Doc/library/pickle.rst
!pickle --- Python object serialization.. module:: pickle :synopsis: Convert Python objects to streams of bytes and back.
Source code: :source:Lib/pickle.py
.. index:: single: persistence pair: persistent; objects pair: serializing; objects pair: marshalling; objects pair: flattening; objects pair: pickling; objects
The :mod:!pickle module implements binary protocols 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
(from a :term:binary file or :term:bytes-like object) 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".
.. warning::
The pickle module is not secure. Only unpickle data you trust.
It is possible to construct malicious pickle data which will execute arbitrary code during unpickling. Never unpickle data that could have come from an untrusted source, or that could have been tampered with.
Consider signing data with :mod:hmac if you need to ensure that it has not
been tampered with.
Safer serialization formats such as :mod:json may be more appropriate if
you are processing untrusted data. See :ref:comparison-with-json.
Comparison with marshal
^^^^^^^^^^^^^^^^^^^^^^^^^^^
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:
: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 provided a compatible pickle protocol is chosen and
pickling and unpickling code deals with Python 2 to Python 3 type differences
if your data is crossing that unique breaking change language boundary.
.. _comparison-with-json:
Comparison with json
^^^^^^^^^^^^^^^^^^^^^^^^
There are fundamental differences between the pickle protocols and
JSON (JavaScript Object Notation) <https://json.org>_:
JSON is a text serialization format (it outputs unicode text, although
most of the time it is then encoded to utf-8), while pickle is
a binary serialization format;
JSON is human-readable, while pickle is not;
JSON is interoperable and widely used outside of the Python ecosystem, while pickle is Python-specific;
JSON, by default, can only represent a subset of the Python built-in
types, and no custom classes; pickle can represent an extremely large
number of Python types (many of them automatically, by clever usage
of Python's introspection facilities; complex cases can be tackled by
implementing :ref:specific object APIs <pickle-inst>);
Unlike pickle, deserializing untrusted JSON does not in itself create an arbitrary code execution vulnerability.
.. seealso::
The :mod:json module: a standard library module allowing JSON
serialization and deserialization.
.. _pickle-protocols:
.. index:: 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
JSON (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 relatively compact binary
representation. If you need optimal size characteristics, you can efficiently
:doc:compress <archiving> pickled data.
The module :mod:pickletools contains tools for analyzing data streams
generated by :mod:!pickle. :mod:pickletools source code has extensive
comments about opcodes used by pickle protocols.
There are currently 6 different protocols which can be used for pickling. The higher the protocol used, the more recent the version of Python needed to read the pickle produced.
Protocol version 0 is the original "human-readable" protocol and is backwards compatible with earlier versions of Python.
Protocol version 1 is an 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 classes <new-style class>. Refer to :pep:307 for
information about improvements brought by protocol 2.
Protocol version 3 was added in Python 3.0. It has explicit support for
:class:bytes objects and cannot be unpickled by Python 2.x. This was
the default protocol in Python 3.0--3.7.
Protocol version 4 was added in Python 3.4. It adds support for very large
objects, pickling more kinds of objects, and some data format
optimizations. This was the default protocol in Python 3.8--3.13.
Refer to :pep:3154 for information about improvements brought by
protocol 4.
Protocol version 5 was added in Python 3.8. It adds support for out-of-band
data and speedup for in-band data. It is the default protocol starting with
Python 3.14. Refer to :pep:574 for information about improvements brought
by protocol 5.
.. note::
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 :mod:shelve
module provides a simple interface to pickle and unpickle objects on
DBM-style database files.
To serialize an object hierarchy, you simply call the :func:dumps function.
Similarly, to de-serialize a data stream, you call the :func:loads function.
However, if you want more control over serialization and de-serialization,
you can create a :class:Pickler or an :class:Unpickler object, respectively.
The :mod:!pickle module provides the following constants:
.. data:: HIGHEST_PROTOCOL
An integer, the highest :ref:protocol version <pickle-protocols>
available. This value can be passed as a protocol value to functions
:func:dump and :func:dumps as well as the :class:Pickler
constructor.
.. data:: DEFAULT_PROTOCOL
An integer, the default :ref:protocol version <pickle-protocols> used
for pickling. May be less than :data:HIGHEST_PROTOCOL. Currently the
default protocol is 5, introduced in Python 3.8 and incompatible
with previous versions. This version introduces support for out-of-band
buffers, where :pep:3118-compatible data can be transmitted separately
from the main pickle stream.
.. versionchanged:: 3.0
The default protocol is 3.
.. versionchanged:: 3.8
The default protocol is 4.
.. versionchanged:: 3.14
The default protocol is 5.
The :mod:!pickle module provides the following functions to make the pickling
process more convenient:
.. function:: dump(obj, file, protocol=None, *, fix_imports=True, buffer_callback=None)
Write the pickled representation of the object obj to the open
:term:file object file. This is equivalent to
Pickler(file, protocol).dump(obj).
Arguments file, protocol, fix_imports and buffer_callback have
the same meaning as in the :class:Pickler constructor.
.. versionchanged:: 3.8 The buffer_callback argument was added.
.. function:: dumps(obj, protocol=None, *, fix_imports=True, buffer_callback=None)
Return the pickled representation of the object obj as a :class:bytes object,
instead of writing it to a file.
Arguments protocol, fix_imports and buffer_callback have the same
meaning as in the :class:Pickler constructor.
.. versionchanged:: 3.8 The buffer_callback argument was added.
.. function:: load(file, *, fix_imports=True, encoding="ASCII", errors="strict", buffers=None)
Read the pickled representation of an object from the open :term:file object
file and return the reconstituted object hierarchy specified therein.
This is equivalent to Unpickler(file).load().
The protocol version of the pickle is detected automatically, so no protocol argument is needed. Bytes past the pickled representation of the object are ignored.
Arguments file, fix_imports, encoding, errors, strict and buffers
have the same meaning as in the :class:Unpickler constructor.
.. versionchanged:: 3.8 The buffers argument was added.
.. function:: loads(data, /, *, fix_imports=True, encoding="ASCII", errors="strict", buffers=None)
Return the reconstituted object hierarchy of the pickled representation
data of an object. data must be a :term:bytes-like object.
The protocol version of the pickle is detected automatically, so no protocol argument is needed. Bytes past the pickled representation of the object are ignored.
Arguments fix_imports, encoding, errors, strict and buffers
have the same meaning as in the :class:Unpickler constructor.
.. versionchanged:: 3.8 The buffers argument was added.
The :mod:!pickle module defines three exceptions:
.. exception:: PickleError
Common base class for the other pickling exceptions. It inherits from
:exc:Exception.
.. exception:: PicklingError
Error raised when an unpicklable object is encountered by :class:Pickler.
It inherits from :exc:PickleError.
Refer to :ref:pickle-picklable to learn what kinds of objects can be
pickled.
.. exception:: UnpicklingError
Error raised when there is a problem unpickling an object, such as a data
corruption or a security violation. It inherits from :exc:PickleError.
Note that other exceptions may also be raised during unpickling, including (but not necessarily limited to) AttributeError, EOFError, ImportError, and IndexError.
The :mod:!pickle module exports three classes, :class:Pickler,
:class:Unpickler and :class:PickleBuffer:
.. class:: Pickler(file, protocol=None, *, fix_imports=True, buffer_callback=None)
This takes a binary file for writing a pickle data stream.
The optional protocol argument, an integer, tells the pickler to use
the given protocol; supported protocols are 0 to :data:HIGHEST_PROTOCOL.
If not specified, the default is :data:DEFAULT_PROTOCOL. If a negative
number is specified, :data:HIGHEST_PROTOCOL is selected.
The file argument must have a write() method that accepts a single bytes
argument. It can thus be an on-disk file opened for binary writing, an
:class:io.BytesIO instance, or any other custom object that meets this
interface.
If fix_imports is true and protocol is less than 3, pickle will try to map the new Python 3 names to the old module names used in Python 2, so that the pickle data stream is readable with Python 2.
If buffer_callback is None (the default), buffer views are
serialized into file as part of the pickle stream.
If buffer_callback is not None, then it can be called any number
of times with a buffer view. If the callback returns a false value
(such as None), the given buffer is :ref:out-of-band <pickle-oob>;
otherwise the buffer is serialized in-band, i.e. inside the pickle stream.
It is an error if buffer_callback is not None and protocol is
None or smaller than 5.
.. versionchanged:: 3.8 The buffer_callback argument was added.
.. method:: dump(obj)
Write the pickled representation of *obj* to the open file object given in
the constructor.
.. method:: persistent_id(obj)
Do nothing by default. This exists so a subclass can override it.
If :meth:`persistent_id` returns ``None``, *obj* is pickled as usual. Any
other value causes :class:`Pickler` to emit the returned value as a
persistent ID for *obj*. The meaning of this persistent ID should be
defined by :meth:`Unpickler.persistent_load`. Note that the value
returned by :meth:`persistent_id` cannot itself have a persistent ID.
See :ref:`pickle-persistent` for details and examples of uses.
.. versionchanged:: 3.13
Add the default implementation of this method in the C implementation
of :class:`!Pickler`.
.. attribute:: dispatch_table
A pickler object's dispatch table is a registry of *reduction
functions* of the kind which can be declared using
:func:`copyreg.pickle`. It is a mapping whose keys are classes
and whose values are reduction functions. A reduction function
takes a single argument of the associated class and should
conform to the same interface as a :meth:`~object.__reduce__`
method.
By default, a pickler object will not have a
:attr:`dispatch_table` attribute, and it will instead use the
global dispatch table managed by the :mod:`copyreg` module.
However, to customize the pickling for a specific pickler object
one can set the :attr:`dispatch_table` attribute to a dict-like
object. Alternatively, if a subclass of :class:`Pickler` has a
:attr:`dispatch_table` attribute then this will be used as the
default dispatch table for instances of that class.
See :ref:`pickle-dispatch` for usage examples.
.. versionadded:: 3.3
.. method:: reducer_override(obj)
Special reducer that can be defined in :class:`Pickler` subclasses. This
method has priority over any reducer in the :attr:`dispatch_table`. It
should conform to the same interface as a :meth:`~object.__reduce__` method, and
can optionally return :data:`NotImplemented` to fallback on
:attr:`dispatch_table`-registered reducers to pickle ``obj``.
For a detailed example, see :ref:`reducer_override`.
.. versionadded:: 3.8
.. attribute:: fast
Deprecated. Enable fast mode if set to a true value. The fast mode
disables the usage of memo, therefore speeding the pickling process by not
generating superfluous PUT opcodes. It should not be used with
self-referential objects, doing otherwise will cause :class:`Pickler` to
recurse infinitely.
Use :func:`pickletools.optimize` if you need more compact pickles.
.. 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
are pickled by reference and not by value. This method is
useful when re-using picklers.
.. class:: Unpickler(file, *, fix_imports=True, encoding="ASCII", errors="strict", buffers=None)
This takes a binary file for reading a pickle data stream.
The protocol version of the pickle is detected automatically, so no protocol argument is needed.
The argument file must have three methods, a read() method that takes an
integer argument, a readinto() method that takes a buffer argument
and a readline() method that requires no arguments, as in the
:class:io.BufferedIOBase interface. Thus file can be an on-disk file
opened for binary reading, an :class:io.BytesIO object, or any other
custom object that meets this interface.
The optional arguments fix_imports, encoding and errors are used
to control compatibility support for pickle stream generated by Python 2.
If fix_imports is true, pickle will try to map the old Python 2 names
to the new names used in Python 3. The encoding and errors tell
pickle how to decode 8-bit string instances pickled by Python 2;
these default to 'ASCII' and 'strict', respectively. The encoding can
be 'bytes' to read these 8-bit string instances as bytes objects.
Using encoding='latin1' is required for unpickling NumPy arrays and
instances of :class:~datetime.datetime, :class:~datetime.date and
:class:~datetime.time pickled by Python 2.
If buffers is None (the default), then all data necessary for
deserialization must be contained in the pickle stream. This means
that the buffer_callback argument was None when a :class:Pickler
was instantiated (or when :func:dump or :func:dumps was called).
If buffers is not None, it should be an iterable of buffer-enabled
objects that is consumed each time the pickle stream references
an :ref:out-of-band <pickle-oob> buffer view. Such buffers have been
given in order to the buffer_callback of a Pickler object.
.. versionchanged:: 3.8 The buffers argument was added.
.. method:: load()
Read the pickled representation of an object from the open file object
given in the constructor, and return the reconstituted object hierarchy
specified therein. Bytes past the pickled representation of the object
are ignored.
.. method:: persistent_load(pid)
Raise an :exc:`UnpicklingError` by default.
If defined, :meth:`persistent_load` should return the object specified by
the persistent ID *pid*. If an invalid persistent ID is encountered, an
:exc:`UnpicklingError` should be raised.
See :ref:`pickle-persistent` for details and examples of uses.
.. versionchanged:: 3.13
Add the default implementation of this method in the C implementation
of :class:`!Unpickler`.
.. method:: find_class(module, name)
Import *module* if necessary and return the object called *name* from it,
where the *module* and *name* arguments are :class:`str` objects. Note,
unlike its name suggests, :meth:`find_class` is also used for finding
functions.
Subclasses may override this to gain control over what type of objects and
how they can be loaded, potentially reducing security risks. Refer to
:ref:`pickle-restrict` for details.
.. audit-event:: pickle.find_class module,name pickle.Unpickler.find_class
.. class:: PickleBuffer(buffer)
A wrapper for a buffer representing picklable data. buffer must be a
:ref:buffer-providing <bufferobjects> object, such as a
:term:bytes-like object or a N-dimensional array.
:class:PickleBuffer is itself a buffer provider, therefore it is
possible to pass it to other APIs expecting a buffer-providing object,
such as :class:memoryview.
:class:PickleBuffer objects can only be serialized using pickle
protocol 5 or higher. They are eligible for
:ref:out-of-band serialization <pickle-oob>.
.. versionadded:: 3.8
.. method:: raw()
Return a :class:`memoryview` of the memory area underlying this buffer.
The returned object is a one-dimensional, C-contiguous memoryview
with format ``B`` (unsigned bytes). :exc:`BufferError` is raised if
the buffer is neither C- nor Fortran-contiguous.
.. method:: release()
Release the underlying buffer exposed by the PickleBuffer object.
.. _pickle-picklable:
The following types can be pickled:
built-in constants (None, True, False, Ellipsis, and
:data:NotImplemented);
integers, floating-point numbers, complex numbers;
strings, bytes, bytearrays;
tuples, lists, sets, and dictionaries containing only picklable objects;
functions (built-in and user-defined) accessible from the top level of a
module (using :keyword:def, not :keyword:lambda);
classes accessible from the top level of a module;
instances of such classes for which the result of calling :meth:~object.__getstate__
is picklable (see section :ref:pickle-inst 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:RecursionError 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
:term:qualified name, not by value. [#]_ This means that only the function name is
pickled, along with the name of the containing module and classes. 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 fully qualified name, 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 attribute'
picklestring = pickle.dumps(Foo)
These restrictions are why picklable functions and classes must be defined at 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:~object.__setstate__ method.
.. _pickle-inst:
.. currentmodule:: None
In this section, we describe the general mechanisms available to you to define, customize, and control how class instances are pickled and unpickled.
In most cases, no additional code is needed to make instances picklable. By
default, pickle will retrieve the class and the attributes of an instance via
introspection. When a class instance is unpickled, its :meth:~object.__init__ method
is usually not invoked. The default behaviour first creates an uninitialized
instance and then restores the saved attributes. The following code shows an
implementation of this behaviour::
def save(obj): return (obj.class, obj.dict)
def restore(cls, attributes): obj = cls.new(cls) obj.dict.update(attributes) return obj
Classes can alter the default behaviour by providing one or several special methods:
.. method:: object.getnewargs_ex()
In protocols 2 and newer, classes that implement the
:meth:__getnewargs_ex__ method can dictate the values passed to the
:meth:__new__ method upon unpickling. The method must return a pair
(args, kwargs) where args is a tuple of positional arguments
and kwargs a dictionary of named arguments for constructing the
object. Those will be passed to the :meth:__new__ method upon
unpickling.
You should implement this method if the :meth:__new__ method of your
class requires keyword-only arguments. Otherwise, it is recommended for
compatibility to implement :meth:__getnewargs__.
.. versionchanged:: 3.6
:meth:__getnewargs_ex__ is now used in protocols 2 and 3.
.. method:: object.getnewargs()
This method serves a similar purpose as :meth:__getnewargs_ex__, but
supports only positional arguments. It must return a tuple of arguments
args which will be passed to the :meth:__new__ method upon unpickling.
:meth:__getnewargs__ will not be called if :meth:__getnewargs_ex__ is
defined.
.. versionchanged:: 3.6
Before Python 3.6, :meth:__getnewargs__ was called instead of
:meth:__getnewargs_ex__ in protocols 2 and 3.
.. method:: object.getstate()
Classes can further influence how their instances are pickled by overriding
the method :meth:__getstate__. It is called and the returned object
is pickled as the contents for the instance, instead of a default state.
There are several cases:
For a class that has no instance :attr:~object.__dict__ and no
:attr:~object.__slots__, the default state is None.
For a class that has an instance :attr:~object.__dict__ and no
:attr:~object.__slots__, the default state is self.__dict__.
For a class that has an instance :attr:~object.__dict__ and
:attr:~object.__slots__, the default state is a tuple consisting of two
dictionaries: self.__dict__, and a dictionary mapping slot
names to slot values. Only slots that have a value are
included in the latter.
For a class that has :attr:~object.__slots__ and no instance
:attr:~object.__dict__, the default state is a tuple whose first item
is None and whose second item is a dictionary mapping slot names
to slot values described in the previous bullet.
.. versionchanged:: 3.11
Added the default implementation of the __getstate__() method in the
:class:object class.
.. method:: object.setstate(state)
Upon unpickling, if the class defines :meth:__setstate__, it is called with
the unpickled state. In that case, there is no requirement for the state
object to be a dictionary. Otherwise, the pickled state must be a dictionary
and its items are assigned to the new instance's dictionary.
.. note::
If :meth:`__reduce__` returns a state with value ``None`` at pickling,
the :meth:`__setstate__` method will not be called upon unpickling.
Refer to the section :ref:pickle-state for more information about how to use
the methods :meth:~object.__getstate__ and :meth:~object.__setstate__.
.. note::
At unpickling time, some methods like :meth:~object.__getattr__,
:meth:~object.__getattribute__, or :meth:~object.__setattr__ may be called upon the
instance. In case those methods rely on some internal invariant being
true, the type should implement :meth:~object.__new__ to establish such an
invariant, as :meth:~object.__init__ is not called when unpickling an
instance.
.. index:: pair: copy; protocol
As we shall see, pickle does not use directly the methods described above. In
fact, these methods are part of the copy protocol which implements the
:meth:~object.__reduce__ special method. The copy protocol provides a unified
interface for retrieving the data necessary for pickling and copying
objects. [#]_
Although powerful, implementing :meth:~object.__reduce__ directly in your classes is
error prone. For this reason, class designers should use the high-level
interface (i.e., :meth:~object.__getnewargs_ex__, :meth:~object.__getstate__ and
:meth:~object.__setstate__) whenever possible. We will show, however, cases where
using :meth:!__reduce__ is the only option or leads to more efficient pickling
or both.
.. method:: object.reduce()
The interface is currently defined as follows. The :meth:__reduce__ method
takes no argument and shall return either a string or preferably a tuple (the
returned object is often referred to as the "reduce value").
If a string is returned, the string should be interpreted as the name of a global variable. It should be the object's local name relative to its module; the pickle module searches the module namespace to determine the object's module. This behaviour is typically useful for singletons.
When a tuple is returned, it must be between two and six items long.
Optional items can either be omitted, or None can be provided as their
value. The semantics of each item are in order:
.. XXX Mention newobj special-case?
A callable object that will be called to create the initial version of the object.
A tuple of arguments for the callable object. An empty tuple must be given if the callable does not accept any argument.
Optionally, the object's state, which will be passed to the object's
:meth:__setstate__ method as previously described. If the object has no
such method then, the value must be a dictionary and it will be added to
the object's :attr:~object.__dict__ attribute.
Optionally, an iterator (and not a sequence) yielding successive items.
These items will be appended to the object either using
obj.append(item) or, in batch, using 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:~sequence.append
and :meth:~sequence.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 key-value
pairs. These items will be 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__.
Optionally, a callable with a (obj, state) signature. This
callable allows the user to programmatically control the state-updating
behavior of a specific object, instead of using obj's static
:meth:__setstate__ method. If not None, this callable will have
priority over obj's :meth:__setstate__.
.. versionadded:: 3.8
The optional sixth tuple item, (obj, state), was added.
.. method:: object.reduce_ex(protocol)
Alternatively, a :meth:__reduce_ex__ method may be defined. The only
difference is this method should take a single integer argument, the protocol
version. When defined, pickle will prefer it over the :meth:__reduce__
method. In addition, :meth:__reduce__ automatically becomes a synonym for
the extended version. The main use for this method is to provide
backwards-compatible reduce values for older Python releases.
.. currentmodule:: pickle
.. _pickle-persistent:
Persistence of 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 should be either a string of
alphanumeric characters (for protocol 0) [#]_ or just an arbitrary object (for
any newer protocol).
The resolution of such persistent IDs is not defined by the :mod:!pickle
module; it will delegate this resolution to the user-defined methods on the
pickler and unpickler, :meth:~Pickler.persistent_id and
:meth:~Unpickler.persistent_load respectively.
To pickle objects that have an external persistent ID, the pickler must have a
custom :meth:~Pickler.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 object,
along with a marker so that the unpickler will recognize it as a persistent ID.
To unpickle external objects, the unpickler must have a custom
:meth:~Unpickler.persistent_load method that takes a persistent ID object and
returns the referenced object.
Here is a comprehensive example presenting how persistent ID can be used to pickle external objects by reference.
.. literalinclude:: ../includes/dbpickle.py
.. _pickle-dispatch:
Dispatch Tables ^^^^^^^^^^^^^^^
If one wants to customize pickling of some classes without disturbing any other code which depends on pickling, then one can create a pickler with a private dispatch table.
The global dispatch table managed by the :mod:copyreg module is
available as :data:!copyreg.dispatch_table. Therefore, one may
choose to use a modified copy of :data:!copyreg.dispatch_table as a
private dispatch table.
For example ::
f = io.BytesIO() p = pickle.Pickler(f) p.dispatch_table = copyreg.dispatch_table.copy() p.dispatch_table[SomeClass] = reduce_SomeClass
creates an instance of :class:pickle.Pickler with a private dispatch
table which handles the SomeClass class specially. Alternatively,
the code ::
class MyPickler(pickle.Pickler): dispatch_table = copyreg.dispatch_table.copy() dispatch_table[SomeClass] = reduce_SomeClass f = io.BytesIO() p = MyPickler(f)
does the same but all instances of MyPickler will by default
share the private dispatch table. On the other hand, the code ::
copyreg.pickle(SomeClass, reduce_SomeClass) f = io.BytesIO() p = pickle.Pickler(f)
modifies the global dispatch table shared by all users of the :mod:copyreg module.
.. _pickle-state:
Handling Stateful Objects ^^^^^^^^^^^^^^^^^^^^^^^^^
.. index:: single: getstate() (copy protocol) single: setstate() (copy protocol)
Here's an example that shows how to modify pickling behavior for a class.
The :class:!TextReader class below 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. ::
class TextReader: """Print and number lines in a text file."""
def __init__(self, filename):
self.filename = filename
self.file = open(filename)
self.lineno = 0
def readline(self):
self.lineno += 1
line = self.file.readline()
if not line:
return None
if line.endswith('\n'):
line = line[:-1]
return "%i: %s" % (self.lineno, line)
def __getstate__(self):
# Copy the object's state from self.__dict__ which contains
# all our instance attributes. Always use the dict.copy()
# method to avoid modifying the original state.
state = self.__dict__.copy()
# Remove the unpicklable entries.
del state['file']
return state
def __setstate__(self, state):
# Restore instance attributes (i.e., filename and lineno).
self.__dict__.update(state)
# Restore the previously opened file's state. To do so, we need to
# reopen it and read from it until the line count is restored.
file = open(self.filename)
for _ in range(self.lineno):
file.readline()
# Finally, save the file.
self.file = file
A sample usage might be something like this::
reader = TextReader("hello.txt") reader.readline() '1: Hello world!' reader.readline() '2: I am line number two.' new_reader = pickle.loads(pickle.dumps(reader)) new_reader.readline() '3: Goodbye!'
.. _reducer_override:
.. versionadded:: 3.8
Sometimes, :attr:~Pickler.dispatch_table may not be flexible enough.
In particular we may want to customize pickling based on another criterion
than the object's type, or we may want to customize the pickling of
functions and classes.
For those cases, it is possible to subclass from the :class:Pickler class and
implement a :meth:~Pickler.reducer_override method. This method can return an
arbitrary reduction tuple (see :meth:~object.__reduce__). It can alternatively return
:data:NotImplemented to fallback to the traditional behavior.
If both the :attr:~Pickler.dispatch_table and
:meth:~Pickler.reducer_override are defined, then
:meth:~Pickler.reducer_override method takes priority.
.. Note::
For performance reasons, :meth:~Pickler.reducer_override may not be
called for the following objects: None, True, False, and
exact instances of :class:int, :class:float, :class:bytes,
:class:str, :class:dict, :class:set, :class:frozenset, :class:list
and :class:tuple.
Here is a simple example where we allow pickling and reconstructing a given class::
import io import pickle
class MyClass: my_attribute = 1
class MyPickler(pickle.Pickler): def reducer_override(self, obj): """Custom reducer for MyClass.""" if getattr(obj, "name", None) == "MyClass": return type, (obj.name, obj.bases, {'my_attribute': obj.my_attribute}) else: # For any other object, fallback to usual reduction return NotImplemented
f = io.BytesIO() p = MyPickler(f) p.dump(MyClass)
del MyClass
unpickled_class = pickle.loads(f.getvalue())
assert isinstance(unpickled_class, type) assert unpickled_class.name == "MyClass" assert unpickled_class.my_attribute == 1
.. _pickle-oob:
.. versionadded:: 3.8
In some contexts, the :mod:!pickle module is used to transfer massive amounts
of data. Therefore, it can be important to minimize the number of memory
copies, to preserve performance and resource consumption. However, normal
operation of the :mod:!pickle module, as it transforms a graph-like structure
of objects into a sequential stream of bytes, intrinsically involves copying
data to and from the pickle stream.
This constraint can be eschewed if both the provider (the implementation of the object types to be transferred) and the consumer (the implementation of the communications system) support the out-of-band transfer facilities provided by pickle protocol 5 and higher.
Provider API ^^^^^^^^^^^^
The large data objects to be pickled must implement a :meth:~object.__reduce_ex__
method specialized for protocol 5 and higher, which returns a
:class:PickleBuffer instance (instead of e.g. a :class:bytes object)
for any large data.
A :class:PickleBuffer object signals that the underlying buffer is
eligible for out-of-band data transfer. Those objects remain compatible
with normal usage of the :mod:!pickle module. However, consumers can also
opt-in to tell :mod:!pickle that they will handle those buffers by
themselves.
Consumer API ^^^^^^^^^^^^
A communications system can enable custom handling of the :class:PickleBuffer
objects generated when serializing an object graph.
On the sending side, it needs to pass a buffer_callback argument to
:class:Pickler (or to the :func:dump or :func:dumps function), which
will be called with each :class:PickleBuffer generated while pickling
the object graph. Buffers accumulated by the buffer_callback will not
see their data copied into the pickle stream, only a cheap marker will be
inserted.
On the receiving side, it needs to pass a buffers argument to
:class:Unpickler (or to the :func:load or :func:loads function),
which is an iterable of the buffers which were passed to buffer_callback.
That iterable should produce buffers in the same order as they were passed
to buffer_callback. Those buffers will provide the data expected by the
reconstructors of the objects whose pickling produced the original
:class:PickleBuffer objects.
Between the sending side and the receiving side, the communications system is free to implement its own transfer mechanism for out-of-band buffers. Potential optimizations include the use of shared memory or datatype-dependent compression.
Example ^^^^^^^
Here is a trivial example where we implement a :class:bytearray subclass
able to participate in out-of-band buffer pickling::
class ZeroCopyByteArray(bytearray):
def __reduce_ex__(self, protocol):
if protocol >= 5:
return type(self)._reconstruct, (PickleBuffer(self),), None
else:
# PickleBuffer is forbidden with pickle protocols <= 4.
return type(self)._reconstruct, (bytearray(self),)
@classmethod
def _reconstruct(cls, obj):
with memoryview(obj) as m:
# Get a handle over the original buffer object
obj = m.obj
if type(obj) is cls:
# Original buffer object is a ZeroCopyByteArray, return it
# as-is.
return obj
else:
return cls(obj)
The reconstructor (the _reconstruct class method) returns the buffer's
providing object if it has the right type. This is an easy way to simulate
zero-copy behaviour on this toy example.
On the consumer side, we can pickle those objects the usual way, which when unserialized will give us a copy of the original object::
b = ZeroCopyByteArray(b"abc") data = pickle.dumps(b, protocol=5) new_b = pickle.loads(data) print(b == new_b) # True print(b is new_b) # False: a copy was made
But if we pass a buffer_callback and then give back the accumulated buffers when unserializing, we are able to get back the original object::
b = ZeroCopyByteArray(b"abc") buffers = [] data = pickle.dumps(b, protocol=5, buffer_callback=buffers.append) new_b = pickle.loads(data, buffers=buffers) print(b == new_b) # True print(b is new_b) # True: no copy was made
This example is limited by the fact that :class:bytearray allocates its
own memory: you cannot create a :class:bytearray instance that is backed
by another object's memory. However, third-party datatypes such as NumPy
arrays do not have this limitation, and allow use of zero-copy pickling
(or making as few copies as possible) when transferring between distinct
processes or systems.
.. seealso:: :pep:574 -- Pickle protocol 5 with out-of-band data
.. _pickle-restrict:
.. index:: single: find_class() (pickle protocol)
By default, unpickling will import any class or function that it finds in the pickle data. For many applications, this behaviour is unacceptable as it permits the unpickler to import and invoke arbitrary code. Just consider what this hand-crafted pickle data stream does when loaded::
>>> import pickle
>>> pickle.loads(b"cos\nsystem\n(S'echo hello world'\ntR.")
hello world
0
In this example, the unpickler imports the :func:os.system function and then
apply the string argument "echo hello world". Although this example is
inoffensive, it is not difficult to imagine one that could damage your system.
For this reason, you may want to control what gets unpickled by customizing
:meth:Unpickler.find_class. Unlike its name suggests,
:meth:Unpickler.find_class is called whenever a global (i.e., a class or
a function) is requested. Thus it is possible to either completely forbid
globals or restrict them to a safe subset.
Here is an example of an unpickler allowing only few safe classes from the
:mod:builtins module to be loaded::
import builtins import io import pickle
safe_builtins = { 'range', 'complex', 'set', 'frozenset', 'slice', }
class RestrictedUnpickler(pickle.Unpickler):
def find_class(self, module, name):
# Only allow safe classes from builtins.
if module == "builtins" and name in safe_builtins:
return getattr(builtins, name)
# Forbid everything else.
raise pickle.UnpicklingError("global '%s.%s' is forbidden" %
(module, name))
def restricted_loads(s): """Helper function analogous to pickle.loads().""" return RestrictedUnpickler(io.BytesIO(s)).load()
A sample usage of our unpickler working as intended::
>>> restricted_loads(pickle.dumps([1, 2, range(15)]))
[1, 2, range(0, 15)]
>>> restricted_loads(b"cos\nsystem\n(S'echo hello world'\ntR.")
Traceback (most recent call last):
...
pickle.UnpicklingError: global 'os.system' is forbidden
>>> restricted_loads(b'cbuiltins\neval\n'
... b'(S\'getattr(__import__("os"), "system")'
... b'("echo hello world")\'\ntR.')
Traceback (most recent call last):
...
pickle.UnpicklingError: global 'builtins.eval' is forbidden
.. XXX Add note about how extension codes could evade our protection mechanism (e.g. cached classes do not invokes find_class()).
As our examples shows, you have to be careful with what you allow to be
unpickled. Therefore if security is a concern, you may want to consider
alternatives such as the marshalling API in :mod:xmlrpc.client or
third-party solutions.
Recent versions of the pickle protocol (from protocol 2 and upwards) feature
efficient binary encodings for several common features and built-in types.
Also, the :mod:!pickle module has a transparent optimizer written in C.
.. _pickle-example:
For the simplest code, use the :func:dump and :func:load functions. ::
import pickle
data = { 'a': [1, 2.0, 3+4j], 'b': ("character string", b"byte string"), 'c': {None, True, False} }
with open('data.pickle', 'wb') as f: # Pickle the 'data' dictionary using the highest protocol available. pickle.dump(data, f, pickle.HIGHEST_PROTOCOL)
The following example reads the resulting pickled data. ::
import pickle
with open('data.pickle', 'rb') as f: # The protocol version used is detected automatically, so we do not # have to specify it. data = pickle.load(f)
.. XXX: Add examples showing how to optimize pickles for size (like using .. pickletools.optimize() or the gzip module).
.. _pickle-cli:
The :mod:!pickle module can be invoked as a script from the command line,
it will display contents of the pickle files. However, when the pickle file
that you want to examine comes from an untrusted source, -m pickletools
is a safer option because it does not execute pickle bytecode, see
:ref:pickletools CLI usage <pickletools-cli>.
.. code-block:: bash
python -m pickle pickle_file [pickle_file ...]
The following option is accepted:
.. program:: pickle
.. option:: pickle_file
A pickle file to read, or - to indicate reading from standard input.
.. seealso::
Module :mod:copyreg
Pickle interface constructor registration for extension types.
Module :mod:pickletools
Tools for working with and analyzing pickled data.
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.
.. rubric:: Footnotes
.. [#] Don't confuse this with the :mod:marshal module
.. [#] This is why :keyword:lambda functions cannot be pickled: all
:keyword:!lambda functions share the same name: <lambda>.
.. [#] The exception raised will likely be an :exc:ImportError or an
:exc:AttributeError but it could be something else.
.. [#] The :mod:copy module uses this protocol for shallow and deep copying
operations.
.. [#] The limitation on alphanumeric characters is due to the fact that persistent IDs in protocol 0 are delimited by the newline character. Therefore if any kind of newline characters occurs in persistent IDs, the resulting pickled data will become unreadable.