pyairnow 1.2.2

Description:

pyairnow 1.2.2

pyairnow: a thin Python wrapper for the AirNow API





pyairnow is a simple, tested, thin client library for interacting with the
AirNow United States EPA Air Quality Index API.

Python Versions
Installation
API Key
Usage
Contributing

Python Versions
pyairnow is currently supported and tested on:

Python 3.8
Python 3.9
Python 3.10
Python 3.11

Installation
pip install pyairnow

API Key
You can get an AirNow API key from
the AirNow API site. Ensure you
read and understand the expectations and limitations of API usage, which can
be found at the AirNow FAQ.
Usage
import asyncio
import datetime

from pyairnow import WebServiceAPI


async def main() -> None:
client = WebServiceAPI('your-api-key')

# Get current observational data based on a zip code
data = await client.observations.zipCode(
'90001',
# if there are no observation stations in this zip code, optionally
# provide a radius to search (in miles)
distance=50,
)

# Get current observational data based on a latitude and longitude
data = await client.observations.latLong(
34.053718, -118.244842,
# if there are no observation stations at this location, optionally
# provide a radius to search (in miles)
distance=50,
)

# Get forecast data based on a zip code
data = await client.forecast.zipCode(
'90001',
# to get a forecast for a certain day, provide a date in yyyy-mm-dd,
# if not specified the current day will be used
date='2020-09-01',
# if there are no observation stations in this zip code, optionally
# provide a radius to search (in miles)
distance=50,
)

# Get forecast data based on a latitude and longitude
data = await client.forecast.latLong(
# Lat/Long may be strings or floats
'34.053718', '-118.244842',
# forecast dates may also be datetime.date or datetime.datetime objects
date=datetime.date(2020, 9, 1),
# if there are no observation stations in this zip code, optionally
# provide a radius to search (in miles)
distance=50,
)


asyncio.run(main())

By default, the library creates a new connection to AirNow with each coroutine.
If you are calling a large number of coroutines (or merely want to squeeze out
every second of runtime savings possible), an
aiohttp ClientSession can be used
for connection pooling:
import asyncio
import datetime

from aiohttp import ClientSession

from pyairnow import WebServiceAPI


async def main() -> None:
async with ClientSession() as session:
client = WebServiceAPI('your-api-key', session=session)

# ...


asyncio.run(main())

The library provides two convenience functions to convert between AQI and
pollutant concentrations. See
this EPA document
for more details.
from pyairnow.conv import aqi_to_concentration, concentration_to_aqi

# Supported Pollutants
# --------------------
# Ozone ('O3'): ppm
# pm2.5 ('PM2.5'): ug/m^3
# pm10 ('PM10'): ug/m^3
# Carbon Monoxide ('CO'): ppm
# Sulfur Dioxide ('SO2'): ppm
# Nitrogen Dioxide ('NO2'): ppm

# Returns AQI = 144 for pm2.5 of 53.0 ug/m^3
aqi_to_concentration(144, 'PM2.5')

# Returns Cp = 53.0 ug/m^3
concentration_to_aqi(53.0, 'PM2.5')

Contributing

Check for open features/bugs
or start a discussion on one.
Fork the repository.
Install Poetry and set up the development workspace:
poetry install
Code your new feature or bug fix.
Write tests that cover your new functionality.
Run tests and ensure 100% code coverage: make test
Run the linter to ensure 100% code style correctness: make lint
Update README.md with any new documentation.
Add yourself to AUTHORS.md.
Submit a pull request!