pyidfm — Île-de-France Mobilités API

AI-ready Python API wrapper for the Île-de-France Mobilités open-data API. It exposes next-schedule lookups, traffic disruption reports and traffic messages for the Paris / Île-de-France public transport network (Metro, RER, Transilien, Tram, Bus).

The package is designed both as a regular Python library and as a CLI that is easy to drive from an LLM agent.

Part of this codebase (notably the SIRI / Navitia request plumbing in idfm.py and the dataclasses in models.py) is derived from the idfm-api package, with heavy modifications focused on reliability and LLM-friendliness rather than raw feature completeness.

Installation

pip install pyidfm

Or, from a checkout of this repository:

pip install .

API key

Live endpoints (next schedules, traffic reports, messages) require a free API key from the IDFM PRIM platform: https://prim.iledefrance-mobilites.fr/.

Once you have a key, expose it via the IDFM_API_KEY environment variable (every CLI command picks it up automatically) or pass it explicitly with the --apikey option.

export IDFM_API_KEY="your-key-here"

Static datasets

Lines and stops are resolved from local snapshots of the IDFM open-data datasets. They are downloaded on first use, but you can refresh them if required.

pyidfm update-data

CLI usage

The CLI is exposed as pyidfm once installed. Top-level commands:

All commands accept --json to emit machine-readable output, and the top-level --debug flag for verbose logging.

Examples

Find the ID of the RER D:

pyidfm search lines --mode rail

List the stops on a line:

pyidfm search stops C01742

Get the next departures at a stop:

pyidfm traffic --stop-id "STIF:StopArea:SP:43135:"

Get current disruptions on a line:

pyidfm line-report C01742

Python usage

from pyidfm.idfm import IDFMApi
from pyidfm.dataset import Dataset


# Live data (PRIM API key required)
api = IDFMApi(apikey="your-key-here")

stops = api.get_stops("C01742")
for s in stops:
    print(s.name, s.stop_id)

departures = api.get_traffic("STIF:StopArea:SP:43135:")
for d in departures:
    print(d.schedule, d.destination_name, d.direction)

reports = api.get_line_reports("C01742")
for r in reports:
    print(r.name, r.severity, r.effect)

Usage through LLMs

The CLI is the recommended entry point for LLM agents. A typical flow is three calls — search lines → search stops → traffic (or line-report / messages).

Output format guidance:

• Standard output (default) — formatted table; use this when reporting information to the user.
• --json — machine-parseable array; use this when extracting a specific value (an ID to pass to the next command, a departure time, a status).

See SKILL.md in this repository for the agent skill packaging used during development.

License

MIT — see LICENCE.

The IDFM open-data datasets bundled at runtime are redistributed under the ODbL; the live PRIM API is covered by the Licence Mobilité.