---
id: aioairq
version: "0.6.0"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# aioairq — Asynchronous library to retrieve data from air-Q devices.

License: permissive · Maintenance: active · Downloads: 73.8K/mo

## What it is and what it does

aioairq is an async Python client for air-Q air quality sensors—devices that measure indoor air parameters and store historical data on an SD card. It wraps the air-Q HTTP API, letting you query real-time sensor readings (CO₂, particulates, temperature, etc.) and browse or download timestamped historical measurements from the device's local storage. The library requires you to provide an aiohttp session and handles device discovery via mDNS (converting a 5-character device ID to a hostname) or direct IP/hostname connection.

The main use case is home automation, environmental monitoring dashboards, or data logging systems that need to pull air quality data from one or more air-Q devices on a local network. It's built on async/await, so it integrates naturally with other async Python code and avoids blocking I/O. Historical data can be downloaded compressed (about 1/5 the size) or uncompressed, and the library supports verbose DEBUG-level logging to track sensor reading changes.

Use it for:

- Poll real-time air quality metrics from an air-Q device and feed them into a Home Assistant or other home automation system.
- Download and archive historical air quality data from the device's SD card for analysis or compliance reporting.
- Build a web dashboard that displays current and historical air quality trends by querying multiple air-Q devices asynchronously.
- Trigger alerts or HVAC adjustments based on CO₂ or particulate thresholds by monitoring sensor readings in a background task.
- Integrate air-Q data into a scientific study or environmental monitoring project that requires local, non-cloud sensor access.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Asynchronous Python library for retrieving real-time and historical sensor data from local air-Q air quality monitoring devices over the network.

Yes. The package is actively maintained, has low install friction, carries a permissive license, and solves a specific problem well: async access to air-Q devices without external dependencies beyond aiohttp and pycryptodome. Install it if you own an air-Q device and need to integrate its data into a Python application. Not relevant if you don't have an air-Q device or need cloud-based air quality APIs instead.

## Install

pip install aioairq
uv add aioairq
poetry add aioairq

## Installing aioairq

Before you install: Low friction: pure Python wheel with only aiohttp and pycryptodome as runtime dependencies. Actively maintained with recent commits; last release 143 days ago. Supports Python 3.9 through 3.13.

License in practice: Apache-2.0 (permissive): you can use, modify, and distribute this library freely in commercial or private projects, provided you include a copy of the license and state any significant changes.

Quickstart:

import asyncio
import aiohttp
from aioairq import AirQ

async def main():
    async with aiohttp.ClientSession() as session:
        airq = await AirQ.connect("123ab", "airqsetup", session)
        data = await airq.data
        print(data)

asyncio.run(main())

Requires an air-Q device on the local network; mDNS resolution (Avahi/Bonjour) needed for device ID lookup, or use IP address directly if mDNS is blocked.

Verify before relying:

- Whether the library handles device authentication failures or network timeouts gracefully.
- Performance characteristics when downloading large historical datasets or querying many sensors simultaneously.
- Whether debug logging overhead is negligible at non-DEBUG levels as claimed.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 73.8K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

air quality sensor data python, air-Q device async client, local air quality monitoring, aiohttp async sensor library, air-Q historical data download, real-time air quality readings, mDNS device discovery python, air-quality-sensor, async-iot, local-network

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