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Backend API

Last updated: June 2026

The backend of Crestr is a lightweight Python web application built with Flask (with plans to migrate to FastAPI). It serves the interactive map, handles authentication, stores user data, and executes routing requests.

Architecture

The backend follows a classic monolithic structure suitable for the current scale of the application:

  • Flask App (app.py): Main application with routes and auth.
  • Pathfinding Module (pathfinder.py): Contains the A* routing engine and spatial helpers.
  • Database Models (models.py): SQLModel definitions for PostgreSQL.
  • NodeFinder Service: Central class managing graph loading, coordinate conversions, and route building.

Core Responsibilities

  • User authentication and session management
  • Saving and loading user routes and saved points
  • Executing A* pathfinding requests
  • File import/export (GPX, GeoJSON, KML, FIT)
  • Search functionality via LocationIQ API
  • Settings persistence

Key Endpoints

Authentication

  • POST /login
  • POST /registering
  • POST /logout
  • POST /validate-beta-code

Routing

  • POST /calculate_path → Main endpoint that returns an optimised hiking route as GeoJSON
  • POST /save_route → Persists a generated route to the database
  • POST /load_route → Retrieves a saved route
  • POST /delete_route

Points of Interest

  • POST /save_point
  • GET /get_saved_points
  • POST /delete_point

File Handling

  • POST /download_route → Returns GPX or GeoJSON file
  • POST /import_route_file –-> Supports GPX, FIT, KML, and GeoJSON uploads

Other

  • GET /get_settings / POST /save_settings
  • POST /search_area –-> Location search

Database

  • PostgreSQL with SQLModel
  • Main tables: user, route, point, settings, betacode
  • Routes and points are scoped to individual users

Design Highlights

  • Rate Limiting: Implemented via Flask-Limiter to protect against abuse.
  • Coordinate Handling: Robust conversion between Web Mercator, WGS84, and BNG using pyproj.
  • Graph Management: Lazy loading of the large trail graph with KDTree optimisation.
  • Error Handling: Consistent JSON responses and custom error pages.
  • Session Security: Configured with secure defaults (ready for HTTPS).

Current Limitations

  • Flask is used for simplicity, but the codebase already has the start of the creation FastAPI components in some areas.
  • All routing runs synchronously → acceptable for current usage but will need review at scale.
  • Beta code system is temporary.

Future Migration Path

  • Full migration to FastAPI for better performance, automatic documentation, and async support.
  • Move heavy pathfinding to a separate microservice or background worker if needed.
  • Add proper API authentication (JWT) for potential mobile or third-party integrations.