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        "author": "Xwiz",
        "author_email": "c.opata@robosyslive.com",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
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        "description": "# spaCy Symspell\n## Spelling correction implementation in spaCy via Symspell\n\nThis package is a [spaCy 2.0 extension](https://spacy.io/usage/processing-pipelines#section-extensions) that adds sentnece/spelling corrections via Symspell to spaCy's text processing pipeline.\n\n## Installation\n\n`pip install spacy_symspell`\n\n## Notes\nThis package is still in Alpha and there may be unforeseen errors. Dictionary loading time is also significant, can take up to 30 seconds on slow machines.\n\n## Usage\n\nAdding the component to the processing pipeline is relatively simple:\n\n    import spacy\n    from spacy_symspell import SpellingCorrector\n\n    nlp = spacy.load('en_core_web_sm')\n    corrector = SpellingCorrector()\n    nlp.add_pipe(corrector)\n    doc = nlp('What doyuoknowabout antyhing')\n\n    for s in doc._.suggestions:#iterable\n        print(s) #What doyon about anything\n\n    doc._.segmentation  #::segmented_string - What doyouk now about antyhing ::corrected_string - that dook now about anything\n\nspaCy_symspell operates on `Doc` and `Span` spaCy objects. When called on a `Doc` or `Span`, the object is given two attributes: `suggestions` (a list of all found spelling suggestions) and `segmentation` (a corrected sentence in the case of ommitted spaces).\n\n## Todo\nSymspell accuracy can be improved with the help of spaCy by extracting and analyzing resulting n-grams and cross-referencing with possible n-grams deductible from the character groups in the symspell result. For example the correction 'that dook now' leaves us with a verbless sentence, and on closer analysis will reveal that the character group 'now' is related with the verb 'know', and the verb know is associated with the n-gram 'you know'.\n\n## Under the hood\n[spacy_symspell](https://github.com/xwiz/spacy_symspell) is currently a wrapper of the [python port](https://github.com/mammothb/symspellpy) for [Symspell](https://github.com/wolfgarbe/SymSpell). For additional details, see the linked project pages.\n\n",
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        "license": "MIT",
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        "name": "spacy-symspell",
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