Doc/library/pickle.rst

:mod:`pickle` --- Python object serialization
=============================================

.. index::
   single: persistence
   pair: persistent; objects
   pair: serializing; objects
   pair: marshalling; objects
   pair: flattening; objects
   pair: pickling; objects

.. module:: pickle
   :synopsis: Convert Python objects to streams of bytes and back.
.. sectionauthor:: Jim Kerr <jbkerr@sr.hp.com>.
.. sectionauthor:: Barry Warsaw <barry@zope.com>

The :mod:`pickle` module implements a fundamental, but powerful algorithm for
serializing and de-serializing a Python object structure.  "Pickling" is the
process whereby a Python object hierarchy is converted into a byte stream, and
"unpickling" is the inverse operation, whereby a byte stream is converted back
into an object hierarchy.  Pickling (and unpickling) is alternatively known as
"serialization", "marshalling," [#]_ or "flattening", however, to avoid
confusion, the terms used here are "pickling" and "unpickling".

This documentation describes both the :mod:`pickle` module and the
:mod:`cPickle` module.

.. warning::

   The :mod:`pickle` module is not intended to be secure against erroneous or
   maliciously constructed data.  Never unpickle data received from an untrusted
   or unauthenticated source.


Relationship to other Python modules
------------------------------------

The :mod:`pickle` module has an optimized cousin called the :mod:`cPickle`
module.  As its name implies, :mod:`cPickle` is written in C, so it can be up to
1000 times faster than :mod:`pickle`.  However it does not support subclassing
of the :func:`Pickler` and :func:`Unpickler` classes, because in :mod:`cPickle`
these are functions, not classes.  Most applications have no need for this
functionality, and can benefit from the improved performance of :mod:`cPickle`.
Other than that, the interfaces of the two modules are nearly identical; the
common interface is described in this manual and differences are pointed out
where necessary.  In the following discussions, we use the term "pickle" to
collectively describe the :mod:`pickle` and :mod:`cPickle` modules.

The data streams the two modules produce are guaranteed to be interchangeable.

Python has a more primitive serialization module called :mod:`marshal`, but in
general :mod:`pickle` should always be the preferred way to serialize Python
objects.  :mod:`marshal` exists primarily to support Python's :file:`.pyc`
files.

The :mod:`pickle` module differs from :mod:`marshal` in several significant ways:

* The :mod:`pickle` module keeps track of the objects it has already serialized,
  so that later references to the same object won't be serialized again.
  :mod:`marshal` doesn't do this.

  This has implications both for recursive objects and object sharing.  Recursive
  objects are objects that contain references to themselves.  These are not
  handled by marshal, and in fact, attempting to marshal recursive objects will
  crash your Python interpreter.  Object sharing happens when there are multiple
  references to the same object in different places in the object hierarchy being
  serialized.  :mod:`pickle` stores such objects only once, and ensures that all
  other references point to the master copy.  Shared objects remain shared, which
  can be very important for mutable objects.

* :mod:`marshal` cannot be used to serialize user-defined classes and their
  instances.  :mod:`pickle` can save and restore class instances transparently,
  however the class definition must be importable and live in the same module as
  when the object was stored.

* The :mod:`marshal` serialization format is not guaranteed to be portable
  across Python versions.  Because its primary job in life is to support
  :file:`.pyc` files, the Python implementers reserve the right to change the
  serialization format in non-backwards compatible ways should the need arise.
  The :mod:`pickle` serialization format is guaranteed to be backwards compatible
  across Python releases.

Note that serialization is a more primitive notion than persistence; although
:mod:`pickle` reads and writes file objects, it does not handle the issue of
naming persistent objects, nor the (even more complicated) issue of concurrent
access to persistent objects.  The :mod:`pickle` module can transform a complex
object into a byte stream and it can transform the byte stream into an object
with the same internal structure.  Perhaps the most obvious thing to do with
these byte streams is to write them onto a file, but it is also conceivable to
send them across a network or store them in a database.  The module
:mod:`shelve` provides a simple interface to pickle and unpickle objects on
DBM-style database files.


Data stream format
------------------

.. index::
   single: XDR
   single: External Data Representation

The data format used by :mod:`pickle` is Python-specific.  This has the
advantage that there are no restrictions imposed by external standards such as
XDR (which can't represent pointer sharing); however it means that non-Python
programs may not be able to reconstruct pickled Python objects.

By default, the :mod:`pickle` data format uses a printable ASCII representation.
This is slightly more voluminous than a binary representation.  The big
advantage of using printable ASCII (and of some other characteristics of
:mod:`pickle`'s representation) is that for debugging or recovery purposes it is
possible for a human to read the pickled file with a standard text editor.

There are currently 3 different protocols which can be used for pickling.

* Protocol version 0 is the original ASCII protocol and is backwards compatible
  with earlier versions of Python.

* Protocol version 1 is the old binary format which is also compatible with
  earlier versions of Python.

* Protocol version 2 was introduced in Python 2.3.  It provides much more
  efficient pickling of :term:`new-style class`\es.

Refer to :pep:`307` for more information.

If a *protocol* is not specified, protocol 0 is used. If *protocol* is specified
as a negative value or :const:`HIGHEST_PROTOCOL`, the highest protocol version
available will be used.

.. versionchanged:: 2.3
   Introduced the *protocol* parameter.

A binary format, which is slightly more efficient, can be chosen by specifying a
*protocol* version >= 1.


Usage
-----

To serialize an object hierarchy, you first create a pickler, then you call the
pickler's :meth:`dump` method.  To de-serialize a data stream, you first create
an unpickler, then you call the unpickler's :meth:`load` method.  The
:mod:`pickle` module provides the following constant:


.. data:: HIGHEST_PROTOCOL

   The highest protocol version available.  This value can be passed as a
   *protocol* value.

   .. versionadded:: 2.3

.. note::

   Be sure to always open pickle files created with protocols >= 1 in binary mode.
   For the old ASCII-based pickle protocol 0 you can use either text mode or binary
   mode as long as you stay consistent.

   A pickle file written with protocol 0 in binary mode will contain lone linefeeds
   as line terminators and therefore will look "funny" when viewed in Notepad or
   other editors which do not support this format.

The :mod:`pickle` module provides the following functions to make the pickling
process more convenient:


.. function:: dump(obj, file[, protocol])

   Write a pickled representation of *obj* to the open file object *file*.  This is
   equivalent to ``Pickler(file, protocol).dump(obj)``.

   If the *protocol* parameter is omitted, protocol 0 is used. If *protocol* is
   specified as a negative value or :const:`HIGHEST_PROTOCOL`, the highest protocol
   version will be used.

   .. versionchanged:: 2.3
      Introduced the *protocol* parameter.

   *file* must have a :meth:`write` method that accepts a single string argument.
   It can thus be a file object opened for writing, a :mod:`StringIO` object, or
   any other custom object that meets this interface.


.. function:: load(file)

   Read a string from the open file object *file* and interpret it as a pickle data
   stream, reconstructing and returning the original object hierarchy.  This is
   equivalent to ``Unpickler(file).load()``.

   *file* must have two methods, a :meth:`read` method that takes an integer
   argument, and a :meth:`readline` method that requires no arguments.  Both
   methods should return a string.  Thus *file* can be a file object opened for
   reading, a :mod:`StringIO` object, or any other custom object that meets this
   interface.

   This function automatically determines whether the data stream was written in
   binary mode or not.


.. function:: dumps(obj[, protocol])

   Return the pickled representation of the object as a string, instead of writing
   it to a file.

   If the *protocol* parameter is omitted, protocol 0 is used. If *protocol* is
   specified as a negative value or :const:`HIGHEST_PROTOCOL`, the highest protocol
   version will be used.

   .. versionchanged:: 2.3
      The *protocol* parameter was added.


.. function:: loads(string)

   Read a pickled object hierarchy from a string.  Characters in the string past
   the pickled object's representation are ignored.

The :mod:`pickle` module also defines three exceptions:


.. exception:: PickleError

   A common base class for the other exceptions defined below.  This inherits from
   :exc:`Exception`.


.. exception:: PicklingError

   This exception is raised when an unpicklable object is passed to the
   :meth:`dump` method.


.. exception:: UnpicklingError

   This exception is raised when there is a problem unpickling an object. Note that
   other exceptions may also be raised during unpickling, including (but not
   necessarily limited to) :exc:`AttributeError`, :exc:`EOFError`,
   :exc:`ImportError`, and :exc:`IndexError`.

The :mod:`pickle` module also exports two callables [#]_, :class:`Pickler` and
:class:`Unpickler`:


.. class:: Pickler(file[, protocol])

   This takes a file-like object to which it will write a pickle data stream.

   If the *protocol* parameter is omitted, protocol 0 is used. If *protocol* is
   specified as a negative value or :const:`HIGHEST_PROTOCOL`, the highest
   protocol version will be used.

   .. versionchanged:: 2.3
      Introduced the *protocol* parameter.

   *file* must have a :meth:`write` method that accepts a single string argument.
   It can thus be an open file object, a :mod:`StringIO` object, or any other
   custom object that meets this interface.

   :class:`Pickler` objects define one (or two) public methods:


   .. method:: dump(obj)

      Write a pickled representation of *obj* to the open file object given in the
      constructor.  Either the binary or ASCII format will be used, depending on the
      value of the *protocol* argument passed to the constructor.


   .. method:: clear_memo()

      Clears the pickler's "memo".  The memo is the data structure that remembers
      which objects the pickler has already seen, so that shared or recursive objects
      pickled by reference and not by value.  This method is useful when re-using
      picklers.

      .. note::

         Prior to Python 2.3, :meth:`clear_memo` was only available on the picklers
         created by :mod:`cPickle`.  In the :mod:`pickle` module, picklers have an
         instance variable called :attr:`memo` which is a Python dictionary.  So to clear
         the memo for a :mod:`pickle` module pickler, you could do the following::

            mypickler.memo.clear()

         Code that does not need to support older versions of Python should simply use
         :meth:`clear_memo`.

It is possible to make multiple calls to the :meth:`dump` method of the same
:class:`Pickler` instance.  These must then be matched to the same number of
calls to the :meth:`load` method of the corresponding :class:`Unpickler`
instance.  If the same object is pickled by multiple :meth:`dump` calls, the
:meth:`load` will all yield references to the same object. [#]_

:class:`Unpickler` objects are defined as:


.. class:: Unpickler(file)

   This takes a file-like object from which it will read a pickle data stream.
   This class automatically determines whether the data stream was written in
   binary mode or not, so it does not need a flag as in the :class:`Pickler`
   factory.

   *file* must have two methods, a :meth:`read` method that takes an integer
   argument, and a :meth:`readline` method that requires no arguments.  Both
   methods should return a string.  Thus *file* can be a file object opened for
   reading, a :mod:`StringIO` object, or any other custom object that meets this
   interface.

   :class:`Unpickler` objects have one (or two) public methods:


   .. method:: load()

      Read a pickled object representation from the open file object given in
      the constructor, and return the reconstituted object hierarchy specified
      therein.

      This method automatically determines whether the data stream was written
      in binary mode or not.


   .. method:: noload()

      This is just like :meth:`load` except that it doesn't actually create any
      objects.  This is useful primarily for finding what's called "persistent
      ids" that may be referenced in a pickle data stream.  See section
      :ref:`pickle-protocol` below for more details.

      **Note:** the :meth:`noload` method is currently only available on
      :class:`Unpickler` objects created with the :mod:`cPickle` module.
      :mod:`pickle` module :class:`Unpickler`\ s do not have the :meth:`noload`
      method.


What can be pickled and unpickled?
----------------------------------

The following types can be pickled:

* ``None``, ``True``, and ``False``

* integers, long integers, floating point numbers, complex numbers

* normal and Unicode strings

* tuples, lists, sets, and dictionaries containing only picklable objects

* functions defined at the top level of a module

* built-in functions defined at the top level of a module

* classes that are defined at the top level of a module

* instances of such classes whose :attr:`__dict__` or the result of calling
  :meth:`__getstate__` is picklable  (see section :ref:`pickle-protocol` for
  details).

Attempts to pickle unpicklable objects will raise the :exc:`PicklingError`
exception; when this happens, an unspecified number of bytes may have already
been written to the underlying file. Trying to pickle a highly recursive data
structure may exceed the maximum recursion depth, a :exc:`RuntimeError` will be
raised in this case. You can carefully raise this limit with
:func:`sys.setrecursionlimit`.

Note that functions (built-in and user-defined) are pickled by "fully qualified"
name reference, not by value.  This means that only the function name is
pickled, along with the name of the module the function is defined in.  Neither
the function's code, nor any of its function attributes are pickled.  Thus the
defining module must be importable in the unpickling environment, and the module
must contain the named object, otherwise an exception will be raised. [#]_

Similarly, classes are pickled by named reference, so the same restrictions in
the unpickling environment apply.  Note that none of the class's code or data is
pickled, so in the following example the class attribute ``attr`` is not
restored in the unpickling environment::

   class Foo:
       attr = 'a class attr'

   picklestring = pickle.dumps(Foo)

These restrictions are why picklable functions and classes must be defined in
the top level of a module.

Similarly, when class instances are pickled, their class's code and data are not
pickled along with them.  Only the instance data are pickled.  This is done on
purpose, so you can fix bugs in a class or add methods to the class and still
load objects that were created with an earlier version of the class.  If you
plan to have long-lived objects that will see many versions of a class, it may
be worthwhile to put a version number in the objects so that suitable
conversions can be made by the class's :meth:`__setstate__` method.


.. _pickle-protocol:

The pickle protocol
-------------------

.. currentmodule:: None

This section describes the "pickling protocol" that defines the interface
between the pickler/unpickler and the objects that are being serialized.  This
protocol provides a standard way for you to define, customize, and control how
your objects are serialized and de-serialized.  The description in this section
doesn't cover specific customizations that you can employ to make the unpickling
environment slightly safer from untrusted pickle data streams; see section
:ref:`pickle-sub` for more details.


.. _pickle-inst:

Pickling and unpickling normal class instances
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. method:: object.__getinitargs__()

   When a pickled class instance is unpickled, its :meth:`__init__` method is
   normally *not* invoked.  If it is desirable that the :meth:`__init__` method
   be called on unpickling, an old-style class can define a method
   :meth:`__getinitargs__`, which should return a *tuple* containing the
   arguments to be passed to the class constructor (:meth:`__init__` for
   example).  The :meth:`__getinitargs__` method is called at pickle time; the
   tuple it returns is incorporated in the pickle for the instance.

.. method:: object.__getnewargs__()

   New-style types can provide a :meth:`__getnewargs__` method that is used for
   protocol 2.  Implementing this method is needed if the type establishes some
   internal invariants when the instance is created, or if the memory allocation
   is affected by the values passed to the :meth:`__new__` method for the type
   (as it is for tuples and strings).  Instances of a :term:`new-style class`
   ``C`` are created using ::

      obj = C.__new__(C, *args)

   where *args* is the result of calling :meth:`__getnewargs__` on the original
   object; if there is no :meth:`__getnewargs__`, an empty tuple is assumed.

.. method:: object.__getstate__()

   Classes can further influence how their instances are pickled; if the class
   defines the method :meth:`__getstate__`, it is called and the return state is
   pickled as the contents for the instance, instead of the contents of the
   instance's dictionary.  If there is no :meth:`__getstate__` method, the
   instance's :attr:`__dict__` is pickled.

.. method:: object.__setstate__(state)

   Upon unpickling, if the class also defines the method :meth:`__setstate__`,
   it is called with the unpickled state. [#]_ If there is no
   :meth:`__setstate__` method, the pickled state must be a dictionary and its
   items are assigned to the new instance's dictionary.  If a class defines both
   :meth:`__getstate__` and :meth:`__setstate__`, the state object needn't be a
   dictionary and these methods can do what they want. [#]_

   .. note::

      For :term:`new-style class`\es, if :meth:`__getstate__` returns a false
      value, the :meth:`__setstate__` method will not be called.

.. note::

   At unpickling time, some methods like :meth:`__getattr__`,
   :meth:`__getattribute__`, or :meth:`__setattr__` may be called upon the
   instance.  In case those methods rely on some internal invariant being
   true, the type should implement either :meth:`__getinitargs__` or
   :meth:`__getnewargs__` to establish such an invariant; otherwise, neither
   :meth:`__new__` nor :meth:`__init__` will be called.


Pickling and unpickling extension types
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. method:: object.__reduce__()

   When the :class:`Pickler` encounters an object of a type it knows nothing
   about --- such as an extension type --- it looks in two places for a hint of
   how to pickle it.  One alternative is for the object to implement a
   :meth:`__reduce__` method.  If provided, at pickling time :meth:`__reduce__`
   will be called with no arguments, and it must return either a string or a
   tuple.

   If a string is returned, it names a global variable whose contents are
   pickled as normal.  The string returned by :meth:`__reduce__` should be the
   object's local name relative to its module; the pickle module searches the
   module namespace to determine the object's module.

   When a tuple is returned, it must be between two and five elements long.
   Optional elements can either be omitted, or ``None`` can be provided as their
   value.  The contents of this tuple are pickled as normal and used to
   reconstruct the object at unpickling time.  The semantics of each element
   are:

   * A callable object that will be called to create the initial version of the
     object.  The next element of the tuple will provide arguments for this
     callable, and later elements provide additional state information that will
     subsequently be used to fully reconstruct the pickled data.

     In the unpickling environment this object must be either a class, a
     callable registered as a "safe constructor" (see below), or it must have an
     attribute :attr:`__safe_for_unpickling__` with a true value. Otherwise, an
     :exc:`UnpicklingError` will be raised in the unpickling environment.  Note
     that as usual, the callable itself is pickled by name.

   * A tuple of arguments for the callable object.

     .. versionchanged:: 2.5
        Formerly, this argument could also be ``None``.

   * Optionally, the object's state, which will be passed to the object's
     :meth:`__setstate__` method as described in section :ref:`pickle-inst`.  If
     the object has no :meth:`__setstate__` method, then, as above, the value
     must be a dictionary and it will be added to the object's :attr:`__dict__`.

   * Optionally, an iterator (and not a sequence) yielding successive list
     items.  These list items will be pickled, and appended to the object using
     either ``obj.append(item)`` or ``obj.extend(list_of_items)``.  This is
     primarily used for list subclasses, but may be used by other classes as
     long as they have :meth:`append` and :meth:`extend` methods with the
     appropriate signature.  (Whether :meth:`append` or :meth:`extend` is used
     depends on which pickle protocol version is used as well as the number of
     items to append, so both must be supported.)

   * Optionally, an iterator (not a sequence) yielding successive dictionary
     items, which should be tuples of the form ``(key, value)``.  These items
     will be pickled and stored to the object using ``obj[key] = value``. This
     is primarily used for dictionary subclasses, but may be used by other
     classes as long as they implement :meth:`__setitem__`.

.. method:: object.__reduce_ex__(protocol)

   It is sometimes useful to know the protocol version when implementing
   :meth:`__reduce__`.  This can be done by implementing a method named
   :meth:`__reduce_ex__` instead of :meth:`__reduce__`. :meth:`__reduce_ex__`,
   when it exists, is called in preference over :meth:`__reduce__` (you may
   still provide :meth:`__reduce__` for backwards compatibility).  The
   :meth:`__reduce_ex__` method will be called with a single integer argument,
   the protocol version.

   The :class:`object` class implements both :meth:`__reduce__` and
   :meth:`__reduce_ex__`; however, if a subclass overrides :meth:`__reduce__`
   but not :meth:`__reduce_ex__`, the :meth:`__reduce_ex__` implementation
   detects this and calls :meth:`__reduce__`.

An alternative to implementing a :meth:`__reduce__` method on the object to be
pickled, is to register the callable with the :mod:`copy_reg` module.  This
module provides a way for programs to register "reduction functions" and
constructors for user-defined types.   Reduction functions have the same
semantics and interface as the :meth:`__reduce__` method described above, except
that they are called with a single argument, the object to be pickled.

The registered constructor is deemed a "safe constructor" for purposes of
unpickling as described above.


Pickling and unpickling external objects
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. index::
   single: persistent_id (pickle protocol)
   single: persistent_load (pickle protocol)

For the benefit of object persistence, the :mod:`pickle` module supports the
notion of a reference to an object outside the pickled data stream.  Such
objects are referenced by a "persistent id", which is just an arbitrary string
of printable ASCII characters. The resolution of such names is not defined by
the :mod:`pickle` module; it will delegate this resolution to user defined
functions on the pickler and unpickler. [#]_

To define external persistent id resolution, you need to set the
:attr:`persistent_id` attribute of the pickler object and the
:attr:`persistent_load` attribute of the unpickler object.

To pickle objects that have an external persistent id, the pickler must have a
custom :func:`persistent_id` method that takes an object as an argument and
returns either ``None`` or the persistent id for that object.  When ``None`` is
returned, the pickler simply pickles the object as normal.  When a persistent id
string is returned, the pickler will pickle that string, along with a marker so
that the unpickler will recognize the string as a persistent id.

To unpickle external objects, the unpickler must have a custom
:func:`persistent_load` function that takes a persistent id string and returns
the referenced object.

Here's a silly example that *might* shed more light::

   import pickle
   from cStringIO import StringIO

   src = StringIO()
   p = pickle.Pickler(src)

   def persistent_id(obj):
       if hasattr(obj, 'x'):
           return 'the value %d' % obj.x
       else:
           return None

   p.persistent_id = persistent_id

   class Integer:
       def __init__(self, x):
           self.x = x
       def __str__(self):
           return 'My name is integer %d' % self.x

   i = Integer(7)
   print i
   p.dump(i)

   datastream = src.getvalue()
   print repr(datastream)
   dst = StringIO(datastream)

   up = pickle.Unpickler(dst)

   class FancyInteger(Integer):
       def __str__(self):
           return 'I am the integer %d' % self.x

   def persistent_load(persid):
       if persid.startswith('the value '):
           value = int(persid.split()[2])
           return FancyInteger(value)
       else:
           raise pickle.UnpicklingError, 'Invalid persistent id'

   up.persistent_load = persistent_load

   j = up.load()
   print j

In the :mod:`cPickle` module, the unpickler's :attr:`persistent_load` attribute
can also be set to a Python list, in which case, when the unpickler reaches a
persistent id, the persistent id string will simply be appended to this list.
This functionality exists so that a pickle data stream can be "sniffed" for
object references without actually instantiating all the objects in a pickle.
[#]_  Setting :attr:`persistent_load` to a list is usually used in conjunction
with the :meth:`noload` method on the Unpickler.

.. BAW: Both pickle and cPickle support something called inst_persistent_id()
   which appears to give unknown types a second shot at producing a persistent
   id.  Since Jim Fulton can't remember why it was added or what it's for, I'm
   leaving it undocumented.


.. _pickle-sub:

Subclassing Unpicklers
----------------------

.. index::
   single: load_global() (pickle protocol)
   single: find_global() (pickle protocol)

By default, unpickling will import any class that it finds in the pickle data.
You can control exactly what gets unpickled and what gets called by customizing
your unpickler.  Unfortunately, exactly how you do this is different depending
on whether you're using :mod:`pickle` or :mod:`cPickle`. [#]_

In the :mod:`pickle` module, you need to derive a subclass from
:class:`Unpickler`, overriding the :meth:`load_global` method.
:meth:`load_global` should read two lines from the pickle data stream where the
first line will the name of the module containing the class and the second line
will be the name of the instance's class.  It then looks up the class, possibly
importing the module and digging out the attribute, then it appends what it
finds to the unpickler's stack.  Later on, this class will be assigned to the
:attr:`__class__` attribute of an empty class, as a way of magically creating an
instance without calling its class's :meth:`__init__`. Your job (should you
choose to accept it), would be to have :meth:`load_global` push onto the
unpickler's stack, a known safe version of any class you deem safe to unpickle.
It is up to you to produce such a class.  Or you could raise an error if you
want to disallow all unpickling of instances.  If this sounds like a hack,
you're right.  Refer to the source code to make this work.

Things are a little cleaner with :mod:`cPickle`, but not by much. To control
what gets unpickled, you can set the unpickler's :attr:`find_global` attribute
to a function or ``None``.  If it is ``None`` then any attempts to unpickle
instances will raise an :exc:`UnpicklingError`.  If it is a function, then it
should accept a module name and a class name, and return the corresponding class
object.  It is responsible for looking up the class and performing any necessary
imports, and it may raise an error to prevent instances of the class from being
unpickled.

The moral of the story is that you should be really careful about the source of
the strings your application unpickles.


.. _pickle-example:

Example
-------

For the simplest code, use the :func:`dump` and :func:`load` functions.  Note
that a self-referencing list is pickled and restored correctly. ::

   import pickle

   data1 = {'a': [1, 2.0, 3, 4+6j],
            'b': ('string', u'Unicode string'),
            'c': None}

   selfref_list = [1, 2, 3]
   selfref_list.append(selfref_list)

   output = open('data.pkl', 'wb')

   # Pickle dictionary using protocol 0.
   pickle.dump(data1, output)

   # Pickle the list using the highest protocol available.
   pickle.dump(selfref_list, output, -1)

   output.close()

The following example reads the resulting pickled data.  When reading a
pickle-containing file, you should open the file in binary mode because you
can't be sure if the ASCII or binary format was used. ::

   import pprint, pickle

   pkl_file = open('data.pkl', 'rb')

   data1 = pickle.load(pkl_file)
   pprint.pprint(data1)

   data2 = pickle.load(pkl_file)
   pprint.pprint(data2)

   pkl_file.close()

Here's a larger example that shows how to modify pickling behavior for a class.
The :class:`TextReader` class opens a text file, and returns the line number and
line contents each time its :meth:`readline` method is called. If a
:class:`TextReader` instance is pickled, all attributes *except* the file object
member are saved. When the instance is unpickled, the file is reopened, and
reading resumes from the last location. The :meth:`__setstate__` and
:meth:`__getstate__` methods are used to implement this behavior. ::

   #!/usr/local/bin/python

   class TextReader:
       """Print and number lines in a text file."""
       def __init__(self, file):
           self.file = file
           self.fh = open(file)
           self.lineno = 0

       def readline(self):
           self.lineno = self.lineno + 1
           line = self.fh.readline()
           if not line:
               return None
           if line.endswith("\n"):
               line = line[:-1]
           return "%d: %s" % (self.lineno, line)

       def __getstate__(self):
           odict = self.__dict__.copy() # copy the dict since we change it
           del odict['fh']              # remove filehandle entry
           return odict

       def __setstate__(self, dict):
           fh = open(dict['file'])      # reopen file
           count = dict['lineno']       # read from file...
           while count:                 # until line count is restored
               fh.readline()
               count = count - 1
           self.__dict__.update(dict)   # update attributes
           self.fh = fh                 # save the file object

A sample usage might be something like this::

   >>> import TextReader
   >>> obj = TextReader.TextReader("TextReader.py")
   >>> obj.readline()
   '1: #!/usr/local/bin/python'
   >>> obj.readline()
   '2: '
   >>> obj.readline()
   '3: class TextReader:'
   >>> import pickle
   >>> pickle.dump(obj, open('save.p', 'wb'))

If you want to see that :mod:`pickle` works across Python processes, start
another Python session, before continuing.  What follows can happen from either
the same process or a new process. ::

   >>> import pickle
   >>> reader = pickle.load(open('save.p', 'rb'))
   >>> reader.readline()
   '4:     """Print and number lines in a text file."""'


.. seealso::

   Module :mod:`copy_reg`
      Pickle interface constructor registration for extension types.

   Module :mod:`shelve`
      Indexed databases of objects; uses :mod:`pickle`.

   Module :mod:`copy`
      Shallow and deep object copying.

   Module :mod:`marshal`
      High-performance serialization of built-in types.


:mod:`cPickle` --- A faster :mod:`pickle`
=========================================

.. module:: cPickle
   :synopsis: Faster version of pickle, but not subclassable.
.. moduleauthor:: Jim Fulton <jim@zope.com>
.. sectionauthor:: Fred L. Drake, Jr. <fdrake@acm.org>


.. index:: module: pickle

The :mod:`cPickle` module supports serialization and de-serialization of Python
objects, providing an interface and functionality nearly identical to the
:mod:`pickle` module.  There are several differences, the most important being
performance and subclassability.

First, :mod:`cPickle` can be up to 1000 times faster than :mod:`pickle` because
the former is implemented in C.  Second, in the :mod:`cPickle` module the
callables :func:`Pickler` and :func:`Unpickler` are functions, not classes.
This means that you cannot use them to derive custom pickling and unpickling
subclasses.  Most applications have no need for this functionality and should
benefit from the greatly improved performance of the :mod:`cPickle` module.

The pickle data stream produced by :mod:`pickle` and :mod:`cPickle` are
identical, so it is possible to use :mod:`pickle` and :mod:`cPickle`
interchangeably with existing pickles. [#]_

There are additional minor differences in API between :mod:`cPickle` and
:mod:`pickle`, however for most applications, they are interchangeable.  More
documentation is provided in the :mod:`pickle` module documentation, which
includes a list of the documented differences.

.. rubric:: Footnotes

.. [#] Don't confuse this with the :mod:`marshal` module

.. [#] In the :mod:`pickle` module these callables are classes, which you could
   subclass to customize the behavior.  However, in the :mod:`cPickle` module these
   callables are factory functions and so cannot be subclassed.  One common reason
   to subclass is to control what objects can actually be unpickled.  See section
   :ref:`pickle-sub` for more details.

.. [#] *Warning*: this is intended for pickling multiple objects without intervening
   modifications to the objects or their parts.  If you modify an object and then
   pickle it again using the same :class:`Pickler` instance, the object is not
   pickled again --- a reference to it is pickled and the :class:`Unpickler` will
   return the old value, not the modified one. There are two problems here: (1)
   detecting changes, and (2) marshalling a minimal set of changes.  Garbage
   Collection may also become a problem here.

.. [#] The exception raised will likely be an :exc:`ImportError` or an
   :exc:`AttributeError` but it could be something else.

.. [#] These methods can also be used to implement copying class instances.

.. [#] This protocol is also used by the shallow and deep copying operations defined in
   the :mod:`copy` module.

.. [#] The actual mechanism for associating these user defined functions is slightly
   different for :mod:`pickle` and :mod:`cPickle`.  The description given here
   works the same for both implementations.  Users of the :mod:`pickle` module
   could also use subclassing to effect the same results, overriding the
   :meth:`persistent_id` and :meth:`persistent_load` methods in the derived
   classes.

.. [#] We'll leave you with the image of Guido and Jim sitting around sniffing pickles
   in their living rooms.

.. [#] A word of caution: the mechanisms described here use internal attributes and
   methods, which are subject to change in future versions of Python.  We intend to
   someday provide a common interface for controlling this behavior, which will
   work in either :mod:`pickle` or :mod:`cPickle`.

.. [#] Since the pickle data format is actually a tiny stack-oriented programming
   language, and some freedom is taken in the encodings of certain objects, it is
   possible that the two modules produce different data streams for the same input
   objects.  However it is guaranteed that they will always be able to read each
   other's data streams.