pyairvisual 2.0.0

A simple API for AirVisual air quality data

☀️ pyairvisual: a thin Python wrapper for the AirVisual© API

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pyairvisual is a simple, clean, well-tested library for interacting with AirVisual <https://www.airvisual.com/>_ to retrieve air quality information.

☀️ PLEASE READ: 1.0.0 and Beyond

Version 1.0.0 of pyairvisual makes several breaking, but necessary changes:

• Moves the underlying library from Requests <http://docs.python-requests.org/en/master/>_ to aiohttp <https://aiohttp.readthedocs.io/en/stable/>_
• Changes the entire library to use :code:asyncio
• Makes 3.5 the minimum version of Python required

If you wish to continue using the previous, synchronous version of pyairvisual, make sure to pin version 1.0.0.

💧 Installation

.. code-block:: bash

$ pip install pyairvisual

💧 Example

pyairvisual starts within an aiohttp <https://aiohttp.readthedocs.io/en/stable/>_ :code:ClientSession:

.. code-block:: python

import asyncio

from aiohttp import ClientSession

from pyairvisual import Client

async def main() -> None: """Create the aiohttp session and run the example.""" async with ClientSession() as websession: await run(websession)

async def run(websession): """Run.""" # YOUR CODE HERE

asyncio.get_event_loop().run_until_complete(main())

Create a client:

.. code-block:: python

client = Client('')

Then, get to work:

.. code-block:: python

Get data based on the city nearest to your IP address:

data = await client.data.nearest_city()

...or get data based on the city nearest to a latitude/longitude:

data = await client.data.nearest_city( latitude=39.742599, longitude=-104.9942557)

...or get it explicitly:

data = await client.data.city( city='Los Angeles', state='California', country='USA')

If you have the appropriate API key, you can also get data based on station

(nearest or explicit):

data = await client.data.nearest_station() data = await client.data.nearest_station( latitude=39.742599, longitude=-104.9942557) data = await client.data.station( station='US Embassy in Beijing', city='Beijing', state='Beijing', country='China')

With the appropriate API key, you can get an air quality ranking:

data = client.data.ranking()

Lastly, pyairvisual gives you several methods to look locations up:

countries = await client.supported.countries() states = await client.supported.states('USA') cities = await client.supported.cities('USA', 'Colorado') stations = await client.supported.stations('USA', 'Colorado', 'Denver')

Check out example.py, the tests, and the source files themselves for method signatures and more examples.

💧 Contributing

#. Check for open features/bugs <https://github.com/bachya/regenmaschine/issues>_ or initiate a discussion on one <https://github.com/bachya/regenmaschine/issues/new>. #. Fork the repository <https://github.com/bachya/regenmaschine/fork>. #. Install the dev environment: :code:make init. #. Enter the virtual environment: :code:pipenv shell #. Code your new feature or bug fix. #. Write a test that covers your new functionality. #. Run tests: :code:make test #. Build new docs: :code:make docs #. Add yourself to AUTHORS.rst. #. Submit a pull request!