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    "info": {
        "author": "Lokendra Singh, Arghya Bhatttacharya, Sushain K. Cherivirala, Andi Qu",
        "author_email": "sushain@skc.name",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3 :: Only",
            "Topic :: Text Processing :: Linguistic"
        ],
        "description": "# Apertium + Python\n\n[![Travis Build Status](https://travis-ci.com/apertium/apertium-python.svg?branch=master)](https://travis-ci.com/apertium/apertium-python)\n[![Appveyor Build status](https://ci.appveyor.com/api/projects/status/sesdinoy4cw2p1tk/branch/master?svg=true)](https://ci.appveyor.com/project/apertium/apertium-python/branch/master)\n[![ReadTheDocs Docs Status](https://readthedocs.org/projects/apertium-python/badge)](https://readthedocs.org/projects/apertium-python)\n[![Coverage Status](https://coveralls.io/repos/github/apertium/apertium-python/badge.svg?branch=master)](https://coveralls.io/github/apertium/apertium-python?branch=master)\n[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/apertium.svg)]((https://pypi.org/project/apertium/))\n\n## Introduction\n\n- The codebase is in development for the GSoC '19 project called **Apertium API in Python**\n- The Apertium core modules are written in C++.\n- This project makes the Apertium modules available in Python, which because of its simplicity is more appealing to users.\n\n## About the Exisiting Code Base\n\n- The existing codebase has `Subprocess` and [SWIG](http://www.swig.org/) wrapper implementations of the higher level functions of Apertium and CG modules.\n\n## Installation\n\n- Installation on Ubuntu and Windows is natively supported:\n\n    ```\n    pip install apertium\n    ```\n\n- For developers, `pipenv` can be used to install the development dependencies and enter a shell with them:\n\n    ```\n    pip install pipenv\n    pipenv install --dev\n    pipenv shell\n    ```\n\n- Apertium packages can be installed from Python interpreter as well.\n  - Install `apertium-all-dev` by calling `apertium.installer.install_apertium()`\n  - Install language packages with `apertium.installer.install_module(language_name)`. For example `apertium-eng` can be installed by executing `apertium.installer.install_module('eng')`\n\n## Usage\n\n- For multiple invocations `Method 1` is more performant, as the dictionary needs to be loaded only once.\n\n### Analysis\n\nPerforming Morphological Analysis\n\nMethod 1: Create an `Analyzer` object and call its `analyze` method.\n```python\nIn [1]: import apertium\nIn [2]: a = apertium.Analyzer('en')\nIn [3]: a.analyze('cats')\nOut[3]: [cats/cat<n><pl>, ./.<sent>]\n```\n\nMethod 2: Calling `analyze()` directly.\n```python\nIn [1]: import apertium\nIn [2]: apertium.analyze('en', 'cats')\nOut[2]: cats/cat<n><pl>\n```\n\n### Generation\n\nPerforming Morphological Generation\n\nMethod 1:  Create a `Generator` object and call its `generate` method.\n```python\nIn [1]: import apertium\nIn [2]: g = apertium.Generator('en')\nIn [3]: g.generate('^cat<n><pl>$')\nOut[3]: 'cats'\n```\n\nMethod 2: Calling `generate()` directly.\n```python\nIn [1]: import apertium\nIn [2]: apertium.generate('en', '^cat<n><pl>$')\nOut[2]: 'cats'\n```\n\n### Tagger\n\nMethod 1:  Create a `Tagger` object and call its `tag` method.\n```python\nIn [1]: import apertium\nIn [2]: tagger = apertium.Tagger('eng')\nIn [3]: tagger.tag('cats')\nOut[3]: [cats/cat<n><pl>]\n```\n\nMethod 2: Calling `tag()` directly.\n```python\nIn [1]: import apertium\nIn [2]: apertium.tag('en', 'cats')\nOut[2]: [cats/cat<n><pl>]\n```\n\n### Translation\n\nMethod 1:  Create a `Translator` object and call its `translate` method.\n```python\nIn [1]: import apertium\nIn [2]: t = apertium.Translator('eng', 'spa')\nIn [3]: t.translate('cats')\nOut[3]: 'Gatos'\n```\n\nMethod 2: Calling `translate()` directly.\n```python\nIn [1]: import apertium\nIn [2]: apertium.translate('en', 'spa', 'cats')\nOut[2]: 'Gatos'\n```\n\n### Installing more modes from other language data\n\nOne can also install modes by providing the path to the `lang-data`:\n\n```python\nIn [1]: import apertium\nIn [2]: apertium.append_pair_path('..')\n```",
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        "keywords": "apertium machine translation linguistics",
        "license": "GNU General Public License v3.0",
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