open-rando

Train station-to-station hiking on French GR paths -- car-free hiking made easy.

A Python pipeline fetches hiking routes, train stations, bus stops, and elevation data from open sources, then exports a catalog. An Astro static website displays routes on a map with filters, elevation profiles, section selection, and GPX download.

How it works

BUILD TIME                                    RUNTIME (static files)
+-----------------------------------------+   +----------------------------+
| Python Pipeline                         |   | Astro Static Site          |
|                                         |   |                            |
| Overpass API --+                        |   |  Leaflet Map + List/Filter |
| SNCF stations -+-> fetch -> match ->   |   |  Elevation chart           |
| GTFS bus data --+   geography ->        |   |  Section selector + QR     |
| SRTM tiles ----+    elevation ->        |   |         |                  |
|                      export             |   |    catalog.json            |
|               data/catalog.json         |   |    /gpx/{id}.gpx           |
|               data/gpx/*.gpx            |   |    /geojson/{id}.json      |
|               data/geojson/*.json       |   |    /elevation/{id}.json    |
|               data/elevation/*.json     |   +----------------------------+
+-----------------------------------------+

The pipeline:

1. Loads curated GR routes from routes.yaml (176 trails with OSM relation IDs)
2. Fetches trail geometry from the Overpass API (resolves super-relations recursively)
3. Fetches active train stations near the route (OSM + SNCF filtering)
4. Matches stations to the trail using Shapely
5. Fetches bus stops with GTFS enrichment (route names from transport.data.gouv.fr)
6. Fetches nearby accommodation (hotel, guest house, hostel, camping) for each station
7. Samples elevation from SRTM tiles every 50m, classifies geography (region, terrain, difficulty)
8. Exports GPX files, GeoJSON, elevation profiles, and a catalog.json consumed by the website

Getting started

Prerequisites

On macOS, brew bundle at the repo root installs every native tool (uv, osmium-tool, gdal, tippecanoe, rclone, bun). Otherwise:

• Python 3.13+ with uv
• Bun (or Node.js)
• osmium-tool to build the local OSM extracts (required by the pois stage; tracks fall back to the Overpass API)

Run the pipeline

cd pipeline
uv sync --all-extras
uv run python -m open_rando pipeline

pipeline chains five stages: tracks, gtfs, pois, link, catalog. The POI stage reads the local OSM extract index, so build it first (make -f Makefile.osm). Each stage also runs alone, see docs/SPLIT_PIPELINE.md.

Options:

uv run python -m open_rando pipeline --route "GR 13"   # single route
uv run python -m open_rando pipeline --dry-run          # list routes without processing
uv run python -m open_rando pipeline --retry-failed     # only routes that failed before
uv run python -m open_rando pipeline --skip-gtfs        # reuse the GTFS stop index

Pipeline output goes to ~/.local/share/open-rando/data/, cache to ~/.cache/open-rando/.

Run the website

cd website
bun install
bun run dev

The dev server copies pipeline data into public/data/ automatically.

To build for production:

bun run build

Static output goes to website/dist/.

Features

• Interactive Leaflet map with trail visualization and POI overlays
• Filter routes by region and terrain type
• Route detail pages with elevation profile (slope-colored), station list, and map
• Section selector: pick start/end train stations, view section stats (distance, elevation, duration)
• QR code sharing for selected sections (downloadable or scannable with companion app)
• GPX download for full routes and selected sections
• Bus stop display with GTFS route names
• Accommodation info (hotel/camping) per station
• Bilingual: French (default) and English

Project structure

open-rando/
  pipeline/              Python data pipeline
    src/open_rando/
      cli.py             Entry point
      config.py          Constants (API config, search radius)
      fetchers/          Overpass, SNCF, GTFS, SRTM, POI fetchers
      processors/        Station matching, elevation, geography, slicing
      exporters/         GPX, GeoJSON, elevation, catalog writers
    routes.yaml          Curated GR route catalog (176 trails)
  website/               Astro static site
    src/
      pages/             Landing, app (list + map), route detail (FR + EN)
      components/        ElevationChart, RouteCard, RouteFilters, RouteList, SearchableSelect
      lib/               catalog.ts, i18n.ts, elevation.ts, route-filters.ts
  docs/                  Architecture, data sources, deployment

Stack

Layer	Tech
Pipeline	Python 3.13+, Shapely, requests, gpxpy, pyyaml
Website	Astro, Leaflet, Tailwind CSS, qrcode-generator
Data sources	OpenStreetMap Overpass API, SNCF open data, transport.data.gouv.fr GTFS, OSRM, SRTM elevation tiles

Data sources

All data comes from open sources under the ODbL license.

• Hiking routes: OpenStreetMap via Overpass API (route=hiking, ref~"^GR")
• Train stations: OpenStreetMap (railway=station / railway=halt), filtered for active service via SNCF data
• Bus stops: OpenStreetMap, enriched with route names from GTFS feeds (transport.data.gouv.fr)
• Accommodation: OpenStreetMap (tourism=hotel|guest_house|hostel|camp_site) near the trail
• Elevation: SRTM .hgt tiles, sampled every 50m along the trail

Development

# Lint and format (Python)
cd pipeline
uv run ruff check src/
uv run ruff format src/

# Type check
uv run mypy src/

License

Code and website: GPLv3

Data: ODbL (OpenStreetMap)