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        "description": "easy-geoparsing\n---\n\nEasy-to-use module for streamlined parsing of countries from plaintext locations and top-level domains, plus manipulation of country names and ISO 2 & 3 character codes.\n\nImplementation relies on:\n\n- the [RESTcountries](https://restcountries.eu/) API\n- the [geotext](https://pypi.org/project/geotext/) module\n\n## installation\n\nTo install from the command line via [pip](https://pip.pypa.io/en/stable/), do:\n\n`pip install easy-geoparsing`\n\nTo upgrade to the latest version via `pip` do:\n\n`pip install easy-geoparsing --upgrade`\n\nTo use via [pipenv](https://docs.pipenv.org/en/latest/) put the following in your Pipfile:\n\n```\n[packages]\neasy-geoparsing = \">=1.0.0\"\n```\n\n## development\n\nIf you've cloned the repository, the best way to make it work is using `pipenv`\n\nIf you don't yet have `pipenv`, you can use `pip` to install it from the command line:\n\n`pip install pipenv --upgrade`\n\nThen, in the top level directory of this repository, `easy-geoparsing`, do:\n\n`pipenv install --dev`\n\nThis will create the virtual environment and install the requirements (viewable in the Pipfile). The `--dev` flag will install packages needed for testing etc.\n\n## usage\n\n### GETTING STARTED\n\nDo the following to get the parser utilities, noting that creating an instance of `EasyCountryParser` will automatically download the country data payload from RESTcountries and set up all the resources. Speed will therefore depend on your internet connection, but the payload is not large.\n\n```\nfrom easy_geoparsing import EasyCountryParser\n\nez_parser = EasyCountryParser()\n```\n\nor, if you don't want to use our alternative names for some of the countries (i.e. you want to exactly follow the RESTcountries standard)\n\n`ez_parser = EasyCountryParser(altnames=False)`\n\nThe `EasyCountryParser` class provides utilities, based on the data from the RESTcountries API and the GeoText natural-language parser library, for easily extracting and handling country names and codes.\n\n### PARSER RESOURCES\n\nThe parser is initialised with the following resources:\n\n  - `.data`       - pandas DataFrame containing RESTcountries data\n  - `.tld_to_a2c` - python dict, maps TLDs to 2-character ISO codes\n  - `.tld_to_a3c` - python dict, maps TLDs to 3-character ISO codes\n  - `.iso2to3`    - python dict, maps 2-character ISO codes to 3\n  - `.iso3to2`    - python dict, maps 3-character ISO codes to 2\n  - `.a2c_map`    - python dict, maps 2-char ISO codes to full names\n  - `.a3c_map`    - python dict, maps 3-char ISO codes to full names\n\n### PARSER METHODS\n\nThe parser has the following methods for handling locations data:\n\n  - `.retrieve_country` - parses plaintext for extractable 2-character ISO codes for countries (which can then be manipulated using the mappers above)",
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