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# biking_home — cycling ride analysis
A Go toolkit for analyzing cycling rides from GPX exports: parse rides, detect climbs, score their difficulty, match the same climb across rides, and load French mountain passes from OpenStreetMap into SQLite.
## Features
- **GPX parsing** — reads elevation-tracked rides from Garmin/Strava GPX exports into a `Ride` model
- **Climb detection** — automatically finds climbs within a ride, each scored and categorized (Cat 4 … HC)
- **Difficulty score (Cotacol)** — scores any ride or climb by splitting it into 100 m segments and summing `0.1 km × slope²` per segment. This fixed step is a deliberate compromise: smaller steps increase sensitivity to elevation noise, while unconstrained variable steps maximize noise rather than meaningful difficulty.
- **Similar-climb matching** — finds the same climb across rides by matching start/end coordinates, so times can be compared
- **Mountain pass extraction** — extracts French mountain passes from an OpenStreetMap PBF export (nodes tagged `mountain_pass=yes` / `natural=mountain_pass`) into a SQLite database
- **Pass crossing detection** — flags which passes a ride crosses and names each climb after the pass it tops (e.g. "Col de Castellaras")
- **Interactive ride profiles** — explores elevation, climbs, and mountain-pass crossings in the web ride detail view
- **Official climb cards** — separates matched climbs from pending matches and expands each matched climb with its own elevation profile
- **Web ride library** — starts a local web server by default, imports Strava rides over a date range, stores metadata in SQLite, and keeps their GPX files on disk
- **Materialized ride values** — computes Cotacol on import, stores its algorithm version in SQLite, and refreshes all computed values with `-backfill`
- **Strava stream metrics** — preserves heart rate, cadence, and power in Garmin-compatible GPX files and in-memory ride columns
- **Metadata-only ride imports** — stores Strava activity statistics for rides without GPS tracks, without Cotacol or route data
- **Ride table sorting** — sorts every ride-library column through clickable server-side headers and query parameters
- **Ride library filters** — filters rides by distance, moving duration, start date, Cotacol score, and route availability through shareable query URLs
- **Computed moving time** — computes moving time from the GPX track with a speed-threshold algorithm, persists it as the canonical value (keeping Strava's as `external_moving_time_s`), and benchmarks against that reference via `-backtest`
- **Ride detail maps** — opens a stored ride with its recorded route on an interactive OpenStreetMap map
- **Strava import progress** — streams live import progress with an aggregate progress bar and prevents overlapping syncs
## Getting started
```bash
mise run build
```
## Usage
```bash
# Start the web server on http://localhost:8080
mise run dev-watch
```
## Options / Configuration
| Flag | Description | Default |
| --- | --- | --- |
| `-fetch-osm` | Download the France OSM PBF (resumable) | `false` |
| `-extract-osm` | Extract mountain passes from a France OSM PBF | `""` |
| `-backfill` | Recompute and persist all ride computed values | `false` |
| `-backtest` | Benchmark computed vs stored ride values | `false` |
Configuration is stored in `config.yaml`. Start from `config.example.yaml` and set the Strava credentials before launching the server.
## Strava API
The Strava v3 API (OAuth2) is the platform's public access point; scopes gate each resource (`read`, `activity:read_all`, `activity:write`, `push:subscriptions`). It offers:
- **Activities** — list and fetch ride detail, plus data streams (lat/lng, altitude, time, distance, heart rate, cadence, power) to rebuild GPX or compute metrics
- **Segments** — explore segments, match segment efforts, pull personal records
- **Uploads** — create activities by pushing FIT, GPX or TCX files
- **Webhooks** — push subscriptions notify a callback URL on activity create/delete, enabling real-time sync
- **Extras** — clubs, routes, gear, photos, kudos
Standard apps are rate-limited to 100 calls per 15 minutes and 1,000 per day.
## Architecture
- Go 1.27; SQLite via `mattn/go-sqlite3`
- `ride` — GPX parsing, climb detection, difficulty scores (KOM + Cotacol), similarity index
- `mountain_pass` — OSM PBF extraction (`mountain_pass=yes` / `natural=mountain_pass` nodes), pass storage and querying, and crossings/climb matching
- `strava` — OAuth2 client returning activity metadata and GPX data
- `rides` — SQLite persistence for imported ride metadata and versioned computed values
- `config` — typed YAML configuration and atomic persistence
- `web` — HTTP server, OAuth callback, sync orchestration, and templ pages
- `cli` — command handlers for data import, backfill, and benchmarking
```mermaid
flowchart TB
%% Arrow X --> Y means: X depends on Y
main["main (bootstrap: main.go)"]
ride["ride (GPX parsing, climbs, Cotacol)"]
mpass["mountain_pass (OSM PBF, crossings)"]
strava["strava (OAuth, List, Get)"]
rides["rides (SQLite persistence)"]
config["config (YAML)"]
web["web (HTTP + templ)"]
cli["cli (import, backfill, benchmark)"]
main --> cli
cli --> ride
cli --> mpass
cli --> web
mpass --> ride
web --> strava
web --> rides
web --> config
```
## Research
MapLibre can render local vector-tile maps in the browser from OpenStreetMap PBF data after preprocessing. It supports GeoJSON overlays, dynamic styling, interactive points and lines, feature selection, and offline use with locally served tiles, styles, fonts, and sprites. This enables rich map layers without depending on external basemap tile services.
## Development
```bash
mise run check
mise run build
```
TypeScript checks can also be run directly with `npm run check`, covering formatting, linting, compilation, type checking, and tests.
## TODO
- bug: Ride details > header > 2 lines
- Compute estimated power, speed
- Plot speed and slope per segment, colored by heart rate
- Plot speed vs ctc/100km
- http://localhost:8080/rides/378: Repentance partial climb
- regroup ride and rides packages
- screaming archi + hexagon
- Blog with pictures and markdown
- Road quality (Arbois = 2/5, Roquefavour = 4/5)
- OffClimb
- Keep trace appart from ride to display slope profile, compute cotacol
- Profile - Adaptative to show ramps
- Record ride times on official climbs
- Destination via Start
- Planning rides
- performance/profile tracking
- progress bar cli
- processing takes components as input, not entities
## Resources
- [Climbfinder: difficulty points](https://climbfinder.com/en/difficulty-points) — the Cotacol formula behind the difficulty score
- [Pogacar 21 July 2022](https://www.strava.com/activities/7505784085) — example ride used for climb detection
- [gpxgo](https://github.com/tkrajina/gpxgo) — GPX parsing library
- [geodist](https://github.com/jftuga/geodist) — haversine distance used for climb matching
|
