Crestr
Open-source hiking route planner for Cumbria with elevation-aware A* routing, manual snap-to-path plotting, POIs, and GPX/GeoJSON export.
What is Crestr?
Crestr is a free, open-source hiking route planner built specifically for walkers in Cumbria (the Lake District and surrounding fells). It offers an interactive topographic map, automatic and manual route generation, points of interest, and standard route export — all without the subscriptions that commercial hiking apps charge.
Key features
- Interactive topographic map — High-resolution OpenStreetMap and OpenTopoMap tiles rendered with OpenLayers, showing paths, contours, and landmarks.
- Automatic route generation — A custom A* pathfinding engine that is elevation-aware, so generated routes account for terrain difficulty, not just distance.
- Manual mode with snap-to-path — Click on the map to drop waypoints, with snap-to-path to keep routes on real trails.
- POI management — Save points of interest to your account and reuse them across routes.
- Universal export — Download routes as GPX (for GPS watches and handheld devices) or GeoJSON (for Google Maps, Strava, OS Maps, and more).
- Place search — Search any area in Great Britain and the map jumps there.
Self-hosting
Crestr ships with a docker-compose.yml so the whole stack (Flask backend, PostgreSQL with PostGIS-ready schema, and the JavaScript frontend) comes up with a single command. Run docker-compose up --build and access the app at localhost:5000.
How it compares to Komoot and AllTrails
Like Komoot, Crestr generates routes that follow real paths rather than straight lines, and exports them in formats that work with GPS hardware. Like AllTrails, it overlays trails and landmarks on a topographic map and supports manual route building. The big difference is that Crestr is fully self-hostable, MIT-licensed, and free — no region bundles, no premium subscription, no data lock-in.
Tech stack
Python + Flask backend, PostgreSQL database, vanilla JavaScript frontend with OpenLayers, custom A* pathfinding over OSM data with KDTree spatial indexing.
