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v2.3.0-rc.2 · independent testing and demonstration project. Made by Akila DJ using OpenAI ChatGPT / Codex to test and demonstrate AirGradient API connections: fetch public readings, inspect fields and raw JSON, compare devices, and explore air-quality data on a map. Click a location or read its device card for compact parameter/value rows, with explained N/A, N/D and missing-field notation. This is not an official AirGradient product.
Testing and demo only: software, labels, calculations and source readings may contain mistakes. Values are not independently validated; check original records and timestamps before relying on results. AQI is an illustrative PM2.5 estimate.
The Python + localhost app is the main version. It provides on-demand requests,
configurable devices, raw/corrected PM2.5 selection and optional authorized hourly
history. Install Python (3.9+ compatibility;
a currently supported stable release is recommended) and keep an internet connection.
Download and extract the release ZIP, run
py serve.py on Windows or python3 serve.py on macOS/Linux, then open the exact
local address printed by Python. Keep the terminal running. No pip packages needed.
Full installation guide.
The supplementary website is an easy first look without installation. It shows five fixed devices using snapshots collected about every 15 minutes. GitHub delays may make them older; reloading only reloads published data. No token entry, device additions or hourly history. Use the main app for fuller API testing; it does not improve sensor accuracy.
- Devices and parameters: device order, NO2/O3, units and interpretation.
- Credits and licensing: courtesy to data providers, tool licenses and app reuse.
- Source and user guide · Release notes.
Original code and documentation: MIT No Attribution (MIT-0). Use, change, share and sell freely; attribution is optional and welcome. No share-alike requirement for original code. Provided as is without warranty; third-party terms remain separate.
Thank you to AirGradient, its API team, and the monitor owners and contributors who choose to share data publicly. Their measurements make this demo possible.
Enjoying the experiment? Fuel the next API adventure with an optional Ko-fi contribution or visit Gadash on Ko-fi. Free to use; a coffee is always optional.
Testing and demo only; mistakes may be present. Original code/docs: MIT No Attribution (MIT-0); optional credit welcome. AirGradient public data: CC BY-SA 4.0.
Keep the experiments brewing: project Ko-fi · Gadash. Always optional.