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dill
====
serialize all of python
About Dill
----------
``dill`` extends python's ``pickle`` module for serializing and de-serializing
python objects to the majority of the built-in python types. Serialization
is the process of converting an object to a byte stream, and the inverse
of which is converting a byte stream back to on python object hierarchy.
``dill`` provides the user the same interface as the ``pickle`` module, and
also includes some additional features. In addition to pickling python
objects, ``dill`` provides the ability to save the state of an interpreter
session in a single command. Hence, it would be feasable to save a
interpreter session, close the interpreter, ship the pickled file to
another computer, open a new interpreter, unpickle the session and
thus continue from the 'saved' state of the original interpreter
session.
``dill`` can be used to store python objects to a file, but the primary
usage is to send python objects across the network as a byte stream.
``dill`` is quite flexible, and allows arbitrary user defined classes
and functions to be serialized. Thus ``dill`` is not intended to be
secure against erroneously or maliciously constructed data. It is
left to the user to decide whether the data they unpickle is from
a trustworthy source.
``dill`` is part of ``pathos``, a python framework for heterogeneous computing.
``dill`` is in active development, so any user feedback, bug reports, comments,
or suggestions are highly appreciated. A list of known issues is maintained
at http://trac.mystic.cacr.caltech.edu/project/pathos/query.html, with a public
ticket list at https://github.com/uqfoundation/dill/issues.
Major Features
--------------
``dill`` can pickle the following standard types:
* none, type, bool, int, long, float, complex, str, unicode,
* tuple, list, dict, file, buffer, builtin,
* both old and new style classes,
* instances of old and new style classes,
* set, frozenset, array, functions, exceptions
``dill`` can also pickle more 'exotic' standard types:
* functions with yields, nested functions, lambdas
* cell, method, unboundmethod, module, code, methodwrapper,
* dictproxy, methoddescriptor, getsetdescriptor, memberdescriptor,
* wrapperdescriptor, xrange, slice,
* notimplemented, ellipsis, quit
``dill`` cannot yet pickle these standard types:
* frame, generator, traceback
``dill`` also provides the capability to:
* save and load python interpreter sessions
* save and extract the source code from functions and classes
* interactively diagnose pickling errors
Current Release
---------------
The latest released version of ``dill`` is available from:
https://pypi.org/project/dill
``dill`` is distributed under a 3-clause BSD license.
Development Version
-------------------
You can get the latest development version with all the shiny new features at:
https://github.com/uqfoundation
If you have a new contribution, please submit a pull request.
More Information
----------------
Probably the best way to get started is to look at the documentation at
http://dill.rtfd.io. Also see ``dill.tests`` for a set of scripts that
demonstrate how ``dill`` can serialize different python objects. You can
run the test suite with ``python -m dill.tests``. The contents of any
pickle file can be examined with ``undill``. As ``dill`` conforms to
the ``pickle`` interface, the examples and documentation found at
http://docs.python.org/library/pickle.html also apply to ``dill``
if one will ``import dill as pickle``. The source code is also generally
well documented, so further questions may be resolved by inspecting the
code itself. Please feel free to submit a ticket on github, or ask a
question on stackoverflow (**@Mike McKerns**).
If you would like to share how you use ``dill`` in your work, please send
an email (to **mmckerns at uqfoundation dot org**).
Citation
--------
If you use ``dill`` to do research that leads to publication, we ask that you
acknowledge use of ``dill`` by citing the following in your publication::
M.M. McKerns, L. Strand, T. Sullivan, A. Fang, M.A.G. Aivazis,
"Building a framework for predictive science", Proceedings of
the 10th Python in Science Conference, 2011;
http://arxiv.org/pdf/1202.1056
Michael McKerns and Michael Aivazis,
"pathos: a framework for heterogeneous computing", 2010- ;
http://trac.mystic.cacr.caltech.edu/project/pathos
Please see http://trac.mystic.cacr.caltech.edu/project/pathos or
http://arxiv.org/pdf/1202.1056 for further information.
|
