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Cela permet de ne pas avoir de problèmes de compatibilité car python est dans le git.
274 lines
9.7 KiB
Plaintext
274 lines
9.7 KiB
Plaintext
Metadata-Version: 2.1
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Name: dill
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Version: 0.3.7
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Summary: serialize all of Python
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Home-page: https://github.com/uqfoundation/dill
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Download-URL: https://pypi.org/project/dill/#files
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Author: Mike McKerns
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Author-email: mmckerns@uqfoundation.org
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Maintainer: Mike McKerns
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Maintainer-email: mmckerns@uqfoundation.org
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License: BSD-3-Clause
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Project-URL: Documentation, http://dill.rtfd.io
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Project-URL: Source Code, https://github.com/uqfoundation/dill
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Project-URL: Bug Tracker, https://github.com/uqfoundation/dill/issues
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Platform: Linux
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Platform: Windows
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Platform: Mac
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Classifier: Development Status :: 5 - Production/Stable
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Classifier: Intended Audience :: Developers
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Classifier: Intended Audience :: Science/Research
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Classifier: License :: OSI Approved :: BSD License
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3.7
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Classifier: Programming Language :: Python :: 3.8
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Classifier: Programming Language :: Python :: 3.9
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Classifier: Programming Language :: Python :: 3.10
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Classifier: Programming Language :: Python :: 3.11
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Classifier: Programming Language :: Python :: Implementation :: CPython
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Classifier: Programming Language :: Python :: Implementation :: PyPy
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Classifier: Topic :: Scientific/Engineering
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Classifier: Topic :: Software Development
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Requires-Python: >=3.7
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License-File: LICENSE
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Provides-Extra: graph
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Requires-Dist: objgraph (>=1.7.2) ; extra == 'graph'
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Provides-Extra: readline
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-----------------------------
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dill: serialize all of Python
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-----------------------------
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About Dill
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==========
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``dill`` extends Python's ``pickle`` module for serializing and de-serializing
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Python objects to the majority of the built-in Python types. Serialization
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is the process of converting an object to a byte stream, and the inverse
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of which is converting a byte stream back to a Python object hierarchy.
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``dill`` provides the user the same interface as the ``pickle`` module, and
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also includes some additional features. In addition to pickling Python
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objects, ``dill`` provides the ability to save the state of an interpreter
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session in a single command. Hence, it would be feasible to save an
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interpreter session, close the interpreter, ship the pickled file to
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another computer, open a new interpreter, unpickle the session and
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thus continue from the 'saved' state of the original interpreter
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session.
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``dill`` can be used to store Python objects to a file, but the primary
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usage is to send Python objects across the network as a byte stream.
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``dill`` is quite flexible, and allows arbitrary user defined classes
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and functions to be serialized. Thus ``dill`` is not intended to be
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secure against erroneously or maliciously constructed data. It is
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left to the user to decide whether the data they unpickle is from
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a trustworthy source.
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``dill`` is part of ``pathos``, a Python framework for heterogeneous computing.
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``dill`` is in active development, so any user feedback, bug reports, comments,
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or suggestions are highly appreciated. A list of issues is located at
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https://github.com/uqfoundation/dill/issues, with a legacy list maintained at
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https://uqfoundation.github.io/project/pathos/query.
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Major Features
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==============
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``dill`` can pickle the following standard types:
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- none, type, bool, int, float, complex, bytes, str,
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- tuple, list, dict, file, buffer, builtin,
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- Python classes, namedtuples, dataclasses, metaclasses,
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- instances of classes,
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- set, frozenset, array, functions, exceptions
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``dill`` can also pickle more 'exotic' standard types:
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- functions with yields, nested functions, lambdas,
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- cell, method, unboundmethod, module, code, methodwrapper,
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- methoddescriptor, getsetdescriptor, memberdescriptor, wrapperdescriptor,
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- dictproxy, slice, notimplemented, ellipsis, quit
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``dill`` cannot yet pickle these standard types:
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- frame, generator, traceback
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``dill`` also provides the capability to:
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- save and load Python interpreter sessions
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- save and extract the source code from functions and classes
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- interactively diagnose pickling errors
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Current Release
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===============
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The latest released version of ``dill`` is available from:
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https://pypi.org/project/dill
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``dill`` is distributed under a 3-clause BSD license.
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Development Version
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===================
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You can get the latest development version with all the shiny new features at:
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https://github.com/uqfoundation
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If you have a new contribution, please submit a pull request.
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Installation
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============
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``dill`` can be installed with ``pip``::
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$ pip install dill
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To optionally include the ``objgraph`` diagnostic tool in the install::
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$ pip install dill[graph]
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For windows users, to optionally install session history tools::
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$ pip install dill[readline]
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Requirements
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============
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``dill`` requires:
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- ``python`` (or ``pypy``), **>=3.7**
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- ``setuptools``, **>=42**
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Optional requirements:
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- ``objgraph``, **>=1.7.2**
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- ``pyreadline``, **>=1.7.1** (on windows)
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Basic Usage
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===========
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``dill`` is a drop-in replacement for ``pickle``. Existing code can be
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updated to allow complete pickling using::
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>>> import dill as pickle
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or::
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>>> from dill import dumps, loads
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``dumps`` converts the object to a unique byte string, and ``loads`` performs
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the inverse operation::
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>>> squared = lambda x: x**2
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>>> loads(dumps(squared))(3)
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9
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There are a number of options to control serialization which are provided
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as keyword arguments to several ``dill`` functions:
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* with *protocol*, the pickle protocol level can be set. This uses the
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same value as the ``pickle`` module, *DEFAULT_PROTOCOL*.
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* with *byref=True*, ``dill`` to behave a lot more like pickle with
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certain objects (like modules) pickled by reference as opposed to
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attempting to pickle the object itself.
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* with *recurse=True*, objects referred to in the global dictionary are
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recursively traced and pickled, instead of the default behavior of
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attempting to store the entire global dictionary.
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* with *fmode*, the contents of the file can be pickled along with the file
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handle, which is useful if the object is being sent over the wire to a
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remote system which does not have the original file on disk. Options are
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*HANDLE_FMODE* for just the handle, *CONTENTS_FMODE* for the file content
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and *FILE_FMODE* for content and handle.
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* with *ignore=False*, objects reconstructed with types defined in the
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top-level script environment use the existing type in the environment
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rather than a possibly different reconstructed type.
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The default serialization can also be set globally in *dill.settings*.
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Thus, we can modify how ``dill`` handles references to the global dictionary
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locally or globally::
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>>> import dill.settings
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>>> dumps(absolute) == dumps(absolute, recurse=True)
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False
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>>> dill.settings['recurse'] = True
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>>> dumps(absolute) == dumps(absolute, recurse=True)
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True
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``dill`` also includes source code inspection, as an alternate to pickling::
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>>> import dill.source
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>>> print(dill.source.getsource(squared))
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squared = lambda x:x**2
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To aid in debugging pickling issues, use *dill.detect* which provides
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tools like pickle tracing::
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>>> import dill.detect
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>>> with dill.detect.trace():
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>>> dumps(squared)
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┬ F1: <function <lambda> at 0x7fe074f8c280>
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├┬ F2: <function _create_function at 0x7fe074c49c10>
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│└ # F2 [34 B]
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├┬ Co: <code object <lambda> at 0x7fe07501eb30, file "<stdin>", line 1>
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│├┬ F2: <function _create_code at 0x7fe074c49ca0>
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││└ # F2 [19 B]
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│└ # Co [87 B]
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├┬ D1: <dict object at 0x7fe0750d4680>
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│└ # D1 [22 B]
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├┬ D2: <dict object at 0x7fe074c5a1c0>
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│└ # D2 [2 B]
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├┬ D2: <dict object at 0x7fe074f903c0>
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│├┬ D2: <dict object at 0x7fe074f8ebc0>
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││└ # D2 [2 B]
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│└ # D2 [23 B]
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└ # F1 [180 B]
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With trace, we see how ``dill`` stored the lambda (``F1``) by first storing
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``_create_function``, the underlying code object (``Co``) and ``_create_code``
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(which is used to handle code objects), then we handle the reference to
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the global dict (``D2``) plus other dictionaries (``D1`` and ``D2``) that
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save the lambda object's state. A ``#`` marks when the object is actually stored.
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More Information
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================
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Probably the best way to get started is to look at the documentation at
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http://dill.rtfd.io. Also see ``dill.tests`` for a set of scripts that
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demonstrate how ``dill`` can serialize different Python objects. You can
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run the test suite with ``python -m dill.tests``. The contents of any
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pickle file can be examined with ``undill``. As ``dill`` conforms to
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the ``pickle`` interface, the examples and documentation found at
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http://docs.python.org/library/pickle.html also apply to ``dill``
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if one will ``import dill as pickle``. The source code is also generally
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well documented, so further questions may be resolved by inspecting the
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code itself. Please feel free to submit a ticket on github, or ask a
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question on stackoverflow (**@Mike McKerns**).
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If you would like to share how you use ``dill`` in your work, please send
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an email (to **mmckerns at uqfoundation dot org**).
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Citation
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========
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If you use ``dill`` to do research that leads to publication, we ask that you
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acknowledge use of ``dill`` by citing the following in your publication::
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M.M. McKerns, L. Strand, T. Sullivan, A. Fang, M.A.G. Aivazis,
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"Building a framework for predictive science", Proceedings of
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the 10th Python in Science Conference, 2011;
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http://arxiv.org/pdf/1202.1056
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Michael McKerns and Michael Aivazis,
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"pathos: a framework for heterogeneous computing", 2010- ;
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https://uqfoundation.github.io/project/pathos
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Please see https://uqfoundation.github.io/project/pathos or
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http://arxiv.org/pdf/1202.1056 for further information.
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