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efficient storage of large features data

Project description

Documentation Status https://travis-ci.org/bootphon/h5features.svg?branch=master

h5features

The h5features python package provides easy to use and efficient storage of large features data on the HDF5 binary file format.

Installation

  • dependancies

    The package depends on numpy, scipy and h5py. They can be automatically installed by the setup script but it takes a long time (full compilation). You may want to install the dependancies through your system package manager.

    On Debian/Ubuntu:

    sudo apt-get install python3-numpy python3-scipy python3-h5py
    

    Using Python anaconda:

    conda install numpy scipy h5py
    
  • h5features

    Install it from the sources with:

    python setup.py build && python setup.py install
    

    Or you can install it with pip:

    pip install h5features
    

Documentation

  • See the complete documentation online

  • Or build it with:

    pip install Sphinx
    cd docs && make html
    

    The home page of the compiled documentation is docs/_build/html/index.html.

Test

The package comes with a unit-tests suit. To run it, first install pytest on your Python environment:

pip install pytest

Then run the tests with:

pytest -v ./test

Project details


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Filename, size & hash SHA256 hash help File type Python version Upload date
h5features-1.2.2.tar.gz (43.3 kB) Copy SHA256 hash SHA256 Source None Mar 29, 2018

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