README.md

Simple asynchronous Python client for IRCEL - CELINE open data

Work in progress

Python module to get data from the IRCEL - CELINE open data

Target features:

• Get data for real time measurements interpolated
• Get forecast data for PM10, PM2.5 and O3
• Compute or fetch BelAQI index (observation and forecast)
• Maybe: also provide data from the stations and not only interpolation

Install

The library is published on PyPI. Install it using pip

pip install open-irceline

Example of use

import aiohttp
import asyncio
from datetime import datetime
from open_irceline import IrcelineRioClient, IrcelineForecastClient, ForecastFeature, RioFeature


async def get_rio_interpolated_data():
    """Get current level of PM2.5 and PM10 at Brussels from the RIO interpolated data"""
    async with aiohttp.ClientSession() as session:
        client = IrcelineRioClient(session)
        result = await client.get_data(
            timestamp=datetime.utcnow(),  # must be timezone aware
            features=[RioFeature.PM25_HMEAN, RioFeature.PM10_HMEAN],
            position=(50.85, 4.35)  # (lat, lon) for Brussels
        )

    print(f"PM2.5  {result[RioFeature.PM25_HMEAN]['value']} µg/m³")
    print(f"PM10   {result[RioFeature.PM10_HMEAN]['value']} µg/m³")


async def get_o3_forecast():
    """Get forecast for O3 concentration for Brussels for the next days"""
    async with aiohttp.ClientSession() as session:
        client = IrcelineForecastClient(session)
        result = await client.get_data(
            features=[ForecastFeature.O3_MAXHMEAN],
            position=(50.85, 4.35)  # (lat, lon) for Brussels
        )

    for (feature, day), v in result.items():
        print(f"{feature} {day} {v['value']} µg/m³")


async def get_belaqi_forecast():
    """Get current BelAQI index from RIO interpolated values"""
    async with aiohttp.ClientSession() as session:
        client = IrcelineForecastClient(session)
        result = await client.get_data(
            features=[ForecastFeature.BELAQI],
            position=(50.85, 4.35)        # (lat, lon) for Brussels
        )

    for (_, day), value in result.items():
        print(day, value['value'])


if __name__ == '__main__':
    print("\nInterpolated data")
    asyncio.run(get_rio_interpolated_data())

    print("\nO3 forecast for Brussels")
    asyncio.run(get_o3_forecast())

    print("\nForecast BelAQI index")
    asyncio.run(get_belaqi_forecast())

Attribution

The data provided by this module is provided by the Belgian Interregional Environment Agency (IRCEL - CELINE). No change to the provided data is made. Their data is made available under the Creative Commons Attribution 4.0 license.

This work is not endorsed by the Belgian Interregional Environment Agency (IRCEL - CELINE).