data_grand_lyon_ha

Python library to retrieve data from the Grand Lyon open data platform.

Intended for use as a Home Assistant integration backend.

Installation

pip install data-grand-lyon-ha

Or with uv:

uv add data-grand-lyon-ha

Usage

import asyncio
from datetime import datetime
import aiohttp
from data_grand_lyon_ha import (
    DataGrandLyonClient,
    extract_tcl_pictogram_from_zip,
    filter_tcl_alerts_by_line,
    filter_tcl_passages_by_line,
    filter_tcl_passages_by_stop,
    find_tcl_line_pictogram_by_code,
    find_tcl_park_and_ride_by_id,
    find_tcl_stop_by_id,
    find_velov_station_by_id,
    sort_tcl_alerts_by_relevance,
    sort_tcl_passages_by_time,
)

async def main():
    async with aiohttp.ClientSession() as session:
        client = DataGrandLyonClient(session)
        # Or with authentication (required for real-time TCL passages):
        # client = DataGrandLyonClient(session, username="user", password="pass")

        # TCL passages: fetch all, then filter and sort client-side
        all_passages = await client.get_tcl_passages()
        passages = filter_tcl_passages_by_stop(
            filter_tcl_passages_by_line(all_passages, "A"), 30101
        )
        for p in sort_tcl_passages_by_time(passages):
            print(f"{p.ligne} → {p.direction} in {p.delai_passage} [{p.type}]")

        # TCL stops: fetch all, then look one up by ID
        stops = await client.get_tcl_stops()
        stop = find_tcl_stop_by_id(stops, 1041)
        if stop:
            print(f"{stop.nom} ({stop.commune}) — lines: {stop.desserte}")

        # Vélo'v stations: fetch all, then look one up by ID
        stations = await client.get_velov_stations()
        station = find_velov_station_by_id(stations, 10044)
        if station:
            print(
                f"{station.name}: {station.available_bikes}/{station.bike_stands} bikes"
            )

        # TCL park-and-rides (P+R): fetch all, then look one up by ID
        parks = await client.get_tcl_park_and_rides()
        park = find_tcl_park_and_ride_by_id(parks, "VAI2")
        if park:
            print(
                f"{park.nom}: {park.nb_tot_place_dispo}/{park.capacite} places"
            )

        # TCL traffic alerts: fetch all, filter by line, then sort most-relevant-first
        # (ongoing or starting today come before later days; ended alerts last).
        all_alerts = await client.get_tcl_alerts()
        alerts = filter_tcl_alerts_by_line(all_alerts, "27")
        for a in sort_tcl_alerts_by_relevance(alerts, datetime.now()):
            print(f"[{a.type}] {a.titre} ({a.debut:%d/%m %H:%M} → {a.fin:%d/%m %H:%M})")

        # TCL line pictograms: list lines, then extract one line's SVG as bytes
        # (e.g. for a Home Assistant image entity).
        lines = await client.get_tcl_line_pictograms()
        line = find_tcl_line_pictogram_by_code(lines, "10")
        if line:
            zip_bytes = await client.get_tcl_line_pictograms_zip()
            svg = extract_tcl_pictogram_from_zip(zip_bytes, line.picto_complet)
            if svg:
                print(f"Pictogram for line 10: {len(svg)} bytes")

asyncio.run(main())

Development

This project uses uv for dependency management.

# Run tests
uv run pytest

# Build the package
uv build

License

MIT