Metadata-Version: 2.4
Name: pyairnow
Version: 1.4.0
Summary: A lightweight Python wrapper for EPA AirNow Air Quality API
License: MIT
License-File: AUTHORS.md
License-File: LICENSE
Author: Jonathan Krauss
Author-email: jkrauss@asymworks.com
Requires-Python: >=3.10,<4.0
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Typing :: Typed
Requires-Dist: aiohttp (>=3.10.0,<4.0.0)
Project-URL: Repository, https://github.com/asymworks/pyairnow
Description-Content-Type: text/markdown

# pyairnow: a thin Python wrapper for the AirNow API

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`pyairnow` is a simple, tested, thin client library for interacting with the
[AirNow](https://www.airnow.gov) United States EPA Air Quality Index API.

- [Python Versions](#python-versions)
- [Installation](#installation)
- [API Key](#api-key)
- [Usage](#usage)
- [Contributing](#contributing)

# Python Versions

`pyairnow` is currently supported and tested on:

* Python 3.10
* Python 3.11
* Python 3.12
* Python 3.13

# Installation

```python
pip install pyairnow
```

# API Key

You can get an AirNow API key from
[the AirNow API site](https://docs.airnowapi.org/account/request/). Ensure you
read and understand the expectations and limitations of API usage, which can
be found at [the AirNow FAQ](https://docs.airnowapi.org/faq).

# Usage

```python
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')

  # Get current observational data based on a latitude and longitude
  data = await client.observations.latLong(34.053718, -118.244842)

  # 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',
  )

  # 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),
  )


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`](https://github.com/aio-libs/aiohttp) `ClientSession` can be used
for connection pooling:

```python
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](https://document.airnow.gov/technical-assistance-document-for-the-reporting-of-daily-air-quailty.pdf)
for more details.

```python

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')

```

# Legacy API Format
AirNow announced in June 2026 that the forecast and current observation APIs would be
retired and replaced with new APIs with slightly changed output format. PyAirNow 1.4.0
uses the new API endpoints by default, and can provide data in the legacy format for
clients which expect it. To use the legacy format, pass `legacy_format=True` to the
API constructor:

```python
import asyncio
import datetime

from pyairnow import WebServiceAPI


async def main() -> None:
  client_legacy = WebServiceAPI('your-api-key', legacy_format=True)
  client_current = WebServiceAPI('your-api-key')

  # Get current observational data based on a zip code
  data_legacy = await client_legacy.observations.zipCode('90001')

  # data_legacy = [{
  #   'DateObserved': ...,
  #   'HourObserved': ...,
  #   ...,
  #   'AQI': ...,
  #   ...,
  # }]

  data_current = await client_current.observations.zipCode('90001')

  # data_current = [{
  #   'dateObserved': ...,
  #   'hourObserved': ...,
  #   ...,
  #   'nowcastAQI': ...,
  #   ...,
  # }]
```

# Contributing

1. [Check for open features/bugs](https://github.com/asymworks/pyairnow/issues)
  or [start a discussion on one](https://github.com/asymworks/pyairnow/issues/new).
2. [Fork the repository](https://github.com/asymworks/pyairnow/fork).
3. Install [Poetry](https://python-poetry.org/) and set up the development workspace:
  `poetry install`
4. Code your new feature or bug fix.
5. Write tests that cover your new functionality.
6. Run tests and ensure 100% code coverage: `make test`
7. Run the linter to ensure 100% code style correctness: `make lint`
8. Run the type checker to ensure type correctness: `make type-check`
9. Update `README.md` with any new documentation.
10. Add yourself to `AUTHORS.md`.
11. Submit a pull request!

