A simple API for AirVisual air quality data
Project description
☀️ 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/>_ toaiohttp <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!
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