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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 download French mountain passes 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
- **Similar-climb matching** — finds the same climb across rides by matching start/end coordinates, so times can be compared
- **Mountain pass download** — imports French mountain passes from centcols.org into a SQLite database
- **Pass crossing detection** — enriches passes with OSM coordinates, flags which passes a ride crosses, and names each climb after the pass it tops (e.g. "Col de Castellaras")
- **Plots** — renders elevation and score-profile charts as PNG
## Getting started
```bash
go build -o biking_home .
```
## Usage
```bash
# Download French mountain passes into biking_home.db (SQLite)
./biking_home -download
# Resume an interrupted download, reusing departments already cached on disk
./biking_home -download -resume
# Run the climb-similarity and difficulty-score demo on the example rides
./biking_home -demo
# Import cached department CSVs (debug_department_06.csv, 13.csv) into the DB
./biking_home -import-cached
# Extract mountain passes from a France OSM PBF into the DB
./biking_home -extract-osm /path/to/france-latest.osm.pbf
# Backfill OSM coordinates onto passes (needs -extract-osm run first)
./biking_home -enrich
# Render an elevation chart with climb highlights and pass markers
./biking_home -chart examples/2023-06-17.AlpesVerdonTour.gpx
# Profile the demo with Go's CPU profiler
./biking_home -demo -cpuprofile /tmp/cpu.prof
```
## Options / Configuration
| Flag | Description | Default |
| --- | --- | --- |
| `-download` | Download mountain passes into the database | `false` |
| `-resume` | Skip departments already cached on disk | `false` |
| `-import-cached` | Import cached department CSVs into the database | `false` |
| `-extract-osm` | Extract mountain passes from a France OSM PBF | `""` |
| `-enrich` | Backfill OSM coordinates onto passes | `false` |
| `-chart` | Render an elevation chart (climbs + passes) for a GPX file | `""` |
| `-demo` | Run the climb-similarity demo | `false` |
| `-cpuprofile` | Write a CPU profile to file | `""` |
## Architecture
- Go 1.23; SQLite via `mattn/go-sqlite3`; charts via `gonum.org/v1/plot`
- `ride` — GPX parsing, climb detection, difficulty scores (KOM + Cotacol), similarity index
- `mountain_pass` — centcols.org department CSV download into SQLite, with disk caching and retries
- `osmpass` — OSM PBF extraction (`mountain_pass=yes` nodes) and pass coordinate enrichment
- **Notable choices** — the difficulty score follows the Cotacol method: the ride is split into fixed 100 m segments and each scores `distance_km × slope²`, so steep sections weigh exponentially more than long flat ones
## Development
```bash
go vet ./...
go test ./...
```
## TODO
- Compute estimated power
- Export data from Strava / Garmin (GPX, TCX, FIT)
- Plot speed and slope per segment, colored by heart rate
- Persist the chosen climb variant across activities
- Handle historical data
- Blog with pictures and markdown
- Store GPX files
## Resources
- [Climbfinder: difficulty points](https://climbfinder.com/en/difficulty-points) — the Cotacol formula behind the difficulty score
- [centcols.org](https://www.centcols.org) — French mountain pass reference used for the SQLite data
- [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
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