{
    "info": {
        "author": "Matt Yan",
        "author_email": "syan4@ualberta.ca",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Software Development :: Build Tools"
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        "description": "# hfstol\n![travis-badge](https://travis-ci.org/Madoshakalaka/hfstol.svg?branch=master)\n![code-cov](https://codecov.io/gh/Madoshakalaka/hfstol/branch/master/graphs/badge.svg)\n[![PyPI pyversions](https://img.shields.io/pypi/pyversions/hfstol.svg)](https://pypi.python.org/pypi/hfstol/)\n\nhfst-optimized-lookup in python\n\n\n`pip install hfstol`\n\nAll below examples are based on two `.hfstol` files\n\nrespectively: [crk-descriptive-analyzer.hfstol crk-normative-generator.hfstol](https://github.com/UAlbertaALTLab/plains-cree-fsts/releases)\n\n\n# Use\n\nexample with `crk-descriptive-analyzer.hfstol` :\n\n```python\nfrom hfstol import HFSTOL\n\nhfst = HFSTOL.from_file('crk-descriptive-analyzer.hfstol')\n\nhfst.feed('niska')\n# returns: \n# (('niska', '+N', '+A', '+Sg'), ('niska', '+N', '+A', '+Obv'))\n\nhfst.feed_in_bulk(['niska', 'kinip\u00e2n\u00e2naw'])\n# returns: \n# {'niska': {('niska', '+N', '+A', '+Obv'), ('niska', '+N', '+A', '+Sg')}, 'kinip\u00e2n\u00e2naw': {('nip\u00e2w', '+V', '+AI', '+Ind', '+Prs', '+12Pl')}}\n\nhfst.feed_in_bulk_fast(['niska', 'kinip\u00e2n\u00e2naw'], multi_process=4)\n# returns:\n# {'niska': {'niska+N+A+Obv', 'niska+N+A+Sg'}, 'kinip\u00e2n\u00e2naw': {'nip\u00e2w+V+AI+Ind+Prs+12Pl'}}\n\n```\n\nexample with `crk-normative-generator.hfstol` :\n\n```python\nfrom hfstol import HFSTOL\n\nhfst = HFSTOL.from_file('crk-normative-generator.hfstol')\n\nhfst.feed('niska+N+A+Pl')\n# returns: \n# (('niskak',),)\n\nhfst.feed_in_bulk([\"niska+N+A+Pl\", 'nip\u00e2w+V+AI+Ind+Prs+12Pl'])\n# returns: \n# {'niska+N+A+Pl': {('niskak',)}, 'nip\u00e2w+V+AI+Ind+Prs+12Pl': {('kinip\u00e2n\u00e2naw',), ('kinip\u00e2naw',)}}\n\nhfst.feed_in_bulk_fast([\"niska+N+A+Pl\", 'nip\u00e2w+V+AI+Ind+Prs+12Pl'], multi_process=4)\n# returns:\n# {'niska+N+A+Pl': {'niskak'}, 'nip\u00e2w+V+AI+Ind+Prs+12Pl': {'kinip\u00e2n\u00e2naw', 'kinip\u00e2naw'}}\n```\n\nto see a comprehensive API behaviour including edge cases, see [this test file](https://github.com/Madoshakalaka/hfstol/blob/master/tests/test_apply.py) (what if I `feed('absolute garbage')`)\n\n# API signatures\n\n\n```python\n\n# HFSTOL.from_file\n\n@classmethod\ndef from_file(cls, filename: Union[str, pathlib.Path]): \n    \"\"\"\n    :param filename: the `.hfstol` file\n    :return: an `HFSTOL` instance, which you can use to convert surface forms to deep forms\n    \"\"\"\n    pass\n\n\n# HFSTOL.feed\n\ndef feed(self, surface_form: str, concat: bool = True) -> Tuple[Tuple[str, ...], ...]:\n    \"\"\"\n    feed surface form to hfst\n\n    :param surface_form: the surface form\n    :param concat: whether to concatenate single characters\n\n        example output for `surface_form` = 'niskak', with `crk-descriptive-analyzer.hfstol`\n        - True: (('niska', '+N', '+A', '+Pl'), ('n\u00eesk\u00e2w', '+V', '+II', '+II', '+Cnj', '+Prs', '+3Sg'))\n        - False: (('n', 'i', 's', 'k', 'a', '+N', '+A', '+Pl'), ('n', '\u00ee', 's', 'k', '\u00e2', 'w', '+V', '+II', '+II', '+Cnj', '+Prs', '+3Sg'))\n\n        example output for `surface_form` = 'niska+N+A+Pl' with `crk-normative-generator.hfstol`\n        - True: (('niskak',),)\n        - False: (('n', 'i', 's', 'k', 'a', 'k'),)\n\n        example output for `surface_form` = 'niska+N+A+Pl' with `crk-normative-generator.hfstol` (an inflection that has two spellings)\n        - True: (('kinip\u00e2naw',), ('kinip\u00e2n\u00e2naw',))\n        -False: (('k', 'i', 'n', 'i', 'p', '\u00e2', 'n', 'a', 'w'), ('k', 'i', 'n', 'i', 'p', '\u00e2', 'n', '\u00e2', 'n', 'a', 'w'))\n    \"\"\"\n    pass\n    \n# HFSTOL.feed_in_bulk   \n\ndef feed_in_bulk(self, surface_forms: List[str], concat=True) -> Dict[str, Set[Tuple[str, ...]]]:\n    \"\"\"\n    feed a multiple of surface forms to hfst at once\n\n    :param surface_forms:\n    :return: a dictionary with keys being each surface form fed in, values being their corresponding deep forms\n    \"\"\"\n    pass\n\n# HFSTOL.feed_in_bulk_fast\n\ndef feed_in_bulk_fast(self, strings: Iterable[str], multi_process: int = 1) -> Dict[str, Set[str]]:\n    \"\"\"\n    calls `hfstol-optimized-lookup`. Evaluation is magnitudes faster. Note the generated symbols will all be all concatenated.\n    e.g. instead of ['n', 'i', 's', 'k', 'a', '+N', '+A', '+Pl'] it returns ['niska+N+A+Pl']\n\n    :keyword multi_process: Defaults to 1. Specify how many parallel processes you want to speed up computation. A rule is to have processes at most your machine core count.\n    \"\"\"\n\n```\n\n\n# To Use `feed_in_bulk_fast`\n\n`feed_in_bulk_fast` calls compiled C code, which can be 100 times faster than `feed_in_bulk`. \n\nIt requires `hfst-optimized-lookup` installed. Version 1.2 is tested to work. For linux system, installing can be as easy as `sudo apt install hfst`. For other systems see [installation guide](https://github.com/hfst/hfst#installation)\n\nIf `hfst-optimized-lookup` is not found, calling `feed_in_bulk_fast` throws `ImportError`",
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