$ show Freika/dawarich
Dawarich is a production Ruby on Rails 8 monolith for personal location history tracking, positioning itself as a self-hostable Google Timeline replacement. It ingests timestamped geospatial points from a broad range of trackers (OwnTracks, Overland, Traccar) and file formats (GPX, GeoJSON, KML/KMZ, TCX, FIT, CSV, Google Takeout), then drives them through heavy background processing: reverse geocoding, anomaly filtering, visit detection, track generation, transportation-mode classification, trip building, and monthly/yearly statistics with digest emails. The web frontend is a MapLibre GL JavaScript application using vector-tile rendering, WebSocket real-time updates, and novel in-browser encoding studios for route videos (WebCodecs MP4) and printable posters (hand-rolled PNG encoder). The system also integrates photo libraries (Immich, PhotoPrism), flight logs (AirTrail), TeslaMate, and TREK trip planning, plus family location sharing, achievements, and an MCP API endpoint. Architecturally it is a conventional but well-executed Rails service-object monolith: controllers are thin, domain logic lives in app/services (command pattern with call methods), heavy processing is delegated to a large Sidekiq job surface with named queues, and cross-process coordination uses Redis-based debouncers, per-user advisory locks, and tile epochs for cache invalidation. PostGIS powers spatial queries (ST_DWithin, lonlat geography, H3 hexagons, vector tiles). The codebase ships dual-mode: self-hosted Docker deployments and a cloud SaaS with subscription/entitlement gating, with many env-conditional branches. Test coverage is extensive (RSpec with regression specs for timezone/race/geospatial edge cases, Playwright e2e, locale-parity and schedule-consistency specs), CI includes RuboCop, Trivy, and Dependabot. The strongest engineering is in the data-ingestion and processing layer: streaming SAX-style JSON parsers for huge Google Takeout files, batched upsert with deduplication and Null Island filtering, deterministic nearest-centroid transportation-mode classification with explicit explainability, and Redis coordination patterns for geocoding claims and per-user job locks. Weaknesses include a sprawling surface area (35+ service subdomains in one repo), significant schema churn via migration-enqueued backfill jobs, and dual self-hosted/cloud branches that add cognitive load. Overall this is a well-maintained, feature-complete application with genuinely reusable geospatial and streaming-data patterns.
The LLM identified 6 files worth highlighting for reuse:
A shared module for batched upsert of geospatial points across all importers (OwnTracks, GPX, Google Takeout, CSV, etc.). Encapsulates Null Island filtering, exact-duplicate detection, dimension resolution, counter maintenance, and progress broadcasting. Extractable into any location-data ingestion pipeline; demonstrates non-obvious handling of large-volume point insertion with idempotency.
SAX-style streaming JSON handler (via Oj::Saj) for parsing multi-gigabyte GeoJSON files without loading them into memory. Used for Google Takeout imports. The pattern of callback-based streaming JSON parsing with cursor-based DB persistence is reusable for any memory-constrained JSON ingestion pipeline.
A deterministic, explainable nearest-centroid classifier that maps a 5-dimensional feature vector (speed percentiles, heading change rate, motion variance, stop fraction) to a transportation mode (stationary/walking/running/cycling/driving). No ML training dependency — pure threshold/centroid logic with a clean call interface. Reusable as a template for lightweight, explainable sensor-data classifiers.
Redis-based per-user mutex with heartbeat renewal for long-running track-generation jobs. Prevents concurrent duplicate work across Sidekiq workers while surviving worker crashes via TTL. Demonstrates a robust distributed-lock pattern with lease renewal, extractable for any multi-worker job system needing per-key exclusion.
Hand-rolled MP4 file writer using the WebCodecs API to encode route-replay videos entirely in the browser. Implements MP4 box structure (ftyp/moov/mdat), codec negotiation, and sample timing without any third-party encoder library. Demonstrates deep, non-obvious knowledge of container formats and browser media APIs.
A self-contained PNG encoder that serializes canvas pixel data into a valid PNG file with proper CRCs and zlib compression — no external library. Used to export printable route posters from the browser. Genuinely reusable for any client-side image-export feature and a strong example of low-level image-format craftsmanship.