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        "author": "Mathieu FRANCK",
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            "Development Status :: 3 - Alpha",
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            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Operating System :: MacOS :: MacOS X",
            "Operating System :: Microsoft :: Windows",
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            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "# fraddress-parser\nfraddress is a python library for parsing unstructured FR addresses strings into address components using a custom NLP model that learns from patterns. \nThis library relies on the [parserator](https://github.com/datamade/parserator) library.\n\n\n## How to use fraddress\nInstall fraddress with pip.\n```\npip install fraddress\n ```\n\nThen parse some address with parse or tag.\n```\n>>> import fraddress\n>>> fraddress.parse('51 rue Nationale Paris 75006')\n[('51', 'AddressNumber'), ('rue', 'StreetType'), ('Nationale', 'StreetName'), ('Paris', 'City'), ('75006', 'Zipcode')]\n\n>>> fraddress.tag('51 rue Nationale Paris 75006')\nOrderedDict([('AddressNumber', '51'), ('StreetType', 'rue'), ('StreetName', 'Nationale'), ('City', 'Paris'), ('Zipcode', '75006')])\n```\n\n## Check trained patterns\nGo to the training directory and check the file [trained_pattern.txt](https://github.com/fahrtass/fraddress-parser/blob/master/training/trained_pattern.txt) to see which pattern is already known by the model.\n\n\n## How to train a new parser\nAll you need is some training data to teach your parser about its domain, and then [follow the instructions of the U.S version](https://github.com/datamade/usaddress/tree/master/training).\n\n",
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        "license": "The MIT License: http://www.opensource.org/licenses/mit-license.php",
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        "name": "fraddress",
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        "summary": "Library for parsing unstructured FR addresses strings into address components",
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