Metadata-Version: 1.1
Name: msgpack-numpy
Version: 0.4.5
Summary: Numpy data serialization using msgpack
Home-page: https://github.com/lebedov/msgpack-numpy
Author: Lev E. Givon
Author-email: lev@columbia.edu
License: BSD
Description: Package Description
        -------------------
        This package provides encoding and decoding routines that enable the
        serialization and deserialization of numerical and array data types provided by 
        `numpy <http://www.numpy.org/>`_ using the highly efficient
        `msgpack <http://msgpack.org/>`_ format. Serialization of Python's
        native complex data types is also supported.
        
        .. image:: https://img.shields.io/pypi/v/msgpack-numpy.svg
            :target: https://pypi.python.org/pypi/msgpack-numpy
            :alt: Latest Version
        .. image:: https://travis-ci.org/lebedov/msgpack-numpy.svg?branch=master
            :target: https://travis-ci.org/lebedov/msgpack-numpy
        
        Installation
        ------------
        msgpack-numpy requires msgpack-python and numpy. If you 
        have `pip <http://www.pip-installer.org/>`_ installed on your
        system, run ::
        
            pip install msgpack-numpy
        
        to install the package and all dependencies. You can also download 
        the source tarball, unpack it, and run ::
        
            python setup.py install
        
        from within the source directory.
        
        Usage
        -----
        The easiest way to use msgpack-numpy is to call its monkey patching
        function after importing the Python msgpack package: ::
        
            import msgpack
            import msgpack_numpy as m
            m.patch()
        
        This will automatically force all msgpack serialization and deserialization
        routines (and other packages that use them) to become numpy-aware. 
        Of course, one can also manually pass the encoder and 
        decoder provided by msgpack-numpy to the msgpack routines: ::
        
            import msgpack
            import msgpack_numpy as m
            import numpy as np
        
            x = np.random.rand(5)
            x_enc = msgpack.packb(x, default=m.encode)
            x_rec = msgpack.unpackb(x_enc, object_hook=m.decode)
        
        msgpack-numpy will try to use the binary (fast) extension in msgpack by default.  
        If msgpack was not compiled with Cython (or if the ``MSGPACK_PUREPYTHON`` 
        variable is set), it will fall back to using the slower pure Python msgpack 
        implementation.
        
        Notes
        -----
        The primary design goal of msgpack-numpy is ensuring preservation of numerical
        data types during msgpack serialization and deserialization. Inclusion of type
        information in the serialized data necessarily incurs some storage overhead; if
        preservation of type information is not needed, one may be able to avoid some
        of this overhead by writing a custom encoder/decoder pair that produces more
        efficient serializations for those specific use cases.
        
        Development
        -----------
        The latest source code can be obtained from
        `GitHub <https://github.com/lebedov/msgpack-numpy/>`_.
        
        Authors
        -------
        See the included `AUTHORS.rst 
        <https://github.com/lebedov/msgpack-numpy/blob/master/AUTHORS.rst>`_ file for 
        more information.
        
        License
        -------
        This software is licensed under the `BSD License 
        <http://www.opensource.org/licenses/bsd-license>`_.
        See the included `LICENSE.rst 
        <https://github.com/lebedov/msgpack-numpy/blob/master/LICENSE.rst>`_ file for 
        more information.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
