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    "info": {
        "author": "Aaron Bach",
        "author_email": "bachya1208@gmail.com",
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        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
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        "description": "\n# \u2600\ufe0f pyairvisual: a thin Python wrapper for the AirVisual\u00a9 API\n\n[![Travis CI](https://travis-ci.org/bachya/pyairvisual.svg?branch=master)](https://travis-ci.org/bachya/pyairvisual)\n[![PyPi](https://img.shields.io/pypi/v/pyairvisual.svg)](https://pypi.python.org/pypi/pyairvisual)\n[![Version](https://img.shields.io/pypi/pyversions/pyairvisual.svg)](https://pypi.python.org/pypi/pyairvisual)\n[![License](https://img.shields.io/pypi/l/pyairvisual.svg)](https://github.com/bachya/pyairvisual/blob/master/LICENSE)\n[![Code Coverage](https://codecov.io/gh/bachya/pyairvisual/branch/master/graph/badge.svg)](https://codecov.io/gh/bachya/pyairvisual)\n[![Maintainability](https://api.codeclimate.com/v1/badges/948e4e3c84e5c49826f1/maintainability)](https://codeclimate.com/github/bachya/pyairvisual/maintainability)\n[![Say Thanks](https://img.shields.io/badge/SayThanks-!-1EAEDB.svg)](https://saythanks.io/to/bachya)\n\n`pyairvisual` is a simple, clean, well-tested library for interacting with\n[AirVisual](https://www.airvisual.com/) to retrieve air quality information.\n\n# PLEASE READ: Version 2.0.0 and Beyond\n\nVersion 2.0.0 of `pyairvisual` makes several breaking, but necessary changes:\n\n* Moves the underlying library from\n  [Requests](http://docs.python-requests.org/en/master/) to\n  [aiohttp](https://aiohttp.readthedocs.io/en/stable/)\n* Changes the entire library to use `asyncio`\n* Makes 3.6 the minimum version of Python required\n\nIf you wish to continue using the previous, synchronous version of\n`pyairvisual`, make sure to pin version 1.0.0.\n\n# Python Versions\n\n`pyairvisual` is currently supported on:\n\n* Python 3.6\n* Python 3.7\n\n# Installation\n\n```python\npip install pyairvisual\n```\n\n# API Key\n\nYou can get an AirVisual API key from\n[the AirVisual API site](https://www.airvisual.com/user/api). Depending on\nthe plan you choose, more functionality will be available from the API:\n\n## Community\n\nThe Community Plan gives access to:\n\n* List supported countries\n* List supported states\n* List supported cities\n* Get data from the nearest city based on IP address\n* Get data from the nearest city based on latitude/longitude\n* Get data from a specific city\n\n## Startup\n\nThe Startup Plan gives access to:\n\n* List supported stations in a city\n* Get data from the nearest station based on IP address\n* Get data from the nearest station based on latitude/longitude\n* Get data from a specific station\n\n## Enterprise\n\nThe Enterprise Plan gives access to:\n\n* Get a global city ranking of air quality\n\n# Usage\n\n`pyairvisual` starts within an\n[aiohttp](https://aiohttp.readthedocs.io/en/stable/) `ClientSession`:\n\n```python\nimport asyncio\n\nfrom aiohttp import ClientSession\n\nfrom pyairvisual import Client\n\n\nasync def main() -> None:\n    \"\"\"Create the aiohttp session and run the example.\"\"\"\n    async with ClientSession() as websession:\n      # YOUR CODE HERE\n\n\nasyncio.get_event_loop().run_until_complete(main())\n```\n\nCreate a client and get to work:\n\n```python\nimport asyncio\n\nfrom aiohttp import ClientSession\n\nfrom pyairvisual import Client\n\n\nasync def main() -> None:\n    \"\"\"Create the aiohttp session and run the example.\"\"\"\n    async with ClientSession() as websession:\n    # If an API key isn't provided, only Nodes can be queried; everything else\n    # requires an API key:\n    client = Client(websession, api_key='<YOUR AIRVISUAL API KEY>')\n\n    # Get data based on the city nearest to your IP address:\n    data = await client.data.nearest_city()\n\n    # ...or get data based on the city nearest to a latitude/longitude:\n    data = await client.data.nearest_city(\n        latitude=39.742599, longitude=-104.9942557)\n\n    # ...or get it explicitly:\n    data = await client.data.city(\n        city='Los Angeles', state='California', country='USA')\n\n    # If you have the appropriate API key, you can also get data based on\n    # station (nearest or explicit):\n    data = await client.data.nearest_station()\n    data = await client.data.nearest_station(\n        latitude=39.742599, longitude=-104.9942557)\n    data = await client.data.station(\n        station='US Embassy in Beijing',\n        city='Beijing',\n        state='Beijing',\n        country='China')\n\n    # With the appropriate API key, you can get an air quality ranking:\n    data = await client.data.ranking()\n\n    # pyairvisual gives you several methods to look locations up:\n    countries = await client.supported.countries()\n    states = await client.supported.states('USA')\n    cities = await client.supported.cities('USA', 'Colorado')\n    stations = await client.supported.stations('USA', 'Colorado', 'Denver')\n\n    # AirVisual Nodes can also be queried by ID\n    data = await client.api.node('12345abcdef')\n\n\nasyncio.get_event_loop().run_until_complete(main())\n```\n\nCheck out `example.py`, the tests, and the source files themselves for method\nsignatures and more examples.\n\n# Contributing\n\n1. [Check for open features/bugs](https://github.com/bachya/pyairvisual/issues)\n  or [initiate a discussion on one](https://github.com/bachya/pyairvisual/issues/new).\n2. [Fork the repository](https://github.com/bachya/pyairvisual/fork).\n3. Install the dev environment: `make init`.\n4. Enter the virtual environment: `pipenv shell`\n5. Code your new feature or bug fix.\n6. Write a test that covers your new functionality.\n7. Run tests and ensure 100% code coverage: `make coverage`\n8. Add yourself to `AUTHORS.md`.\n9. Submit a pull request!\n\n\n",
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