)
+ return cls(type(exc), exc, exc.__traceback__, *args, **kwargs)
def _load_lines(self):
"""Private API. force all lines in the stack to be loaded."""
diff --git a/Lib/urllib/parse.py b/Lib/urllib/parse.py
index 01c9e58..5e2155c 100644
--- a/Lib/urllib/parse.py
+++ b/Lib/urllib/parse.py
@@ -156,9 +156,8 @@
port = self._hostinfo[1]
if port is not None:
port = int(port, 10)
- # Return None on an illegal port
if not ( 0 <= port <= 65535):
- return None
+ raise ValueError("Port out of range 0-65535")
return port
diff --git a/Lib/urllib/request.py b/Lib/urllib/request.py
index a7fd017..e6abf34 100644
--- a/Lib/urllib/request.py
+++ b/Lib/urllib/request.py
@@ -138,6 +138,71 @@
_opener = None
def urlopen(url, data=None, timeout=socket._GLOBAL_DEFAULT_TIMEOUT,
*, cafile=None, capath=None, cadefault=False, context=None):
+ '''Open the URL url, which can be either a string or a Request object.
+
+ *data* must be a bytes object specifying additional data to be sent to the
+ server, or None if no such data is needed. data may also be an iterable
+ object and in that case Content-Length value must be specified in the
+ headers. Currently HTTP requests are the only ones that use data; the HTTP
+ request will be a POST instead of a GET when the data parameter is
+ provided.
+
+ *data* should be a buffer in the standard application/x-www-form-urlencoded
+ format. The urllib.parse.urlencode() function takes a mapping or sequence
+ of 2-tuples and returns a string in this format. It should be encoded to
+ bytes before being used as the data parameter. The charset parameter in
+ Content-Type header may be used to specify the encoding. If charset
+ parameter is not sent with the Content-Type header, the server following
+ the HTTP 1.1 recommendation may assume that the data is encoded in
+ ISO-8859-1 encoding. It is advisable to use charset parameter with encoding
+ used in Content-Type header with the Request.
+
+ urllib.request module uses HTTP/1.1 and includes a "Connection:close"
+ header in its HTTP requests.
+
+ The optional *timeout* parameter specifies a timeout in seconds for
+ blocking operations like the connection attempt (if not specified, the
+ global default timeout setting will be used). This only works for HTTP,
+ HTTPS and FTP connections.
+
+ If *context* is specified, it must be a ssl.SSLContext instance describing
+ the various SSL options. See HTTPSConnection for more details.
+
+ The optional *cafile* and *capath* parameters specify a set of trusted CA
+ certificates for HTTPS requests. cafile should point to a single file
+ containing a bundle of CA certificates, whereas capath should point to a
+ directory of hashed certificate files. More information can be found in
+ ssl.SSLContext.load_verify_locations().
+
+ The *cadefault* parameter is ignored.
+
+ For http and https urls, this function returns a http.client.HTTPResponse
+ object which has the following HTTPResponse Objects methods.
+
+ For ftp, file, and data urls and requests explicitly handled by legacy
+ URLopener and FancyURLopener classes, this function returns a
+ urllib.response.addinfourl object which can work as context manager and has
+ methods such as:
+
+ * geturl() — return the URL of the resource retrieved, commonly used to
+ determine if a redirect was followed
+
+ * info() — return the meta-information of the page, such as headers, in the
+ form of an email.message_from_string() instance (see Quick Reference to
+ HTTP Headers)
+
+ * getcode() – return the HTTP status code of the response. Raises URLError
+ on errors.
+
+ Note that *None& may be returned if no handler handles the request (though
+ the default installed global OpenerDirector uses UnknownHandler to ensure
+ this never happens).
+
+ In addition, if proxy settings are detected (for example, when a *_proxy
+ environment variable like http_proxy is set), ProxyHandler is default
+ installed and makes sure the requests are handled through the proxy.
+
+ '''
global _opener
if cafile or capath or cadefault:
if context is not None:
diff --git a/Misc/ACKS b/Misc/ACKS
index 050ae31..be6ba2d 100644
--- a/Misc/ACKS
+++ b/Misc/ACKS
@@ -1405,6 +1405,7 @@
Christian Tanzer
Steven Taschuk
Amy Taylor
+Julian Taylor
Monty Taylor
Anatoly Techtonik
Gustavo Temple
diff --git a/Misc/NEWS b/Misc/NEWS
index 7a48b06..278327c 100644
--- a/Misc/NEWS
+++ b/Misc/NEWS
@@ -2,6 +2,95 @@
Python News
+++++++++++
+What's New in Python 3.6.0 alpha 1?
+===================================
+
+Release date: XXXX-XX-XX
+
+Core and Builtins
+-----------------
+
+- Issue #9232: Modify Python's grammar to allow trailing commas in the
+ argument list of a function declaration. For example, "def f(*, a =
+ 3,): pass" is now legal. Patch from Mark Dickinson.
+
+Library
+-------
+
+- Issue #22241: timezone.utc name is now plain 'UTC', not 'UTC-00:00'.
+
+- Issue #23517: fromtimestamp() and utcfromtimestamp() methods of
+ datetime.datetime now round microseconds to nearest with ties going to
+ nearest even integer (ROUND_HALF_EVEN), as round(float), instead of rounding
+ towards -Infinity (ROUND_FLOOR).
+
+- Issue #23552: Timeit now warns when there is substantial (4x) variance
+ between best and worst times. Patch from Serhiy Storchaka.
+
+- Issue #24633: site-packages/README -> README.txt.
+
+- Issue #24879: help() and pydoc can now list named tuple fields in the
+ order they were defined rather than alphabetically. The ordering is
+ determined by the _fields attribute if present.
+
+- Issue #24874: Improve speed of itertools.cycle() and make its
+ pickle more compact.
+
+- Fix crash in itertools.cycle.__setstate__() when the first argument wasn't
+ a list.
+
+- Issue #20059: urllib.parse raises ValueError on all invalid ports.
+ Patch by Martin Panter.
+
+- Issue #24360: Improve __repr__ of argparse.Namespace() for invalid
+ identifiers. Patch by Matthias Bussonnier.
+
+- Issue #23426: run_setup was broken in distutils.
+ Patch from Alexander Belopolsky.
+
+- Issue #13938: 2to3 converts StringTypes to a tuple. Patch from Mark Hammond.
+
+- Issue #2091: open() accepted a 'U' mode string containing '+', but 'U' can
+ only be used with 'r'. Patch from Jeff Balogh and John O'Connor.
+
+- Issue #8585: improved tests for zipimporter2. Patch from Mark Lawrence.
+
+- Issue #18622: unittest.mock.mock_open().reset_mock would recurse infinitely.
+ Patch from Nicola Palumbo and Laurent De Buyst.
+
+- Issue #24426: Fast searching optimization in regular expressions now works
+ for patterns that starts with capturing groups. Fast searching optimization
+ now can't be disabled at compile time.
+
+- Issue #23661: unittest.mock side_effects can now be exceptions again. This
+ was a regression vs Python 3.4. Patch from Ignacio Rossi
+
+- Issue #13248: Remove deprecated inspect.getargspec and inspect.getmoduleinfo
+ functions.
+
+Documentation
+-------------
+
+- Issue #24952: Clarify the default size argument of stack_size() in
+ the "threading" and "_thread" modules. Patch from Mattip.
+
+Tests
+-----
+
+- PCbuild\rt.bat now accepts an unlimited number of arguments to pass along
+ to regrtest.py. Previously there was a limit of 9.
+
+Build
+-----
+
+- Issue #24986: It is now possible to build Python on Windows without errors
+ when external libraries are not available.
+
+Windows
+-------
+
+- Issue #25022: Removed very outdated PC/example_nt/ directory.
+
What's New in Python 3.5.1
==========================
@@ -93,11 +182,6 @@
- Issue #24986: It is now possible to build Python on Windows without errors
when external libraries are not available.
-Windows
--------
-
-- Issue #25022: Removed very outdated PC/example_nt/ directory.
-
What's New in Python 3.5.0 release candidate 4?
===============================================
@@ -332,12 +416,6 @@
- Issue #24631: Fixed regression in the timeit module with multiline setup.
-- Issue #18622: unittest.mock.mock_open().reset_mock would recurse infinitely.
- Patch from Nicola Palumbo and Laurent De Buyst.
-
-- Issue #23661: unittest.mock side_effects can now be exceptions again. This
- was a regression vs Python 3.4. Patch from Ignacio Rossi
-
- Issue #24608: chunk.Chunk.read() now always returns bytes, not str.
- Issue #18684: Fixed reading out of the buffer in the re module.
@@ -348,6 +426,9 @@
- Issue #15014: SMTP.auth() and SMTP.login() now support RFC 4954's optional
initial-response argument to the SMTP AUTH command.
+- Issue #6549: Remove hyphen from ttk.Style().element options. Only return result
+ from ttk.Style().configure if a result was generated or a query submitted.
+
- Issue #24669: Fix inspect.getsource() for 'async def' functions.
Patch by Kai Groner.
@@ -359,7 +440,6 @@
- Issue #24603: Update Windows builds and OS X 10.5 installer to use OpenSSL
1.0.2d.
-
What's New in Python 3.5.0 beta 3?
==================================
@@ -520,6 +600,9 @@
- Issue #24268: PEP 489: Multi-phase extension module initialization.
Patch by Petr Viktorin.
+- Issue #23359: Optimize set object internals by specializing the
+ hash table search into a lookup function and an insert function.
+
- Issue #23955: Add pyvenv.cfg option to suppress registry/environment
lookup for generating sys.path on Windows.
diff --git a/Modules/_collectionsmodule.c b/Modules/_collectionsmodule.c
index f450f25..db27e92 100644
--- a/Modules/_collectionsmodule.c
+++ b/Modules/_collectionsmodule.c
@@ -539,32 +539,6 @@
static void deque_clear(dequeobject *deque);
static PyObject *
-deque_repeat(dequeobject *deque, Py_ssize_t n)
-{
- dequeobject *new_deque;
- PyObject *result;
-
- /* XXX add a special case for when maxlen is defined */
- if (n < 0)
- n = 0;
- else if (n > 0 && Py_SIZE(deque) > MAX_DEQUE_LEN / n)
- return PyErr_NoMemory();
-
- new_deque = (dequeobject *)deque_new(&deque_type, (PyObject *)NULL, (PyObject *)NULL);
- new_deque->maxlen = deque->maxlen;
-
- for ( ; n ; n--) {
- result = deque_extend(new_deque, (PyObject *)deque);
- if (result == NULL) {
- Py_DECREF(new_deque);
- return NULL;
- }
- Py_DECREF(result);
- }
- return (PyObject *)new_deque;
-}
-
-static PyObject *
deque_inplace_repeat(dequeobject *deque, Py_ssize_t n)
{
Py_ssize_t i, size;
@@ -583,10 +557,6 @@
return (PyObject *)deque;
}
- if (size > MAX_DEQUE_LEN / n) {
- return PyErr_NoMemory();
- }
-
if (size == 1) {
/* common case, repeating a single element */
PyObject *item = deque->leftblock->data[deque->leftindex];
@@ -594,6 +564,9 @@
if (deque->maxlen != -1 && n > deque->maxlen)
n = deque->maxlen;
+ if (n > MAX_DEQUE_LEN)
+ return PyErr_NoMemory();
+
for (i = 0 ; i < n-1 ; i++) {
rv = deque_append(deque, item);
if (rv == NULL)
@@ -604,6 +577,10 @@
return (PyObject *)deque;
}
+ if ((size_t)size > MAX_DEQUE_LEN / (size_t)n) {
+ return PyErr_NoMemory();
+ }
+
seq = PySequence_List((PyObject *)deque);
if (seq == NULL)
return seq;
@@ -621,6 +598,17 @@
return (PyObject *)deque;
}
+static PyObject *
+deque_repeat(dequeobject *deque, Py_ssize_t n)
+{
+ dequeobject *new_deque;
+
+ new_deque = (dequeobject *)deque_copy((PyObject *) deque);
+ if (new_deque == NULL)
+ return NULL;
+ return deque_inplace_repeat(new_deque, n);
+}
+
/* The rotate() method is part of the public API and is used internally
as a primitive for other methods.
@@ -792,7 +780,7 @@
block *rightblock = deque->rightblock;
Py_ssize_t leftindex = deque->leftindex;
Py_ssize_t rightindex = deque->rightindex;
- Py_ssize_t n = Py_SIZE(deque) / 2;
+ Py_ssize_t n = Py_SIZE(deque) >> 1;
Py_ssize_t i;
PyObject *tmp;
@@ -1053,7 +1041,7 @@
static int
valid_index(Py_ssize_t i, Py_ssize_t limit)
{
- /* The cast to size_t let us use just a single comparison
+ /* The cast to size_t lets us use just a single comparison
to check whether i is in the range: 0 <= i < limit */
return (size_t) i < (size_t) limit;
}
@@ -2173,13 +2161,13 @@
oldval = _PyDict_GetItem_KnownHash(mapping, key, hash);
if (oldval == NULL) {
- if (_PyDict_SetItem_KnownHash(mapping, key, one, hash) == -1)
+ if (_PyDict_SetItem_KnownHash(mapping, key, one, hash) < 0)
goto done;
} else {
newval = PyNumber_Add(oldval, one);
if (newval == NULL)
goto done;
- if (_PyDict_SetItem_KnownHash(mapping, key, newval, hash) == -1)
+ if (_PyDict_SetItem_KnownHash(mapping, key, newval, hash) < 0)
goto done;
Py_CLEAR(newval);
}
@@ -2205,7 +2193,7 @@
Py_DECREF(oldval);
if (newval == NULL)
break;
- if (PyObject_SetItem(mapping, key, newval) == -1)
+ if (PyObject_SetItem(mapping, key, newval) < 0)
break;
Py_CLEAR(newval);
Py_DECREF(key);
diff --git a/Modules/_datetimemodule.c b/Modules/_datetimemodule.c
index 7e4be5b..bbc51c6 100644
--- a/Modules/_datetimemodule.c
+++ b/Modules/_datetimemodule.c
@@ -3287,6 +3287,11 @@
Py_INCREF(self->name);
return self->name;
}
+ if ((PyObject *)self == PyDateTime_TimeZone_UTC ||
+ (GET_TD_DAYS(self->offset) == 0 &&
+ GET_TD_SECONDS(self->offset) == 0 &&
+ GET_TD_MICROSECONDS(self->offset) == 0))
+ return PyUnicode_FromString("UTC");
/* Offset is normalized, so it is negative if days < 0 */
if (GET_TD_DAYS(self->offset) < 0) {
sign = '-';
@@ -4098,9 +4103,8 @@
long us;
if (_PyTime_ObjectToTimeval(timestamp,
- &timet, &us, _PyTime_ROUND_FLOOR) == -1)
+ &timet, &us, _PyTime_ROUND_HALF_EVEN) == -1)
return NULL;
- assert(0 <= us && us <= 999999);
return datetime_from_timet_and_us(cls, f, timet, (int)us, tzinfo);
}
@@ -4708,7 +4712,7 @@
if (seconds == NULL)
goto error;
Py_DECREF(delta);
- timestamp = PyLong_AsLong(seconds);
+ timestamp = _PyLong_AsTime_t(seconds);
Py_DECREF(seconds);
if (timestamp == -1 && PyErr_Occurred())
return NULL;
diff --git a/Modules/_heapqmodule.c b/Modules/_heapqmodule.c
index c343862..28604af 100644
--- a/Modules/_heapqmodule.c
+++ b/Modules/_heapqmodule.c
@@ -66,7 +66,7 @@
/* Bubble up the smaller child until hitting a leaf. */
arr = _PyList_ITEMS(heap);
- limit = endpos / 2; /* smallest pos that has no child */
+ limit = endpos >> 1; /* smallest pos that has no child */
while (pos < limit) {
/* Set childpos to index of smaller child. */
childpos = 2*pos + 1; /* leftmost child position */
@@ -347,7 +347,7 @@
n is odd = 2*j+1, this is (2*j+1-1)/2 = j so j-1 is the largest,
and that's again n//2-1.
*/
- for (i = n/2 - 1 ; i >= 0 ; i--)
+ for (i = (n >> 1) - 1 ; i >= 0 ; i--)
if (siftup_func((PyListObject *)heap, i))
return NULL;
Py_RETURN_NONE;
@@ -420,7 +420,7 @@
/* Bubble up the smaller child until hitting a leaf. */
arr = _PyList_ITEMS(heap);
- limit = endpos / 2; /* smallest pos that has no child */
+ limit = endpos >> 1; /* smallest pos that has no child */
while (pos < limit) {
/* Set childpos to index of smaller child. */
childpos = 2*pos + 1; /* leftmost child position */
diff --git a/Modules/_io/_iomodule.c b/Modules/_io/_iomodule.c
index 528bcd4..7428aed 100644
--- a/Modules/_io/_iomodule.c
+++ b/Modules/_io/_iomodule.c
@@ -238,7 +238,8 @@
int text = 0, binary = 0, universal = 0;
char rawmode[6], *m;
- int line_buffering, isatty;
+ int line_buffering;
+ long isatty;
PyObject *raw, *modeobj = NULL, *buffer, *wrapper, *result = NULL;
@@ -248,8 +249,8 @@
_Py_IDENTIFIER(close);
if (!PyUnicode_Check(file) &&
- !PyBytes_Check(file) &&
- !PyNumber_Check(file)) {
+ !PyBytes_Check(file) &&
+ !PyNumber_Check(file)) {
PyErr_Format(PyExc_TypeError, "invalid file: %R", file);
return NULL;
}
@@ -307,9 +308,9 @@
/* Parameters validation */
if (universal) {
- if (writing || appending) {
+ if (creating || writing || appending || updating) {
PyErr_SetString(PyExc_ValueError,
- "can't use U and writing mode at once");
+ "mode U cannot be combined with x', 'w', 'a', or '+'");
return NULL;
}
if (PyErr_WarnEx(PyExc_DeprecationWarning,
@@ -437,10 +438,10 @@
/* wraps into a TextIOWrapper */
wrapper = PyObject_CallFunction((PyObject *)&PyTextIOWrapper_Type,
- "Osssi",
- buffer,
- encoding, errors, newline,
- line_buffering);
+ "Osssi",
+ buffer,
+ encoding, errors, newline,
+ line_buffering);
if (wrapper == NULL)
goto error;
result = wrapper;
diff --git a/Modules/_sre.c b/Modules/_sre.c
index 957ccbc..6a3d811 100644
--- a/Modules/_sre.c
+++ b/Modules/_sre.c
@@ -62,9 +62,6 @@
/* -------------------------------------------------------------------- */
/* optional features */
-/* enables fast searching */
-#define USE_FAST_SEARCH
-
/* enables copy/deepcopy handling (work in progress) */
#undef USE_BUILTIN_COPY
diff --git a/Modules/_testcapimodule.c b/Modules/_testcapimodule.c
index ba0a24b..1f013c2 100644
--- a/Modules/_testcapimodule.c
+++ b/Modules/_testcapimodule.c
@@ -2646,7 +2646,9 @@
static int
check_time_rounding(int round)
{
- if (round != _PyTime_ROUND_FLOOR && round != _PyTime_ROUND_CEILING) {
+ if (round != _PyTime_ROUND_FLOOR
+ && round != _PyTime_ROUND_CEILING
+ && round != _PyTime_ROUND_HALF_EVEN) {
PyErr_SetString(PyExc_ValueError, "invalid rounding");
return -1;
}
@@ -4112,6 +4114,7 @@
PyModule_AddObject(m, "PY_SSIZE_T_MAX", PyLong_FromSsize_t(PY_SSIZE_T_MAX));
PyModule_AddObject(m, "PY_SSIZE_T_MIN", PyLong_FromSsize_t(PY_SSIZE_T_MIN));
PyModule_AddObject(m, "SIZEOF_PYGC_HEAD", PyLong_FromSsize_t(sizeof(PyGC_Head)));
+ PyModule_AddObject(m, "SIZEOF_TIME_T", PyLong_FromSsize_t(sizeof(time_t)));
Py_INCREF(&PyInstanceMethod_Type);
PyModule_AddObject(m, "instancemethod", (PyObject *)&PyInstanceMethod_Type);
diff --git a/Modules/clinic/posixmodule.c.h b/Modules/clinic/posixmodule.c.h
index 9ef702a..a48de6a 100644
--- a/Modules/clinic/posixmodule.c.h
+++ b/Modules/clinic/posixmodule.c.h
@@ -2116,7 +2116,7 @@
"sched_getaffinity($module, pid, /)\n"
"--\n"
"\n"
-"Return the affinity of the process identified by pid.\n"
+"Return the affinity of the process identified by pid (or the current process if zero).\n"
"\n"
"The affinity is returned as a set of CPU identifiers.");
@@ -5178,7 +5178,11 @@
"cpu_count($module, /)\n"
"--\n"
"\n"
-"Return the number of CPUs in the system; return None if indeterminable.");
+"Return the number of CPUs in the system; return None if indeterminable.\n"
+"\n"
+"This number is not equivalent to the number of CPUs the current process can\n"
+"use. The number of usable CPUs can be obtained with\n"
+"``len(os.sched_getaffinity(0))``");
#define OS_CPU_COUNT_METHODDEF \
{"cpu_count", (PyCFunction)os_cpu_count, METH_NOARGS, os_cpu_count__doc__},
@@ -5788,4 +5792,4 @@
#ifndef OS_SET_HANDLE_INHERITABLE_METHODDEF
#define OS_SET_HANDLE_INHERITABLE_METHODDEF
#endif /* !defined(OS_SET_HANDLE_INHERITABLE_METHODDEF) */
-/*[clinic end generated code: output=95824c52fd034654 input=a9049054013a1b77]*/
+/*[clinic end generated code: output=a5c9bef9ad11a20b input=a9049054013a1b77]*/
diff --git a/Modules/itertoolsmodule.c b/Modules/itertoolsmodule.c
index ac31e2f..c7e1919 100644
--- a/Modules/itertoolsmodule.c
+++ b/Modules/itertoolsmodule.c
@@ -1,15 +1,16 @@
+#define PY_SSIZE_T_CLEAN
#include "Python.h"
#include "structmember.h"
/* Itertools module written and maintained
by Raymond D. Hettinger <python@rcn.com>
- Copyright (c) 2003-2013 Python Software Foundation.
+ Copyright (c) 2003-2015 Python Software Foundation.
All rights reserved.
*/
-/* groupby object ***********************************************************/
+/* groupby object ************************************************************/
typedef struct {
PyObject_HEAD
@@ -87,8 +88,7 @@
else {
int rcmp;
- rcmp = PyObject_RichCompareBool(gbo->tgtkey,
- gbo->currkey, Py_EQ);
+ rcmp = PyObject_RichCompareBool(gbo->tgtkey, gbo->currkey, Py_EQ);
if (rcmp == -1)
return NULL;
else if (rcmp == 0)
@@ -103,8 +103,7 @@
newkey = newvalue;
Py_INCREF(newvalue);
} else {
- newkey = PyObject_CallFunctionObjArgs(gbo->keyfunc,
- newvalue, NULL);
+ newkey = PyObject_CallFunctionObjArgs(gbo->keyfunc, newvalue, NULL);
if (newkey == NULL) {
Py_DECREF(newvalue);
return NULL;
@@ -178,7 +177,7 @@
reduce_doc},
{"__setstate__", (PyCFunction)groupby_setstate, METH_O,
setstate_doc},
- {NULL, NULL} /* sentinel */
+ {NULL, NULL} /* sentinel */
};
PyDoc_STRVAR(groupby_doc,
@@ -301,8 +300,7 @@
newkey = newvalue;
Py_INCREF(newvalue);
} else {
- newkey = PyObject_CallFunctionObjArgs(gbo->keyfunc,
- newvalue, NULL);
+ newkey = PyObject_CallFunctionObjArgs(gbo->keyfunc, newvalue, NULL);
if (newkey == NULL) {
Py_DECREF(newvalue);
return NULL;
@@ -330,8 +328,7 @@
static PyObject *
_grouper_reduce(_grouperobject *lz)
{
- return Py_BuildValue("O(OO)", Py_TYPE(lz),
- lz->parent, lz->tgtkey);
+ return Py_BuildValue("O(OO)", Py_TYPE(lz), lz->parent, lz->tgtkey);
}
static PyMethodDef _grouper_methods[] = {
@@ -364,7 +361,7 @@
0, /* tp_as_buffer */
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC, /* tp_flags */
0, /* tp_doc */
- (traverseproc)_grouper_traverse,/* tp_traverse */
+ (traverseproc)_grouper_traverse, /* tp_traverse */
0, /* tp_clear */
0, /* tp_richcompare */
0, /* tp_weaklistoffset */
@@ -385,8 +382,7 @@
};
-
-/* tee object and with supporting function and objects ***************/
+/* tee object and with supporting function and objects ***********************/
/* The teedataobject pre-allocates space for LINKCELLS number of objects.
To help the object fit neatly inside cache lines (space for 16 to 32
@@ -401,7 +397,7 @@
typedef struct {
PyObject_HEAD
PyObject *it;
- int numread; /* 0 <= numread <= LINKCELLS */
+ int numread; /* 0 <= numread <= LINKCELLS */
PyObject *nextlink;
PyObject *(values[LINKCELLS]);
} teedataobject;
@@ -409,7 +405,7 @@
typedef struct {
PyObject_HEAD
teedataobject *dataobj;
- int index; /* 0 <= index <= LINKCELLS */
+ int index; /* 0 <= index <= LINKCELLS */
PyObject *weakreflist;
} teeobject;
@@ -466,6 +462,7 @@
teedataobject_traverse(teedataobject *tdo, visitproc visit, void * arg)
{
int i;
+
Py_VISIT(tdo->it);
for (i = 0; i < tdo->numread; i++)
Py_VISIT(tdo->values[i]);
@@ -515,6 +512,7 @@
int i;
/* create a temporary list of already iterated values */
PyObject *values = PyList_New(tdo->numread);
+
if (!values)
return NULL;
for (i=0 ; i<tdo->numread ; i++) {
@@ -582,7 +580,7 @@
PyDoc_STRVAR(teedataobject_doc, "Data container common to multiple tee objects.");
static PyTypeObject teedataobject_type = {
- PyVarObject_HEAD_INIT(0, 0) /* Must fill in type value later */
+ PyVarObject_HEAD_INIT(0, 0) /* Must fill in type value later */
"itertools._tee_dataobject", /* tp_name */
sizeof(teedataobject), /* tp_basicsize */
0, /* tp_itemsize */
@@ -602,7 +600,7 @@
PyObject_GenericGetAttr, /* tp_getattro */
0, /* tp_setattro */
0, /* tp_as_buffer */
- Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC, /* tp_flags */
+ Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC, /* tp_flags */
teedataobject_doc, /* tp_doc */
(traverseproc)teedataobject_traverse, /* tp_traverse */
(inquiry)teedataobject_clear, /* tp_clear */
@@ -759,9 +757,9 @@
"Iterator wrapped to make it copyable");
static PyMethodDef tee_methods[] = {
- {"__copy__", (PyCFunction)tee_copy, METH_NOARGS, teecopy_doc},
- {"__reduce__", (PyCFunction)tee_reduce, METH_NOARGS, reduce_doc},
- {"__setstate__", (PyCFunction)tee_setstate, METH_O, setstate_doc},
+ {"__copy__", (PyCFunction)tee_copy, METH_NOARGS, teecopy_doc},
+ {"__reduce__", (PyCFunction)tee_reduce, METH_NOARGS, reduce_doc},
+ {"__setstate__", (PyCFunction)tee_setstate, METH_O, setstate_doc},
{NULL, NULL} /* sentinel */
};
@@ -791,7 +789,7 @@
(traverseproc)tee_traverse, /* tp_traverse */
(inquiry)tee_clear, /* tp_clear */
0, /* tp_richcompare */
- offsetof(teeobject, weakreflist), /* tp_weaklistoffset */
+ offsetof(teeobject, weakreflist), /* tp_weaklistoffset */
PyObject_SelfIter, /* tp_iter */
(iternextfunc)tee_next, /* tp_iternext */
tee_methods, /* tp_methods */
@@ -857,12 +855,13 @@
"tee(iterable, n=2) --> tuple of n independent iterators.");
-/* cycle object **********************************************************/
+/* cycle object **************************************************************/
typedef struct {
PyObject_HEAD
PyObject *it;
PyObject *saved;
+ Py_ssize_t index;
int firstpass;
} cycleobject;
@@ -902,6 +901,7 @@
}
lz->it = it;
lz->saved = saved;
+ lz->index = 0;
lz->firstpass = 0;
return (PyObject *)lz;
@@ -911,15 +911,16 @@
cycle_dealloc(cycleobject *lz)
{
PyObject_GC_UnTrack(lz);
- Py_XDECREF(lz->saved);
Py_XDECREF(lz->it);
+ Py_XDECREF(lz->saved);
Py_TYPE(lz)->tp_free(lz);
}
static int
cycle_traverse(cycleobject *lz, visitproc visit, void *arg)
{
- Py_VISIT(lz->it);
+ if (lz->it)
+ Py_VISIT(lz->it);
Py_VISIT(lz->saved);
return 0;
}
@@ -928,57 +929,70 @@
cycle_next(cycleobject *lz)
{
PyObject *item;
- PyObject *it;
- PyObject *tmp;
- while (1) {
+ if (lz->it != NULL) {
item = PyIter_Next(lz->it);
if (item != NULL) {
- if (!lz->firstpass && PyList_Append(lz->saved, item)) {
+ if (lz->firstpass)
+ return item;
+ if (PyList_Append(lz->saved, item)) {
Py_DECREF(item);
return NULL;
}
return item;
}
- if (PyErr_Occurred()) {
- if (PyErr_ExceptionMatches(PyExc_StopIteration))
- PyErr_Clear();
- else
- return NULL;
- }
- if (PyList_Size(lz->saved) == 0)
+ /* Note: StopIteration is already cleared by PyIter_Next() */
+ if (PyErr_Occurred())
return NULL;
- it = PyObject_GetIter(lz->saved);
- if (it == NULL)
- return NULL;
- tmp = lz->it;
- lz->it = it;
- lz->firstpass = 1;
- Py_DECREF(tmp);
+ Py_CLEAR(lz->it);
}
+ if (Py_SIZE(lz->saved) == 0)
+ return NULL;
+ item = PyList_GET_ITEM(lz->saved, lz->index);
+ lz->index++;
+ if (lz->index >= Py_SIZE(lz->saved))
+ lz->index = 0;
+ Py_INCREF(item);
+ return item;
}
static PyObject *
cycle_reduce(cycleobject *lz)
{
- /* Create a new cycle with the iterator tuple, then set
- * the saved state on it.
- */
- return Py_BuildValue("O(O)(Oi)", Py_TYPE(lz),
- lz->it, lz->saved, lz->firstpass);
+ /* Create a new cycle with the iterator tuple, then set the saved state */
+ if (lz->it == NULL) {
+ PyObject *it = PyObject_GetIter(lz->saved);
+ if (it == NULL)
+ return NULL;
+ if (lz->index != 0) {
+ _Py_IDENTIFIER(__setstate__);
+ PyObject *res = _PyObject_CallMethodId(it, &PyId___setstate__,
+ "n", lz->index);
+ if (res == NULL) {
+ Py_DECREF(it);
+ return NULL;
+ }
+ Py_DECREF(res);
+ }
+ return Py_BuildValue("O(N)(Oi)", Py_TYPE(lz), it, lz->saved, 1);
}
+ return Py_BuildValue("O(O)(Oi)", Py_TYPE(lz), lz->it, lz->saved,
+ lz->firstpass);
+}
static PyObject *
cycle_setstate(cycleobject *lz, PyObject *state)
{
PyObject *saved=NULL;
int firstpass;
- if (!PyArg_ParseTuple(state, "Oi", &saved, &firstpass))
+
+ if (!PyArg_ParseTuple(state, "O!i", &PyList_Type, &saved, &firstpass))
return NULL;
+ Py_INCREF(saved);
Py_CLEAR(lz->saved);
lz->saved = saved;
- Py_XINCREF(lz->saved);
lz->firstpass = firstpass != 0;
+ lz->index = 0;
Py_RETURN_NONE;
}
@@ -1047,7 +1061,7 @@
PyObject_HEAD
PyObject *func;
PyObject *it;
- long start;
+ long start;
} dropwhileobject;
static PyTypeObject dropwhile_type;
@@ -1137,8 +1151,7 @@
static PyObject *
dropwhile_reduce(dropwhileobject *lz)
{
- return Py_BuildValue("O(OO)l", Py_TYPE(lz),
- lz->func, lz->it, lz->start);
+ return Py_BuildValue("O(OO)l", Py_TYPE(lz), lz->func, lz->it, lz->start);
}
static PyObject *
@@ -1189,13 +1202,13 @@
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC |
Py_TPFLAGS_BASETYPE, /* tp_flags */
dropwhile_doc, /* tp_doc */
- (traverseproc)dropwhile_traverse, /* tp_traverse */
+ (traverseproc)dropwhile_traverse, /* tp_traverse */
0, /* tp_clear */
0, /* tp_richcompare */
0, /* tp_weaklistoffset */
PyObject_SelfIter, /* tp_iter */
(iternextfunc)dropwhile_next, /* tp_iternext */
- dropwhile_methods, /* tp_methods */
+ dropwhile_methods, /* tp_methods */
0, /* tp_members */
0, /* tp_getset */
0, /* tp_base */
@@ -1216,7 +1229,7 @@
PyObject_HEAD
PyObject *func;
PyObject *it;
- long stop;
+ long stop;
} takewhileobject;
static PyTypeObject takewhile_type;
@@ -1291,7 +1304,7 @@
}
ok = PyObject_IsTrue(good);
Py_DECREF(good);
- if (ok == 1)
+ if (ok > 0)
return item;
Py_DECREF(item);
if (ok == 0)
@@ -1302,14 +1315,14 @@
static PyObject *
takewhile_reduce(takewhileobject *lz)
{
- return Py_BuildValue("O(OO)l", Py_TYPE(lz),
- lz->func, lz->it, lz->stop);
+ return Py_BuildValue("O(OO)l", Py_TYPE(lz), lz->func, lz->it, lz->stop);
}
static PyObject *
takewhile_reduce_setstate(takewhileobject *lz, PyObject *state)
{
int stop = PyObject_IsTrue(state);
+
if (stop < 0)
return NULL;
lz->stop = stop;
@@ -1353,7 +1366,7 @@
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC |
Py_TPFLAGS_BASETYPE, /* tp_flags */
takewhile_doc, /* tp_doc */
- (traverseproc)takewhile_traverse, /* tp_traverse */
+ (traverseproc)takewhile_traverse, /* tp_traverse */
0, /* tp_clear */
0, /* tp_richcompare */
0, /* tp_weaklistoffset */
@@ -1374,7 +1387,7 @@
};
-/* islice object ************************************************************/
+/* islice object *************************************************************/
typedef struct {
PyObject_HEAD
@@ -1410,7 +1423,8 @@
if (PyErr_Occurred())
PyErr_Clear();
PyErr_SetString(PyExc_ValueError,
- "Stop argument for islice() must be None or an integer: 0 <= x <= sys.maxsize.");
+ "Stop argument for islice() must be None or "
+ "an integer: 0 <= x <= sys.maxsize.");
return NULL;
}
}
@@ -1425,14 +1439,16 @@
if (PyErr_Occurred())
PyErr_Clear();
PyErr_SetString(PyExc_ValueError,
- "Stop argument for islice() must be None or an integer: 0 <= x <= sys.maxsize.");
+ "Stop argument for islice() must be None or "
+ "an integer: 0 <= x <= sys.maxsize.");
return NULL;
}
}
}
if (start<0 || stop<-1) {
PyErr_SetString(PyExc_ValueError,
- "Indices for islice() must be None or an integer: 0 <= x <= sys.maxsize.");
+ "Indices for islice() must be None or "
+ "an integer: 0 <= x <= sys.maxsize.");
return NULL;
}
@@ -1529,6 +1545,7 @@
* then 'setstate' with the next and count
*/
PyObject *stop;
+
if (lz->it == NULL) {
PyObject *empty_list;
PyObject *empty_it;
@@ -1558,6 +1575,7 @@
islice_setstate(isliceobject *lz, PyObject *state)
{
Py_ssize_t cnt = PyLong_AsSsize_t(state);
+
if (cnt == -1 && PyErr_Occurred())
return NULL;
lz->cnt = cnt;
@@ -1772,7 +1790,7 @@
};
-/* chain object ************************************************************/
+/* chain object **************************************************************/
typedef struct {
PyObject_HEAD
@@ -1848,32 +1866,32 @@
PyObject *item;
if (lz->source == NULL)
- return NULL; /* already stopped */
+ return NULL; /* already stopped */
if (lz->active == NULL) {
PyObject *iterable = PyIter_Next(lz->source);
if (iterable == NULL) {
Py_CLEAR(lz->source);
- return NULL; /* no more input sources */
+ return NULL; /* no more input sources */
}
lz->active = PyObject_GetIter(iterable);
Py_DECREF(iterable);
if (lz->active == NULL) {
Py_CLEAR(lz->source);
- return NULL; /* input not iterable */
+ return NULL; /* input not iterable */
}
}
- item = PyIter_Next(lz->active);
+ item = (*Py_TYPE(lz->active)->tp_iternext)(lz->active);
if (item != NULL)
return item;
if (PyErr_Occurred()) {
if (PyErr_ExceptionMatches(PyExc_StopIteration))
PyErr_Clear();
else
- return NULL; /* input raised an exception */
+ return NULL; /* input raised an exception */
}
Py_CLEAR(lz->active);
- return chain_next(lz); /* recurse and use next active */
+ return chain_next(lz); /* recurse and use next active */
}
static PyObject *
@@ -1899,6 +1917,7 @@
chain_setstate(chainobject *lz, PyObject *state)
{
PyObject *source, *active=NULL;
+
if (! PyArg_ParseTuple(state, "O|O", &source, &active))
return NULL;
@@ -1925,13 +1944,13 @@
that evaluates lazily.");
static PyMethodDef chain_methods[] = {
- {"from_iterable", (PyCFunction) chain_new_from_iterable, METH_O | METH_CLASS,
- chain_from_iterable_doc},
+ {"from_iterable", (PyCFunction) chain_new_from_iterable, METH_O | METH_CLASS,
+ chain_from_iterable_doc},
{"__reduce__", (PyCFunction)chain_reduce, METH_NOARGS,
reduce_doc},
{"__setstate__", (PyCFunction)chain_setstate, METH_O,
setstate_doc},
- {NULL, NULL} /* sentinel */
+ {NULL, NULL} /* sentinel */
};
static PyTypeObject chain_type = {
@@ -1983,10 +2002,10 @@
typedef struct {
PyObject_HEAD
- PyObject *pools; /* tuple of pool tuples */
- Py_ssize_t *indices; /* one index per pool */
- PyObject *result; /* most recently returned result tuple */
- int stopped; /* set to 1 when the product iterator is exhausted */
+ PyObject *pools; /* tuple of pool tuples */
+ Py_ssize_t *indices; /* one index per pool */
+ PyObject *result; /* most recently returned result tuple */
+ int stopped; /* set to 1 when the iterator is exhausted */
} productobject;
static PyTypeObject product_type;
@@ -2005,7 +2024,8 @@
PyObject *tmpargs = PyTuple_New(0);
if (tmpargs == NULL)
return NULL;
- if (!PyArg_ParseTupleAndKeywords(tmpargs, kwds, "|n:product", kwlist, &repeat)) {
+ if (!PyArg_ParseTupleAndKeywords(tmpargs, kwds, "|n:product",
+ kwlist, &repeat)) {
Py_DECREF(tmpargs);
return NULL;
}
@@ -2287,7 +2307,7 @@
static PyTypeObject product_type = {
PyVarObject_HEAD_INIT(NULL, 0)
"itertools.product", /* tp_name */
- sizeof(productobject), /* tp_basicsize */
+ sizeof(productobject), /* tp_basicsize */
0, /* tp_itemsize */
/* methods */
(destructor)product_dealloc, /* tp_dealloc */
@@ -2329,15 +2349,15 @@
};
-/* combinations object ************************************************************/
+/* combinations object *******************************************************/
typedef struct {
PyObject_HEAD
- PyObject *pool; /* input converted to a tuple */
- Py_ssize_t *indices; /* one index per result element */
- PyObject *result; /* most recently returned result tuple */
- Py_ssize_t r; /* size of result tuple */
- int stopped; /* set to 1 when the combinations iterator is exhausted */
+ PyObject *pool; /* input converted to a tuple */
+ Py_ssize_t *indices; /* one index per result element */
+ PyObject *result; /* most recently returned result tuple */
+ Py_ssize_t r; /* size of result tuple */
+ int stopped; /* set to 1 when the iterator is exhausted */
} combinationsobject;
static PyTypeObject combinations_type;
@@ -2547,17 +2567,16 @@
Py_ssize_t i;
Py_ssize_t n = PyTuple_GET_SIZE(lz->pool);
- if (!PyTuple_Check(state) || PyTuple_GET_SIZE(state) != lz->r)
- {
+ if (!PyTuple_Check(state) || PyTuple_GET_SIZE(state) != lz->r) {
PyErr_SetString(PyExc_ValueError, "invalid arguments");
return NULL;
}
- for (i=0; i<lz->r; i++)
- {
+ for (i=0; i<lz->r; i++) {
Py_ssize_t max;
PyObject* indexObject = PyTuple_GET_ITEM(state, i);
Py_ssize_t index = PyLong_AsSsize_t(indexObject);
+
if (index == -1 && PyErr_Occurred())
return NULL; /* not an integer */
max = i + n - lz->r;
@@ -2644,7 +2663,7 @@
};
-/* combinations with replacement object *******************************************/
+/* combinations with replacement object **************************************/
/* Equivalent to:
@@ -2674,11 +2693,11 @@
*/
typedef struct {
PyObject_HEAD
- PyObject *pool; /* input converted to a tuple */
+ PyObject *pool; /* input converted to a tuple */
Py_ssize_t *indices; /* one index per result element */
PyObject *result; /* most recently returned result tuple */
- Py_ssize_t r; /* size of result tuple */
- int stopped; /* set to 1 when the cwr iterator is exhausted */
+ Py_ssize_t r; /* size of result tuple */
+ int stopped; /* set to 1 when the cwr iterator is exhausted */
} cwrobject;
static PyTypeObject cwr_type;
@@ -2695,8 +2714,9 @@
Py_ssize_t i;
static char *kwargs[] = {"iterable", "r", NULL};
- if (!PyArg_ParseTupleAndKeywords(args, kwds, "On:combinations_with_replacement", kwargs,
- &iterable, &r))
+ if (!PyArg_ParseTupleAndKeywords(args, kwds,
+ "On:combinations_with_replacement",
+ kwargs, &iterable, &r))
return NULL;
pool = PySequence_Tuple(iterable);
@@ -2861,8 +2881,7 @@
indices = PyTuple_New(lz->r);
if (!indices)
return NULL;
- for (i=0; i<lz->r; i++)
- {
+ for (i=0; i<lz->r; i++) {
PyObject* index = PyLong_FromSsize_t(lz->indices[i]);
if (!index) {
Py_DECREF(indices);
@@ -2888,10 +2907,10 @@
}
n = PyTuple_GET_SIZE(lz->pool);
- for (i=0; i<lz->r; i++)
- {
+ for (i=0; i<lz->r; i++) {
PyObject* indexObject = PyTuple_GET_ITEM(state, i);
Py_ssize_t index = PyLong_AsSsize_t(indexObject);
+
if (index < 0 && PyErr_Occurred())
return NULL; /* not an integer */
/* clamp the index */
@@ -2976,7 +2995,7 @@
};
-/* permutations object ************************************************************
+/* permutations object ********************************************************
def permutations(iterable, r=None):
'permutations(range(3), 2) --> (0,1) (0,2) (1,0) (1,2) (2,0) (2,1)'
@@ -3003,12 +3022,12 @@
typedef struct {
PyObject_HEAD
- PyObject *pool; /* input converted to a tuple */
- Py_ssize_t *indices; /* one index per element in the pool */
- Py_ssize_t *cycles; /* one rollover counter per element in the result */
- PyObject *result; /* most recently returned result tuple */
- Py_ssize_t r; /* size of result tuple */
- int stopped; /* set to 1 when the permutations iterator is exhausted */
+ PyObject *pool; /* input converted to a tuple */
+ Py_ssize_t *indices; /* one index per element in the pool */
+ Py_ssize_t *cycles; /* one rollover counter per element in the result */
+ PyObject *result; /* most recently returned result tuple */
+ Py_ssize_t r; /* size of result tuple */
+ int stopped; /* set to 1 when the iterator is exhausted */
} permutationsobject;
static PyTypeObject permutations_type;
@@ -3223,7 +3242,7 @@
indices = PyTuple_New(n);
if (indices == NULL)
goto err;
- for (i=0; i<n; i++){
+ for (i=0; i<n; i++) {
PyObject* index = PyLong_FromSsize_t(po->indices[i]);
if (!index)
goto err;
@@ -3233,8 +3252,7 @@
cycles = PyTuple_New(po->r);
if (cycles == NULL)
goto err;
- for (i=0; i<po->r; i++)
- {
+ for (i=0 ; i<po->r ; i++) {
PyObject* index = PyLong_FromSsize_t(po->cycles[i]);
if (!index)
goto err;
@@ -3262,15 +3280,12 @@
return NULL;
n = PyTuple_GET_SIZE(po->pool);
- if (PyTuple_GET_SIZE(indices) != n ||
- PyTuple_GET_SIZE(cycles) != po->r)
- {
+ if (PyTuple_GET_SIZE(indices) != n || PyTuple_GET_SIZE(cycles) != po->r) {
PyErr_SetString(PyExc_ValueError, "invalid arguments");
return NULL;
}
- for (i=0; i<n; i++)
- {
+ for (i=0; i<n; i++) {
PyObject* indexObject = PyTuple_GET_ITEM(indices, i);
Py_ssize_t index = PyLong_AsSsize_t(indexObject);
if (index < 0 && PyErr_Occurred())
@@ -3283,8 +3298,7 @@
po->indices[i] = index;
}
- for (i=0; i<po->r; i++)
- {
+ for (i=0; i<po->r; i++) {
PyObject* indexObject = PyTuple_GET_ITEM(cycles, i);
Py_ssize_t index = PyLong_AsSsize_t(indexObject);
if (index < 0 && PyErr_Occurred())
@@ -3326,11 +3340,11 @@
static PyTypeObject permutations_type = {
PyVarObject_HEAD_INIT(NULL, 0)
- "itertools.permutations", /* tp_name */
+ "itertools.permutations", /* tp_name */
sizeof(permutationsobject), /* tp_basicsize */
0, /* tp_itemsize */
/* methods */
- (destructor)permutations_dealloc, /* tp_dealloc */
+ (destructor)permutations_dealloc, /* tp_dealloc */
0, /* tp_print */
0, /* tp_getattr */
0, /* tp_setattr */
@@ -3347,13 +3361,13 @@
0, /* tp_as_buffer */
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC |
Py_TPFLAGS_BASETYPE, /* tp_flags */
- permutations_doc, /* tp_doc */
- (traverseproc)permutations_traverse, /* tp_traverse */
+ permutations_doc, /* tp_doc */
+ (traverseproc)permutations_traverse,/* tp_traverse */
0, /* tp_clear */
0, /* tp_richcompare */
0, /* tp_weaklistoffset */
PyObject_SelfIter, /* tp_iter */
- (iternextfunc)permutations_next, /* tp_iternext */
+ (iternextfunc)permutations_next, /* tp_iternext */
permuations_methods, /* tp_methods */
0, /* tp_members */
0, /* tp_getset */
@@ -3364,11 +3378,11 @@
0, /* tp_dictoffset */
0, /* tp_init */
0, /* tp_alloc */
- permutations_new, /* tp_new */
+ permutations_new, /* tp_new */
PyObject_GC_Del, /* tp_free */
};
-/* accumulate object ************************************************************/
+/* accumulate object ********************************************************/
typedef struct {
PyObject_HEAD
@@ -3437,7 +3451,7 @@
{
PyObject *val, *oldtotal, *newtotal;
- val = PyIter_Next(lz->it);
+ val = (*Py_TYPE(lz->it)->tp_iternext)(lz->it);
if (val == NULL)
return NULL;
@@ -3469,7 +3483,7 @@
return Py_BuildValue("O(OO)O", Py_TYPE(lz),
lz->it, lz->binop?lz->binop:Py_None,
lz->total?lz->total:Py_None);
- }
+}
static PyObject *
accumulate_setstate(accumulateobject *lz, PyObject *state)
@@ -3632,7 +3646,7 @@
ok = PyObject_IsTrue(selector);
Py_DECREF(selector);
- if (ok == 1)
+ if (ok > 0)
return datum;
Py_DECREF(datum);
if (ok < 0)
@@ -3645,7 +3659,7 @@
{
return Py_BuildValue("O(OO)", Py_TYPE(lz),
lz->data, lz->selectors);
- }
+}
static PyMethodDef compress_methods[] = {
{"__reduce__", (PyCFunction)compress_reduce, METH_NOARGS,
@@ -3664,44 +3678,44 @@
PyVarObject_HEAD_INIT(NULL, 0)
"itertools.compress", /* tp_name */
sizeof(compressobject), /* tp_basicsize */
- 0, /* tp_itemsize */
+ 0, /* tp_itemsize */
/* methods */
(destructor)compress_dealloc, /* tp_dealloc */
- 0, /* tp_print */
- 0, /* tp_getattr */
- 0, /* tp_setattr */
- 0, /* tp_reserved */
- 0, /* tp_repr */
- 0, /* tp_as_number */
- 0, /* tp_as_sequence */
- 0, /* tp_as_mapping */
- 0, /* tp_hash */
- 0, /* tp_call */
- 0, /* tp_str */
- PyObject_GenericGetAttr, /* tp_getattro */
- 0, /* tp_setattro */
- 0, /* tp_as_buffer */
+ 0, /* tp_print */
+ 0, /* tp_getattr */
+ 0, /* tp_setattr */
+ 0, /* tp_reserved */
+ 0, /* tp_repr */
+ 0, /* tp_as_number */
+ 0, /* tp_as_sequence */
+ 0, /* tp_as_mapping */
+ 0, /* tp_hash */
+ 0, /* tp_call */
+ 0, /* tp_str */
+ PyObject_GenericGetAttr, /* tp_getattro */
+ 0, /* tp_setattro */
+ 0, /* tp_as_buffer */
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC |
- Py_TPFLAGS_BASETYPE, /* tp_flags */
- compress_doc, /* tp_doc */
- (traverseproc)compress_traverse, /* tp_traverse */
- 0, /* tp_clear */
- 0, /* tp_richcompare */
- 0, /* tp_weaklistoffset */
- PyObject_SelfIter, /* tp_iter */
+ Py_TPFLAGS_BASETYPE, /* tp_flags */
+ compress_doc, /* tp_doc */
+ (traverseproc)compress_traverse, /* tp_traverse */
+ 0, /* tp_clear */
+ 0, /* tp_richcompare */
+ 0, /* tp_weaklistoffset */
+ PyObject_SelfIter, /* tp_iter */
(iternextfunc)compress_next, /* tp_iternext */
- compress_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 */
- 0, /* tp_init */
- 0, /* tp_alloc */
- compress_new, /* tp_new */
- PyObject_GC_Del, /* tp_free */
+ compress_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 */
+ 0, /* tp_init */
+ 0, /* tp_alloc */
+ compress_new, /* tp_new */
+ PyObject_GC_Del, /* tp_free */
};
@@ -3782,8 +3796,7 @@
ok = PyObject_IsTrue(item);
} else {
PyObject *good;
- good = PyObject_CallFunctionObjArgs(lz->func,
- item, NULL);
+ good = PyObject_CallFunctionObjArgs(lz->func, item, NULL);
if (good == NULL) {
Py_DECREF(item);
return NULL;
@@ -3802,9 +3815,8 @@
static PyObject *
filterfalse_reduce(filterfalseobject *lz)
{
- return Py_BuildValue("O(OO)", Py_TYPE(lz),
- lz->func, lz->it);
- }
+ return Py_BuildValue("O(OO)", Py_TYPE(lz), lz->func, lz->it);
+}
static PyMethodDef filterfalse_methods[] = {
{"__reduce__", (PyCFunction)filterfalse_reduce, METH_NOARGS,
@@ -3824,7 +3836,7 @@
sizeof(filterfalseobject), /* tp_basicsize */
0, /* tp_itemsize */
/* methods */
- (destructor)filterfalse_dealloc, /* tp_dealloc */
+ (destructor)filterfalse_dealloc, /* tp_dealloc */
0, /* tp_print */
0, /* tp_getattr */
0, /* tp_setattr */
@@ -3842,7 +3854,7 @@
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC |
Py_TPFLAGS_BASETYPE, /* tp_flags */
filterfalse_doc, /* tp_doc */
- (traverseproc)filterfalse_traverse, /* tp_traverse */
+ (traverseproc)filterfalse_traverse, /* tp_traverse */
0, /* tp_clear */
0, /* tp_richcompare */
0, /* tp_weaklistoffset */
@@ -4081,15 +4093,15 @@
0, /* tp_setattro */
0, /* tp_as_buffer */
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC |
- Py_TPFLAGS_BASETYPE, /* tp_flags */
+ Py_TPFLAGS_BASETYPE, /* tp_flags */
count_doc, /* tp_doc */
- (traverseproc)count_traverse, /* tp_traverse */
+ (traverseproc)count_traverse, /* tp_traverse */
0, /* tp_clear */
0, /* tp_richcompare */
0, /* tp_weaklistoffset */
PyObject_SelfIter, /* tp_iter */
(iternextfunc)count_next, /* tp_iternext */
- count_methods, /* tp_methods */
+ count_methods, /* tp_methods */
0, /* tp_members */
0, /* tp_getset */
0, /* tp_base */
@@ -4255,9 +4267,7 @@
PyObject_GC_Del, /* tp_free */
};
-/* ziplongest object ************************************************************/
-
-#include "Python.h"
+/* ziplongest object *********************************************************/
typedef struct {
PyObject_HEAD
@@ -4296,7 +4306,7 @@
ittuple = PyTuple_New(tuplesize);
if (ittuple == NULL)
return NULL;
- for (i=0; i < tuplesize; ++i) {
+ for (i=0; i < tuplesize; i++) {
PyObject *item = PyTuple_GET_ITEM(args, i);
PyObject *it = PyObject_GetIter(item);
if (it == NULL) {
@@ -4437,6 +4447,7 @@
*/
int i;
PyObject *args = PyTuple_New(PyTuple_GET_SIZE(lz->ittuple));
+
if (args == NULL)
return NULL;
for (i=0; i<PyTuple_GET_SIZE(lz->ittuple); i++) {
@@ -4488,7 +4499,7 @@
sizeof(ziplongestobject), /* tp_basicsize */
0, /* tp_itemsize */
/* methods */
- (destructor)zip_longest_dealloc, /* tp_dealloc */
+ (destructor)zip_longest_dealloc, /* tp_dealloc */
0, /* tp_print */
0, /* tp_getattr */
0, /* tp_setattr */
@@ -4505,8 +4516,8 @@
0, /* tp_as_buffer */
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC |
Py_TPFLAGS_BASETYPE, /* tp_flags */
- zip_longest_doc, /* tp_doc */
- (traverseproc)zip_longest_traverse, /* tp_traverse */
+ zip_longest_doc, /* tp_doc */
+ (traverseproc)zip_longest_traverse, /* tp_traverse */
0, /* tp_clear */
0, /* tp_richcompare */
0, /* tp_weaklistoffset */
@@ -4522,7 +4533,7 @@
0, /* tp_dictoffset */
0, /* tp_init */
0, /* tp_alloc */
- zip_longest_new, /* tp_new */
+ zip_longest_new, /* tp_new */
PyObject_GC_Del, /* tp_free */
};
diff --git a/Modules/nismodule.c b/Modules/nismodule.c
index 64eb5db..b6a855c 100644
--- a/Modules/nismodule.c
+++ b/Modules/nismodule.c
@@ -76,11 +76,7 @@
*pfix = 0;
for (i=0; aliases[i].alias != 0L; i++) {
- if (!strcmp (aliases[i].alias, map)) {
- *pfix = aliases[i].fix;
- return aliases[i].map;
- }
- if (!strcmp (aliases[i].map, map)) {
+ if (!strcmp (aliases[i].alias, map) || !strcmp (aliases[i].map, map)) {
*pfix = aliases[i].fix;
return aliases[i].map;
}
diff --git a/Modules/posixmodule.c b/Modules/posixmodule.c
index c0baf6a..d2e2801 100644
--- a/Modules/posixmodule.c
+++ b/Modules/posixmodule.c
@@ -5756,14 +5756,14 @@
pid: pid_t
/
-Return the affinity of the process identified by pid.
+Return the affinity of the process identified by pid (or the current process if zero).
The affinity is returned as a set of CPU identifiers.
[clinic start generated code]*/
static PyObject *
os_sched_getaffinity_impl(PyModuleDef *module, pid_t pid)
-/*[clinic end generated code: output=b431a8f310e369e7 input=eaf161936874b8a1]*/
+/*[clinic end generated code: output=b431a8f310e369e7 input=983ce7cb4a565980]*/
{
int cpu, ncpus, count;
size_t setsize;
@@ -9482,7 +9482,7 @@
*/
struct constdef {
char *name;
- long value;
+ int value;
};
static int
@@ -9490,7 +9490,10 @@
size_t tablesize)
{
if (PyLong_Check(arg)) {
- *valuep = PyLong_AS_LONG(arg);
+ int value = _PyLong_AsInt(arg);
+ if (value == -1 && PyErr_Occurred())
+ return 0;
+ *valuep = value;
return 1;
}
else {
@@ -11199,11 +11202,15 @@
os.cpu_count
Return the number of CPUs in the system; return None if indeterminable.
+
+This number is not equivalent to the number of CPUs the current process can
+use. The number of usable CPUs can be obtained with
+``len(os.sched_getaffinity(0))``
[clinic start generated code]*/
static PyObject *
os_cpu_count_impl(PyModuleDef *module)
-/*[clinic end generated code: output=c59ee7f6bce832b8 input=d55e2f8f3823a628]*/
+/*[clinic end generated code: output=c59ee7f6bce832b8 input=e7c8f4ba6dbbadd3]*/
{
int ncpu = 0;
#ifdef MS_WINDOWS
diff --git a/Modules/readline.c b/Modules/readline.c
index f6b52a0..09877f2 100644
--- a/Modules/readline.c
+++ b/Modules/readline.c
@@ -840,7 +840,7 @@
if (r == Py_None)
result = 0;
else {
- result = PyLong_AsLong(r);
+ result = _PyLong_AsInt(r);
if (result == -1 && PyErr_Occurred())
goto error;
}
diff --git a/Modules/sre_lib.h b/Modules/sre_lib.h
index 128c71e..6ad2ab7 100644
--- a/Modules/sre_lib.h
+++ b/Modules/sre_lib.h
@@ -1256,7 +1256,32 @@
prefix, prefix_len, prefix_skip));
TRACE(("charset = %p\n", charset));
-#if defined(USE_FAST_SEARCH)
+ if (prefix_len == 1) {
+ /* pattern starts with a literal character */
+ SRE_CHAR c = (SRE_CHAR) prefix[0];
+#if SIZEOF_SRE_CHAR < 4
+ if ((SRE_CODE) c != prefix[0])
+ return 0; /* literal can't match: doesn't fit in char width */
+#endif
+ end = (SRE_CHAR *)state->end;
+ while (ptr < end) {
+ while (*ptr != c) {
+ if (++ptr >= end)
+ return 0;
+ }
+ TRACE(("|%p|%p|SEARCH LITERAL\n", pattern, ptr));
+ state->start = ptr;
+ state->ptr = ptr + prefix_skip;
+ if (flags & SRE_INFO_LITERAL)
+ return 1; /* we got all of it */
+ status = SRE(match)(state, pattern + 2*prefix_skip, 0);
+ if (status != 0)
+ return status;
+ ++ptr;
+ }
+ return 0;
+ }
+
if (prefix_len > 1) {
/* pattern starts with a known prefix. use the overlap
table to skip forward as fast as we possibly can */
@@ -1305,32 +1330,8 @@
}
return 0;
}
-#endif
- if (pattern[0] == SRE_OP_LITERAL) {
- /* pattern starts with a literal character. this is used
- for short prefixes, and if fast search is disabled */
- SRE_CHAR c = (SRE_CHAR) pattern[1];
-#if SIZEOF_SRE_CHAR < 4
- if ((SRE_CODE) c != pattern[1])
- return 0; /* literal can't match: doesn't fit in char width */
-#endif
- end = (SRE_CHAR *)state->end;
- while (ptr < end) {
- while (*ptr != c) {
- if (++ptr >= end)
- return 0;
- }
- TRACE(("|%p|%p|SEARCH LITERAL\n", pattern, ptr));
- state->start = ptr;
- state->ptr = ++ptr;
- if (flags & SRE_INFO_LITERAL)
- return 1; /* we got all of it */
- status = SRE(match)(state, pattern + 2, 0);
- if (status != 0)
- break;
- }
- } else if (charset) {
+ if (charset) {
/* pattern starts with a character from a known set */
end = (SRE_CHAR *)state->end;
for (;;) {
diff --git a/Objects/abstract.c b/Objects/abstract.c
index 31cc0a8..039a4ca 100644
--- a/Objects/abstract.c
+++ b/Objects/abstract.c
@@ -2131,7 +2131,7 @@
/* PyObject_Call() must not be called with an exception set,
because it may clear it (directly or indirectly) and so the
- caller looses its exception */
+ caller loses its exception */
assert(!PyErr_Occurred());
call = func->ob_type->tp_call;
diff --git a/Objects/setobject.c b/Objects/setobject.c
index 704d7e2..03bb230 100644
--- a/Objects/setobject.c
+++ b/Objects/setobject.c
@@ -29,7 +29,6 @@
#include "Python.h"
#include "structmember.h"
-#include "stringlib/eq.h"
/* Object used as dummy key to fill deleted entries */
static PyObject _dummy_struct;
@@ -51,19 +50,20 @@
static setentry *
set_lookkey(PySetObject *so, PyObject *key, Py_hash_t hash)
{
- setentry *table = so->table;
- setentry *freeslot = NULL;
+ setentry *table;
setentry *entry;
- size_t perturb = hash;
+ size_t perturb;
size_t mask = so->mask;
size_t i = (size_t)hash & mask; /* Unsigned for defined overflow behavior */
size_t j;
int cmp;
- entry = &table[i];
+ entry = &so->table[i];
if (entry->key == NULL)
return entry;
+ perturb = hash;
+
while (1) {
if (entry->hash == hash) {
PyObject *startkey = entry->key;
@@ -73,8 +73,9 @@
return entry;
if (PyUnicode_CheckExact(startkey)
&& PyUnicode_CheckExact(key)
- && unicode_eq(startkey, key))
+ && _PyUnicode_EQ(startkey, key))
return entry;
+ table = so->table;
Py_INCREF(startkey);
cmp = PyObject_RichCompareBool(startkey, key, Py_EQ);
Py_DECREF(startkey);
@@ -86,14 +87,12 @@
return entry;
mask = so->mask; /* help avoid a register spill */
}
- if (entry->hash == -1 && freeslot == NULL)
- freeslot = entry;
if (i + LINEAR_PROBES <= mask) {
for (j = 0 ; j < LINEAR_PROBES ; j++) {
entry++;
- if (entry->key == NULL)
- goto found_null;
+ if (entry->hash == 0 && entry->key == NULL)
+ return entry;
if (entry->hash == hash) {
PyObject *startkey = entry->key;
assert(startkey != dummy);
@@ -101,8 +100,9 @@
return entry;
if (PyUnicode_CheckExact(startkey)
&& PyUnicode_CheckExact(key)
- && unicode_eq(startkey, key))
+ && _PyUnicode_EQ(startkey, key))
return entry;
+ table = so->table;
Py_INCREF(startkey);
cmp = PyObject_RichCompareBool(startkey, key, Py_EQ);
Py_DECREF(startkey);
@@ -114,7 +114,104 @@
return entry;
mask = so->mask;
}
- if (entry->hash == -1 && freeslot == NULL)
+ }
+ }
+
+ perturb >>= PERTURB_SHIFT;
+ i = (i * 5 + 1 + perturb) & mask;
+
+ entry = &so->table[i];
+ if (entry->key == NULL)
+ return entry;
+ }
+}
+
+static int set_table_resize(PySetObject *, Py_ssize_t);
+
+static int
+set_add_entry(PySetObject *so, PyObject *key, Py_hash_t hash)
+{
+ setentry *table;
+ setentry *freeslot;
+ setentry *entry;
+ size_t perturb;
+ size_t mask;
+ size_t i; /* Unsigned for defined overflow behavior */
+ size_t j;
+ int cmp;
+
+ /* Pre-increment is necessary to prevent arbitrary code in the rich
+ comparison from deallocating the key just before the insertion. */
+ Py_INCREF(key);
+
+ restart:
+
+ mask = so->mask;
+ i = (size_t)hash & mask;
+
+ entry = &so->table[i];
+ if (entry->key == NULL)
+ goto found_unused;
+
+ freeslot = NULL;
+ perturb = hash;
+
+ while (1) {
+ if (entry->hash == hash) {
+ PyObject *startkey = entry->key;
+ /* startkey cannot be a dummy because the dummy hash field is -1 */
+ assert(startkey != dummy);
+ if (startkey == key)
+ goto found_active;
+ if (PyUnicode_CheckExact(startkey)
+ && PyUnicode_CheckExact(key)
+ && _PyUnicode_EQ(startkey, key))
+ goto found_active;
+ table = so->table;
+ Py_INCREF(startkey);
+ cmp = PyObject_RichCompareBool(startkey, key, Py_EQ);
+ Py_DECREF(startkey);
+ if (cmp > 0) /* likely */
+ goto found_active;
+ if (cmp < 0)
+ goto comparison_error;
+ /* Continuing the search from the current entry only makes
+ sense if the table and entry are unchanged; otherwise,
+ we have to restart from the beginning */
+ if (table != so->table || entry->key != startkey)
+ goto restart;
+ mask = so->mask; /* help avoid a register spill */
+ }
+ else if (entry->hash == -1 && freeslot == NULL)
+ freeslot = entry;
+
+ if (i + LINEAR_PROBES <= mask) {
+ for (j = 0 ; j < LINEAR_PROBES ; j++) {
+ entry++;
+ if (entry->hash == 0 && entry->key == NULL)
+ goto found_unused_or_dummy;
+ if (entry->hash == hash) {
+ PyObject *startkey = entry->key;
+ assert(startkey != dummy);
+ if (startkey == key)
+ goto found_active;
+ if (PyUnicode_CheckExact(startkey)
+ && PyUnicode_CheckExact(key)
+ && _PyUnicode_EQ(startkey, key))
+ goto found_active;
+ table = so->table;
+ Py_INCREF(startkey);
+ cmp = PyObject_RichCompareBool(startkey, key, Py_EQ);
+ Py_DECREF(startkey);
+ if (cmp > 0)
+ goto found_active;
+ if (cmp < 0)
+ goto comparison_error;
+ if (table != so->table || entry->key != startkey)
+ goto restart;
+ mask = so->mask;
+ }
+ else if (entry->hash == -1 && freeslot == NULL)
freeslot = entry;
}
}
@@ -122,12 +219,35 @@
perturb >>= PERTURB_SHIFT;
i = (i * 5 + 1 + perturb) & mask;
- entry = &table[i];
+ entry = &so->table[i];
if (entry->key == NULL)
- goto found_null;
+ goto found_unused_or_dummy;
}
- found_null:
- return freeslot == NULL ? entry : freeslot;
+
+ found_unused_or_dummy:
+ if (freeslot == NULL)
+ goto found_unused;
+ so->used++;
+ freeslot->key = key;
+ freeslot->hash = hash;
+ return 0;
+
+ found_unused:
+ so->fill++;
+ so->used++;
+ entry->key = key;
+ entry->hash = hash;
+ if ((size_t)so->fill*3 < mask*2)
+ return 0;
+ return set_table_resize(so, so->used);
+
+ found_active:
+ Py_DECREF(key);
+ return 0;
+
+ comparison_error:
+ Py_DECREF(key);
+ return -1;
}
/*
@@ -172,38 +292,6 @@
/* ======== End logic for probing the hash table ========================== */
/* ======================================================================== */
-
-/*
-Internal routine to insert a new key into the table.
-Used by the public insert routine.
-Eats a reference to key.
-*/
-static int
-set_insert_key(PySetObject *so, PyObject *key, Py_hash_t hash)
-{
- setentry *entry;
-
- entry = set_lookkey(so, key, hash);
- if (entry == NULL)
- return -1;
- if (entry->key == NULL) {
- /* UNUSED */
- entry->key = key;
- entry->hash = hash;
- so->fill++;
- so->used++;
- } else if (entry->key == dummy) {
- /* DUMMY */
- entry->key = key;
- entry->hash = hash;
- so->used++;
- } else {
- /* ACTIVE */
- Py_DECREF(key);
- }
- return 0;
-}
-
/*
Restructure the table by allocating a new table and reinserting all
keys again. When entries have been deleted, the new table may
@@ -220,6 +308,7 @@
setentry small_copy[PySet_MINSIZE];
assert(minused >= 0);
+ minused = (minused > 50000) ? minused * 2 : minused * 4;
/* Find the smallest table size > minused. */
/* XXX speed-up with intrinsics */
@@ -295,57 +384,30 @@
return 0;
}
-/* CAUTION: set_add_key/entry() must guarantee it won't resize the table */
-
static int
-set_add_entry(PySetObject *so, setentry *entry)
+set_contains_entry(PySetObject *so, PyObject *key, Py_hash_t hash)
{
- Py_ssize_t n_used;
- PyObject *key = entry->key;
- Py_hash_t hash = entry->hash;
+ setentry *entry;
- assert(so->fill <= so->mask); /* at least one empty slot */
- n_used = so->used;
- Py_INCREF(key);
- if (set_insert_key(so, key, hash)) {
- Py_DECREF(key);
- return -1;
- }
- if (!(so->used > n_used && so->fill*3 >= (so->mask+1)*2))
- return 0;
- return set_table_resize(so, so->used>50000 ? so->used*2 : so->used*4);
-}
-
-static int
-set_add_key(PySetObject *so, PyObject *key)
-{
- setentry entry;
- Py_hash_t hash;
-
- if (!PyUnicode_CheckExact(key) ||
- (hash = ((PyASCIIObject *) key)->hash) == -1) {
- hash = PyObject_Hash(key);
- if (hash == -1)
- return -1;
- }
- entry.key = key;
- entry.hash = hash;
- return set_add_entry(so, &entry);
+ entry = set_lookkey(so, key, hash);
+ if (entry != NULL)
+ return entry->key != NULL;
+ return -1;
}
#define DISCARD_NOTFOUND 0
#define DISCARD_FOUND 1
static int
-set_discard_entry(PySetObject *so, setentry *oldentry)
+set_discard_entry(PySetObject *so, PyObject *key, Py_hash_t hash)
{
setentry *entry;
PyObject *old_key;
- entry = set_lookkey(so, oldentry->key, oldentry->hash);
+ entry = set_lookkey(so, key, hash);
if (entry == NULL)
return -1;
- if (entry->key == NULL || entry->key == dummy)
+ if (entry->key == NULL)
return DISCARD_NOTFOUND;
old_key = entry->key;
entry->key = dummy;
@@ -356,22 +418,45 @@
}
static int
-set_discard_key(PySetObject *so, PyObject *key)
+set_add_key(PySetObject *so, PyObject *key)
{
- setentry entry;
Py_hash_t hash;
- assert (PyAnySet_Check(so));
-
if (!PyUnicode_CheckExact(key) ||
(hash = ((PyASCIIObject *) key)->hash) == -1) {
hash = PyObject_Hash(key);
if (hash == -1)
return -1;
}
- entry.key = key;
- entry.hash = hash;
- return set_discard_entry(so, &entry);
+ return set_add_entry(so, key, hash);
+}
+
+static int
+set_contains_key(PySetObject *so, PyObject *key)
+{
+ Py_hash_t hash;
+
+ if (!PyUnicode_CheckExact(key) ||
+ (hash = ((PyASCIIObject *) key)->hash) == -1) {
+ hash = PyObject_Hash(key);
+ if (hash == -1)
+ return -1;
+ }
+ return set_contains_entry(so, key, hash);
+}
+
+static int
+set_discard_key(PySetObject *so, PyObject *key)
+{
+ Py_hash_t hash;
+
+ if (!PyUnicode_CheckExact(key) ||
+ (hash = ((PyASCIIObject *) key)->hash) == -1) {
+ hash = PyObject_Hash(key);
+ if (hash == -1)
+ return -1;
+ }
+ return set_discard_entry(so, key, hash);
}
static void
@@ -452,20 +537,22 @@
{
Py_ssize_t i;
Py_ssize_t mask;
- setentry *table;
+ setentry *entry;
assert (PyAnySet_Check(so));
i = *pos_ptr;
assert(i >= 0);
- table = so->table;
mask = so->mask;
- while (i <= mask && (table[i].key == NULL || table[i].key == dummy))
+ entry = &so->table[i];
+ while (i <= mask && (entry->key == NULL || entry->key == dummy)) {
i++;
+ entry++;
+ }
*pos_ptr = i+1;
if (i > mask)
return 0;
- assert(table[i].key != NULL);
- *entry_ptr = &table[i];
+ assert(entry != NULL);
+ *entry_ptr = entry;
return 1;
}
@@ -563,8 +650,8 @@
* incrementally resizing as we insert new keys. Expect
* that there will be no (or few) overlapping keys.
*/
- if ((so->fill + other->used)*3 >= (so->mask+1)*2) {
- if (set_table_resize(so, (so->used + other->used)*2) != 0)
+ if ((so->fill + other->used)*3 >= so->mask*2) {
+ if (set_table_resize(so, so->used + other->used) != 0)
return -1;
}
so_entry = so->table;
@@ -604,46 +691,13 @@
other_entry = &other->table[i];
key = other_entry->key;
if (key != NULL && key != dummy) {
- Py_INCREF(key);
- if (set_insert_key(so, key, other_entry->hash)) {
- Py_DECREF(key);
+ if (set_add_entry(so, key, other_entry->hash))
return -1;
- }
}
}
return 0;
}
-static int
-set_contains_entry(PySetObject *so, setentry *entry)
-{
- PyObject *key;
- setentry *lu_entry;
-
- lu_entry = set_lookkey(so, entry->key, entry->hash);
- if (lu_entry == NULL)
- return -1;
- key = lu_entry->key;
- return key != NULL && key != dummy;
-}
-
-static int
-set_contains_key(PySetObject *so, PyObject *key)
-{
- setentry entry;
- Py_hash_t hash;
-
- if (!PyUnicode_CheckExact(key) ||
- (hash = ((PyASCIIObject *) key)->hash) == -1) {
- hash = PyObject_Hash(key);
- if (hash == -1)
- return -1;
- }
- entry.key = key;
- entry.hash = hash;
- return set_contains_entry(so, &entry);
-}
-
static PyObject *
set_pop(PySetObject *so)
{
@@ -685,43 +739,64 @@
return 0;
}
+/* Work to increase the bit dispersion for closely spaced hash values.
+ This is important because some use cases have many combinations of a
+ small number of elements with nearby hashes so that many distinct
+ combinations collapse to only a handful of distinct hash values. */
+
+static Py_uhash_t
+_shuffle_bits(Py_uhash_t h)
+{
+ return ((h ^ 89869747UL) ^ (h << 16)) * 3644798167UL;
+}
+
+/* Most of the constants in this hash algorithm are randomly chosen
+ large primes with "interesting bit patterns" and that passed tests
+ for good collision statistics on a variety of problematic datasets
+ including powersets and graph structures (such as David Eppstein's
+ graph recipes in Lib/test/test_set.py) */
+
static Py_hash_t
frozenset_hash(PyObject *self)
{
- /* Most of the constants in this hash algorithm are randomly choosen
- large primes with "interesting bit patterns" and that passed
- tests for good collision statistics on a variety of problematic
- datasets such as:
-
- ps = []
- for r in range(21):
- ps += itertools.combinations(range(20), r)
- num_distinct_hashes = len({hash(frozenset(s)) for s in ps})
-
- */
PySetObject *so = (PySetObject *)self;
- Py_uhash_t h, hash = 1927868237UL;
+ Py_uhash_t hash = 0;
setentry *entry;
- Py_ssize_t pos = 0;
if (so->hash != -1)
return so->hash;
- hash *= (Py_uhash_t)PySet_GET_SIZE(self) + 1;
- while (set_next(so, &pos, &entry)) {
- /* Work to increase the bit dispersion for closely spaced hash
- values. This is important because some use cases have many
- combinations of a small number of elements with nearby
- hashes so that many distinct combinations collapse to only
- a handful of distinct hash values. */
- h = entry->hash;
- hash ^= ((h ^ 89869747UL) ^ (h << 16)) * 3644798167UL;
- }
- /* Make the final result spread-out in a different pattern
- than the algorithm for tuples or other python objects. */
+ /* Xor-in shuffled bits from every entry's hash field because xor is
+ commutative and a frozenset hash should be independent of order.
+
+ For speed, include null entries and dummy entries and then
+ subtract out their effect afterwards so that the final hash
+ depends only on active entries. This allows the code to be
+ vectorized by the compiler and it saves the unpredictable
+ branches that would arise when trying to exclude null and dummy
+ entries on every iteration. */
+
+ for (entry = so->table; entry <= &so->table[so->mask]; entry++)
+ hash ^= _shuffle_bits(entry->hash);
+
+ /* Remove the effect of an odd number of NULL entries */
+ if ((so->mask + 1 - so->fill) & 1)
+ hash ^= _shuffle_bits(0);
+
+ /* Remove the effect of an odd number of dummy entries */
+ if ((so->fill - so->used) & 1)
+ hash ^= _shuffle_bits(-1);
+
+ /* Factor in the number of active entries */
+ hash ^= ((Py_uhash_t)PySet_GET_SIZE(self) + 1) * 1927868237UL;
+
+ /* Disperse patterns arising in nested frozensets */
hash = hash * 69069U + 907133923UL;
+
+ /* -1 is reserved as an error code */
if (hash == (Py_uhash_t)-1)
hash = 590923713UL;
+
so->hash = hash;
return hash;
}
@@ -868,7 +943,7 @@
PyObject_GenericGetAttr, /* tp_getattro */
0, /* tp_setattro */
0, /* tp_as_buffer */
- Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC,/* tp_flags */
+ Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC, /* tp_flags */
0, /* tp_doc */
(traverseproc)setiter_traverse, /* tp_traverse */
0, /* tp_clear */
@@ -913,18 +988,14 @@
* incrementally resizing as we insert new keys. Expect
* that there will be no (or few) overlapping keys.
*/
- if (dictsize == -1)
+ if (dictsize < 0)
return -1;
- if ((so->fill + dictsize)*3 >= (so->mask+1)*2) {
- if (set_table_resize(so, (so->used + dictsize)*2) != 0)
+ if ((so->fill + dictsize)*3 >= so->mask*2) {
+ if (set_table_resize(so, so->used + dictsize) != 0)
return -1;
}
while (_PyDict_Next(other, &pos, &key, &value, &hash)) {
- setentry an_entry;
-
- an_entry.hash = hash;
- an_entry.key = key;
- if (set_add_entry(so, &an_entry))
+ if (set_add_entry(so, key, hash))
return -1;
}
return 0;
@@ -1204,6 +1275,8 @@
{
PySetObject *result;
PyObject *key, *it, *tmp;
+ Py_hash_t hash;
+ int rv;
if ((PyObject *)so == other)
return set_copy(so);
@@ -1223,13 +1296,15 @@
}
while (set_next((PySetObject *)other, &pos, &entry)) {
- int rv = set_contains_entry(so, entry);
- if (rv == -1) {
+ key = entry->key;
+ hash = entry->hash;
+ rv = set_contains_entry(so, key, hash);
+ if (rv < 0) {
Py_DECREF(result);
return NULL;
}
if (rv) {
- if (set_add_entry(result, entry)) {
+ if (set_add_entry(result, key, hash)) {
Py_DECREF(result);
return NULL;
}
@@ -1245,32 +1320,15 @@
}
while ((key = PyIter_Next(it)) != NULL) {
- int rv;
- setentry entry;
- Py_hash_t hash = PyObject_Hash(key);
-
- if (hash == -1) {
- Py_DECREF(it);
- Py_DECREF(result);
- Py_DECREF(key);
- return NULL;
- }
- entry.hash = hash;
- entry.key = key;
- rv = set_contains_entry(so, &entry);
- if (rv == -1) {
- Py_DECREF(it);
- Py_DECREF(result);
- Py_DECREF(key);
- return NULL;
- }
+ hash = PyObject_Hash(key);
+ if (hash == -1)
+ goto error;
+ rv = set_contains_entry(so, key, hash);
+ if (rv < 0)
+ goto error;
if (rv) {
- if (set_add_entry(result, &entry)) {
- Py_DECREF(it);
- Py_DECREF(result);
- Py_DECREF(key);
- return NULL;
- }
+ if (set_add_entry(result, key, hash))
+ goto error;
}
Py_DECREF(key);
}
@@ -1280,6 +1338,11 @@
return NULL;
}
return (PyObject *)result;
+ error:
+ Py_DECREF(it);
+ Py_DECREF(result);
+ Py_DECREF(key);
+ return NULL;
}
static PyObject *
@@ -1366,6 +1429,7 @@
set_isdisjoint(PySetObject *so, PyObject *other)
{
PyObject *key, *it, *tmp;
+ int rv;
if ((PyObject *)so == other) {
if (PySet_GET_SIZE(so) == 0)
@@ -1384,8 +1448,8 @@
other = tmp;
}
while (set_next((PySetObject *)other, &pos, &entry)) {
- int rv = set_contains_entry(so, entry);
- if (rv == -1)
+ rv = set_contains_entry(so, entry->key, entry->hash);
+ if (rv < 0)
return NULL;
if (rv)
Py_RETURN_FALSE;
@@ -1398,8 +1462,6 @@
return NULL;
while ((key = PyIter_Next(it)) != NULL) {
- int rv;
- setentry entry;
Py_hash_t hash = PyObject_Hash(key);
if (hash == -1) {
@@ -1407,11 +1469,9 @@
Py_DECREF(it);
return NULL;
}
- entry.hash = hash;
- entry.key = key;
- rv = set_contains_entry(so, &entry);
+ rv = set_contains_entry(so, key, hash);
Py_DECREF(key);
- if (rv == -1) {
+ if (rv < 0) {
Py_DECREF(it);
return NULL;
}
@@ -1440,7 +1500,7 @@
Py_ssize_t pos = 0;
while (set_next((PySetObject *)other, &pos, &entry))
- if (set_discard_entry(so, entry) == -1)
+ if (set_discard_entry(so, entry->key, entry->hash) < 0)
return -1;
} else {
PyObject *key, *it;
@@ -1449,7 +1509,7 @@
return -1;
while ((key = PyIter_Next(it)) != NULL) {
- if (set_discard_key(so, key) == -1) {
+ if (set_discard_key(so, key) < 0) {
Py_DECREF(it);
Py_DECREF(key);
return -1;
@@ -1460,10 +1520,10 @@
if (PyErr_Occurred())
return -1;
}
- /* If more than 1/5 are dummies, then resize them away. */
- if ((so->fill - so->used) * 5 < so->mask)
+ /* If more than 1/4th are dummies, then resize them away. */
+ if ((size_t)(so->fill - so->used) <= (size_t)so->mask / 4)
return 0;
- return set_table_resize(so, so->used>50000 ? so->used*2 : so->used*4);
+ return set_table_resize(so, so->used);
}
static PyObject *
@@ -1490,7 +1550,7 @@
result = set_copy(so);
if (result == NULL)
return NULL;
- if (set_difference_update_internal((PySetObject *) result, other) != -1)
+ if (set_difference_update_internal((PySetObject *) result, other) == 0)
return result;
Py_DECREF(result);
return NULL;
@@ -1500,8 +1560,11 @@
set_difference(PySetObject *so, PyObject *other)
{
PyObject *result;
+ PyObject *key;
+ Py_hash_t hash;
setentry *entry;
Py_ssize_t pos = 0;
+ int rv;
if (!PyAnySet_Check(other) && !PyDict_CheckExact(other)) {
return set_copy_and_difference(so, other);
@@ -1519,17 +1582,15 @@
if (PyDict_CheckExact(other)) {
while (set_next(so, &pos, &entry)) {
- setentry entrycopy;
- int rv;
- entrycopy.hash = entry->hash;
- entrycopy.key = entry->key;
- rv = _PyDict_Contains(other, entry->key, entry->hash);
+ key = entry->key;
+ hash = entry->hash;
+ rv = _PyDict_Contains(other, key, hash);
if (rv < 0) {
Py_DECREF(result);
return NULL;
}
if (!rv) {
- if (set_add_entry((PySetObject *)result, &entrycopy)) {
+ if (set_add_entry((PySetObject *)result, key, hash)) {
Py_DECREF(result);
return NULL;
}
@@ -1540,13 +1601,15 @@
/* Iterate over so, checking for common elements in other. */
while (set_next(so, &pos, &entry)) {
- int rv = set_contains_entry((PySetObject *)other, entry);
- if (rv == -1) {
+ key = entry->key;
+ hash = entry->hash;
+ rv = set_contains_entry((PySetObject *)other, key, hash);
+ if (rv < 0) {
Py_DECREF(result);
return NULL;
}
if (!rv) {
- if (set_add_entry((PySetObject *)result, entry)) {
+ if (set_add_entry((PySetObject *)result, key, hash)) {
Py_DECREF(result);
return NULL;
}
@@ -1608,29 +1671,24 @@
PySetObject *otherset;
PyObject *key;
Py_ssize_t pos = 0;
+ Py_hash_t hash;
setentry *entry;
+ int rv;
if ((PyObject *)so == other)
return set_clear(so);
if (PyDict_CheckExact(other)) {
PyObject *value;
- int rv;
- Py_hash_t hash;
while (_PyDict_Next(other, &pos, &key, &value, &hash)) {
- setentry an_entry;
-
Py_INCREF(key);
- an_entry.hash = hash;
- an_entry.key = key;
-
- rv = set_discard_entry(so, &an_entry);
- if (rv == -1) {
+ rv = set_discard_entry(so, key, hash);
+ if (rv < 0) {
Py_DECREF(key);
return NULL;
}
if (rv == DISCARD_NOTFOUND) {
- if (set_add_entry(so, &an_entry)) {
+ if (set_add_entry(so, key, hash)) {
Py_DECREF(key);
return NULL;
}
@@ -1650,13 +1708,15 @@
}
while (set_next(otherset, &pos, &entry)) {
- int rv = set_discard_entry(so, entry);
- if (rv == -1) {
+ key = entry->key;
+ hash = entry->hash;
+ rv = set_discard_entry(so, key, hash);
+ if (rv < 0) {
Py_DECREF(otherset);
return NULL;
}
if (rv == DISCARD_NOTFOUND) {
- if (set_add_entry(so, entry)) {
+ if (set_add_entry(so, key, hash)) {
Py_DECREF(otherset);
return NULL;
}
@@ -1718,6 +1778,7 @@
{
setentry *entry;
Py_ssize_t pos = 0;
+ int rv;
if (!PyAnySet_Check(other)) {
PyObject *tmp, *result;
@@ -1732,8 +1793,8 @@
Py_RETURN_FALSE;
while (set_next(so, &pos, &entry)) {
- int rv = set_contains_entry((PySetObject *)other, entry);
- if (rv == -1)
+ rv = set_contains_entry((PySetObject *)other, entry->key, entry->hash);
+ if (rv < 0)
return NULL;
if (!rv)
Py_RETURN_FALSE;
@@ -1824,7 +1885,7 @@
int rv;
rv = set_contains_key(so, key);
- if (rv == -1) {
+ if (rv < 0) {
if (!PySet_Check(key) || !PyErr_ExceptionMatches(PyExc_TypeError))
return -1;
PyErr_Clear();
@@ -1843,7 +1904,7 @@
long result;
result = set_contains(so, key);
- if (result == -1)
+ if (result < 0)
return NULL;
return PyBool_FromLong(result);
}
@@ -1857,7 +1918,7 @@
int rv;
rv = set_discard_key(so, key);
- if (rv == -1) {
+ if (rv < 0) {
if (!PySet_Check(key) || !PyErr_ExceptionMatches(PyExc_TypeError))
return NULL;
PyErr_Clear();
@@ -1866,7 +1927,7 @@
return NULL;
rv = set_discard_key(so, tmpkey);
Py_DECREF(tmpkey);
- if (rv == -1)
+ if (rv < 0)
return NULL;
}
@@ -1889,7 +1950,7 @@
int rv;
rv = set_discard_key(so, key);
- if (rv == -1) {
+ if (rv < 0) {
if (!PySet_Check(key) || !PyErr_ExceptionMatches(PyExc_TypeError))
return NULL;
PyErr_Clear();
@@ -1898,7 +1959,7 @@
return NULL;
rv = set_discard_key(so, tmpkey);
Py_DECREF(tmpkey);
- if (rv == -1)
+ if (rv < 0)
return NULL;
}
Py_RETURN_NONE;
@@ -2125,7 +2186,7 @@
copy_doc},
{"difference", (PyCFunction)set_difference_multi, METH_VARARGS,
difference_doc},
- {"intersection",(PyCFunction)set_intersection_multi, METH_VARARGS,
+ {"intersection", (PyCFunction)set_intersection_multi, METH_VARARGS,
intersection_doc},
{"isdisjoint", (PyCFunction)set_isdisjoint, METH_O,
isdisjoint_doc},
@@ -2196,7 +2257,7 @@
(traverseproc)set_traverse, /* tp_traverse */
(inquiry)set_clear_internal, /* tp_clear */
(richcmpfunc)set_richcompare, /* tp_richcompare */
- offsetof(PySetObject, weakreflist), /* tp_weaklistoffset */
+ offsetof(PySetObject, weakreflist), /* tp_weaklistoffset */
(getiterfunc)set_iter, /* tp_iter */
0, /* tp_iternext */
frozenset_methods, /* tp_methods */
diff --git a/Objects/stringlib/unicode_format.h b/Objects/stringlib/unicode_format.h
index aec221a..d72e47d 100644
--- a/Objects/stringlib/unicode_format.h
+++ b/Objects/stringlib/unicode_format.h
@@ -67,7 +67,7 @@
return PyUnicode_Substring(str->str, str->start, str->end);
}
-/* return a new string. if str->str is NULL, return None */
+/* return a new string. if str->str is NULL, return a new empty string */
Py_LOCAL_INLINE(PyObject *)
SubString_new_object_or_empty(SubString *str)
{
diff --git a/Objects/structseq.c b/Objects/structseq.c
index 664344b..7209738 100644
--- a/Objects/structseq.c
+++ b/Objects/structseq.c
@@ -16,14 +16,14 @@
_Py_IDENTIFIER(n_unnamed_fields);
#define VISIBLE_SIZE(op) Py_SIZE(op)
-#define VISIBLE_SIZE_TP(tp) PyLong_AsLong( \
+#define VISIBLE_SIZE_TP(tp) PyLong_AsSsize_t( \
_PyDict_GetItemId((tp)->tp_dict, &PyId_n_sequence_fields))
-#define REAL_SIZE_TP(tp) PyLong_AsLong( \
+#define REAL_SIZE_TP(tp) PyLong_AsSsize_t( \
_PyDict_GetItemId((tp)->tp_dict, &PyId_n_fields))
#define REAL_SIZE(op) REAL_SIZE_TP(Py_TYPE(op))
-#define UNNAMED_FIELDS_TP(tp) PyLong_AsLong( \
+#define UNNAMED_FIELDS_TP(tp) PyLong_AsSsize_t( \
_PyDict_GetItemId((tp)->tp_dict, &PyId_n_unnamed_fields))
#define UNNAMED_FIELDS(op) UNNAMED_FIELDS_TP(Py_TYPE(op))
@@ -164,7 +164,8 @@
#define TYPE_MAXSIZE 100
PyTypeObject *typ = Py_TYPE(obj);
- int i, removelast = 0;
+ Py_ssize_t i;
+ int removelast = 0;
Py_ssize_t len;
char buf[REPR_BUFFER_SIZE];
char *endofbuf, *pbuf = buf;
@@ -236,8 +237,7 @@
PyObject* tup = NULL;
PyObject* dict = NULL;
PyObject* result;
- Py_ssize_t n_fields, n_visible_fields, n_unnamed_fields;
- int i;
+ Py_ssize_t n_fields, n_visible_fields, n_unnamed_fields, i;
n_fields = REAL_SIZE(self);
n_visible_fields = VISIBLE_SIZE(self);
@@ -325,7 +325,7 @@
{
PyObject *dict;
PyMemberDef* members;
- int n_members, n_unnamed_members, i, k;
+ Py_ssize_t n_members, n_unnamed_members, i, k;
PyObject *v;
#ifdef Py_TRACE_REFS
@@ -373,9 +373,9 @@
Py_INCREF(type);
dict = type->tp_dict;
-#define SET_DICT_FROM_INT(key, value) \
+#define SET_DICT_FROM_SIZE(key, value) \
do { \
- v = PyLong_FromLong((long) value); \
+ v = PyLong_FromSsize_t(value); \
if (v == NULL) \
return -1; \
if (PyDict_SetItemString(dict, key, v) < 0) { \
@@ -385,9 +385,9 @@
Py_DECREF(v); \
} while (0)
- SET_DICT_FROM_INT(visible_length_key, desc->n_in_sequence);
- SET_DICT_FROM_INT(real_length_key, n_members);
- SET_DICT_FROM_INT(unnamed_fields_key, n_unnamed_members);
+ SET_DICT_FROM_SIZE(visible_length_key, desc->n_in_sequence);
+ SET_DICT_FROM_SIZE(real_length_key, n_members);
+ SET_DICT_FROM_SIZE(unnamed_fields_key, n_unnamed_members);
return 0;
}
diff --git a/Objects/typeobject.c b/Objects/typeobject.c
index bb83530..a311e99 100644
--- a/Objects/typeobject.c
+++ b/Objects/typeobject.c
@@ -906,25 +906,33 @@
#endif
obj = type->tp_new(type, args, kwds);
- if (obj != NULL) {
- /* Ugly exception: when the call was type(something),
- don't call tp_init on the result. */
- if (type == &PyType_Type &&
- PyTuple_Check(args) && PyTuple_GET_SIZE(args) == 1 &&
- (kwds == NULL ||
- (PyDict_Check(kwds) && PyDict_Size(kwds) == 0)))
- return obj;
- /* If the returned object is not an instance of type,
- it won't be initialized. */
- if (!PyType_IsSubtype(Py_TYPE(obj), type))
- return obj;
- type = Py_TYPE(obj);
- if (type->tp_init != NULL) {
- int res = type->tp_init(obj, args, kwds);
- if (res < 0) {
- Py_DECREF(obj);
- obj = NULL;
- }
+ obj = _Py_CheckFunctionResult((PyObject*)type, obj, NULL);
+ if (obj == NULL)
+ return NULL;
+
+ /* Ugly exception: when the call was type(something),
+ don't call tp_init on the result. */
+ if (type == &PyType_Type &&
+ PyTuple_Check(args) && PyTuple_GET_SIZE(args) == 1 &&
+ (kwds == NULL ||
+ (PyDict_Check(kwds) && PyDict_Size(kwds) == 0)))
+ return obj;
+
+ /* If the returned object is not an instance of type,
+ it won't be initialized. */
+ if (!PyType_IsSubtype(Py_TYPE(obj), type))
+ return obj;
+
+ type = Py_TYPE(obj);
+ if (type->tp_init != NULL) {
+ int res = type->tp_init(obj, args, kwds);
+ if (res < 0) {
+ assert(PyErr_Occurred());
+ Py_DECREF(obj);
+ obj = NULL;
+ }
+ else {
+ assert(!PyErr_Occurred());
}
}
return obj;
diff --git a/Objects/unicodeobject.c b/Objects/unicodeobject.c
index 9223c99..0709789 100644
--- a/Objects/unicodeobject.c
+++ b/Objects/unicodeobject.c
@@ -42,6 +42,7 @@
#include "Python.h"
#include "ucnhash.h"
#include "bytes_methods.h"
+#include "stringlib/eq.h"
#ifdef MS_WINDOWS
#include <windows.h>
@@ -10887,6 +10888,12 @@
}
int
+_PyUnicode_EQ(PyObject *aa, PyObject *bb)
+{
+ return unicode_eq(aa, bb);
+}
+
+int
PyUnicode_Contains(PyObject *container, PyObject *element)
{
PyObject *str, *sub;
diff --git a/PC/pyconfig.h b/PC/pyconfig.h
index d44173a..8861148 100644
--- a/PC/pyconfig.h
+++ b/PC/pyconfig.h
@@ -312,11 +312,11 @@
their Makefile (other compilers are generally
taken care of by distutils.) */
# if defined(_DEBUG)
-# pragma comment(lib,"python35_d.lib")
+# pragma comment(lib,"python36_d.lib")
# elif defined(Py_LIMITED_API)
# pragma comment(lib,"python3.lib")
# else
-# pragma comment(lib,"python35.lib")
+# pragma comment(lib,"python36.lib")
# endif /* _DEBUG */
# endif /* _MSC_VER */
# endif /* Py_BUILD_CORE */
diff --git a/PC/python3.def b/PC/python3.def
index 88c0742..e146e8f 100644
--- a/PC/python3.def
+++ b/PC/python3.def
@@ -2,712 +2,712 @@
; It is used when building python3dll.vcxproj
LIBRARY "python3"
EXPORTS
- PyArg_Parse=python35.PyArg_Parse
- PyArg_ParseTuple=python35.PyArg_ParseTuple
- PyArg_ParseTupleAndKeywords=python35.PyArg_ParseTupleAndKeywords
- PyArg_UnpackTuple=python35.PyArg_UnpackTuple
- PyArg_VaParse=python35.PyArg_VaParse
- PyArg_VaParseTupleAndKeywords=python35.PyArg_VaParseTupleAndKeywords
- PyArg_ValidateKeywordArguments=python35.PyArg_ValidateKeywordArguments
- PyBaseObject_Type=python35.PyBaseObject_Type DATA
- PyBool_FromLong=python35.PyBool_FromLong
- PyBool_Type=python35.PyBool_Type DATA
- PyByteArrayIter_Type=python35.PyByteArrayIter_Type DATA
- PyByteArray_AsString=python35.PyByteArray_AsString
- PyByteArray_Concat=python35.PyByteArray_Concat
- PyByteArray_FromObject=python35.PyByteArray_FromObject
- PyByteArray_FromStringAndSize=python35.PyByteArray_FromStringAndSize
- PyByteArray_Resize=python35.PyByteArray_Resize
- PyByteArray_Size=python35.PyByteArray_Size
- PyByteArray_Type=python35.PyByteArray_Type DATA
- PyBytesIter_Type=python35.PyBytesIter_Type DATA
- PyBytes_AsString=python35.PyBytes_AsString
- PyBytes_AsStringAndSize=python35.PyBytes_AsStringAndSize
- PyBytes_Concat=python35.PyBytes_Concat
- PyBytes_ConcatAndDel=python35.PyBytes_ConcatAndDel
- PyBytes_DecodeEscape=python35.PyBytes_DecodeEscape
- PyBytes_FromFormat=python35.PyBytes_FromFormat
- PyBytes_FromFormatV=python35.PyBytes_FromFormatV
- PyBytes_FromObject=python35.PyBytes_FromObject
- PyBytes_FromString=python35.PyBytes_FromString
- PyBytes_FromStringAndSize=python35.PyBytes_FromStringAndSize
- PyBytes_Repr=python35.PyBytes_Repr
- PyBytes_Size=python35.PyBytes_Size
- PyBytes_Type=python35.PyBytes_Type DATA
- PyCFunction_Call=python35.PyCFunction_Call
- PyCFunction_ClearFreeList=python35.PyCFunction_ClearFreeList
- PyCFunction_GetFlags=python35.PyCFunction_GetFlags
- PyCFunction_GetFunction=python35.PyCFunction_GetFunction
- PyCFunction_GetSelf=python35.PyCFunction_GetSelf
- PyCFunction_New=python35.PyCFunction_New
- PyCFunction_NewEx=python35.PyCFunction_NewEx
- PyCFunction_Type=python35.PyCFunction_Type DATA
- PyCallIter_New=python35.PyCallIter_New
- PyCallIter_Type=python35.PyCallIter_Type DATA
- PyCallable_Check=python35.PyCallable_Check
- PyCapsule_GetContext=python35.PyCapsule_GetContext
- PyCapsule_GetDestructor=python35.PyCapsule_GetDestructor
- PyCapsule_GetName=python35.PyCapsule_GetName
- PyCapsule_GetPointer=python35.PyCapsule_GetPointer
- PyCapsule_Import=python35.PyCapsule_Import
- PyCapsule_IsValid=python35.PyCapsule_IsValid
- PyCapsule_New=python35.PyCapsule_New
- PyCapsule_SetContext=python35.PyCapsule_SetContext
- PyCapsule_SetDestructor=python35.PyCapsule_SetDestructor
- PyCapsule_SetName=python35.PyCapsule_SetName
- PyCapsule_SetPointer=python35.PyCapsule_SetPointer
- PyCapsule_Type=python35.PyCapsule_Type DATA
- PyClassMethodDescr_Type=python35.PyClassMethodDescr_Type DATA
- PyCodec_BackslashReplaceErrors=python35.PyCodec_BackslashReplaceErrors
- PyCodec_Decode=python35.PyCodec_Decode
- PyCodec_Decoder=python35.PyCodec_Decoder
- PyCodec_Encode=python35.PyCodec_Encode
- PyCodec_Encoder=python35.PyCodec_Encoder
- PyCodec_IgnoreErrors=python35.PyCodec_IgnoreErrors
- PyCodec_IncrementalDecoder=python35.PyCodec_IncrementalDecoder
- PyCodec_IncrementalEncoder=python35.PyCodec_IncrementalEncoder
- PyCodec_KnownEncoding=python35.PyCodec_KnownEncoding
- PyCodec_LookupError=python35.PyCodec_LookupError
- PyCodec_Register=python35.PyCodec_Register
- PyCodec_RegisterError=python35.PyCodec_RegisterError
- PyCodec_ReplaceErrors=python35.PyCodec_ReplaceErrors
- PyCodec_StreamReader=python35.PyCodec_StreamReader
- PyCodec_StreamWriter=python35.PyCodec_StreamWriter
- PyCodec_StrictErrors=python35.PyCodec_StrictErrors
- PyCodec_XMLCharRefReplaceErrors=python35.PyCodec_XMLCharRefReplaceErrors
- PyComplex_FromDoubles=python35.PyComplex_FromDoubles
- PyComplex_ImagAsDouble=python35.PyComplex_ImagAsDouble
- PyComplex_RealAsDouble=python35.PyComplex_RealAsDouble
- PyComplex_Type=python35.PyComplex_Type DATA
- PyDescr_NewClassMethod=python35.PyDescr_NewClassMethod
- PyDescr_NewGetSet=python35.PyDescr_NewGetSet
- PyDescr_NewMember=python35.PyDescr_NewMember
- PyDescr_NewMethod=python35.PyDescr_NewMethod
- PyDictItems_Type=python35.PyDictItems_Type DATA
- PyDictIterItem_Type=python35.PyDictIterItem_Type DATA
- PyDictIterKey_Type=python35.PyDictIterKey_Type DATA
- PyDictIterValue_Type=python35.PyDictIterValue_Type DATA
- PyDictKeys_Type=python35.PyDictKeys_Type DATA
- PyDictProxy_New=python35.PyDictProxy_New
- PyDictProxy_Type=python35.PyDictProxy_Type DATA
- PyDictValues_Type=python35.PyDictValues_Type DATA
- PyDict_Clear=python35.PyDict_Clear
- PyDict_Contains=python35.PyDict_Contains
- PyDict_Copy=python35.PyDict_Copy
- PyDict_DelItem=python35.PyDict_DelItem
- PyDict_DelItemString=python35.PyDict_DelItemString
- PyDict_GetItem=python35.PyDict_GetItem
- PyDict_GetItemString=python35.PyDict_GetItemString
- PyDict_GetItemWithError=python35.PyDict_GetItemWithError
- PyDict_Items=python35.PyDict_Items
- PyDict_Keys=python35.PyDict_Keys
- PyDict_Merge=python35.PyDict_Merge
- PyDict_MergeFromSeq2=python35.PyDict_MergeFromSeq2
- PyDict_New=python35.PyDict_New
- PyDict_Next=python35.PyDict_Next
- PyDict_SetItem=python35.PyDict_SetItem
- PyDict_SetItemString=python35.PyDict_SetItemString
- PyDict_Size=python35.PyDict_Size
- PyDict_Type=python35.PyDict_Type DATA
- PyDict_Update=python35.PyDict_Update
- PyDict_Values=python35.PyDict_Values
- PyEllipsis_Type=python35.PyEllipsis_Type DATA
- PyEnum_Type=python35.PyEnum_Type DATA
- PyErr_BadArgument=python35.PyErr_BadArgument
- PyErr_BadInternalCall=python35.PyErr_BadInternalCall
- PyErr_CheckSignals=python35.PyErr_CheckSignals
- PyErr_Clear=python35.PyErr_Clear
- PyErr_Display=python35.PyErr_Display
- PyErr_ExceptionMatches=python35.PyErr_ExceptionMatches
- PyErr_Fetch=python35.PyErr_Fetch
- PyErr_Format=python35.PyErr_Format
- PyErr_FormatV=python35.PyErr_FormatV
- PyErr_GivenExceptionMatches=python35.PyErr_GivenExceptionMatches
- PyErr_NewException=python35.PyErr_NewException
- PyErr_NewExceptionWithDoc=python35.PyErr_NewExceptionWithDoc
- PyErr_NoMemory=python35.PyErr_NoMemory
- PyErr_NormalizeException=python35.PyErr_NormalizeException
- PyErr_Occurred=python35.PyErr_Occurred
- PyErr_Print=python35.PyErr_Print
- PyErr_PrintEx=python35.PyErr_PrintEx
- PyErr_ProgramText=python35.PyErr_ProgramText
- PyErr_Restore=python35.PyErr_Restore
- PyErr_SetFromErrno=python35.PyErr_SetFromErrno
- PyErr_SetFromErrnoWithFilename=python35.PyErr_SetFromErrnoWithFilename
- PyErr_SetFromErrnoWithFilenameObject=python35.PyErr_SetFromErrnoWithFilenameObject
- PyErr_SetInterrupt=python35.PyErr_SetInterrupt
- PyErr_SetNone=python35.PyErr_SetNone
- PyErr_SetObject=python35.PyErr_SetObject
- PyErr_SetString=python35.PyErr_SetString
- PyErr_SyntaxLocation=python35.PyErr_SyntaxLocation
- PyErr_WarnEx=python35.PyErr_WarnEx
- PyErr_WarnExplicit=python35.PyErr_WarnExplicit
- PyErr_WarnFormat=python35.PyErr_WarnFormat
- PyErr_WriteUnraisable=python35.PyErr_WriteUnraisable
- PyEval_AcquireLock=python35.PyEval_AcquireLock
- PyEval_AcquireThread=python35.PyEval_AcquireThread
- PyEval_CallFunction=python35.PyEval_CallFunction
- PyEval_CallMethod=python35.PyEval_CallMethod
- PyEval_CallObjectWithKeywords=python35.PyEval_CallObjectWithKeywords
- PyEval_EvalCode=python35.PyEval_EvalCode
- PyEval_EvalCodeEx=python35.PyEval_EvalCodeEx
- PyEval_EvalFrame=python35.PyEval_EvalFrame
- PyEval_EvalFrameEx=python35.PyEval_EvalFrameEx
- PyEval_GetBuiltins=python35.PyEval_GetBuiltins
- PyEval_GetCallStats=python35.PyEval_GetCallStats
- PyEval_GetFrame=python35.PyEval_GetFrame
- PyEval_GetFuncDesc=python35.PyEval_GetFuncDesc
- PyEval_GetFuncName=python35.PyEval_GetFuncName
- PyEval_GetGlobals=python35.PyEval_GetGlobals
- PyEval_GetLocals=python35.PyEval_GetLocals
- PyEval_InitThreads=python35.PyEval_InitThreads
- PyEval_ReInitThreads=python35.PyEval_ReInitThreads
- PyEval_ReleaseLock=python35.PyEval_ReleaseLock
- PyEval_ReleaseThread=python35.PyEval_ReleaseThread
- PyEval_RestoreThread=python35.PyEval_RestoreThread
- PyEval_SaveThread=python35.PyEval_SaveThread
- PyEval_ThreadsInitialized=python35.PyEval_ThreadsInitialized
- PyExc_ArithmeticError=python35.PyExc_ArithmeticError DATA
- PyExc_AssertionError=python35.PyExc_AssertionError DATA
- PyExc_AttributeError=python35.PyExc_AttributeError DATA
- PyExc_BaseException=python35.PyExc_BaseException DATA
- PyExc_BufferError=python35.PyExc_BufferError DATA
- PyExc_BytesWarning=python35.PyExc_BytesWarning DATA
- PyExc_DeprecationWarning=python35.PyExc_DeprecationWarning DATA
- PyExc_EOFError=python35.PyExc_EOFError DATA
- PyExc_EnvironmentError=python35.PyExc_EnvironmentError DATA
- PyExc_Exception=python35.PyExc_Exception DATA
- PyExc_FloatingPointError=python35.PyExc_FloatingPointError DATA
- PyExc_FutureWarning=python35.PyExc_FutureWarning DATA
- PyExc_GeneratorExit=python35.PyExc_GeneratorExit DATA
- PyExc_IOError=python35.PyExc_IOError DATA
- PyExc_ImportError=python35.PyExc_ImportError DATA
- PyExc_ImportWarning=python35.PyExc_ImportWarning DATA
- PyExc_IndentationError=python35.PyExc_IndentationError DATA
- PyExc_IndexError=python35.PyExc_IndexError DATA
- PyExc_KeyError=python35.PyExc_KeyError DATA
- PyExc_KeyboardInterrupt=python35.PyExc_KeyboardInterrupt DATA
- PyExc_LookupError=python35.PyExc_LookupError DATA
- PyExc_MemoryError=python35.PyExc_MemoryError DATA
- PyExc_MemoryErrorInst=python35.PyExc_MemoryErrorInst DATA
- PyExc_NameError=python35.PyExc_NameError DATA
- PyExc_NotImplementedError=python35.PyExc_NotImplementedError DATA
- PyExc_OSError=python35.PyExc_OSError DATA
- PyExc_OverflowError=python35.PyExc_OverflowError DATA
- PyExc_PendingDeprecationWarning=python35.PyExc_PendingDeprecationWarning DATA
- PyExc_RecursionErrorInst=python35.PyExc_RecursionErrorInst DATA
- PyExc_ReferenceError=python35.PyExc_ReferenceError DATA
- PyExc_RuntimeError=python35.PyExc_RuntimeError DATA
- PyExc_RuntimeWarning=python35.PyExc_RuntimeWarning DATA
- PyExc_StopIteration=python35.PyExc_StopIteration DATA
- PyExc_SyntaxError=python35.PyExc_SyntaxError DATA
- PyExc_SyntaxWarning=python35.PyExc_SyntaxWarning DATA
- PyExc_SystemError=python35.PyExc_SystemError DATA
- PyExc_SystemExit=python35.PyExc_SystemExit DATA
- PyExc_TabError=python35.PyExc_TabError DATA
- PyExc_TypeError=python35.PyExc_TypeError DATA
- PyExc_UnboundLocalError=python35.PyExc_UnboundLocalError DATA
- PyExc_UnicodeDecodeError=python35.PyExc_UnicodeDecodeError DATA
- PyExc_UnicodeEncodeError=python35.PyExc_UnicodeEncodeError DATA
- PyExc_UnicodeError=python35.PyExc_UnicodeError DATA
- PyExc_UnicodeTranslateError=python35.PyExc_UnicodeTranslateError DATA
- PyExc_UnicodeWarning=python35.PyExc_UnicodeWarning DATA
- PyExc_UserWarning=python35.PyExc_UserWarning DATA
- PyExc_ValueError=python35.PyExc_ValueError DATA
- PyExc_Warning=python35.PyExc_Warning DATA
- PyExc_ZeroDivisionError=python35.PyExc_ZeroDivisionError DATA
- PyException_GetCause=python35.PyException_GetCause
- PyException_GetContext=python35.PyException_GetContext
- PyException_GetTraceback=python35.PyException_GetTraceback
- PyException_SetCause=python35.PyException_SetCause
- PyException_SetContext=python35.PyException_SetContext
- PyException_SetTraceback=python35.PyException_SetTraceback
- PyFile_FromFd=python35.PyFile_FromFd
- PyFile_GetLine=python35.PyFile_GetLine
- PyFile_WriteObject=python35.PyFile_WriteObject
- PyFile_WriteString=python35.PyFile_WriteString
- PyFilter_Type=python35.PyFilter_Type DATA
- PyFloat_AsDouble=python35.PyFloat_AsDouble
- PyFloat_FromDouble=python35.PyFloat_FromDouble
- PyFloat_FromString=python35.PyFloat_FromString
- PyFloat_GetInfo=python35.PyFloat_GetInfo
- PyFloat_GetMax=python35.PyFloat_GetMax
- PyFloat_GetMin=python35.PyFloat_GetMin
- PyFloat_Type=python35.PyFloat_Type DATA
- PyFrozenSet_New=python35.PyFrozenSet_New
- PyFrozenSet_Type=python35.PyFrozenSet_Type DATA
- PyGC_Collect=python35.PyGC_Collect
- PyGILState_Ensure=python35.PyGILState_Ensure
- PyGILState_GetThisThreadState=python35.PyGILState_GetThisThreadState
- PyGILState_Release=python35.PyGILState_Release
- PyGetSetDescr_Type=python35.PyGetSetDescr_Type DATA
- PyImport_AddModule=python35.PyImport_AddModule
- PyImport_AppendInittab=python35.PyImport_AppendInittab
- PyImport_Cleanup=python35.PyImport_Cleanup
- PyImport_ExecCodeModule=python35.PyImport_ExecCodeModule
- PyImport_ExecCodeModuleEx=python35.PyImport_ExecCodeModuleEx
- PyImport_ExecCodeModuleWithPathnames=python35.PyImport_ExecCodeModuleWithPathnames
- PyImport_GetImporter=python35.PyImport_GetImporter
- PyImport_GetMagicNumber=python35.PyImport_GetMagicNumber
- PyImport_GetMagicTag=python35.PyImport_GetMagicTag
- PyImport_GetModuleDict=python35.PyImport_GetModuleDict
- PyImport_Import=python35.PyImport_Import
- PyImport_ImportFrozenModule=python35.PyImport_ImportFrozenModule
- PyImport_ImportModule=python35.PyImport_ImportModule
- PyImport_ImportModuleLevel=python35.PyImport_ImportModuleLevel
- PyImport_ImportModuleNoBlock=python35.PyImport_ImportModuleNoBlock
- PyImport_ReloadModule=python35.PyImport_ReloadModule
- PyInterpreterState_Clear=python35.PyInterpreterState_Clear
- PyInterpreterState_Delete=python35.PyInterpreterState_Delete
- PyInterpreterState_New=python35.PyInterpreterState_New
- PyIter_Next=python35.PyIter_Next
- PyListIter_Type=python35.PyListIter_Type DATA
- PyListRevIter_Type=python35.PyListRevIter_Type DATA
- PyList_Append=python35.PyList_Append
- PyList_AsTuple=python35.PyList_AsTuple
- PyList_GetItem=python35.PyList_GetItem
- PyList_GetSlice=python35.PyList_GetSlice
- PyList_Insert=python35.PyList_Insert
- PyList_New=python35.PyList_New
- PyList_Reverse=python35.PyList_Reverse
- PyList_SetItem=python35.PyList_SetItem
- PyList_SetSlice=python35.PyList_SetSlice
- PyList_Size=python35.PyList_Size
- PyList_Sort=python35.PyList_Sort
- PyList_Type=python35.PyList_Type DATA
- PyLongRangeIter_Type=python35.PyLongRangeIter_Type DATA
- PyLong_AsDouble=python35.PyLong_AsDouble
- PyLong_AsLong=python35.PyLong_AsLong
- PyLong_AsLongAndOverflow=python35.PyLong_AsLongAndOverflow
- PyLong_AsLongLong=python35.PyLong_AsLongLong
- PyLong_AsLongLongAndOverflow=python35.PyLong_AsLongLongAndOverflow
- PyLong_AsSize_t=python35.PyLong_AsSize_t
- PyLong_AsSsize_t=python35.PyLong_AsSsize_t
- PyLong_AsUnsignedLong=python35.PyLong_AsUnsignedLong
- PyLong_AsUnsignedLongLong=python35.PyLong_AsUnsignedLongLong
- PyLong_AsUnsignedLongLongMask=python35.PyLong_AsUnsignedLongLongMask
- PyLong_AsUnsignedLongMask=python35.PyLong_AsUnsignedLongMask
- PyLong_AsVoidPtr=python35.PyLong_AsVoidPtr
- PyLong_FromDouble=python35.PyLong_FromDouble
- PyLong_FromLong=python35.PyLong_FromLong
- PyLong_FromLongLong=python35.PyLong_FromLongLong
- PyLong_FromSize_t=python35.PyLong_FromSize_t
- PyLong_FromSsize_t=python35.PyLong_FromSsize_t
- PyLong_FromString=python35.PyLong_FromString
- PyLong_FromUnsignedLong=python35.PyLong_FromUnsignedLong
- PyLong_FromUnsignedLongLong=python35.PyLong_FromUnsignedLongLong
- PyLong_FromVoidPtr=python35.PyLong_FromVoidPtr
- PyLong_GetInfo=python35.PyLong_GetInfo
- PyLong_Type=python35.PyLong_Type DATA
- PyMap_Type=python35.PyMap_Type DATA
- PyMapping_Check=python35.PyMapping_Check
- PyMapping_GetItemString=python35.PyMapping_GetItemString
- PyMapping_HasKey=python35.PyMapping_HasKey
- PyMapping_HasKeyString=python35.PyMapping_HasKeyString
- PyMapping_Items=python35.PyMapping_Items
- PyMapping_Keys=python35.PyMapping_Keys
- PyMapping_Length=python35.PyMapping_Length
- PyMapping_SetItemString=python35.PyMapping_SetItemString
- PyMapping_Size=python35.PyMapping_Size
- PyMapping_Values=python35.PyMapping_Values
- PyMem_Free=python35.PyMem_Free
- PyMem_Malloc=python35.PyMem_Malloc
- PyMem_Realloc=python35.PyMem_Realloc
- PyMemberDescr_Type=python35.PyMemberDescr_Type DATA
- PyMemoryView_FromObject=python35.PyMemoryView_FromObject
- PyMemoryView_GetContiguous=python35.PyMemoryView_GetContiguous
- PyMemoryView_Type=python35.PyMemoryView_Type DATA
- PyMethodDescr_Type=python35.PyMethodDescr_Type DATA
- PyModule_AddIntConstant=python35.PyModule_AddIntConstant
- PyModule_AddObject=python35.PyModule_AddObject
- PyModule_AddStringConstant=python35.PyModule_AddStringConstant
- PyModule_Create2=python35.PyModule_Create2
- PyModule_GetDef=python35.PyModule_GetDef
- PyModule_GetDict=python35.PyModule_GetDict
- PyModule_GetFilename=python35.PyModule_GetFilename
- PyModule_GetFilenameObject=python35.PyModule_GetFilenameObject
- PyModule_GetName=python35.PyModule_GetName
- PyModule_GetState=python35.PyModule_GetState
- PyModule_New=python35.PyModule_New
- PyModule_Type=python35.PyModule_Type DATA
- PyModuleDef_Init=python35.PyModuleDef_Init
- PyModuleDef_Type=python35.PyModuleDef_Type DATA
- PyNullImporter_Type=python35.PyNullImporter_Type DATA
- PyNumber_Absolute=python35.PyNumber_Absolute
- PyNumber_Add=python35.PyNumber_Add
- PyNumber_And=python35.PyNumber_And
- PyNumber_AsSsize_t=python35.PyNumber_AsSsize_t
- PyNumber_Check=python35.PyNumber_Check
- PyNumber_Divmod=python35.PyNumber_Divmod
- PyNumber_Float=python35.PyNumber_Float
- PyNumber_FloorDivide=python35.PyNumber_FloorDivide
- PyNumber_InPlaceAdd=python35.PyNumber_InPlaceAdd
- PyNumber_InPlaceAnd=python35.PyNumber_InPlaceAnd
- PyNumber_InPlaceFloorDivide=python35.PyNumber_InPlaceFloorDivide
- PyNumber_InPlaceLshift=python35.PyNumber_InPlaceLshift
- PyNumber_InPlaceMultiply=python35.PyNumber_InPlaceMultiply
- PyNumber_InPlaceOr=python35.PyNumber_InPlaceOr
- PyNumber_InPlacePower=python35.PyNumber_InPlacePower
- PyNumber_InPlaceRemainder=python35.PyNumber_InPlaceRemainder
- PyNumber_InPlaceRshift=python35.PyNumber_InPlaceRshift
- PyNumber_InPlaceSubtract=python35.PyNumber_InPlaceSubtract
- PyNumber_InPlaceTrueDivide=python35.PyNumber_InPlaceTrueDivide
- PyNumber_InPlaceXor=python35.PyNumber_InPlaceXor
- PyNumber_Index=python35.PyNumber_Index
- PyNumber_Invert=python35.PyNumber_Invert
- PyNumber_Long=python35.PyNumber_Long
- PyNumber_Lshift=python35.PyNumber_Lshift
- PyNumber_Multiply=python35.PyNumber_Multiply
- PyNumber_Negative=python35.PyNumber_Negative
- PyNumber_Or=python35.PyNumber_Or
- PyNumber_Positive=python35.PyNumber_Positive
- PyNumber_Power=python35.PyNumber_Power
- PyNumber_Remainder=python35.PyNumber_Remainder
- PyNumber_Rshift=python35.PyNumber_Rshift
- PyNumber_Subtract=python35.PyNumber_Subtract
- PyNumber_ToBase=python35.PyNumber_ToBase
- PyNumber_TrueDivide=python35.PyNumber_TrueDivide
- PyNumber_Xor=python35.PyNumber_Xor
- PyOS_AfterFork=python35.PyOS_AfterFork
- PyOS_InitInterrupts=python35.PyOS_InitInterrupts
- PyOS_InputHook=python35.PyOS_InputHook DATA
- PyOS_InterruptOccurred=python35.PyOS_InterruptOccurred
- PyOS_ReadlineFunctionPointer=python35.PyOS_ReadlineFunctionPointer DATA
- PyOS_double_to_string=python35.PyOS_double_to_string
- PyOS_getsig=python35.PyOS_getsig
- PyOS_mystricmp=python35.PyOS_mystricmp
- PyOS_mystrnicmp=python35.PyOS_mystrnicmp
- PyOS_setsig=python35.PyOS_setsig
- PyOS_snprintf=python35.PyOS_snprintf
- PyOS_string_to_double=python35.PyOS_string_to_double
- PyOS_strtol=python35.PyOS_strtol
- PyOS_strtoul=python35.PyOS_strtoul
- PyOS_vsnprintf=python35.PyOS_vsnprintf
- PyObject_ASCII=python35.PyObject_ASCII
- PyObject_AsCharBuffer=python35.PyObject_AsCharBuffer
- PyObject_AsFileDescriptor=python35.PyObject_AsFileDescriptor
- PyObject_AsReadBuffer=python35.PyObject_AsReadBuffer
- PyObject_AsWriteBuffer=python35.PyObject_AsWriteBuffer
- PyObject_Bytes=python35.PyObject_Bytes
- PyObject_Call=python35.PyObject_Call
- PyObject_CallFunction=python35.PyObject_CallFunction
- PyObject_CallFunctionObjArgs=python35.PyObject_CallFunctionObjArgs
- PyObject_CallMethod=python35.PyObject_CallMethod
- PyObject_CallMethodObjArgs=python35.PyObject_CallMethodObjArgs
- PyObject_CallObject=python35.PyObject_CallObject
- PyObject_CheckReadBuffer=python35.PyObject_CheckReadBuffer
- PyObject_ClearWeakRefs=python35.PyObject_ClearWeakRefs
- PyObject_DelItem=python35.PyObject_DelItem
- PyObject_DelItemString=python35.PyObject_DelItemString
- PyObject_Dir=python35.PyObject_Dir
- PyObject_Format=python35.PyObject_Format
- PyObject_Free=python35.PyObject_Free
- PyObject_GC_Del=python35.PyObject_GC_Del
- PyObject_GC_Track=python35.PyObject_GC_Track
- PyObject_GC_UnTrack=python35.PyObject_GC_UnTrack
- PyObject_GenericGetAttr=python35.PyObject_GenericGetAttr
- PyObject_GenericSetAttr=python35.PyObject_GenericSetAttr
- PyObject_GetAttr=python35.PyObject_GetAttr
- PyObject_GetAttrString=python35.PyObject_GetAttrString
- PyObject_GetItem=python35.PyObject_GetItem
- PyObject_GetIter=python35.PyObject_GetIter
- PyObject_HasAttr=python35.PyObject_HasAttr
- PyObject_HasAttrString=python35.PyObject_HasAttrString
- PyObject_Hash=python35.PyObject_Hash
- PyObject_HashNotImplemented=python35.PyObject_HashNotImplemented
- PyObject_Init=python35.PyObject_Init
- PyObject_InitVar=python35.PyObject_InitVar
- PyObject_IsInstance=python35.PyObject_IsInstance
- PyObject_IsSubclass=python35.PyObject_IsSubclass
- PyObject_IsTrue=python35.PyObject_IsTrue
- PyObject_Length=python35.PyObject_Length
- PyObject_Malloc=python35.PyObject_Malloc
- PyObject_Not=python35.PyObject_Not
- PyObject_Realloc=python35.PyObject_Realloc
- PyObject_Repr=python35.PyObject_Repr
- PyObject_RichCompare=python35.PyObject_RichCompare
- PyObject_RichCompareBool=python35.PyObject_RichCompareBool
- PyObject_SelfIter=python35.PyObject_SelfIter
- PyObject_SetAttr=python35.PyObject_SetAttr
- PyObject_SetAttrString=python35.PyObject_SetAttrString
- PyObject_SetItem=python35.PyObject_SetItem
- PyObject_Size=python35.PyObject_Size
- PyObject_Str=python35.PyObject_Str
- PyObject_Type=python35.PyObject_Type DATA
- PyODict_DelItem=python35.PyODict_DelItem
- PyODict_New=python35.PyODict_New
- PyODict_SetItem=python35.PyODict_SetItem
- PyODict_Type=python35.PyODict_Type DATA
- PyODictItems_Type=python35.PyODictItems_Type DATA
- PyODictIter_Type=python35.PyODictIter_Type DATA
- PyODictKeys_Type=python35.PyODictKeys_Type DATA
- PyODictValues_Type=python35.PyODictValues_Type DATA
- PyParser_SimpleParseFileFlags=python35.PyParser_SimpleParseFileFlags
- PyParser_SimpleParseStringFlags=python35.PyParser_SimpleParseStringFlags
- PyProperty_Type=python35.PyProperty_Type DATA
- PyRangeIter_Type=python35.PyRangeIter_Type DATA
- PyRange_Type=python35.PyRange_Type DATA
- PyReversed_Type=python35.PyReversed_Type DATA
- PySeqIter_New=python35.PySeqIter_New
- PySeqIter_Type=python35.PySeqIter_Type DATA
- PySequence_Check=python35.PySequence_Check
- PySequence_Concat=python35.PySequence_Concat
- PySequence_Contains=python35.PySequence_Contains
- PySequence_Count=python35.PySequence_Count
- PySequence_DelItem=python35.PySequence_DelItem
- PySequence_DelSlice=python35.PySequence_DelSlice
- PySequence_Fast=python35.PySequence_Fast
- PySequence_GetItem=python35.PySequence_GetItem
- PySequence_GetSlice=python35.PySequence_GetSlice
- PySequence_In=python35.PySequence_In
- PySequence_InPlaceConcat=python35.PySequence_InPlaceConcat
- PySequence_InPlaceRepeat=python35.PySequence_InPlaceRepeat
- PySequence_Index=python35.PySequence_Index
- PySequence_Length=python35.PySequence_Length
- PySequence_List=python35.PySequence_List
- PySequence_Repeat=python35.PySequence_Repeat
- PySequence_SetItem=python35.PySequence_SetItem
- PySequence_SetSlice=python35.PySequence_SetSlice
- PySequence_Size=python35.PySequence_Size
- PySequence_Tuple=python35.PySequence_Tuple
- PySetIter_Type=python35.PySetIter_Type DATA
- PySet_Add=python35.PySet_Add
- PySet_Clear=python35.PySet_Clear
- PySet_Contains=python35.PySet_Contains
- PySet_Discard=python35.PySet_Discard
- PySet_New=python35.PySet_New
- PySet_Pop=python35.PySet_Pop
- PySet_Size=python35.PySet_Size
- PySet_Type=python35.PySet_Type DATA
- PySlice_GetIndices=python35.PySlice_GetIndices
- PySlice_GetIndicesEx=python35.PySlice_GetIndicesEx
- PySlice_New=python35.PySlice_New
- PySlice_Type=python35.PySlice_Type DATA
- PySortWrapper_Type=python35.PySortWrapper_Type DATA
- PyState_FindModule=python35.PyState_FindModule
- PyState_AddModule=python35.PyState_AddModule
- PyState_RemoveModule=python35.PyState_RemoveModule
- PyStructSequence_GetItem=python35.PyStructSequence_GetItem
- PyStructSequence_New=python35.PyStructSequence_New
- PyStructSequence_NewType=python35.PyStructSequence_NewType
- PyStructSequence_SetItem=python35.PyStructSequence_SetItem
- PySuper_Type=python35.PySuper_Type DATA
- PySys_AddWarnOption=python35.PySys_AddWarnOption
- PySys_AddWarnOptionUnicode=python35.PySys_AddWarnOptionUnicode
- PySys_FormatStderr=python35.PySys_FormatStderr
- PySys_FormatStdout=python35.PySys_FormatStdout
- PySys_GetObject=python35.PySys_GetObject
- PySys_HasWarnOptions=python35.PySys_HasWarnOptions
- PySys_ResetWarnOptions=python35.PySys_ResetWarnOptions
- PySys_SetArgv=python35.PySys_SetArgv
- PySys_SetArgvEx=python35.PySys_SetArgvEx
- PySys_SetObject=python35.PySys_SetObject
- PySys_SetPath=python35.PySys_SetPath
- PySys_WriteStderr=python35.PySys_WriteStderr
- PySys_WriteStdout=python35.PySys_WriteStdout
- PyThreadState_Clear=python35.PyThreadState_Clear
- PyThreadState_Delete=python35.PyThreadState_Delete
- PyThreadState_DeleteCurrent=python35.PyThreadState_DeleteCurrent
- PyThreadState_Get=python35.PyThreadState_Get
- PyThreadState_GetDict=python35.PyThreadState_GetDict
- PyThreadState_New=python35.PyThreadState_New
- PyThreadState_SetAsyncExc=python35.PyThreadState_SetAsyncExc
- PyThreadState_Swap=python35.PyThreadState_Swap
- PyTraceBack_Here=python35.PyTraceBack_Here
- PyTraceBack_Print=python35.PyTraceBack_Print
- PyTraceBack_Type=python35.PyTraceBack_Type DATA
- PyTupleIter_Type=python35.PyTupleIter_Type DATA
- PyTuple_ClearFreeList=python35.PyTuple_ClearFreeList
- PyTuple_GetItem=python35.PyTuple_GetItem
- PyTuple_GetSlice=python35.PyTuple_GetSlice
- PyTuple_New=python35.PyTuple_New
- PyTuple_Pack=python35.PyTuple_Pack
- PyTuple_SetItem=python35.PyTuple_SetItem
- PyTuple_Size=python35.PyTuple_Size
- PyTuple_Type=python35.PyTuple_Type DATA
- PyType_ClearCache=python35.PyType_ClearCache
- PyType_FromSpec=python35.PyType_FromSpec
- PyType_FromSpecWithBases=python35.PyType_FromSpecWithBases
- PyType_GenericAlloc=python35.PyType_GenericAlloc
- PyType_GenericNew=python35.PyType_GenericNew
- PyType_GetFlags=python35.PyType_GetFlags
- PyType_GetSlot=python35.PyType_GetSlot
- PyType_IsSubtype=python35.PyType_IsSubtype
- PyType_Modified=python35.PyType_Modified
- PyType_Ready=python35.PyType_Ready
- PyType_Type=python35.PyType_Type DATA
- PyUnicodeDecodeError_Create=python35.PyUnicodeDecodeError_Create
- PyUnicodeDecodeError_GetEncoding=python35.PyUnicodeDecodeError_GetEncoding
- PyUnicodeDecodeError_GetEnd=python35.PyUnicodeDecodeError_GetEnd
- PyUnicodeDecodeError_GetObject=python35.PyUnicodeDecodeError_GetObject
- PyUnicodeDecodeError_GetReason=python35.PyUnicodeDecodeError_GetReason
- PyUnicodeDecodeError_GetStart=python35.PyUnicodeDecodeError_GetStart
- PyUnicodeDecodeError_SetEnd=python35.PyUnicodeDecodeError_SetEnd
- PyUnicodeDecodeError_SetReason=python35.PyUnicodeDecodeError_SetReason
- PyUnicodeDecodeError_SetStart=python35.PyUnicodeDecodeError_SetStart
- PyUnicodeEncodeError_GetEncoding=python35.PyUnicodeEncodeError_GetEncoding
- PyUnicodeEncodeError_GetEnd=python35.PyUnicodeEncodeError_GetEnd
- PyUnicodeEncodeError_GetObject=python35.PyUnicodeEncodeError_GetObject
- PyUnicodeEncodeError_GetReason=python35.PyUnicodeEncodeError_GetReason
- PyUnicodeEncodeError_GetStart=python35.PyUnicodeEncodeError_GetStart
- PyUnicodeEncodeError_SetEnd=python35.PyUnicodeEncodeError_SetEnd
- PyUnicodeEncodeError_SetReason=python35.PyUnicodeEncodeError_SetReason
- PyUnicodeEncodeError_SetStart=python35.PyUnicodeEncodeError_SetStart
- PyUnicodeIter_Type=python35.PyUnicodeIter_Type DATA
- PyUnicodeTranslateError_GetEnd=python35.PyUnicodeTranslateError_GetEnd
- PyUnicodeTranslateError_GetObject=python35.PyUnicodeTranslateError_GetObject
- PyUnicodeTranslateError_GetReason=python35.PyUnicodeTranslateError_GetReason
- PyUnicodeTranslateError_GetStart=python35.PyUnicodeTranslateError_GetStart
- PyUnicodeTranslateError_SetEnd=python35.PyUnicodeTranslateError_SetEnd
- PyUnicodeTranslateError_SetReason=python35.PyUnicodeTranslateError_SetReason
- PyUnicodeTranslateError_SetStart=python35.PyUnicodeTranslateError_SetStart
- PyUnicode_Append=python35.PyUnicode_Append
- PyUnicode_AppendAndDel=python35.PyUnicode_AppendAndDel
- PyUnicode_AsASCIIString=python35.PyUnicode_AsASCIIString
- PyUnicode_AsCharmapString=python35.PyUnicode_AsCharmapString
- PyUnicode_AsDecodedObject=python35.PyUnicode_AsDecodedObject
- PyUnicode_AsDecodedUnicode=python35.PyUnicode_AsDecodedUnicode
- PyUnicode_AsEncodedObject=python35.PyUnicode_AsEncodedObject
- PyUnicode_AsEncodedString=python35.PyUnicode_AsEncodedString
- PyUnicode_AsEncodedUnicode=python35.PyUnicode_AsEncodedUnicode
- PyUnicode_AsLatin1String=python35.PyUnicode_AsLatin1String
- PyUnicode_AsRawUnicodeEscapeString=python35.PyUnicode_AsRawUnicodeEscapeString
- PyUnicode_AsUTF16String=python35.PyUnicode_AsUTF16String
- PyUnicode_AsUTF32String=python35.PyUnicode_AsUTF32String
- PyUnicode_AsUTF8String=python35.PyUnicode_AsUTF8String
- PyUnicode_AsUnicodeEscapeString=python35.PyUnicode_AsUnicodeEscapeString
- PyUnicode_AsWideChar=python35.PyUnicode_AsWideChar
- PyUnicode_ClearFreelist=python35.PyUnicode_ClearFreelist
- PyUnicode_Compare=python35.PyUnicode_Compare
- PyUnicode_Concat=python35.PyUnicode_Concat
- PyUnicode_Contains=python35.PyUnicode_Contains
- PyUnicode_Count=python35.PyUnicode_Count
- PyUnicode_Decode=python35.PyUnicode_Decode
- PyUnicode_DecodeASCII=python35.PyUnicode_DecodeASCII
- PyUnicode_DecodeCharmap=python35.PyUnicode_DecodeCharmap
- PyUnicode_DecodeFSDefault=python35.PyUnicode_DecodeFSDefault
- PyUnicode_DecodeFSDefaultAndSize=python35.PyUnicode_DecodeFSDefaultAndSize
- PyUnicode_DecodeLatin1=python35.PyUnicode_DecodeLatin1
- PyUnicode_DecodeRawUnicodeEscape=python35.PyUnicode_DecodeRawUnicodeEscape
- PyUnicode_DecodeUTF16=python35.PyUnicode_DecodeUTF16
- PyUnicode_DecodeUTF16Stateful=python35.PyUnicode_DecodeUTF16Stateful
- PyUnicode_DecodeUTF32=python35.PyUnicode_DecodeUTF32
- PyUnicode_DecodeUTF32Stateful=python35.PyUnicode_DecodeUTF32Stateful
- PyUnicode_DecodeUTF8=python35.PyUnicode_DecodeUTF8
- PyUnicode_DecodeUTF8Stateful=python35.PyUnicode_DecodeUTF8Stateful
- PyUnicode_DecodeUnicodeEscape=python35.PyUnicode_DecodeUnicodeEscape
- PyUnicode_FSConverter=python35.PyUnicode_FSConverter
- PyUnicode_FSDecoder=python35.PyUnicode_FSDecoder
- PyUnicode_Find=python35.PyUnicode_Find
- PyUnicode_Format=python35.PyUnicode_Format
- PyUnicode_FromEncodedObject=python35.PyUnicode_FromEncodedObject
- PyUnicode_FromFormat=python35.PyUnicode_FromFormat
- PyUnicode_FromFormatV=python35.PyUnicode_FromFormatV
- PyUnicode_FromObject=python35.PyUnicode_FromObject
- PyUnicode_FromOrdinal=python35.PyUnicode_FromOrdinal
- PyUnicode_FromString=python35.PyUnicode_FromString
- PyUnicode_FromStringAndSize=python35.PyUnicode_FromStringAndSize
- PyUnicode_FromWideChar=python35.PyUnicode_FromWideChar
- PyUnicode_GetDefaultEncoding=python35.PyUnicode_GetDefaultEncoding
- PyUnicode_GetSize=python35.PyUnicode_GetSize
- PyUnicode_IsIdentifier=python35.PyUnicode_IsIdentifier
- PyUnicode_Join=python35.PyUnicode_Join
- PyUnicode_Partition=python35.PyUnicode_Partition
- PyUnicode_RPartition=python35.PyUnicode_RPartition
- PyUnicode_RSplit=python35.PyUnicode_RSplit
- PyUnicode_Replace=python35.PyUnicode_Replace
- PyUnicode_Resize=python35.PyUnicode_Resize
- PyUnicode_RichCompare=python35.PyUnicode_RichCompare
- PyUnicode_SetDefaultEncoding=python35.PyUnicode_SetDefaultEncoding
- PyUnicode_Split=python35.PyUnicode_Split
- PyUnicode_Splitlines=python35.PyUnicode_Splitlines
- PyUnicode_Tailmatch=python35.PyUnicode_Tailmatch
- PyUnicode_Translate=python35.PyUnicode_Translate
- PyUnicode_BuildEncodingMap=python35.PyUnicode_BuildEncodingMap
- PyUnicode_CompareWithASCIIString=python35.PyUnicode_CompareWithASCIIString
- PyUnicode_DecodeUTF7=python35.PyUnicode_DecodeUTF7
- PyUnicode_DecodeUTF7Stateful=python35.PyUnicode_DecodeUTF7Stateful
- PyUnicode_EncodeFSDefault=python35.PyUnicode_EncodeFSDefault
- PyUnicode_InternFromString=python35.PyUnicode_InternFromString
- PyUnicode_InternImmortal=python35.PyUnicode_InternImmortal
- PyUnicode_InternInPlace=python35.PyUnicode_InternInPlace
- PyUnicode_Type=python35.PyUnicode_Type DATA
- PyWeakref_GetObject=python35.PyWeakref_GetObject DATA
- PyWeakref_NewProxy=python35.PyWeakref_NewProxy
- PyWeakref_NewRef=python35.PyWeakref_NewRef
- PyWrapperDescr_Type=python35.PyWrapperDescr_Type DATA
- PyWrapper_New=python35.PyWrapper_New
- PyZip_Type=python35.PyZip_Type DATA
- Py_AddPendingCall=python35.Py_AddPendingCall
- Py_AtExit=python35.Py_AtExit
- Py_BuildValue=python35.Py_BuildValue
- Py_CompileString=python35.Py_CompileString
- Py_DecRef=python35.Py_DecRef
- Py_EndInterpreter=python35.Py_EndInterpreter
- Py_Exit=python35.Py_Exit
- Py_FatalError=python35.Py_FatalError
- Py_FileSystemDefaultEncoding=python35.Py_FileSystemDefaultEncoding DATA
- Py_Finalize=python35.Py_Finalize
- Py_GetBuildInfo=python35.Py_GetBuildInfo
- Py_GetCompiler=python35.Py_GetCompiler
- Py_GetCopyright=python35.Py_GetCopyright
- Py_GetExecPrefix=python35.Py_GetExecPrefix
- Py_GetPath=python35.Py_GetPath
- Py_GetPlatform=python35.Py_GetPlatform
- Py_GetPrefix=python35.Py_GetPrefix
- Py_GetProgramFullPath=python35.Py_GetProgramFullPath
- Py_GetProgramName=python35.Py_GetProgramName
- Py_GetPythonHome=python35.Py_GetPythonHome
- Py_GetRecursionLimit=python35.Py_GetRecursionLimit
- Py_GetVersion=python35.Py_GetVersion
- Py_HasFileSystemDefaultEncoding=python35.Py_HasFileSystemDefaultEncoding DATA
- Py_IncRef=python35.Py_IncRef
- Py_Initialize=python35.Py_Initialize
- Py_InitializeEx=python35.Py_InitializeEx
- Py_IsInitialized=python35.Py_IsInitialized
- Py_Main=python35.Py_Main
- Py_MakePendingCalls=python35.Py_MakePendingCalls
- Py_NewInterpreter=python35.Py_NewInterpreter
- Py_ReprEnter=python35.Py_ReprEnter
- Py_ReprLeave=python35.Py_ReprLeave
- Py_SetProgramName=python35.Py_SetProgramName
- Py_SetPythonHome=python35.Py_SetPythonHome
- Py_SetRecursionLimit=python35.Py_SetRecursionLimit
- Py_SymtableString=python35.Py_SymtableString
- Py_VaBuildValue=python35.Py_VaBuildValue
- _PyErr_BadInternalCall=python35._PyErr_BadInternalCall
- _PyObject_CallFunction_SizeT=python35._PyObject_CallFunction_SizeT
- _PyObject_CallMethod_SizeT=python35._PyObject_CallMethod_SizeT
- _PyObject_GC_Malloc=python35._PyObject_GC_Malloc
- _PyObject_GC_New=python35._PyObject_GC_New
- _PyObject_GC_NewVar=python35._PyObject_GC_NewVar
- _PyObject_GC_Resize=python35._PyObject_GC_Resize
- _PyObject_New=python35._PyObject_New
- _PyObject_NewVar=python35._PyObject_NewVar
- _PyState_AddModule=python35._PyState_AddModule
- _PyThreadState_Init=python35._PyThreadState_Init
- _PyThreadState_Prealloc=python35._PyThreadState_Prealloc
- _PyTrash_delete_later=python35._PyTrash_delete_later DATA
- _PyTrash_delete_nesting=python35._PyTrash_delete_nesting DATA
- _PyTrash_deposit_object=python35._PyTrash_deposit_object
- _PyTrash_destroy_chain=python35._PyTrash_destroy_chain
- _PyWeakref_CallableProxyType=python35._PyWeakref_CallableProxyType DATA
- _PyWeakref_ProxyType=python35._PyWeakref_ProxyType DATA
- _PyWeakref_RefType=python35._PyWeakref_RefType DATA
- _Py_BuildValue_SizeT=python35._Py_BuildValue_SizeT
- _Py_CheckRecursionLimit=python35._Py_CheckRecursionLimit DATA
- _Py_CheckRecursiveCall=python35._Py_CheckRecursiveCall
- _Py_Dealloc=python35._Py_Dealloc
- _Py_EllipsisObject=python35._Py_EllipsisObject DATA
- _Py_FalseStruct=python35._Py_FalseStruct DATA
- _Py_NoneStruct=python35._Py_NoneStruct DATA
- _Py_NotImplementedStruct=python35._Py_NotImplementedStruct DATA
- _Py_SwappedOp=python35._Py_SwappedOp DATA
- _Py_TrueStruct=python35._Py_TrueStruct DATA
- _Py_VaBuildValue_SizeT=python35._Py_VaBuildValue_SizeT
- _PyArg_Parse_SizeT=python35._PyArg_Parse_SizeT
- _PyArg_ParseTuple_SizeT=python35._PyArg_ParseTuple_SizeT
- _PyArg_ParseTupleAndKeywords_SizeT=python35._PyArg_ParseTupleAndKeywords_SizeT
- _PyArg_VaParse_SizeT=python35._PyArg_VaParse_SizeT
- _PyArg_VaParseTupleAndKeywords_SizeT=python35._PyArg_VaParseTupleAndKeywords_SizeT
- _Py_BuildValue_SizeT=python35._Py_BuildValue_SizeT
+ PyArg_Parse=python36.PyArg_Parse
+ PyArg_ParseTuple=python36.PyArg_ParseTuple
+ PyArg_ParseTupleAndKeywords=python36.PyArg_ParseTupleAndKeywords
+ PyArg_UnpackTuple=python36.PyArg_UnpackTuple
+ PyArg_VaParse=python36.PyArg_VaParse
+ PyArg_VaParseTupleAndKeywords=python36.PyArg_VaParseTupleAndKeywords
+ PyArg_ValidateKeywordArguments=python36.PyArg_ValidateKeywordArguments
+ PyBaseObject_Type=python36.PyBaseObject_Type DATA
+ PyBool_FromLong=python36.PyBool_FromLong
+ PyBool_Type=python36.PyBool_Type DATA
+ PyByteArrayIter_Type=python36.PyByteArrayIter_Type DATA
+ PyByteArray_AsString=python36.PyByteArray_AsString
+ PyByteArray_Concat=python36.PyByteArray_Concat
+ PyByteArray_FromObject=python36.PyByteArray_FromObject
+ PyByteArray_FromStringAndSize=python36.PyByteArray_FromStringAndSize
+ PyByteArray_Resize=python36.PyByteArray_Resize
+ PyByteArray_Size=python36.PyByteArray_Size
+ PyByteArray_Type=python36.PyByteArray_Type DATA
+ PyBytesIter_Type=python36.PyBytesIter_Type DATA
+ PyBytes_AsString=python36.PyBytes_AsString
+ PyBytes_AsStringAndSize=python36.PyBytes_AsStringAndSize
+ PyBytes_Concat=python36.PyBytes_Concat
+ PyBytes_ConcatAndDel=python36.PyBytes_ConcatAndDel
+ PyBytes_DecodeEscape=python36.PyBytes_DecodeEscape
+ PyBytes_FromFormat=python36.PyBytes_FromFormat
+ PyBytes_FromFormatV=python36.PyBytes_FromFormatV
+ PyBytes_FromObject=python36.PyBytes_FromObject
+ PyBytes_FromString=python36.PyBytes_FromString
+ PyBytes_FromStringAndSize=python36.PyBytes_FromStringAndSize
+ PyBytes_Repr=python36.PyBytes_Repr
+ PyBytes_Size=python36.PyBytes_Size
+ PyBytes_Type=python36.PyBytes_Type DATA
+ PyCFunction_Call=python36.PyCFunction_Call
+ PyCFunction_ClearFreeList=python36.PyCFunction_ClearFreeList
+ PyCFunction_GetFlags=python36.PyCFunction_GetFlags
+ PyCFunction_GetFunction=python36.PyCFunction_GetFunction
+ PyCFunction_GetSelf=python36.PyCFunction_GetSelf
+ PyCFunction_New=python36.PyCFunction_New
+ PyCFunction_NewEx=python36.PyCFunction_NewEx
+ PyCFunction_Type=python36.PyCFunction_Type DATA
+ PyCallIter_New=python36.PyCallIter_New
+ PyCallIter_Type=python36.PyCallIter_Type DATA
+ PyCallable_Check=python36.PyCallable_Check
+ PyCapsule_GetContext=python36.PyCapsule_GetContext
+ PyCapsule_GetDestructor=python36.PyCapsule_GetDestructor
+ PyCapsule_GetName=python36.PyCapsule_GetName
+ PyCapsule_GetPointer=python36.PyCapsule_GetPointer
+ PyCapsule_Import=python36.PyCapsule_Import
+ PyCapsule_IsValid=python36.PyCapsule_IsValid
+ PyCapsule_New=python36.PyCapsule_New
+ PyCapsule_SetContext=python36.PyCapsule_SetContext
+ PyCapsule_SetDestructor=python36.PyCapsule_SetDestructor
+ PyCapsule_SetName=python36.PyCapsule_SetName
+ PyCapsule_SetPointer=python36.PyCapsule_SetPointer
+ PyCapsule_Type=python36.PyCapsule_Type DATA
+ PyClassMethodDescr_Type=python36.PyClassMethodDescr_Type DATA
+ PyCodec_BackslashReplaceErrors=python36.PyCodec_BackslashReplaceErrors
+ PyCodec_Decode=python36.PyCodec_Decode
+ PyCodec_Decoder=python36.PyCodec_Decoder
+ PyCodec_Encode=python36.PyCodec_Encode
+ PyCodec_Encoder=python36.PyCodec_Encoder
+ PyCodec_IgnoreErrors=python36.PyCodec_IgnoreErrors
+ PyCodec_IncrementalDecoder=python36.PyCodec_IncrementalDecoder
+ PyCodec_IncrementalEncoder=python36.PyCodec_IncrementalEncoder
+ PyCodec_KnownEncoding=python36.PyCodec_KnownEncoding
+ PyCodec_LookupError=python36.PyCodec_LookupError
+ PyCodec_Register=python36.PyCodec_Register
+ PyCodec_RegisterError=python36.PyCodec_RegisterError
+ PyCodec_ReplaceErrors=python36.PyCodec_ReplaceErrors
+ PyCodec_StreamReader=python36.PyCodec_StreamReader
+ PyCodec_StreamWriter=python36.PyCodec_StreamWriter
+ PyCodec_StrictErrors=python36.PyCodec_StrictErrors
+ PyCodec_XMLCharRefReplaceErrors=python36.PyCodec_XMLCharRefReplaceErrors
+ PyComplex_FromDoubles=python36.PyComplex_FromDoubles
+ PyComplex_ImagAsDouble=python36.PyComplex_ImagAsDouble
+ PyComplex_RealAsDouble=python36.PyComplex_RealAsDouble
+ PyComplex_Type=python36.PyComplex_Type DATA
+ PyDescr_NewClassMethod=python36.PyDescr_NewClassMethod
+ PyDescr_NewGetSet=python36.PyDescr_NewGetSet
+ PyDescr_NewMember=python36.PyDescr_NewMember
+ PyDescr_NewMethod=python36.PyDescr_NewMethod
+ PyDictItems_Type=python36.PyDictItems_Type DATA
+ PyDictIterItem_Type=python36.PyDictIterItem_Type DATA
+ PyDictIterKey_Type=python36.PyDictIterKey_Type DATA
+ PyDictIterValue_Type=python36.PyDictIterValue_Type DATA
+ PyDictKeys_Type=python36.PyDictKeys_Type DATA
+ PyDictProxy_New=python36.PyDictProxy_New
+ PyDictProxy_Type=python36.PyDictProxy_Type DATA
+ PyDictValues_Type=python36.PyDictValues_Type DATA
+ PyDict_Clear=python36.PyDict_Clear
+ PyDict_Contains=python36.PyDict_Contains
+ PyDict_Copy=python36.PyDict_Copy
+ PyDict_DelItem=python36.PyDict_DelItem
+ PyDict_DelItemString=python36.PyDict_DelItemString
+ PyDict_GetItem=python36.PyDict_GetItem
+ PyDict_GetItemString=python36.PyDict_GetItemString
+ PyDict_GetItemWithError=python36.PyDict_GetItemWithError
+ PyDict_Items=python36.PyDict_Items
+ PyDict_Keys=python36.PyDict_Keys
+ PyDict_Merge=python36.PyDict_Merge
+ PyDict_MergeFromSeq2=python36.PyDict_MergeFromSeq2
+ PyDict_New=python36.PyDict_New
+ PyDict_Next=python36.PyDict_Next
+ PyDict_SetItem=python36.PyDict_SetItem
+ PyDict_SetItemString=python36.PyDict_SetItemString
+ PyDict_Size=python36.PyDict_Size
+ PyDict_Type=python36.PyDict_Type DATA
+ PyDict_Update=python36.PyDict_Update
+ PyDict_Values=python36.PyDict_Values
+ PyEllipsis_Type=python36.PyEllipsis_Type DATA
+ PyEnum_Type=python36.PyEnum_Type DATA
+ PyErr_BadArgument=python36.PyErr_BadArgument
+ PyErr_BadInternalCall=python36.PyErr_BadInternalCall
+ PyErr_CheckSignals=python36.PyErr_CheckSignals
+ PyErr_Clear=python36.PyErr_Clear
+ PyErr_Display=python36.PyErr_Display
+ PyErr_ExceptionMatches=python36.PyErr_ExceptionMatches
+ PyErr_Fetch=python36.PyErr_Fetch
+ PyErr_Format=python36.PyErr_Format
+ PyErr_FormatV=python36.PyErr_FormatV
+ PyErr_GivenExceptionMatches=python36.PyErr_GivenExceptionMatches
+ PyErr_NewException=python36.PyErr_NewException
+ PyErr_NewExceptionWithDoc=python36.PyErr_NewExceptionWithDoc
+ PyErr_NoMemory=python36.PyErr_NoMemory
+ PyErr_NormalizeException=python36.PyErr_NormalizeException
+ PyErr_Occurred=python36.PyErr_Occurred
+ PyErr_Print=python36.PyErr_Print
+ PyErr_PrintEx=python36.PyErr_PrintEx
+ PyErr_ProgramText=python36.PyErr_ProgramText
+ PyErr_Restore=python36.PyErr_Restore
+ PyErr_SetFromErrno=python36.PyErr_SetFromErrno
+ PyErr_SetFromErrnoWithFilename=python36.PyErr_SetFromErrnoWithFilename
+ PyErr_SetFromErrnoWithFilenameObject=python36.PyErr_SetFromErrnoWithFilenameObject
+ PyErr_SetInterrupt=python36.PyErr_SetInterrupt
+ PyErr_SetNone=python36.PyErr_SetNone
+ PyErr_SetObject=python36.PyErr_SetObject
+ PyErr_SetString=python36.PyErr_SetString
+ PyErr_SyntaxLocation=python36.PyErr_SyntaxLocation
+ PyErr_WarnEx=python36.PyErr_WarnEx
+ PyErr_WarnExplicit=python36.PyErr_WarnExplicit
+ PyErr_WarnFormat=python36.PyErr_WarnFormat
+ PyErr_WriteUnraisable=python36.PyErr_WriteUnraisable
+ PyEval_AcquireLock=python36.PyEval_AcquireLock
+ PyEval_AcquireThread=python36.PyEval_AcquireThread
+ PyEval_CallFunction=python36.PyEval_CallFunction
+ PyEval_CallMethod=python36.PyEval_CallMethod
+ PyEval_CallObjectWithKeywords=python36.PyEval_CallObjectWithKeywords
+ PyEval_EvalCode=python36.PyEval_EvalCode
+ PyEval_EvalCodeEx=python36.PyEval_EvalCodeEx
+ PyEval_EvalFrame=python36.PyEval_EvalFrame
+ PyEval_EvalFrameEx=python36.PyEval_EvalFrameEx
+ PyEval_GetBuiltins=python36.PyEval_GetBuiltins
+ PyEval_GetCallStats=python36.PyEval_GetCallStats
+ PyEval_GetFrame=python36.PyEval_GetFrame
+ PyEval_GetFuncDesc=python36.PyEval_GetFuncDesc
+ PyEval_GetFuncName=python36.PyEval_GetFuncName
+ PyEval_GetGlobals=python36.PyEval_GetGlobals
+ PyEval_GetLocals=python36.PyEval_GetLocals
+ PyEval_InitThreads=python36.PyEval_InitThreads
+ PyEval_ReInitThreads=python36.PyEval_ReInitThreads
+ PyEval_ReleaseLock=python36.PyEval_ReleaseLock
+ PyEval_ReleaseThread=python36.PyEval_ReleaseThread
+ PyEval_RestoreThread=python36.PyEval_RestoreThread
+ PyEval_SaveThread=python36.PyEval_SaveThread
+ PyEval_ThreadsInitialized=python36.PyEval_ThreadsInitialized
+ PyExc_ArithmeticError=python36.PyExc_ArithmeticError DATA
+ PyExc_AssertionError=python36.PyExc_AssertionError DATA
+ PyExc_AttributeError=python36.PyExc_AttributeError DATA
+ PyExc_BaseException=python36.PyExc_BaseException DATA
+ PyExc_BufferError=python36.PyExc_BufferError DATA
+ PyExc_BytesWarning=python36.PyExc_BytesWarning DATA
+ PyExc_DeprecationWarning=python36.PyExc_DeprecationWarning DATA
+ PyExc_EOFError=python36.PyExc_EOFError DATA
+ PyExc_EnvironmentError=python36.PyExc_EnvironmentError DATA
+ PyExc_Exception=python36.PyExc_Exception DATA
+ PyExc_FloatingPointError=python36.PyExc_FloatingPointError DATA
+ PyExc_FutureWarning=python36.PyExc_FutureWarning DATA
+ PyExc_GeneratorExit=python36.PyExc_GeneratorExit DATA
+ PyExc_IOError=python36.PyExc_IOError DATA
+ PyExc_ImportError=python36.PyExc_ImportError DATA
+ PyExc_ImportWarning=python36.PyExc_ImportWarning DATA
+ PyExc_IndentationError=python36.PyExc_IndentationError DATA
+ PyExc_IndexError=python36.PyExc_IndexError DATA
+ PyExc_KeyError=python36.PyExc_KeyError DATA
+ PyExc_KeyboardInterrupt=python36.PyExc_KeyboardInterrupt DATA
+ PyExc_LookupError=python36.PyExc_LookupError DATA
+ PyExc_MemoryError=python36.PyExc_MemoryError DATA
+ PyExc_MemoryErrorInst=python36.PyExc_MemoryErrorInst DATA
+ PyExc_NameError=python36.PyExc_NameError DATA
+ PyExc_NotImplementedError=python36.PyExc_NotImplementedError DATA
+ PyExc_OSError=python36.PyExc_OSError DATA
+ PyExc_OverflowError=python36.PyExc_OverflowError DATA
+ PyExc_PendingDeprecationWarning=python36.PyExc_PendingDeprecationWarning DATA
+ PyExc_RecursionErrorInst=python36.PyExc_RecursionErrorInst DATA
+ PyExc_ReferenceError=python36.PyExc_ReferenceError DATA
+ PyExc_RuntimeError=python36.PyExc_RuntimeError DATA
+ PyExc_RuntimeWarning=python36.PyExc_RuntimeWarning DATA
+ PyExc_StopIteration=python36.PyExc_StopIteration DATA
+ PyExc_SyntaxError=python36.PyExc_SyntaxError DATA
+ PyExc_SyntaxWarning=python36.PyExc_SyntaxWarning DATA
+ PyExc_SystemError=python36.PyExc_SystemError DATA
+ PyExc_SystemExit=python36.PyExc_SystemExit DATA
+ PyExc_TabError=python36.PyExc_TabError DATA
+ PyExc_TypeError=python36.PyExc_TypeError DATA
+ PyExc_UnboundLocalError=python36.PyExc_UnboundLocalError DATA
+ PyExc_UnicodeDecodeError=python36.PyExc_UnicodeDecodeError DATA
+ PyExc_UnicodeEncodeError=python36.PyExc_UnicodeEncodeError DATA
+ PyExc_UnicodeError=python36.PyExc_UnicodeError DATA
+ PyExc_UnicodeTranslateError=python36.PyExc_UnicodeTranslateError DATA
+ PyExc_UnicodeWarning=python36.PyExc_UnicodeWarning DATA
+ PyExc_UserWarning=python36.PyExc_UserWarning DATA
+ PyExc_ValueError=python36.PyExc_ValueError DATA
+ PyExc_Warning=python36.PyExc_Warning DATA
+ PyExc_ZeroDivisionError=python36.PyExc_ZeroDivisionError DATA
+ PyException_GetCause=python36.PyException_GetCause
+ PyException_GetContext=python36.PyException_GetContext
+ PyException_GetTraceback=python36.PyException_GetTraceback
+ PyException_SetCause=python36.PyException_SetCause
+ PyException_SetContext=python36.PyException_SetContext
+ PyException_SetTraceback=python36.PyException_SetTraceback
+ PyFile_FromFd=python36.PyFile_FromFd
+ PyFile_GetLine=python36.PyFile_GetLine
+ PyFile_WriteObject=python36.PyFile_WriteObject
+ PyFile_WriteString=python36.PyFile_WriteString
+ PyFilter_Type=python36.PyFilter_Type DATA
+ PyFloat_AsDouble=python36.PyFloat_AsDouble
+ PyFloat_FromDouble=python36.PyFloat_FromDouble
+ PyFloat_FromString=python36.PyFloat_FromString
+ PyFloat_GetInfo=python36.PyFloat_GetInfo
+ PyFloat_GetMax=python36.PyFloat_GetMax
+ PyFloat_GetMin=python36.PyFloat_GetMin
+ PyFloat_Type=python36.PyFloat_Type DATA
+ PyFrozenSet_New=python36.PyFrozenSet_New
+ PyFrozenSet_Type=python36.PyFrozenSet_Type DATA
+ PyGC_Collect=python36.PyGC_Collect
+ PyGILState_Ensure=python36.PyGILState_Ensure
+ PyGILState_GetThisThreadState=python36.PyGILState_GetThisThreadState
+ PyGILState_Release=python36.PyGILState_Release
+ PyGetSetDescr_Type=python36.PyGetSetDescr_Type DATA
+ PyImport_AddModule=python36.PyImport_AddModule
+ PyImport_AppendInittab=python36.PyImport_AppendInittab
+ PyImport_Cleanup=python36.PyImport_Cleanup
+ PyImport_ExecCodeModule=python36.PyImport_ExecCodeModule
+ PyImport_ExecCodeModuleEx=python36.PyImport_ExecCodeModuleEx
+ PyImport_ExecCodeModuleWithPathnames=python36.PyImport_ExecCodeModuleWithPathnames
+ PyImport_GetImporter=python36.PyImport_GetImporter
+ PyImport_GetMagicNumber=python36.PyImport_GetMagicNumber
+ PyImport_GetMagicTag=python36.PyImport_GetMagicTag
+ PyImport_GetModuleDict=python36.PyImport_GetModuleDict
+ PyImport_Import=python36.PyImport_Import
+ PyImport_ImportFrozenModule=python36.PyImport_ImportFrozenModule
+ PyImport_ImportModule=python36.PyImport_ImportModule
+ PyImport_ImportModuleLevel=python36.PyImport_ImportModuleLevel
+ PyImport_ImportModuleNoBlock=python36.PyImport_ImportModuleNoBlock
+ PyImport_ReloadModule=python36.PyImport_ReloadModule
+ PyInterpreterState_Clear=python36.PyInterpreterState_Clear
+ PyInterpreterState_Delete=python36.PyInterpreterState_Delete
+ PyInterpreterState_New=python36.PyInterpreterState_New
+ PyIter_Next=python36.PyIter_Next
+ PyListIter_Type=python36.PyListIter_Type DATA
+ PyListRevIter_Type=python36.PyListRevIter_Type DATA
+ PyList_Append=python36.PyList_Append
+ PyList_AsTuple=python36.PyList_AsTuple
+ PyList_GetItem=python36.PyList_GetItem
+ PyList_GetSlice=python36.PyList_GetSlice
+ PyList_Insert=python36.PyList_Insert
+ PyList_New=python36.PyList_New
+ PyList_Reverse=python36.PyList_Reverse
+ PyList_SetItem=python36.PyList_SetItem
+ PyList_SetSlice=python36.PyList_SetSlice
+ PyList_Size=python36.PyList_Size
+ PyList_Sort=python36.PyList_Sort
+ PyList_Type=python36.PyList_Type DATA
+ PyLongRangeIter_Type=python36.PyLongRangeIter_Type DATA
+ PyLong_AsDouble=python36.PyLong_AsDouble
+ PyLong_AsLong=python36.PyLong_AsLong
+ PyLong_AsLongAndOverflow=python36.PyLong_AsLongAndOverflow
+ PyLong_AsLongLong=python36.PyLong_AsLongLong
+ PyLong_AsLongLongAndOverflow=python36.PyLong_AsLongLongAndOverflow
+ PyLong_AsSize_t=python36.PyLong_AsSize_t
+ PyLong_AsSsize_t=python36.PyLong_AsSsize_t
+ PyLong_AsUnsignedLong=python36.PyLong_AsUnsignedLong
+ PyLong_AsUnsignedLongLong=python36.PyLong_AsUnsignedLongLong
+ PyLong_AsUnsignedLongLongMask=python36.PyLong_AsUnsignedLongLongMask
+ PyLong_AsUnsignedLongMask=python36.PyLong_AsUnsignedLongMask
+ PyLong_AsVoidPtr=python36.PyLong_AsVoidPtr
+ PyLong_FromDouble=python36.PyLong_FromDouble
+ PyLong_FromLong=python36.PyLong_FromLong
+ PyLong_FromLongLong=python36.PyLong_FromLongLong
+ PyLong_FromSize_t=python36.PyLong_FromSize_t
+ PyLong_FromSsize_t=python36.PyLong_FromSsize_t
+ PyLong_FromString=python36.PyLong_FromString
+ PyLong_FromUnsignedLong=python36.PyLong_FromUnsignedLong
+ PyLong_FromUnsignedLongLong=python36.PyLong_FromUnsignedLongLong
+ PyLong_FromVoidPtr=python36.PyLong_FromVoidPtr
+ PyLong_GetInfo=python36.PyLong_GetInfo
+ PyLong_Type=python36.PyLong_Type DATA
+ PyMap_Type=python36.PyMap_Type DATA
+ PyMapping_Check=python36.PyMapping_Check
+ PyMapping_GetItemString=python36.PyMapping_GetItemString
+ PyMapping_HasKey=python36.PyMapping_HasKey
+ PyMapping_HasKeyString=python36.PyMapping_HasKeyString
+ PyMapping_Items=python36.PyMapping_Items
+ PyMapping_Keys=python36.PyMapping_Keys
+ PyMapping_Length=python36.PyMapping_Length
+ PyMapping_SetItemString=python36.PyMapping_SetItemString
+ PyMapping_Size=python36.PyMapping_Size
+ PyMapping_Values=python36.PyMapping_Values
+ PyMem_Free=python36.PyMem_Free
+ PyMem_Malloc=python36.PyMem_Malloc
+ PyMem_Realloc=python36.PyMem_Realloc
+ PyMemberDescr_Type=python36.PyMemberDescr_Type DATA
+ PyMemoryView_FromObject=python36.PyMemoryView_FromObject
+ PyMemoryView_GetContiguous=python36.PyMemoryView_GetContiguous
+ PyMemoryView_Type=python36.PyMemoryView_Type DATA
+ PyMethodDescr_Type=python36.PyMethodDescr_Type DATA
+ PyModule_AddIntConstant=python36.PyModule_AddIntConstant
+ PyModule_AddObject=python36.PyModule_AddObject
+ PyModule_AddStringConstant=python36.PyModule_AddStringConstant
+ PyModule_Create2=python36.PyModule_Create2
+ PyModule_GetDef=python36.PyModule_GetDef
+ PyModule_GetDict=python36.PyModule_GetDict
+ PyModule_GetFilename=python36.PyModule_GetFilename
+ PyModule_GetFilenameObject=python36.PyModule_GetFilenameObject
+ PyModule_GetName=python36.PyModule_GetName
+ PyModule_GetState=python36.PyModule_GetState
+ PyModule_New=python36.PyModule_New
+ PyModule_Type=python36.PyModule_Type DATA
+ PyModuleDef_Init=python36.PyModuleDef_Init
+ PyModuleDef_Type=python36.PyModuleDef_Type DATA
+ PyNullImporter_Type=python36.PyNullImporter_Type DATA
+ PyNumber_Absolute=python36.PyNumber_Absolute
+ PyNumber_Add=python36.PyNumber_Add
+ PyNumber_And=python36.PyNumber_And
+ PyNumber_AsSsize_t=python36.PyNumber_AsSsize_t
+ PyNumber_Check=python36.PyNumber_Check
+ PyNumber_Divmod=python36.PyNumber_Divmod
+ PyNumber_Float=python36.PyNumber_Float
+ PyNumber_FloorDivide=python36.PyNumber_FloorDivide
+ PyNumber_InPlaceAdd=python36.PyNumber_InPlaceAdd
+ PyNumber_InPlaceAnd=python36.PyNumber_InPlaceAnd
+ PyNumber_InPlaceFloorDivide=python36.PyNumber_InPlaceFloorDivide
+ PyNumber_InPlaceLshift=python36.PyNumber_InPlaceLshift
+ PyNumber_InPlaceMultiply=python36.PyNumber_InPlaceMultiply
+ PyNumber_InPlaceOr=python36.PyNumber_InPlaceOr
+ PyNumber_InPlacePower=python36.PyNumber_InPlacePower
+ PyNumber_InPlaceRemainder=python36.PyNumber_InPlaceRemainder
+ PyNumber_InPlaceRshift=python36.PyNumber_InPlaceRshift
+ PyNumber_InPlaceSubtract=python36.PyNumber_InPlaceSubtract
+ PyNumber_InPlaceTrueDivide=python36.PyNumber_InPlaceTrueDivide
+ PyNumber_InPlaceXor=python36.PyNumber_InPlaceXor
+ PyNumber_Index=python36.PyNumber_Index
+ PyNumber_Invert=python36.PyNumber_Invert
+ PyNumber_Long=python36.PyNumber_Long
+ PyNumber_Lshift=python36.PyNumber_Lshift
+ PyNumber_Multiply=python36.PyNumber_Multiply
+ PyNumber_Negative=python36.PyNumber_Negative
+ PyNumber_Or=python36.PyNumber_Or
+ PyNumber_Positive=python36.PyNumber_Positive
+ PyNumber_Power=python36.PyNumber_Power
+ PyNumber_Remainder=python36.PyNumber_Remainder
+ PyNumber_Rshift=python36.PyNumber_Rshift
+ PyNumber_Subtract=python36.PyNumber_Subtract
+ PyNumber_ToBase=python36.PyNumber_ToBase
+ PyNumber_TrueDivide=python36.PyNumber_TrueDivide
+ PyNumber_Xor=python36.PyNumber_Xor
+ PyOS_AfterFork=python36.PyOS_AfterFork
+ PyOS_InitInterrupts=python36.PyOS_InitInterrupts
+ PyOS_InputHook=python36.PyOS_InputHook DATA
+ PyOS_InterruptOccurred=python36.PyOS_InterruptOccurred
+ PyOS_ReadlineFunctionPointer=python36.PyOS_ReadlineFunctionPointer DATA
+ PyOS_double_to_string=python36.PyOS_double_to_string
+ PyOS_getsig=python36.PyOS_getsig
+ PyOS_mystricmp=python36.PyOS_mystricmp
+ PyOS_mystrnicmp=python36.PyOS_mystrnicmp
+ PyOS_setsig=python36.PyOS_setsig
+ PyOS_snprintf=python36.PyOS_snprintf
+ PyOS_string_to_double=python36.PyOS_string_to_double
+ PyOS_strtol=python36.PyOS_strtol
+ PyOS_strtoul=python36.PyOS_strtoul
+ PyOS_vsnprintf=python36.PyOS_vsnprintf
+ PyObject_ASCII=python36.PyObject_ASCII
+ PyObject_AsCharBuffer=python36.PyObject_AsCharBuffer
+ PyObject_AsFileDescriptor=python36.PyObject_AsFileDescriptor
+ PyObject_AsReadBuffer=python36.PyObject_AsReadBuffer
+ PyObject_AsWriteBuffer=python36.PyObject_AsWriteBuffer
+ PyObject_Bytes=python36.PyObject_Bytes
+ PyObject_Call=python36.PyObject_Call
+ PyObject_CallFunction=python36.PyObject_CallFunction
+ PyObject_CallFunctionObjArgs=python36.PyObject_CallFunctionObjArgs
+ PyObject_CallMethod=python36.PyObject_CallMethod
+ PyObject_CallMethodObjArgs=python36.PyObject_CallMethodObjArgs
+ PyObject_CallObject=python36.PyObject_CallObject
+ PyObject_CheckReadBuffer=python36.PyObject_CheckReadBuffer
+ PyObject_ClearWeakRefs=python36.PyObject_ClearWeakRefs
+ PyObject_DelItem=python36.PyObject_DelItem
+ PyObject_DelItemString=python36.PyObject_DelItemString
+ PyObject_Dir=python36.PyObject_Dir
+ PyObject_Format=python36.PyObject_Format
+ PyObject_Free=python36.PyObject_Free
+ PyObject_GC_Del=python36.PyObject_GC_Del
+ PyObject_GC_Track=python36.PyObject_GC_Track
+ PyObject_GC_UnTrack=python36.PyObject_GC_UnTrack
+ PyObject_GenericGetAttr=python36.PyObject_GenericGetAttr
+ PyObject_GenericSetAttr=python36.PyObject_GenericSetAttr
+ PyObject_GetAttr=python36.PyObject_GetAttr
+ PyObject_GetAttrString=python36.PyObject_GetAttrString
+ PyObject_GetItem=python36.PyObject_GetItem
+ PyObject_GetIter=python36.PyObject_GetIter
+ PyObject_HasAttr=python36.PyObject_HasAttr
+ PyObject_HasAttrString=python36.PyObject_HasAttrString
+ PyObject_Hash=python36.PyObject_Hash
+ PyObject_HashNotImplemented=python36.PyObject_HashNotImplemented
+ PyObject_Init=python36.PyObject_Init
+ PyObject_InitVar=python36.PyObject_InitVar
+ PyObject_IsInstance=python36.PyObject_IsInstance
+ PyObject_IsSubclass=python36.PyObject_IsSubclass
+ PyObject_IsTrue=python36.PyObject_IsTrue
+ PyObject_Length=python36.PyObject_Length
+ PyObject_Malloc=python36.PyObject_Malloc
+ PyObject_Not=python36.PyObject_Not
+ PyObject_Realloc=python36.PyObject_Realloc
+ PyObject_Repr=python36.PyObject_Repr
+ PyObject_RichCompare=python36.PyObject_RichCompare
+ PyObject_RichCompareBool=python36.PyObject_RichCompareBool
+ PyObject_SelfIter=python36.PyObject_SelfIter
+ PyObject_SetAttr=python36.PyObject_SetAttr
+ PyObject_SetAttrString=python36.PyObject_SetAttrString
+ PyObject_SetItem=python36.PyObject_SetItem
+ PyObject_Size=python36.PyObject_Size
+ PyObject_Str=python36.PyObject_Str
+ PyObject_Type=python36.PyObject_Type DATA
+ PyODict_DelItem=python36.PyODict_DelItem
+ PyODict_New=python36.PyODict_New
+ PyODict_SetItem=python36.PyODict_SetItem
+ PyODict_Type=python36.PyODict_Type DATA
+ PyODictItems_Type=python36.PyODictItems_Type DATA
+ PyODictIter_Type=python36.PyODictIter_Type DATA
+ PyODictKeys_Type=python36.PyODictKeys_Type DATA
+ PyODictValues_Type=python36.PyODictValues_Type DATA
+ PyParser_SimpleParseFileFlags=python36.PyParser_SimpleParseFileFlags
+ PyParser_SimpleParseStringFlags=python36.PyParser_SimpleParseStringFlags
+ PyProperty_Type=python36.PyProperty_Type DATA
+ PyRangeIter_Type=python36.PyRangeIter_Type DATA
+ PyRange_Type=python36.PyRange_Type DATA
+ PyReversed_Type=python36.PyReversed_Type DATA
+ PySeqIter_New=python36.PySeqIter_New
+ PySeqIter_Type=python36.PySeqIter_Type DATA
+ PySequence_Check=python36.PySequence_Check
+ PySequence_Concat=python36.PySequence_Concat
+ PySequence_Contains=python36.PySequence_Contains
+ PySequence_Count=python36.PySequence_Count
+ PySequence_DelItem=python36.PySequence_DelItem
+ PySequence_DelSlice=python36.PySequence_DelSlice
+ PySequence_Fast=python36.PySequence_Fast
+ PySequence_GetItem=python36.PySequence_GetItem
+ PySequence_GetSlice=python36.PySequence_GetSlice
+ PySequence_In=python36.PySequence_In
+ PySequence_InPlaceConcat=python36.PySequence_InPlaceConcat
+ PySequence_InPlaceRepeat=python36.PySequence_InPlaceRepeat
+ PySequence_Index=python36.PySequence_Index
+ PySequence_Length=python36.PySequence_Length
+ PySequence_List=python36.PySequence_List
+ PySequence_Repeat=python36.PySequence_Repeat
+ PySequence_SetItem=python36.PySequence_SetItem
+ PySequence_SetSlice=python36.PySequence_SetSlice
+ PySequence_Size=python36.PySequence_Size
+ PySequence_Tuple=python36.PySequence_Tuple
+ PySetIter_Type=python36.PySetIter_Type DATA
+ PySet_Add=python36.PySet_Add
+ PySet_Clear=python36.PySet_Clear
+ PySet_Contains=python36.PySet_Contains
+ PySet_Discard=python36.PySet_Discard
+ PySet_New=python36.PySet_New
+ PySet_Pop=python36.PySet_Pop
+ PySet_Size=python36.PySet_Size
+ PySet_Type=python36.PySet_Type DATA
+ PySlice_GetIndices=python36.PySlice_GetIndices
+ PySlice_GetIndicesEx=python36.PySlice_GetIndicesEx
+ PySlice_New=python36.PySlice_New
+ PySlice_Type=python36.PySlice_Type DATA
+ PySortWrapper_Type=python36.PySortWrapper_Type DATA
+ PyState_FindModule=python36.PyState_FindModule
+ PyState_AddModule=python36.PyState_AddModule
+ PyState_RemoveModule=python36.PyState_RemoveModule
+ PyStructSequence_GetItem=python36.PyStructSequence_GetItem
+ PyStructSequence_New=python36.PyStructSequence_New
+ PyStructSequence_NewType=python36.PyStructSequence_NewType
+ PyStructSequence_SetItem=python36.PyStructSequence_SetItem
+ PySuper_Type=python36.PySuper_Type DATA
+ PySys_AddWarnOption=python36.PySys_AddWarnOption
+ PySys_AddWarnOptionUnicode=python36.PySys_AddWarnOptionUnicode
+ PySys_FormatStderr=python36.PySys_FormatStderr
+ PySys_FormatStdout=python36.PySys_FormatStdout
+ PySys_GetObject=python36.PySys_GetObject
+ PySys_HasWarnOptions=python36.PySys_HasWarnOptions
+ PySys_ResetWarnOptions=python36.PySys_ResetWarnOptions
+ PySys_SetArgv=python36.PySys_SetArgv
+ PySys_SetArgvEx=python36.PySys_SetArgvEx
+ PySys_SetObject=python36.PySys_SetObject
+ PySys_SetPath=python36.PySys_SetPath
+ PySys_WriteStderr=python36.PySys_WriteStderr
+ PySys_WriteStdout=python36.PySys_WriteStdout
+ PyThreadState_Clear=python36.PyThreadState_Clear
+ PyThreadState_Delete=python36.PyThreadState_Delete
+ PyThreadState_DeleteCurrent=python36.PyThreadState_DeleteCurrent
+ PyThreadState_Get=python36.PyThreadState_Get
+ PyThreadState_GetDict=python36.PyThreadState_GetDict
+ PyThreadState_New=python36.PyThreadState_New
+ PyThreadState_SetAsyncExc=python36.PyThreadState_SetAsyncExc
+ PyThreadState_Swap=python36.PyThreadState_Swap
+ PyTraceBack_Here=python36.PyTraceBack_Here
+ PyTraceBack_Print=python36.PyTraceBack_Print
+ PyTraceBack_Type=python36.PyTraceBack_Type DATA
+ PyTupleIter_Type=python36.PyTupleIter_Type DATA
+ PyTuple_ClearFreeList=python36.PyTuple_ClearFreeList
+ PyTuple_GetItem=python36.PyTuple_GetItem
+ PyTuple_GetSlice=python36.PyTuple_GetSlice
+ PyTuple_New=python36.PyTuple_New
+ PyTuple_Pack=python36.PyTuple_Pack
+ PyTuple_SetItem=python36.PyTuple_SetItem
+ PyTuple_Size=python36.PyTuple_Size
+ PyTuple_Type=python36.PyTuple_Type DATA
+ PyType_ClearCache=python36.PyType_ClearCache
+ PyType_FromSpec=python36.PyType_FromSpec
+ PyType_FromSpecWithBases=python36.PyType_FromSpecWithBases
+ PyType_GenericAlloc=python36.PyType_GenericAlloc
+ PyType_GenericNew=python36.PyType_GenericNew
+ PyType_GetFlags=python36.PyType_GetFlags
+ PyType_GetSlot=python36.PyType_GetSlot
+ PyType_IsSubtype=python36.PyType_IsSubtype
+ PyType_Modified=python36.PyType_Modified
+ PyType_Ready=python36.PyType_Ready
+ PyType_Type=python36.PyType_Type DATA
+ PyUnicodeDecodeError_Create=python36.PyUnicodeDecodeError_Create
+ PyUnicodeDecodeError_GetEncoding=python36.PyUnicodeDecodeError_GetEncoding
+ PyUnicodeDecodeError_GetEnd=python36.PyUnicodeDecodeError_GetEnd
+ PyUnicodeDecodeError_GetObject=python36.PyUnicodeDecodeError_GetObject
+ PyUnicodeDecodeError_GetReason=python36.PyUnicodeDecodeError_GetReason
+ PyUnicodeDecodeError_GetStart=python36.PyUnicodeDecodeError_GetStart
+ PyUnicodeDecodeError_SetEnd=python36.PyUnicodeDecodeError_SetEnd
+ PyUnicodeDecodeError_SetReason=python36.PyUnicodeDecodeError_SetReason
+ PyUnicodeDecodeError_SetStart=python36.PyUnicodeDecodeError_SetStart
+ PyUnicodeEncodeError_GetEncoding=python36.PyUnicodeEncodeError_GetEncoding
+ PyUnicodeEncodeError_GetEnd=python36.PyUnicodeEncodeError_GetEnd
+ PyUnicodeEncodeError_GetObject=python36.PyUnicodeEncodeError_GetObject
+ PyUnicodeEncodeError_GetReason=python36.PyUnicodeEncodeError_GetReason
+ PyUnicodeEncodeError_GetStart=python36.PyUnicodeEncodeError_GetStart
+ PyUnicodeEncodeError_SetEnd=python36.PyUnicodeEncodeError_SetEnd
+ PyUnicodeEncodeError_SetReason=python36.PyUnicodeEncodeError_SetReason
+ PyUnicodeEncodeError_SetStart=python36.PyUnicodeEncodeError_SetStart
+ PyUnicodeIter_Type=python36.PyUnicodeIter_Type DATA
+ PyUnicodeTranslateError_GetEnd=python36.PyUnicodeTranslateError_GetEnd
+ PyUnicodeTranslateError_GetObject=python36.PyUnicodeTranslateError_GetObject
+ PyUnicodeTranslateError_GetReason=python36.PyUnicodeTranslateError_GetReason
+ PyUnicodeTranslateError_GetStart=python36.PyUnicodeTranslateError_GetStart
+ PyUnicodeTranslateError_SetEnd=python36.PyUnicodeTranslateError_SetEnd
+ PyUnicodeTranslateError_SetReason=python36.PyUnicodeTranslateError_SetReason
+ PyUnicodeTranslateError_SetStart=python36.PyUnicodeTranslateError_SetStart
+ PyUnicode_Append=python36.PyUnicode_Append
+ PyUnicode_AppendAndDel=python36.PyUnicode_AppendAndDel
+ PyUnicode_AsASCIIString=python36.PyUnicode_AsASCIIString
+ PyUnicode_AsCharmapString=python36.PyUnicode_AsCharmapString
+ PyUnicode_AsDecodedObject=python36.PyUnicode_AsDecodedObject
+ PyUnicode_AsDecodedUnicode=python36.PyUnicode_AsDecodedUnicode
+ PyUnicode_AsEncodedObject=python36.PyUnicode_AsEncodedObject
+ PyUnicode_AsEncodedString=python36.PyUnicode_AsEncodedString
+ PyUnicode_AsEncodedUnicode=python36.PyUnicode_AsEncodedUnicode
+ PyUnicode_AsLatin1String=python36.PyUnicode_AsLatin1String
+ PyUnicode_AsRawUnicodeEscapeString=python36.PyUnicode_AsRawUnicodeEscapeString
+ PyUnicode_AsUTF16String=python36.PyUnicode_AsUTF16String
+ PyUnicode_AsUTF32String=python36.PyUnicode_AsUTF32String
+ PyUnicode_AsUTF8String=python36.PyUnicode_AsUTF8String
+ PyUnicode_AsUnicodeEscapeString=python36.PyUnicode_AsUnicodeEscapeString
+ PyUnicode_AsWideChar=python36.PyUnicode_AsWideChar
+ PyUnicode_ClearFreelist=python36.PyUnicode_ClearFreelist
+ PyUnicode_Compare=python36.PyUnicode_Compare
+ PyUnicode_Concat=python36.PyUnicode_Concat
+ PyUnicode_Contains=python36.PyUnicode_Contains
+ PyUnicode_Count=python36.PyUnicode_Count
+ PyUnicode_Decode=python36.PyUnicode_Decode
+ PyUnicode_DecodeASCII=python36.PyUnicode_DecodeASCII
+ PyUnicode_DecodeCharmap=python36.PyUnicode_DecodeCharmap
+ PyUnicode_DecodeFSDefault=python36.PyUnicode_DecodeFSDefault
+ PyUnicode_DecodeFSDefaultAndSize=python36.PyUnicode_DecodeFSDefaultAndSize
+ PyUnicode_DecodeLatin1=python36.PyUnicode_DecodeLatin1
+ PyUnicode_DecodeRawUnicodeEscape=python36.PyUnicode_DecodeRawUnicodeEscape
+ PyUnicode_DecodeUTF16=python36.PyUnicode_DecodeUTF16
+ PyUnicode_DecodeUTF16Stateful=python36.PyUnicode_DecodeUTF16Stateful
+ PyUnicode_DecodeUTF32=python36.PyUnicode_DecodeUTF32
+ PyUnicode_DecodeUTF32Stateful=python36.PyUnicode_DecodeUTF32Stateful
+ PyUnicode_DecodeUTF8=python36.PyUnicode_DecodeUTF8
+ PyUnicode_DecodeUTF8Stateful=python36.PyUnicode_DecodeUTF8Stateful
+ PyUnicode_DecodeUnicodeEscape=python36.PyUnicode_DecodeUnicodeEscape
+ PyUnicode_FSConverter=python36.PyUnicode_FSConverter
+ PyUnicode_FSDecoder=python36.PyUnicode_FSDecoder
+ PyUnicode_Find=python36.PyUnicode_Find
+ PyUnicode_Format=python36.PyUnicode_Format
+ PyUnicode_FromEncodedObject=python36.PyUnicode_FromEncodedObject
+ PyUnicode_FromFormat=python36.PyUnicode_FromFormat
+ PyUnicode_FromFormatV=python36.PyUnicode_FromFormatV
+ PyUnicode_FromObject=python36.PyUnicode_FromObject
+ PyUnicode_FromOrdinal=python36.PyUnicode_FromOrdinal
+ PyUnicode_FromString=python36.PyUnicode_FromString
+ PyUnicode_FromStringAndSize=python36.PyUnicode_FromStringAndSize
+ PyUnicode_FromWideChar=python36.PyUnicode_FromWideChar
+ PyUnicode_GetDefaultEncoding=python36.PyUnicode_GetDefaultEncoding
+ PyUnicode_GetSize=python36.PyUnicode_GetSize
+ PyUnicode_IsIdentifier=python36.PyUnicode_IsIdentifier
+ PyUnicode_Join=python36.PyUnicode_Join
+ PyUnicode_Partition=python36.PyUnicode_Partition
+ PyUnicode_RPartition=python36.PyUnicode_RPartition
+ PyUnicode_RSplit=python36.PyUnicode_RSplit
+ PyUnicode_Replace=python36.PyUnicode_Replace
+ PyUnicode_Resize=python36.PyUnicode_Resize
+ PyUnicode_RichCompare=python36.PyUnicode_RichCompare
+ PyUnicode_SetDefaultEncoding=python36.PyUnicode_SetDefaultEncoding
+ PyUnicode_Split=python36.PyUnicode_Split
+ PyUnicode_Splitlines=python36.PyUnicode_Splitlines
+ PyUnicode_Tailmatch=python36.PyUnicode_Tailmatch
+ PyUnicode_Translate=python36.PyUnicode_Translate
+ PyUnicode_BuildEncodingMap=python36.PyUnicode_BuildEncodingMap
+ PyUnicode_CompareWithASCIIString=python36.PyUnicode_CompareWithASCIIString
+ PyUnicode_DecodeUTF7=python36.PyUnicode_DecodeUTF7
+ PyUnicode_DecodeUTF7Stateful=python36.PyUnicode_DecodeUTF7Stateful
+ PyUnicode_EncodeFSDefault=python36.PyUnicode_EncodeFSDefault
+ PyUnicode_InternFromString=python36.PyUnicode_InternFromString
+ PyUnicode_InternImmortal=python36.PyUnicode_InternImmortal
+ PyUnicode_InternInPlace=python36.PyUnicode_InternInPlace
+ PyUnicode_Type=python36.PyUnicode_Type DATA
+ PyWeakref_GetObject=python36.PyWeakref_GetObject DATA
+ PyWeakref_NewProxy=python36.PyWeakref_NewProxy
+ PyWeakref_NewRef=python36.PyWeakref_NewRef
+ PyWrapperDescr_Type=python36.PyWrapperDescr_Type DATA
+ PyWrapper_New=python36.PyWrapper_New
+ PyZip_Type=python36.PyZip_Type DATA
+ Py_AddPendingCall=python36.Py_AddPendingCall
+ Py_AtExit=python36.Py_AtExit
+ Py_BuildValue=python36.Py_BuildValue
+ Py_CompileString=python36.Py_CompileString
+ Py_DecRef=python36.Py_DecRef
+ Py_EndInterpreter=python36.Py_EndInterpreter
+ Py_Exit=python36.Py_Exit
+ Py_FatalError=python36.Py_FatalError
+ Py_FileSystemDefaultEncoding=python36.Py_FileSystemDefaultEncoding DATA
+ Py_Finalize=python36.Py_Finalize
+ Py_GetBuildInfo=python36.Py_GetBuildInfo
+ Py_GetCompiler=python36.Py_GetCompiler
+ Py_GetCopyright=python36.Py_GetCopyright
+ Py_GetExecPrefix=python36.Py_GetExecPrefix
+ Py_GetPath=python36.Py_GetPath
+ Py_GetPlatform=python36.Py_GetPlatform
+ Py_GetPrefix=python36.Py_GetPrefix
+ Py_GetProgramFullPath=python36.Py_GetProgramFullPath
+ Py_GetProgramName=python36.Py_GetProgramName
+ Py_GetPythonHome=python36.Py_GetPythonHome
+ Py_GetRecursionLimit=python36.Py_GetRecursionLimit
+ Py_GetVersion=python36.Py_GetVersion
+ Py_HasFileSystemDefaultEncoding=python36.Py_HasFileSystemDefaultEncoding DATA
+ Py_IncRef=python36.Py_IncRef
+ Py_Initialize=python36.Py_Initialize
+ Py_InitializeEx=python36.Py_InitializeEx
+ Py_IsInitialized=python36.Py_IsInitialized
+ Py_Main=python36.Py_Main
+ Py_MakePendingCalls=python36.Py_MakePendingCalls
+ Py_NewInterpreter=python36.Py_NewInterpreter
+ Py_ReprEnter=python36.Py_ReprEnter
+ Py_ReprLeave=python36.Py_ReprLeave
+ Py_SetProgramName=python36.Py_SetProgramName
+ Py_SetPythonHome=python36.Py_SetPythonHome
+ Py_SetRecursionLimit=python36.Py_SetRecursionLimit
+ Py_SymtableString=python36.Py_SymtableString
+ Py_VaBuildValue=python36.Py_VaBuildValue
+ _PyErr_BadInternalCall=python36._PyErr_BadInternalCall
+ _PyObject_CallFunction_SizeT=python36._PyObject_CallFunction_SizeT
+ _PyObject_CallMethod_SizeT=python36._PyObject_CallMethod_SizeT
+ _PyObject_GC_Malloc=python36._PyObject_GC_Malloc
+ _PyObject_GC_New=python36._PyObject_GC_New
+ _PyObject_GC_NewVar=python36._PyObject_GC_NewVar
+ _PyObject_GC_Resize=python36._PyObject_GC_Resize
+ _PyObject_New=python36._PyObject_New
+ _PyObject_NewVar=python36._PyObject_NewVar
+ _PyState_AddModule=python36._PyState_AddModule
+ _PyThreadState_Init=python36._PyThreadState_Init
+ _PyThreadState_Prealloc=python36._PyThreadState_Prealloc
+ _PyTrash_delete_later=python36._PyTrash_delete_later DATA
+ _PyTrash_delete_nesting=python36._PyTrash_delete_nesting DATA
+ _PyTrash_deposit_object=python36._PyTrash_deposit_object
+ _PyTrash_destroy_chain=python36._PyTrash_destroy_chain
+ _PyWeakref_CallableProxyType=python36._PyWeakref_CallableProxyType DATA
+ _PyWeakref_ProxyType=python36._PyWeakref_ProxyType DATA
+ _PyWeakref_RefType=python36._PyWeakref_RefType DATA
+ _Py_BuildValue_SizeT=python36._Py_BuildValue_SizeT
+ _Py_CheckRecursionLimit=python36._Py_CheckRecursionLimit DATA
+ _Py_CheckRecursiveCall=python36._Py_CheckRecursiveCall
+ _Py_Dealloc=python36._Py_Dealloc
+ _Py_EllipsisObject=python36._Py_EllipsisObject DATA
+ _Py_FalseStruct=python36._Py_FalseStruct DATA
+ _Py_NoneStruct=python36._Py_NoneStruct DATA
+ _Py_NotImplementedStruct=python36._Py_NotImplementedStruct DATA
+ _Py_SwappedOp=python36._Py_SwappedOp DATA
+ _Py_TrueStruct=python36._Py_TrueStruct DATA
+ _Py_VaBuildValue_SizeT=python36._Py_VaBuildValue_SizeT
+ _PyArg_Parse_SizeT=python36._PyArg_Parse_SizeT
+ _PyArg_ParseTuple_SizeT=python36._PyArg_ParseTuple_SizeT
+ _PyArg_ParseTupleAndKeywords_SizeT=python36._PyArg_ParseTupleAndKeywords_SizeT
+ _PyArg_VaParse_SizeT=python36._PyArg_VaParse_SizeT
+ _PyArg_VaParseTupleAndKeywords_SizeT=python36._PyArg_VaParseTupleAndKeywords_SizeT
+ _Py_BuildValue_SizeT=python36._Py_BuildValue_SizeT
diff --git a/PCbuild/prepare_ssl.bat b/PCbuild/prepare_ssl.bat
index c08a9f3..3153615 100644
--- a/PCbuild/prepare_ssl.bat
+++ b/PCbuild/prepare_ssl.bat
@@ -3,10 +3,10 @@
if %1 EQU Debug (
shift
set HOST_PYTHON=python_d.exe
- if not exist python35_d.dll exit 1
+ if not exist python36_d.dll exit 1
) ELSE (
set HOST_PYTHON=python.exe
- if not exist python35.dll exit 1
+ if not exist python36.dll exit 1
)
)
%HOST_PYTHON% prepare_ssl.py %1
diff --git a/PCbuild/readme.txt b/PCbuild/readme.txt
index 09a996f..5be66f4 100644
--- a/PCbuild/readme.txt
+++ b/PCbuild/readme.txt
@@ -48,7 +48,7 @@
Used to build Python with extra debugging capabilities, equivalent
to using ./configure --with-pydebug on UNIX. All binaries built
using this configuration have "_d" added to their name:
- python35_d.dll, python_d.exe, parser_d.pyd, and so on. Both the
+ python36_d.dll, python_d.exe, parser_d.pyd, and so on. Both the
build and rt (run test) batch files in this directory accept a -d
option for debug builds. If you are building Python to help with
development of CPython, you will most likely use this configuration.
diff --git a/PCbuild/xxlimited.vcxproj b/PCbuild/xxlimited.vcxproj
index 0144fa9..9dbdc77 100644
--- a/PCbuild/xxlimited.vcxproj
+++ b/PCbuild/xxlimited.vcxproj
@@ -62,7 +62,7 @@
</PropertyGroup>
<ItemDefinitionGroup>
<ClCompile>
- <PreprocessorDefinitions>%(PreprocessorDefinitions);Py_LIMITED_API=0x03050000</PreprocessorDefinitions>
+ <PreprocessorDefinitions>%(PreprocessorDefinitions);Py_LIMITED_API=0x03060000</PreprocessorDefinitions>
</ClCompile>
<Link>
<AdditionalDependencies>wsock32.lib;%(AdditionalDependencies)</AdditionalDependencies>
diff --git a/Parser/asdl_c.py b/Parser/asdl_c.py
index a5e35d9..d597122 100755
--- a/Parser/asdl_c.py
+++ b/Parser/asdl_c.py
@@ -898,7 +898,7 @@
return 1;
}
- i = (int)PyLong_AsLong(obj);
+ i = _PyLong_AsInt(obj);
if (i == -1 && PyErr_Occurred())
return 1;
*out = i;
diff --git a/Python/Python-ast.c b/Python/Python-ast.c
index 8a2dc7c..fd7f17e 100644
--- a/Python/Python-ast.c
+++ b/Python/Python-ast.c
@@ -769,7 +769,7 @@
return 1;
}
- i = (int)PyLong_AsLong(obj);
+ i = _PyLong_AsInt(obj);
if (i == -1 && PyErr_Occurred())
return 1;
*out = i;
diff --git a/Python/ast.c b/Python/ast.c
index b2f09b9..1f7ddfc 100644
--- a/Python/ast.c
+++ b/Python/ast.c
@@ -513,7 +513,7 @@
/* Data structure used internally */
struct compiling {
char *c_encoding; /* source encoding */
- PyArena *c_arena; /* arena for allocating memeory */
+ PyArena *c_arena; /* Arena for allocating memory. */
PyObject *c_filename; /* filename */
PyObject *c_normalize; /* Normalization function from unicodedata. */
PyObject *c_normalize_args; /* Normalization argument tuple. */
@@ -1262,16 +1262,20 @@
and varargslist (lambda definition).
parameters: '(' [typedargslist] ')'
- typedargslist: ((tfpdef ['=' test] ',')*
- ('*' [tfpdef] (',' tfpdef ['=' test])* [',' '**' tfpdef]
- | '**' tfpdef)
- | tfpdef ['=' test] (',' tfpdef ['=' test])* [','])
+ typedargslist: (tfpdef ['=' test] (',' tfpdef ['=' test])* [',' [
+ '*' [tfpdef] (',' tfpdef ['=' test])* [',' ['**' tfpdef [',']]]
+ | '**' tfpdef [',']]]
+ | '*' [tfpdef] (',' tfpdef ['=' test])* [',' ['**' tfpdef [',']]]
+ | '**' tfpdef [','])
tfpdef: NAME [':' test]
- varargslist: ((vfpdef ['=' test] ',')*
- ('*' [vfpdef] (',' vfpdef ['=' test])* [',' '**' vfpdef]
- | '**' vfpdef)
- | vfpdef ['=' test] (',' vfpdef ['=' test])* [','])
+ varargslist: (vfpdef ['=' test] (',' vfpdef ['=' test])* [',' [
+ '*' [vfpdef] (',' vfpdef ['=' test])* [',' ['**' vfpdef [',']]]
+ | '**' vfpdef [',']]]
+ | '*' [vfpdef] (',' vfpdef ['=' test])* [',' ['**' vfpdef [',']]]
+ | '**' vfpdef [',']
+ )
vfpdef: NAME
+
*/
int i, j, k, nposargs = 0, nkwonlyargs = 0;
int nposdefaults = 0, found_default = 0;
@@ -1373,7 +1377,8 @@
i += 2; /* the name and the comma */
break;
case STAR:
- if (i+1 >= NCH(n)) {
+ if (i+1 >= NCH(n) ||
+ (i+2 == NCH(n) && TYPE(CHILD(n, i+1)) == COMMA)) {
ast_error(c, CHILD(n, i),
"named arguments must follow bare *");
return NULL;
@@ -2035,6 +2040,7 @@
PyOS_snprintf(buf, sizeof(buf), "(%s) %s", errtype, s);
Py_DECREF(errstr);
} else {
+ PyErr_Clear();
PyOS_snprintf(buf, sizeof(buf), "(%s) unknown error", errtype);
}
ast_error(c, n, buf);
diff --git a/Python/bltinmodule.c b/Python/bltinmodule.c
index 2f22209..2038d2b 100644
--- a/Python/bltinmodule.c
+++ b/Python/bltinmodule.c
@@ -1158,13 +1158,14 @@
PyObject *result;
Py_ssize_t numargs, i;
- numargs = PyTuple_Size(lz->iters);
+ numargs = PyTuple_GET_SIZE(lz->iters);
argtuple = PyTuple_New(numargs);
if (argtuple == NULL)
return NULL;
for (i=0 ; i<numargs ; i++) {
- val = PyIter_Next(PyTuple_GET_ITEM(lz->iters, i));
+ PyObject *it = PyTuple_GET_ITEM(lz->iters, i);
+ val = Py_TYPE(it)->tp_iternext(it);
if (val == NULL) {
Py_DECREF(argtuple);
return NULL;
diff --git a/Python/compile.c b/Python/compile.c
index 97bb12e..a6884ec 100644
--- a/Python/compile.c
+++ b/Python/compile.c
@@ -3628,9 +3628,9 @@
BLOCK
finally:
if an exception was raised:
- exc = copy of (exception, instance, traceback)
+ exc = copy of (exception, instance, traceback)
else:
- exc = (None, None, None)
+ exc = (None, None, None)
if not (await exit(*exc)):
raise
*/
diff --git a/Python/graminit.c b/Python/graminit.c
index 8212b2a..354dc12 100644
--- a/Python/graminit.c
+++ b/Python/graminit.c
@@ -204,11 +204,13 @@
{32, 7},
{0, 6},
};
-static arc arcs_9_7[2] = {
+static arc arcs_9_7[3] = {
{30, 12},
{34, 3},
+ {0, 7},
};
-static arc arcs_9_8[1] = {
+static arc arcs_9_8[2] = {
+ {32, 13},
{0, 8},
};
static arc arcs_9_9[2] = {
@@ -221,35 +223,39 @@
{0, 10},
};
static arc arcs_9_11[3] = {
- {30, 13},
- {32, 14},
+ {30, 14},
+ {32, 15},
{0, 11},
};
static arc arcs_9_12[3] = {
{32, 7},
- {31, 15},
+ {31, 16},
{0, 12},
};
-static arc arcs_9_13[2] = {
- {32, 14},
+static arc arcs_9_13[1] = {
{0, 13},
};
static arc arcs_9_14[2] = {
- {30, 16},
- {34, 3},
+ {32, 15},
+ {0, 14},
};
-static arc arcs_9_15[1] = {
+static arc arcs_9_15[3] = {
+ {30, 17},
+ {34, 3},
+ {0, 15},
+};
+static arc arcs_9_16[1] = {
{26, 6},
};
-static arc arcs_9_16[3] = {
- {32, 14},
- {31, 17},
- {0, 16},
+static arc arcs_9_17[3] = {
+ {32, 15},
+ {31, 18},
+ {0, 17},
};
-static arc arcs_9_17[1] = {
- {26, 13},
+static arc arcs_9_18[1] = {
+ {26, 14},
};
-static state states_9[18] = {
+static state states_9[19] = {
{3, arcs_9_0},
{3, arcs_9_1},
{3, arcs_9_2},
@@ -257,17 +263,18 @@
{1, arcs_9_4},
{4, arcs_9_5},
{2, arcs_9_6},
- {2, arcs_9_7},
- {1, arcs_9_8},
+ {3, arcs_9_7},
+ {2, arcs_9_8},
{2, arcs_9_9},
{3, arcs_9_10},
{3, arcs_9_11},
{3, arcs_9_12},
- {2, arcs_9_13},
+ {1, arcs_9_13},
{2, arcs_9_14},
- {1, arcs_9_15},
- {3, arcs_9_16},
- {1, arcs_9_17},
+ {3, arcs_9_15},
+ {1, arcs_9_16},
+ {3, arcs_9_17},
+ {1, arcs_9_18},
};
static arc arcs_10_0[1] = {
{23, 1},
@@ -319,11 +326,13 @@
{32, 7},
{0, 6},
};
-static arc arcs_11_7[2] = {
+static arc arcs_11_7[3] = {
{36, 12},
{34, 3},
+ {0, 7},
};
-static arc arcs_11_8[1] = {
+static arc arcs_11_8[2] = {
+ {32, 13},
{0, 8},
};
static arc arcs_11_9[2] = {
@@ -336,35 +345,39 @@
{0, 10},
};
static arc arcs_11_11[3] = {
- {36, 13},
- {32, 14},
+ {36, 14},
+ {32, 15},
{0, 11},
};
static arc arcs_11_12[3] = {
{32, 7},
- {31, 15},
+ {31, 16},
{0, 12},
};
-static arc arcs_11_13[2] = {
- {32, 14},
+static arc arcs_11_13[1] = {
{0, 13},
};
static arc arcs_11_14[2] = {
- {36, 16},
- {34, 3},
+ {32, 15},
+ {0, 14},
};
-static arc arcs_11_15[1] = {
+static arc arcs_11_15[3] = {
+ {36, 17},
+ {34, 3},
+ {0, 15},
+};
+static arc arcs_11_16[1] = {
{26, 6},
};
-static arc arcs_11_16[3] = {
- {32, 14},
- {31, 17},
- {0, 16},
+static arc arcs_11_17[3] = {
+ {32, 15},
+ {31, 18},
+ {0, 17},
};
-static arc arcs_11_17[1] = {
- {26, 13},
+static arc arcs_11_18[1] = {
+ {26, 14},
};
-static state states_11[18] = {
+static state states_11[19] = {
{3, arcs_11_0},
{3, arcs_11_1},
{3, arcs_11_2},
@@ -372,17 +385,18 @@
{1, arcs_11_4},
{4, arcs_11_5},
{2, arcs_11_6},
- {2, arcs_11_7},
- {1, arcs_11_8},
+ {3, arcs_11_7},
+ {2, arcs_11_8},
{2, arcs_11_9},
{3, arcs_11_10},
{3, arcs_11_11},
{3, arcs_11_12},
- {2, arcs_11_13},
+ {1, arcs_11_13},
{2, arcs_11_14},
- {1, arcs_11_15},
- {3, arcs_11_16},
- {1, arcs_11_17},
+ {3, arcs_11_15},
+ {1, arcs_11_16},
+ {3, arcs_11_17},
+ {1, arcs_11_18},
};
static arc arcs_12_0[1] = {
{23, 1},
@@ -1879,11 +1893,11 @@
"\000\000\100\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000"},
{264, "parameters", 0, 4, states_8,
"\000\040\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000"},
- {265, "typedargslist", 0, 18, states_9,
+ {265, "typedargslist", 0, 19, states_9,
"\000\000\200\000\006\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000"},
{266, "tfpdef", 0, 4, states_10,
"\000\000\200\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000"},
- {267, "varargslist", 0, 18, states_11,
+ {267, "varargslist", 0, 19, states_11,
"\000\000\200\000\006\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000"},
{268, "vfpdef", 0, 2, states_12,
"\000\000\200\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000\000"},
diff --git a/Python/pythonrun.c b/Python/pythonrun.c
index ebedd12..1a5dab5 100644
--- a/Python/pythonrun.c
+++ b/Python/pythonrun.c
@@ -431,7 +431,7 @@
parse_syntax_error(PyObject *err, PyObject **message, PyObject **filename,
int *lineno, int *offset, PyObject **text)
{
- long hold;
+ int hold;
PyObject *v;
_Py_IDENTIFIER(msg);
_Py_IDENTIFIER(filename);
@@ -464,11 +464,11 @@
v = _PyObject_GetAttrId(err, &PyId_lineno);
if (!v)
goto finally;
- hold = PyLong_AsLong(v);
+ hold = _PyLong_AsInt(v);
Py_DECREF(v);
if (hold < 0 && PyErr_Occurred())
goto finally;
- *lineno = (int)hold;
+ *lineno = hold;
v = _PyObject_GetAttrId(err, &PyId_offset);
if (!v)
@@ -477,11 +477,11 @@
*offset = -1;
Py_DECREF(v);
} else {
- hold = PyLong_AsLong(v);
+ hold = _PyLong_AsInt(v);
Py_DECREF(v);
if (hold < 0 && PyErr_Occurred())
goto finally;
- *offset = (int)hold;
+ *offset = hold;
}
v = _PyObject_GetAttrId(err, &PyId_text);
diff --git a/Python/pytime.c b/Python/pytime.c
index 77db204..9d0b0fa 100644
--- a/Python/pytime.c
+++ b/Python/pytime.c
@@ -7,6 +7,11 @@
#include <mach/mach_time.h> /* mach_absolute_time(), mach_timebase_info() */
#endif
+#define _PyTime_check_mul_overflow(a, b) \
+ (assert(b > 0), \
+ (_PyTime_t)(a) < _PyTime_MIN / (_PyTime_t)(b) \
+ || _PyTime_MAX / (_PyTime_t)(b) < (_PyTime_t)(a))
+
/* To millisecond (10^-3) */
#define SEC_TO_MS 1000
@@ -60,50 +65,83 @@
#endif
}
+/* Round to nearest with ties going to nearest even integer
+ (_PyTime_ROUND_HALF_EVEN) */
+static double
+_PyTime_RoundHalfEven(double x)
+{
+ double rounded = round(x);
+ if (fabs(x-rounded) == 0.5)
+ /* halfway case: round to even */
+ rounded = 2.0*round(x/2.0);
+ return rounded;
+}
+
+static double
+_PyTime_Round(double x, _PyTime_round_t round)
+{
+ /* volatile avoids optimization changing how numbers are rounded */
+ volatile double d;
+
+ d = x;
+ if (round == _PyTime_ROUND_HALF_EVEN)
+ d = _PyTime_RoundHalfEven(d);
+ else if (round == _PyTime_ROUND_CEILING)
+ d = ceil(d);
+ else
+ d = floor(d);
+ return d;
+}
+
+static int
+_PyTime_DoubleToDenominator(double d, time_t *sec, long *numerator,
+ double denominator, _PyTime_round_t round)
+{
+ double intpart, err;
+ /* volatile avoids optimization changing how numbers are rounded */
+ volatile double floatpart;
+
+ floatpart = modf(d, &intpart);
+
+ floatpart *= denominator;
+ floatpart = _PyTime_Round(floatpart, round);
+ if (floatpart >= denominator) {
+ floatpart -= denominator;
+ intpart += 1.0;
+ }
+ else if (floatpart < 0) {
+ floatpart += denominator;
+ intpart -= 1.0;
+ }
+ assert(0.0 <= floatpart && floatpart < denominator);
+
+ *sec = (time_t)intpart;
+ *numerator = (long)floatpart;
+
+ err = intpart - (double)*sec;
+ if (err <= -1.0 || err >= 1.0) {
+ error_time_t_overflow();
+ return -1;
+ }
+ return 0;
+}
+
static int
_PyTime_ObjectToDenominator(PyObject *obj, time_t *sec, long *numerator,
double denominator, _PyTime_round_t round)
{
- assert(denominator <= LONG_MAX);
+ assert(denominator <= (double)LONG_MAX);
+
if (PyFloat_Check(obj)) {
- double d, intpart, err;
- /* volatile avoids unsafe optimization on float enabled by gcc -O3 */
- volatile double floatpart;
-
- d = PyFloat_AsDouble(obj);
- floatpart = modf(d, &intpart);
- if (floatpart < 0) {
- floatpart = 1.0 + floatpart;
- intpart -= 1.0;
- }
-
- floatpart *= denominator;
- if (round == _PyTime_ROUND_CEILING) {
- floatpart = ceil(floatpart);
- if (floatpart >= denominator) {
- floatpart = 0.0;
- intpart += 1.0;
- }
- }
- else {
- floatpart = floor(floatpart);
- }
-
- *sec = (time_t)intpart;
- err = intpart - (double)*sec;
- if (err <= -1.0 || err >= 1.0) {
- error_time_t_overflow();
- return -1;
- }
-
- *numerator = (long)floatpart;
- return 0;
+ double d = PyFloat_AsDouble(obj);
+ return _PyTime_DoubleToDenominator(d, sec, numerator,
+ denominator, round);
}
else {
*sec = _PyLong_AsTime_t(obj);
+ *numerator = 0;
if (*sec == (time_t)-1 && PyErr_Occurred())
return -1;
- *numerator = 0;
return 0;
}
}
@@ -112,13 +150,12 @@
_PyTime_ObjectToTime_t(PyObject *obj, time_t *sec, _PyTime_round_t round)
{
if (PyFloat_Check(obj)) {
- double d, intpart, err;
+ double intpart, err;
+ /* volatile avoids optimization changing how numbers are rounded */
+ volatile double d;
d = PyFloat_AsDouble(obj);
- if (round == _PyTime_ROUND_CEILING)
- d = ceil(d);
- else
- d = floor(d);
+ d = _PyTime_Round(d, round);
(void)modf(d, &intpart);
*sec = (time_t)intpart;
@@ -141,14 +178,20 @@
_PyTime_ObjectToTimespec(PyObject *obj, time_t *sec, long *nsec,
_PyTime_round_t round)
{
- return _PyTime_ObjectToDenominator(obj, sec, nsec, 1e9, round);
+ int res;
+ res = _PyTime_ObjectToDenominator(obj, sec, nsec, 1e9, round);
+ assert(0 <= *nsec && *nsec < SEC_TO_NS);
+ return res;
}
int
_PyTime_ObjectToTimeval(PyObject *obj, time_t *sec, long *usec,
_PyTime_round_t round)
{
- return _PyTime_ObjectToDenominator(obj, sec, usec, 1e6, round);
+ int res;
+ res = _PyTime_ObjectToDenominator(obj, sec, usec, 1e6, round);
+ assert(0 <= *usec && *usec < SEC_TO_US);
+ return res;
}
static void
@@ -162,12 +205,13 @@
_PyTime_FromSeconds(int seconds)
{
_PyTime_t t;
+ t = (_PyTime_t)seconds;
/* ensure that integer overflow cannot happen, int type should have 32
bits, whereas _PyTime_t type has at least 64 bits (SEC_TO_MS takes 30
bits). */
- assert((seconds >= 0 && seconds <= _PyTime_MAX / SEC_TO_NS)
- || (seconds < 0 && seconds >= _PyTime_MIN / SEC_TO_NS));
- t = (_PyTime_t)seconds * SEC_TO_NS;
+ assert((t >= 0 && t <= _PyTime_MAX / SEC_TO_NS)
+ || (t < 0 && t >= _PyTime_MIN / SEC_TO_NS));
+ t *= SEC_TO_NS;
return t;
}
@@ -187,12 +231,15 @@
_PyTime_t t;
int res = 0;
- t = (_PyTime_t)ts->tv_sec * SEC_TO_NS;
- if (t / SEC_TO_NS != ts->tv_sec) {
+ assert(sizeof(ts->tv_sec) <= sizeof(_PyTime_t));
+ t = (_PyTime_t)ts->tv_sec;
+
+ if (_PyTime_check_mul_overflow(t, SEC_TO_NS)) {
if (raise)
_PyTime_overflow();
res = -1;
}
+ t = t * SEC_TO_NS;
t += ts->tv_nsec;
@@ -206,12 +253,15 @@
_PyTime_t t;
int res = 0;
- t = (_PyTime_t)tv->tv_sec * SEC_TO_NS;
- if (t / SEC_TO_NS != tv->tv_sec) {
+ assert(sizeof(tv->tv_sec) <= sizeof(_PyTime_t));
+ t = (_PyTime_t)tv->tv_sec;
+
+ if (_PyTime_check_mul_overflow(t, SEC_TO_NS)) {
if (raise)
_PyTime_overflow();
res = -1;
}
+ t = t * SEC_TO_NS;
t += (_PyTime_t)tv->tv_usec * US_TO_NS;
@@ -221,50 +271,59 @@
#endif
static int
+_PyTime_FromFloatObject(_PyTime_t *t, double value, _PyTime_round_t round,
+ long unit_to_ns)
+{
+ double err;
+ /* volatile avoids optimization changing how numbers are rounded */
+ volatile double d;
+
+ /* convert to a number of nanoseconds */
+ d = value;
+ d *= (double)unit_to_ns;
+ d = _PyTime_Round(d, round);
+
+ *t = (_PyTime_t)d;
+ err = d - (double)*t;
+ if (fabs(err) >= 1.0) {
+ _PyTime_overflow();
+ return -1;
+ }
+ return 0;
+}
+
+static int
_PyTime_FromObject(_PyTime_t *t, PyObject *obj, _PyTime_round_t round,
- long to_nanoseconds)
+ long unit_to_ns)
{
if (PyFloat_Check(obj)) {
- /* volatile avoids unsafe optimization on float enabled by gcc -O3 */
- volatile double d, err;
-
- /* convert to a number of nanoseconds */
+ double d;
d = PyFloat_AsDouble(obj);
- d *= to_nanoseconds;
-
- if (round == _PyTime_ROUND_CEILING)
- d = ceil(d);
- else
- d = floor(d);
-
- *t = (_PyTime_t)d;
- err = d - (double)*t;
- if (fabs(err) >= 1.0) {
- _PyTime_overflow();
- return -1;
- }
- return 0;
+ return _PyTime_FromFloatObject(t, d, round, unit_to_ns);
}
else {
#ifdef HAVE_LONG_LONG
PY_LONG_LONG sec;
- sec = PyLong_AsLongLong(obj);
assert(sizeof(PY_LONG_LONG) <= sizeof(_PyTime_t));
+
+ sec = PyLong_AsLongLong(obj);
#else
long sec;
- sec = PyLong_AsLong(obj);
assert(sizeof(PY_LONG_LONG) <= sizeof(_PyTime_t));
+
+ sec = PyLong_AsLong(obj);
#endif
if (sec == -1 && PyErr_Occurred()) {
if (PyErr_ExceptionMatches(PyExc_OverflowError))
_PyTime_overflow();
return -1;
}
- *t = sec * to_nanoseconds;
- if (*t / to_nanoseconds != sec) {
+
+ if (_PyTime_check_mul_overflow(sec, unit_to_ns)) {
_PyTime_overflow();
return -1;
}
+ *t = sec * unit_to_ns;
return 0;
}
}
@@ -284,12 +343,21 @@
double
_PyTime_AsSecondsDouble(_PyTime_t t)
{
- _PyTime_t sec, ns;
- /* Divide using integers to avoid rounding issues on the integer part.
- 1e-9 cannot be stored exactly in IEEE 64-bit. */
- sec = t / SEC_TO_NS;
- ns = t % SEC_TO_NS;
- return (double)sec + (double)ns * 1e-9;
+ /* volatile avoids optimization changing how numbers are rounded */
+ volatile double d;
+
+ if (t % SEC_TO_NS == 0) {
+ _PyTime_t secs;
+ /* Divide using integers to avoid rounding issues on the integer part.
+ 1e-9 cannot be stored exactly in IEEE 64-bit. */
+ secs = t / SEC_TO_NS;
+ d = (double)secs;
+ }
+ else {
+ d = (double)t;
+ d /= 1e9;
+ }
+ return d;
}
PyObject *
@@ -305,17 +373,35 @@
}
static _PyTime_t
-_PyTime_Divide(_PyTime_t t, _PyTime_t k, _PyTime_round_t round)
+_PyTime_Divide(const _PyTime_t t, const _PyTime_t k,
+ const _PyTime_round_t round)
{
assert(k > 1);
- if (round == _PyTime_ROUND_CEILING) {
+ if (round == _PyTime_ROUND_HALF_EVEN) {
+ _PyTime_t x, r, abs_r;
+ x = t / k;
+ r = t % k;
+ abs_r = Py_ABS(r);
+ if (abs_r > k / 2 || (abs_r == k / 2 && (Py_ABS(x) & 1))) {
+ if (t >= 0)
+ x++;
+ else
+ x--;
+ }
+ return x;
+ }
+ else if (round == _PyTime_ROUND_CEILING) {
if (t >= 0)
return (t + k - 1) / k;
else
+ return t / k;
+ }
+ else {
+ if (t >= 0)
+ return t / k;
+ else
return (t - (k - 1)) / k;
}
- else
- return t / k;
}
_PyTime_t
@@ -336,51 +422,34 @@
{
_PyTime_t secs, ns;
int res = 0;
+ int usec;
secs = t / SEC_TO_NS;
ns = t % SEC_TO_NS;
- if (ns < 0) {
- ns += SEC_TO_NS;
- secs -= 1;
- }
#ifdef MS_WINDOWS
- /* On Windows, timeval.tv_sec is a long (32 bit),
- whereas time_t can be 64-bit. */
- assert(sizeof(tv->tv_sec) == sizeof(long));
-#if SIZEOF_TIME_T > SIZEOF_LONG
- if (secs > LONG_MAX) {
- secs = LONG_MAX;
- res = -1;
- }
- else if (secs < LONG_MIN) {
- secs = LONG_MIN;
- res = -1;
- }
-#endif
tv->tv_sec = (long)secs;
#else
- /* On OpenBSD 5.4, timeval.tv_sec is a long.
- Example: long is 64-bit, whereas time_t is 32-bit. */
tv->tv_sec = secs;
+#endif
if ((_PyTime_t)tv->tv_sec != secs)
res = -1;
-#endif
- if (round == _PyTime_ROUND_CEILING)
- tv->tv_usec = (int)((ns + US_TO_NS - 1) / US_TO_NS);
- else
- tv->tv_usec = (int)(ns / US_TO_NS);
-
- if (tv->tv_usec >= SEC_TO_US) {
- tv->tv_usec -= SEC_TO_US;
+ usec = (int)_PyTime_Divide(ns, US_TO_NS, round);
+ if (usec < 0) {
+ usec += SEC_TO_US;
+ tv->tv_sec -= 1;
+ }
+ else if (usec >= SEC_TO_US) {
+ usec -= SEC_TO_US;
tv->tv_sec += 1;
}
- if (res && raise)
- _PyTime_overflow();
+ assert(0 <= usec && usec < SEC_TO_US);
+ tv->tv_usec = usec;
- assert(0 <= tv->tv_usec && tv->tv_usec <= 999999);
+ if (res && raise)
+ error_time_t_overflow();
return res;
}
@@ -409,13 +478,13 @@
secs -= 1;
}
ts->tv_sec = (time_t)secs;
- if ((_PyTime_t)ts->tv_sec != secs) {
- _PyTime_overflow();
- return -1;
- }
+ assert(0 <= nsec && nsec < SEC_TO_NS);
ts->tv_nsec = nsec;
- assert(0 <= ts->tv_nsec && ts->tv_nsec <= 999999999);
+ if ((_PyTime_t)ts->tv_sec != secs) {
+ error_time_t_overflow();
+ return -1;
+ }
return 0;
}
#endif
@@ -529,19 +598,20 @@
return pygettimeofday_new(t, info, 1);
}
-
static int
pymonotonic(_PyTime_t *tp, _Py_clock_info_t *info, int raise)
{
#if defined(MS_WINDOWS)
- ULONGLONG result;
+ ULONGLONG ticks;
+ _PyTime_t t;
assert(info == NULL || raise);
- result = GetTickCount64();
+ ticks = GetTickCount64();
+ assert(sizeof(ticks) <= sizeof(_PyTime_t));
+ t = (_PyTime_t)ticks;
- *tp = result * MS_TO_NS;
- if (*tp / MS_TO_NS != result) {
+ if (_PyTime_check_mul_overflow(t, MS_TO_NS)) {
if (raise) {
_PyTime_overflow();
return -1;
@@ -549,6 +619,7 @@
/* Hello, time traveler! */
assert(0);
}
+ *tp = t * MS_TO_NS;
if (info) {
DWORD timeAdjustment, timeIncrement;
diff --git a/README b/README
index 0542e7e..f232755 100644
--- a/README
+++ b/README
@@ -1,5 +1,5 @@
-This is Python version 3.5.0 release candidate 4
-================================================
+This is Python version 3.6.0 alpha 1
+====================================
Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011,
2012, 2013, 2014, 2015 Python Software Foundation. All rights reserved.
@@ -50,9 +50,9 @@
----------
We try to have a comprehensive overview of the changes in the "What's New in
-Python 3.5" document, found at
+Python 3.6" document, found at
- http://docs.python.org/3.5/whatsnew/3.5.html
+ http://docs.python.org/3.6/whatsnew/3.6.html
For a more detailed change log, read Misc/NEWS (though this file, too, is
incomplete, and also doesn't list anything merged in from the 2.7 release under
@@ -65,9 +65,9 @@
Documentation
-------------
-Documentation for Python 3.5 is online, updated daily:
+Documentation for Python 3.6 is online, updated daily:
- http://docs.python.org/3.5/
+ http://docs.python.org/3.6/
It can also be downloaded in many formats for faster access. The documentation
is downloadable in HTML, PDF, and reStructuredText formats; the latter version
@@ -92,7 +92,7 @@
A source-to-source translation tool, "2to3", can take care of the mundane task
of converting large amounts of source code. It is not a complete solution but
is complemented by the deprecation warnings in 2.6. See
-http://docs.python.org/3.5/library/2to3.html for more information.
+http://docs.python.org/3.6/library/2to3.html for more information.
Testing
@@ -130,7 +130,7 @@
Install that version using "make install". Install all other versions using
"make altinstall".
-For example, if you want to install Python 2.6, 2.7 and 3.5 with 2.7 being the
+For example, if you want to install Python 2.6, 2.7 and 3.6 with 2.7 being the
primary version, you would execute "make install" in your 2.7 build directory
and "make altinstall" in the others.
@@ -166,7 +166,7 @@
Release Schedule
----------------
-See PEP 478 for release details: http://www.python.org/dev/peps/pep-0478/
+See PEP 494 for release details: http://www.python.org/dev/peps/pep-0494/
Copyright and License Information
diff --git a/Tools/buildbot/build-amd64.bat b/Tools/buildbot/build-amd64.bat
deleted file mode 100644
index f77407b..0000000
--- a/Tools/buildbot/build-amd64.bat
+++ /dev/null
@@ -1,5 +0,0 @@
-@rem Formerly used by the buildbot "compile" step.
-@echo This script is no longer used and may be removed in the future.
-@echo To get the same effect as this script, use
-@echo PCbuild\build.bat -d -e -k -p x64
-call "%~dp0build.bat" -p x64 %*
diff --git a/Tools/buildbot/clean-amd64.bat b/Tools/buildbot/clean-amd64.bat
deleted file mode 100644
index b53c7c1..0000000
--- a/Tools/buildbot/clean-amd64.bat
+++ /dev/null
@@ -1,5 +0,0 @@
-@rem Formerly used by the buildbot "clean" step.
-@echo This script is no longer used and may be removed in the future.
-@echo To get the same effect as this script, use `clean.bat` from this
-@echo directory and pass `-p x64` as two arguments.
-call "%~dp0clean.bat" -p x64 %*
diff --git a/Tools/buildbot/external-amd64.bat b/Tools/buildbot/external-amd64.bat
deleted file mode 100644
index bfaef05..0000000
--- a/Tools/buildbot/external-amd64.bat
+++ /dev/null
@@ -1,3 +0,0 @@
-@echo This script is no longer used and may be removed in the future.
-@echo Please use PCbuild\get_externals.bat instead.
-@"%~dp0..\..\PCbuild\get_externals.bat" %*
diff --git a/Tools/buildbot/external.bat b/Tools/buildbot/external.bat
deleted file mode 100644
index bfaef05..0000000
--- a/Tools/buildbot/external.bat
+++ /dev/null
@@ -1,3 +0,0 @@
-@echo This script is no longer used and may be removed in the future.
-@echo Please use PCbuild\get_externals.bat instead.
-@"%~dp0..\..\PCbuild\get_externals.bat" %*
diff --git a/Tools/buildbot/test-amd64.bat b/Tools/buildbot/test-amd64.bat
deleted file mode 100644
index e48329c..0000000
--- a/Tools/buildbot/test-amd64.bat
+++ /dev/null
@@ -1,6 +0,0 @@
-@rem Formerly used by the buildbot "test" step.
-@echo This script is no longer used and may be removed in the future.
-@echo To get the same effect as this script, use
-@echo PCbuild\rt.bat -q -d -x64 -uall -rwW
-@echo or use `test.bat` in this directory and pass `-x64` as an argument.
-call "%~dp0test.bat" -x64 %*
diff --git a/configure b/configure
index e823a08..95d953a 100755
--- a/configure
+++ b/configure
@@ -1,6 +1,6 @@
#! /bin/sh
# Guess values for system-dependent variables and create Makefiles.
-# Generated by GNU Autoconf 2.69 for python 3.5.
+# Generated by GNU Autoconf 2.69 for python 3.6.
#
# Report bugs to <http://bugs.python.org/>.
#
@@ -580,8 +580,8 @@
# Identity of this package.
PACKAGE_NAME='python'
PACKAGE_TARNAME='python'
-PACKAGE_VERSION='3.5'
-PACKAGE_STRING='python 3.5'
+PACKAGE_VERSION='3.6'
+PACKAGE_STRING='python 3.6'
PACKAGE_BUGREPORT='http://bugs.python.org/'
PACKAGE_URL=''
@@ -1378,7 +1378,7 @@
# Omit some internal or obsolete options to make the list less imposing.
# This message is too long to be a string in the A/UX 3.1 sh.
cat <<_ACEOF
-\`configure' configures python 3.5 to adapt to many kinds of systems.
+\`configure' configures python 3.6 to adapt to many kinds of systems.
Usage: $0 [OPTION]... [VAR=VALUE]...
@@ -1443,7 +1443,7 @@
if test -n "$ac_init_help"; then
case $ac_init_help in
- short | recursive ) echo "Configuration of python 3.5:";;
+ short | recursive ) echo "Configuration of python 3.6:";;
esac
cat <<\_ACEOF
@@ -1597,7 +1597,7 @@
test -n "$ac_init_help" && exit $ac_status
if $ac_init_version; then
cat <<\_ACEOF
-python configure 3.5
+python configure 3.6
generated by GNU Autoconf 2.69
Copyright (C) 2012 Free Software Foundation, Inc.
@@ -2436,7 +2436,7 @@
This file contains any messages produced by compilers while
running configure, to aid debugging if configure makes a mistake.
-It was created by python $as_me 3.5, which was
+It was created by python $as_me 3.6, which was
generated by GNU Autoconf 2.69. Invocation command line was
$ $0 $@
@@ -3009,7 +3009,7 @@
mv confdefs.h.new confdefs.h
-VERSION=3.5
+VERSION=3.6
# Version number of Python's own shared library file.
@@ -16543,7 +16543,7 @@
# report actual input values of CONFIG_FILES etc. instead of their
# values after options handling.
ac_log="
-This file was extended by python $as_me 3.5, which was
+This file was extended by python $as_me 3.6, which was
generated by GNU Autoconf 2.69. Invocation command line was
CONFIG_FILES = $CONFIG_FILES
@@ -16605,7 +16605,7 @@
cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1
ac_cs_config="`$as_echo "$ac_configure_args" | sed 's/^ //; s/[\\""\`\$]/\\\\&/g'`"
ac_cs_version="\\
-python config.status 3.5
+python config.status 3.6
configured by $0, generated by GNU Autoconf 2.69,
with options \\"\$ac_cs_config\\"
diff --git a/configure.ac b/configure.ac
index 56a73df..668234d 100644
--- a/configure.ac
+++ b/configure.ac
@@ -3,7 +3,7 @@
dnl ***********************************************
# Set VERSION so we only need to edit in one place (i.e., here)
-m4_define(PYTHON_VERSION, 3.5)
+m4_define(PYTHON_VERSION, 3.6)
AC_PREREQ(2.65)