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            "Intended Audience :: Education",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Cython",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Topic :: Documentation :: Sphinx",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Scientific/Engineering :: Information Analysis"
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        "description": ".. -*- coding: utf-8; -*-\n\nLoaders and savers for different implentations of `word embedding <https://en.wikipedia.org/wiki/Word_embedding>`_. The motivation of this project is that it is cumbersome to write loaders for different pretrained word embedding files. This project provides a simple interface for loading pretrained word embedding files in different formats.\n\n.. code:: python\n\n   from word_embedding_loader import WordEmbedding\n\n   # it will automatically determine format from content\n   wv = WordEmbedding.load('path/to/embedding.bin')\n\n   # This project provides minimum interface for word embedding\n   print wv.vectors[wv.vocab['is']]\n\n   # Modify and save word embedding file with arbitrary format\n   wv.save('path/to/save.txt', 'word2vec', binary=False)\n\n\nThis project currently supports following formats:\n\n* `GloVe <https://nlp.stanford.edu/projects/glove/>`_, Global Vectors for Word Representation, by Jeffrey Pennington, Richard Socher, Christopher D. Manning from Stanford NLP group.\n* `word2vec <https://code.google.com/archive/p/word2vec/>`_, by Mikolov.\n    - text (create with ``-binary 0`` option (the default))\n    - binary (create with ``-binary 1`` option)\n* `gensim <https://radimrehurek.com/gensim/>`_ 's ``models.word2vec`` module (coming)\n* original HDFS format: a performance centric option for loading and saving word embedding (coming)\n\n\nSometimes, you want combine an external program with word embedding file of your own choice. This project also provides a simple executable to convert a word embedding format to another.\n\n.. code:: bash\n\n   # it will automatically determine the format from the content\n   word-embedding-loader convert -t glove test/word_embedding_loader/word2vec.bin test.bin\n\n   # Get help for command/subcommand\n   word-embedding-loader --help\n   word-embedding-loader convert --help\n\nIssues with encoding\n--------------------\n\nThis project does decode vocab. It is up to users to determine and decode bytes.\n\n.. code:: python\n\n    decoded_vocab = {k.decode('latin-1'): v for k, v in wv.vocab.iteritems()}\n\n\n.. notes::\n\n   Encoding of pretrained word2vec is latin-1. Encoding of pretrained\n   glove is utf-8\n\n\nDevelopment\n============\n\nThis project us Cython to build some modules, so you need Cython for development.\n\n```bash\npip install -r requirements.txt\n```\n\nIf environment variable ``DEVELOP_WE`` is set, it will try to rebuild ``.pyx`` modules.\n\n```bash\nDEVELOP_WE=1 python setup.py test\n```",
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