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        "author": "Eddie Antonio Santos",
        "author_email": "easantos@ualberta.ca",
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            "Development Status :: 3 - Alpha",
            "License :: OSI Approved :: Apache Software License",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7"
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        "description": "FST Lookup\n==========\n\n[![Build Status](https://travis-ci.org/eddieantonio/fst-lookup.svg?branch=master)](https://travis-ci.org/eddieantonio/fst-lookup)\n[![codecov](https://codecov.io/gh/eddieantonio/fst-lookup/branch/master/graph/badge.svg)](https://codecov.io/gh/eddieantonio/fst-lookup)\n[![PyPI version](https://img.shields.io/pypi/v/fst-lookup.svg)](https://pypi.org/project/fst-lookup/)\n[![calver YYYY.MM.DD](https://img.shields.io/badge/calver-YYYY.MM.DD-22bfda.svg)](http://calver.org/)\n\nImplements lookup for FOMA format finite state transducers.\n\nSupports Python 3.5 and up.\n\nInstall\n-------\n\n    pip install fst-lookup\n\nUsage\n-----\n\nImport the library, and load an FST from a file:\n\n> Hint: Test this module by [downloading the `eat` FST](https://github.com/eddieantonio/fst-lookup/raw/master/tests/data/eat.fomabin)!\n\n```python\n>>> from fst_lookup import FST\n>>> fst = FST.from_file('eat.fomabin')\n```\n\n### Assumed format of the FSTs\n\n`fst_lookup` assumes that the **lower** label corresponds to the surface\nform, while the **upper** label corresponds to the lemma, and linguistic\ntags and features: e.g., your `LEXC` will look something like\nthis---note what is on each side of the colon (`:`):\n\n```lexc\nMultichar_Symbols +N +Sg +Pl\nLexicon Root\n    cow+N+Sg:cow #;\n    cow+N+Pl:cows #;\n    goose+N+Sg:goose #;\n    goose+N+Pl:geese #;\n    sheep+N+Sg:sheep #;\n    sheep+N+Pl:sheep #;\n```\n\nIf your FST has labels on the opposite sides--e.g., the **upper** label\ncorresponds to the surface form and the **upper** label corresponds to\nthe lemma and linguistic tags---then instantiate the FST by providing\nthe `labels=\"invert\"` keyword argument:\n\n```python\nfst = FST.from_file('eat-inverted.fomabin', labels=\"invert\")\n```\n\n> **Hint**: FSTs originating from the HFST suite are often inverted, so\n> try to loading the FST inverted first if `.generate()` or `.analyze()`\n> aren't working correctly!\n\n\n### Analyze a word form\n\nTo _analyze_ a form (take a word form, and get its linguistic analyzes)\ncall the `analyze()` function:\n\n```python\ndef analyze(self, surface_form: str) -> Iterator[Analysis]\n```\n\nThis will yield all possible linguistic analyses produced by the FST.\n\nAn analysis is a tuple of strings. The strings are either linguistic\ntags, or the _lemma_ (base form of the word).\n\n`FST.analyze()` is a generator, so you must call `list()` to get a list.\n\n```python\n>>> list(sorted(fst.analyze('eats')))\n[('eat', '+N', '+Mass'),\n ('eat', '+V', '+3P', '+Sg')]\n```\n\n\n### Generate a word form\n\nTo _generate_ a form (take a linguistic analysis, and get its concrete\nword forms), call the `generate()` function:\n\n```python\ndef generate(self, analysis: str) -> Iterator[str]\n```\n\n`FST.generate()` is a Python generator, so you must call `list()` to get\na list.\n\n```python\n>>> list(fst.generate('eat+V+Past')))\n['ate']\n```\n\n\nLicense\n-------\n\nCopyright \u00a9 2019 Eddie Antonio Santos. Released under the terms of the\nApache license. See `LICENSE` for more info.\n\n\n",
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