Metadata-Version: 2.1
Name: pyairvisual
Version: 2.0.3
Summary: A simple API for AirVisual air quality data
Home-page: https://github.com/bachya/pyairvisual
Author: Aaron Bach
Author-email: bachya1208@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.6.0
Description-Content-Type: text/markdown
Requires-Dist: aiodns
Requires-Dist: aiohttp

# ☀️ 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: Version 2.0.0 and Beyond

Version 2.0.0 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 `asyncio`
* Makes 3.6 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

```python
pip install pyairvisual
```

# API Key

You can get an AirVisual API key from
[the AirVisual API site](https://www.airvisual.com/user/api). Depending on
the plan you choose, more functionality will be available from the API:

## Community

The Community Plan gives access to:

* List supported countries
* List supported states
* List supported cities
* Get data from the nearest city based on IP address
* Get data from the nearest city based on latitude/longitude
* Get data from a specific city

## Startup

The Startup Plan gives access to:

* List supported stations in a city
* Get data from the nearest station based on IP address
* Get data from the nearest station based on latitude/longitude
* Get data from a specific station

## Enterprise

The Enterprise Plan gives access to:

* Get a global city ranking of air quality

# Usage

`pyairvisual` starts within an
[aiohttp](https://aiohttp.readthedocs.io/en/stable/) `ClientSession`:

```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:
      # YOUR CODE HERE


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

Create a client and get to work:

```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:
      client = Client('<YOUR AIRVISUAL API KEY>', websession)

      # 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 = await 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')


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

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

# Contributing

1. [Check for open features/bugs](https://github.com/bachya/pyairvisual/issues)
  or [initiate a discussion on one](https://github.com/bachya/pyairvisual/issues/new).
2. [Fork the repository](https://github.com/bachya/pyairvisual/fork).
3. Install the dev environment: `make init`.
4. Enter the virtual environment: `pipenv shell`
5. Code your new feature or bug fix.
6. Write a test that covers your new functionality.
7. Run tests and ensure 100% code coverage: `make coverage`
8. Add yourself to `AUTHORS.md`.
9. Submit a pull request!


