Metadata-Version: 2.1
Name: msgpack-numpy
Version: 0.4.6.1
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.
        
        [![Latest Version](https://img.shields.io/pypi/v/msgpack-numpy.svg)](https://pypi.python.org/pypi/msgpack-numpy)
        [![Build Status](https://travis-ci.org/lebedov/msgpack-numpy.svg?branch=master)](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.
        
        Note that numpy arrays deserialized by msgpack-numpy are read-only and must be copied 
        if they are to be modified.
        
        Development
        -----------
        The latest source code can be obtained from [GitHub](https://github.com/lebedov/msgpack-numpy/).
        
        Authors
        -------
        See the included [AUTHORS.md](https://github.com/lebedov/msgpack-numpy/blob/master/AUTHORS.md) file for 
        more information.
        
        License
        -------
        This software is licensed under the [BSD License](http://www.opensource.org/licenses/bsd-license).
        See the included [LICENSE.md](https://github.com/lebedov/msgpack-numpy/blob/master/LICENSE.md) 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: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Description-Content-Type: text/markdown
