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dill 0.2.3-1~bpo70+1
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Metadata-Version: 1.1
Name: dill
Version: 0.2.3
Summary: a utility for serialization of python objects
Home-page: http://www.cacr.caltech.edu/~mmckerns
Author: Mike McKerns
Author-email: mmckerns@caltech.edu
License: BSD
Description: -----------------------------
        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 funcitons 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, 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
        ===============
        
        This version is dill-0.2.3.
        
        The latest stable version of dill is available from::
        
            http://trac.mystic.cacr.caltech.edu/project/pathos
        
        or::
        
            https://github.com/uqfoundation/dill/releases
        
        or also::
        
            https://pypi.python.org/pypi/dill
        
        Dill is distributed under a 3-clause BSD license.
        
            >>> import dill
            >>> print (dill.license())
        
        
        Development Version 
        ===================
        
        You can get the latest development version with all the shiny new features at::
        
            https://github.com/uqfoundation
        
        Feel free to fork the github mirror of our svn trunk.  If you have a new
        contribution, please submit a pull request.
        
        
        Installation
        ============
        
        Dill is packaged to install from source, so you must
        download the tarball, unzip, and run the installer::
        
            [download]
            $ tar -xvzf dill-0.2.3.tgz
            $ cd dill-0.2.3
            $ python setup py build
            $ python setup py install
        
        You will be warned of any missing dependencies and/or settings
        after you run the "build" step above. 
        
        Alternately, dill can be installed with pip or easy_install::
        
            $ pip install dill
        
        
        Requirements
        ============
        
        Dill requires::
        
            - python2, version >= 2.5  *or*  python3, version >= 3.1
        
        Optional requirements::
        
            - setuptools, version >= 0.6
            - objgraph, version >= 1.7.2
        
        
        More Information
        ================
        
        Probably the best way to get started is to look at the tests that are
        provided within dill. See `dill.tests` for a set of scripts that demonstrate
        dill's ability to serialize different python objects.  Since dill conforms
        to the 'pickle' interface, the examples and documentation 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 also feel free to submit a ticket on github, or ask a
        question on stackoverflow (@Mike McKerns).
        
        Dill is an active research tool. There are a growing number of publications
        and presentations that discuss real-world examples and new features of dill
        in greater detail than presented in the user's guide.  If you would like to
        share how you use dill in your work, please post a link or send an email
        (to mmckerns at caltech dot edu).
        
        
        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.
        
        
Platform: any
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Topic :: Physics Programming