ref: 5f7a6b7ea3c4ae1b51beffe3309e9b6b0491e71f
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\section{\module{pickle} --- Python object serialization}
\declaremodule{standard}{pickle}
\modulesynopsis{Convert Python objects to streams of bytes and back.}
% Substantial improvements by Jim Kerr <[email protected]>.
% Rewritten by Barry Warsaw <[email protected]>
\index{persistence}
\indexii{persistent}{objects}
\indexii{serializing}{objects}
\indexii{marshalling}{objects}
\indexii{flattening}{objects}
\indexii{pickling}{objects}
The \module{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,''\footnote{Don't confuse this with
the \refmodule{marshal} module} or ``flattening'',
however, to avoid confusion, the terms used here are ``pickling'' and
``unpickling''.
This documentation describes both the \module{pickle} module and the
\refmodule{cPickle} module.
\subsection{Relationship to other Python modules}
The \module{pickle} module has an optimized cousin called the
\module{cPickle} module. As its name implies, \module{cPickle} is
written in C, so it can be up to 1000 times faster than
\module{pickle}. However it does not support subclassing of the
\function{Pickler()} and \function{Unpickler()} classes, because in
\module{cPickle} these are functions, not classes. Most applications
have no need for this functionality, and can benefit from the improved
performance of \module{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 \module{pickle} and
\module{cPickle} modules.
The data streams the two modules produce are guaranteed to be
interchangeable.
Python has a more primitive serialization module called
\refmodule{marshal}, but in general
\module{pickle} should always be the preferred way to serialize Python
objects. \module{marshal} exists primarily to support Python's
\file{.pyc} files.
The \module{pickle} module differs from \refmodule{marshal} several
significant ways:
\begin{itemize}
\item The \module{pickle} module keeps track of the objects it has
already serialized, so that later references to the same object
won't be serialized again. \module{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. \module{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.
\item \module{marshal} cannot be used to serialize user-defined
classes and their instances. \module{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.
\item The \module{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
\module{pickle} serialization format is guaranteed to be
backwards compatible across Python releases.
\end{itemize}
\begin{notice}[warning]
The \module{pickle} module is not intended to be secure against
erroneous or maliciously constructed data. Never unpickle data
received from an untrusted or unauthenticated source.
\end{notice}
Note that serialization is a more primitive notion than persistence;
although
\module{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 \module{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
\refmodule{shelve} provides a simple interface
to pickle and unpickle objects on DBM-style database files.
\subsection{Data stream format}
The data format used by \module{pickle} is Python-specific. This has
the advantage that there are no restrictions imposed by external
standards such as XDR\index{XDR}\index{External Data Representation}
(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 \module{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 \module{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.
\begin{itemize}
\item Protocol version 0 is the original ASCII protocol and is backwards
compatible with earlier versions of Python.
\item Protocol version 1 is the old binary format which is also compatible
with earlier versions of Python.
\item Protocol version 2 was introduced in Python 2.3. It provides
much more efficient pickling of new-style classes.
\end{itemize}
Refer to PEP 307 for more information.
If a \var{protocol} is not specified, protocol 0 is used.
If \var{protocol} is specified as a negative value
or \constant{HIGHEST_PROTOCOL},
the highest protocol version available will be used.
\versionchanged[Introduced the \var{protocol} parameter]{2.3}
A binary format, which is slightly more efficient, can be chosen by
specifying a \var{protocol} version >= 1.
\subsection{Usage}
To serialize an object hierarchy, you first create a pickler, then you
call the pickler's \method{dump()} method. To de-serialize a data
stream, you first create an unpickler, then you call the unpickler's
\method{load()} method. The \module{pickle} module provides the
following constant:
\begin{datadesc}{HIGHEST_PROTOCOL}
The highest protocol version available. This value can be passed
as a \var{protocol} value.
\versionadded{2.3}
\end{datadesc}
\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 \module{pickle} module provides the
following functions to make the pickling process more convenient:
\begin{funcdesc}{dump}{obj, file\optional{, protocol}}
Write a pickled representation of \var{obj} to the open file object
\var{file}. This is equivalent to
\code{Pickler(\var{file}, \var{protocol}).dump(\var{obj})}.
If the \var{protocol} parameter is omitted, protocol 0 is used.
If \var{protocol} is specified as a negative value
or \constant{HIGHEST_PROTOCOL},
the highest protocol version will be used.
\versionchanged[Introduced the \var{protocol} parameter]{2.3}
\var{file} must have a \method{write()} method that accepts a single
string argument. It can thus be a file object opened for writing, a
\refmodule{StringIO} object, or any other custom
object that meets this interface.
\end{funcdesc}
\begin{funcdesc}{load}{file}
Read a string from the open file object \var{file} and interpret it as
a pickle data stream, reconstructing and returning the original object
hierarchy. This is equivalent to \code{Unpickler(\var{file}).load()}.
\var{file} must have two methods, a \method{read()} method that takes
an integer argument, and a \method{readline()} method that requires no
arguments. Both methods should return a string. Thus \var{file} can
be a file object opened for reading, a
\module{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.
\end{funcdesc}
\begin{funcdesc}{dumps}{obj\optional{, protocol}}
Return the pickled representation of the object as a string, instead
of writing it to a file.
If the \var{protocol} parameter is omitted, protocol 0 is used.
If \var{protocol} is specified as a negative value
or \constant{HIGHEST_PROTOCOL},
the highest protocol version will be used.
\versionchanged[The \var{protocol} parameter was added]{2.3}
\end{funcdesc}
\begin{funcdesc}{loads}{string}
Read a pickled object hierarchy from a string. Characters in the
string past the pickled object's representation are ignored.
\end{funcdesc}
The \module{pickle} module also defines three exceptions:
\begin{excdesc}{PickleError}
A common base class for the other exceptions defined below. This
inherits from \exception{Exception}.
\end{excdesc}
\begin{excdesc}{PicklingError}
This exception is raised when an unpicklable object is passed to
the \method{dump()} method.
\end{excdesc}
\begin{excdesc}{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) \exception{AttributeError},
\exception{EOFError}, \exception{ImportError}, and \exception{IndexError}.
\end{excdesc}
The \module{pickle} module also exports two callables\footnote{In the
\module{pickle} module these callables are classes, which you could
subclass to customize the behavior. However, in the \refmodule{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.}, \class{Pickler} and \class{Unpickler}:
\begin{classdesc}{Pickler}{file\optional{, protocol}}
This takes a file-like object to which it will write a pickle data
stream.
If the \var{protocol} parameter is omitted, protocol 0 is used.
If \var{protocol} is specified as a negative value,
the highest protocol version will be used.
\versionchanged[Introduced the \var{protocol} parameter]{2.3}
\var{file} must have a \method{write()} method that accepts a single
string argument. It can thus be an open file object, a
\module{StringIO} object, or any other custom
object that meets this interface.
\end{classdesc}
\class{Pickler} objects define one (or two) public methods:
\begin{methoddesc}[Pickler]{dump}{obj}
Write a pickled representation of \var{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 \var{protocol} argument passed to the
constructor.
\end{methoddesc}
\begin{methoddesc}[Pickler]{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.
\begin{notice}
Prior to Python 2.3, \method{clear_memo()} was only available on the
picklers created by \refmodule{cPickle}. In the \module{pickle} module,
picklers have an instance variable called \member{memo} which is a
Python dictionary. So to clear the memo for a \module{pickle} module
pickler, you could do the following:
\begin{verbatim}
mypickler.memo.clear()
\end{verbatim}
Code that does not need to support older versions of Python should
simply use \method{clear_memo()}.
\end{notice}
\end{methoddesc}
It is possible to make multiple calls to the \method{dump()} method of
the same \class{Pickler} instance. These must then be matched to the
same number of calls to the \method{load()} method of the
corresponding \class{Unpickler} instance. If the same object is
pickled by multiple \method{dump()} calls, the \method{load()} will
all yield references to the same object.\footnote{\emph{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.}
\class{Unpickler} objects are defined as:
\begin{classdesc}{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.
\var{file} must have two methods, a \method{read()} method that takes
an integer argument, and a \method{readline()} method that requires no
arguments. Both methods should return a string. Thus \var{file} can
be a file object opened for reading, a
\module{StringIO} object, or any other custom
object that meets this interface.
\end{classdesc}
\class{Unpickler} objects have one (or two) public methods:
\begin{methoddesc}[Unpickler]{load}{}
Read a pickled object representation from the open file object given
in the constructor, and return the reconstituted object hierarchy
specified therein.
\end{methoddesc}
\begin{methoddesc}[Unpickler]{noload}{}
This is just like \method{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.
\strong{Note:} the \method{noload()} method is currently only
available on \class{Unpickler} objects created with the
\module{cPickle} module. \module{pickle} module \class{Unpickler}s do
not have the \method{noload()} method.
\end{methoddesc}
\subsection{What can be pickled and unpickled?}
The following types can be pickled:
\begin{itemize}
\item \code{None}, \code{True}, and \code{False}
\item integers, long integers, floating point numbers, complex numbers
\item normal and Unicode strings
\item tuples, lists, sets, and dictionaries containing only picklable objects
\item functions defined at the top level of a module
\item built-in functions defined at the top level of a module
\item classes that are defined at the top level of a module
\item instances of such classes whose \member{__dict__} or
\method{__setstate__()} is picklable (see
section~\ref{pickle-protocol} for details)
\end{itemize}
Attempts to pickle unpicklable objects will raise the
\exception{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 \exception{RuntimeError} will be raised
in this case. You can carefully raise this limit with
\function{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 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.\footnote{The exception
raised will likely be an \exception{ImportError} or an
\exception{AttributeError} but it could be something else.}
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 \code{attr} is not restored in the unpickling
environment:
\begin{verbatim}
class Foo:
attr = 'a class attr'
picklestring = pickle.dumps(Foo)
\end{verbatim}
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 \method{__setstate__()} method.
\subsection{The pickle protocol
\label{pickle-protocol}}\setindexsubitem{(pickle protocol)}
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.
\subsubsection{Pickling and unpickling normal class
instances\label{pickle-inst}}
When a pickled class instance is unpickled, its \method{__init__()}
method is normally \emph{not} invoked. If it is desirable that the
\method{__init__()} method be called on unpickling, an old-style class
can define a method \method{__getinitargs__()}, which should return a
\emph{tuple} containing the arguments to be passed to the class
constructor (\method{__init__()} for example). The
\method{__getinitargs__()} method is called at
pickle time; the tuple it returns is incorporated in the pickle for
the instance.
\withsubitem{(copy protocol)}{\ttindex{__getinitargs__()}}
\withsubitem{(instance constructor)}{\ttindex{__init__()}}
\withsubitem{(copy protocol)}{\ttindex{__getnewargs__()}}
New-style types can provide a \method{__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
\method{__new__()} method for the type (as it is for tuples and
strings). Instances of a new-style type \class{C} are created using
\begin{alltt}
obj = C.__new__(C, *\var{args})
\end{alltt}
where \var{args} is the result of calling \method{__getnewargs__()} on
the original object; if there is no \method{__getnewargs__()}, an
empty tuple is assumed.
\withsubitem{(copy protocol)}{
\ttindex{__getstate__()}\ttindex{__setstate__()}}
\withsubitem{(instance attribute)}{
\ttindex{__dict__}}
Classes can further influence how their instances are pickled; if the
class defines the method \method{__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
\method{__getstate__()} method, the instance's \member{__dict__} is
pickled.
Upon unpickling, if the class also defines the method
\method{__setstate__()}, it is called with the unpickled
state.\footnote{These methods can also be used to implement copying
class instances.} If there is no \method{__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
\method{__getstate__()} and \method{__setstate__()}, the state object
needn't be a dictionary and these methods can do what they
want.\footnote{This protocol is also used by the shallow and deep
copying operations defined in the
\refmodule{copy} module.}
\begin{notice}[warning]
For new-style classes, if \method{__getstate__()} returns a false
value, the \method{__setstate__()} method will not be called.
\end{notice}
\subsubsection{Pickling and unpickling extension types}
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 \method{__reduce__()} method. If provided, at pickling
time \method{__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 \method{__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 \code{None} can be provided
as their value. The semantics of each element are:
\begin{itemize}
\item 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 \member{__safe_for_unpickling__} with a true value.
Otherwise, an \exception{UnpicklingError} will be raised in the
unpickling environment. Note that as usual, the callable itself is
pickled by name.
\item A tuple of arguments for the callable object.
\versionchanged[Formerly, this argument could also be \code{None}]{2.5}
\item Optionally, the object's state, which will be passed to
the object's \method{__setstate__()} method as described in
section~\ref{pickle-inst}. If the object has no
\method{__setstate__()} method, then, as above, the value must
be a dictionary and it will be added to the object's
\member{__dict__}.
\item Optionally, an iterator (and not a sequence) yielding successive
list items. These list items will be pickled, and appended to the
object using either \code{obj.append(\var{item})} or
\code{obj.extend(\var{list_of_items})}. This is primarily used for
list subclasses, but may be used by other classes as long as they have
\method{append()} and \method{extend()} methods with the appropriate
signature. (Whether \method{append()} or \method{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.)
\item Optionally, an iterator (not a sequence)
yielding successive dictionary items, which should be tuples of the
form \code{(\var{key}, \var{value})}. These items will be pickled
and stored to the object using \code{obj[\var{key}] = \var{value}}.
This is primarily used for dictionary subclasses, but may be used by
other classes as long as they implement \method{__setitem__}.
\end{itemize}
It is sometimes useful to know the protocol version when implementing
\method{__reduce__}. This can be done by implementing a method named
\method{__reduce_ex__} instead of \method{__reduce__}.
\method{__reduce_ex__}, when it exists, is called in preference over
\method{__reduce__} (you may still provide \method{__reduce__} for
backwards compatibility). The \method{__reduce_ex__} method will be
called with a single integer argument, the protocol version.
The \class{object} class implements both \method{__reduce__} and
\method{__reduce_ex__}; however, if a subclass overrides
\method{__reduce__} but not \method{__reduce_ex__}, the
\method{__reduce_ex__} implementation detects this and calls
\method{__reduce__}.
An alternative to implementing a \method{__reduce__()} method on the
object to be pickled, is to register the callable with the
\refmodule[copyreg]{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 \method{__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.
\subsubsection{Pickling and unpickling external objects}
For the benefit of object persistence, the \module{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 \module{pickle}
module; it will delegate this resolution to user defined functions on
the pickler and unpickler.\footnote{The actual mechanism for
associating these user defined functions is slightly different for
\module{pickle} and \module{cPickle}. The description given here
works the same for both implementations. Users of the \module{pickle}
module could also use subclassing to effect the same results,
overriding the \method{persistent_id()} and \method{persistent_load()}
methods in the derived classes.}
To define external persistent id resolution, you need to set the
\member{persistent_id} attribute of the pickler object and the
\member{persistent_load} attribute of the unpickler object.
To pickle objects that have an external persistent id, the pickler
must have a custom \function{persistent_id()} method that takes an
object as an argument and returns either \code{None} or the persistent
id for that object. When \code{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
\function{persistent_load()} function that takes a persistent id
string and returns the referenced object.
Here's a silly example that \emph{might} shed more light:
\begin{verbatim}
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
\end{verbatim}
In the \module{cPickle} module, the unpickler's
\member{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.\footnote{We'll leave you with the image of Guido and Jim
sitting around sniffing pickles in their living rooms.} Setting
\member{persistent_load} to a list is usually used in conjunction with
the \method{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.
\subsection{Subclassing Unpicklers \label{pickle-sub}}
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
\module{pickle} or \module{cPickle}.\footnote{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 \module{pickle} or \module{cPickle}.}
In the \module{pickle} module, you need to derive a subclass from
\class{Unpickler}, overriding the \method{load_global()}
method. \method{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
\member{__class__} attribute of an empty class, as a way of magically
creating an instance without calling its class's \method{__init__()}.
Your job (should you choose to accept it), would be to have
\method{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 \module{cPickle}, but not by much.
To control what gets unpickled, you can set the unpickler's
\member{find_global} attribute to a function or \code{None}. If it is
\code{None} then any attempts to unpickle instances will raise an
\exception{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.
\subsection{Example \label{pickle-example}}
For the simplest code, use the \function{dump()} and \function{load()}
functions. Note that a self-referencing list is pickled and restored
correctly.
\begin{verbatim}
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()
\end{verbatim}
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.
\begin{verbatim}
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()
\end{verbatim}
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 \method{readline()}
method is called. If a \class{TextReader} instance is pickled, all
attributes \emph{except} the file object member are saved. When the
instance is unpickled, the file is reopened, and reading resumes from
the last location. The \method{__setstate__()} and
\method{__getstate__()} methods are used to implement this behavior.
\begin{verbatim}
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
\end{verbatim}
A sample usage might be something like this:
\begin{verbatim}
>>> import TextReader
>>> obj = TextReader.TextReader("TextReader.py")
>>> obj.readline()
'1: #!/usr/local/bin/python'
>>> # (more invocations of obj.readline() here)
... obj.readline()
'7: class TextReader:'
>>> import pickle
>>> pickle.dump(obj,open('save.p','w'))
\end{verbatim}
If you want to see that \refmodule{pickle} works across Python
processes, start another Python session, before continuing. What
follows can happen from either the same process or a new process.
\begin{verbatim}
>>> import pickle
>>> reader = pickle.load(open('save.p'))
>>> reader.readline()
'8: "Print and number lines in a text file."'
\end{verbatim}
\begin{seealso}
\seemodule[copyreg]{copy_reg}{Pickle interface constructor
registration for extension types.}
\seemodule{shelve}{Indexed databases of objects; uses \module{pickle}.}
\seemodule{copy}{Shallow and deep object copying.}
\seemodule{marshal}{High-performance serialization of built-in types.}
\end{seealso}
\section{\module{cPickle} --- A faster \module{pickle}}
\declaremodule{builtin}{cPickle}
\modulesynopsis{Faster version of \refmodule{pickle}, but not subclassable.}
\moduleauthor{Jim Fulton}{[email protected]}
\sectionauthor{Fred L. Drake, Jr.}{[email protected]}
The \module{cPickle} module supports serialization and
de-serialization of Python objects, providing an interface and
functionality nearly identical to the
\refmodule{pickle}\refstmodindex{pickle} module. There are several
differences, the most important being performance and subclassability.
First, \module{cPickle} can be up to 1000 times faster than
\module{pickle} because the former is implemented in C. Second, in
the \module{cPickle} module the callables \function{Pickler()} and
\function{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
\module{cPickle} module.
The pickle data stream produced by \module{pickle} and
\module{cPickle} are identical, so it is possible to use
\module{pickle} and \module{cPickle} interchangeably with existing
pickles.\footnote{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.}
There are additional minor differences in API between \module{cPickle}
and \module{pickle}, however for most applications, they are
interchangeable. More documentation is provided in the
\module{pickle} module documentation, which
includes a list of the documented differences.