Part 1 covered the basics: six crates, Valhalla’s tile format, a driving cost model, bidirectional A*, many-to-many matrix, and an Axum HTTP server. Everything worked for the driving case on the Monaco dataset.

Since then, the engine gained bicycle and pedestrian costing, memory-mapped tiles, a comparison webapp, turn-by-turn directions in 34 languages, and enough performance work to make it usable on France-scale data. This is what changed.

A routing engine in Rust. Bidirectional A*, many-to-many distance matrices, Valhalla-compatible API. Six crates, about 8,000 lines.

Why

We use Valhalla for routing and distance matrices at Woosmap. It works most of the time. When it doesn’t, we’re stuck. We treat it as a black box: file an issue, upgrade, hope the next release fixes things. When the matrix returns wrong costs for certain edge cases or the engine routes you through someone’s driveway, there’s no realistic way for us to dig in. It’s a massive C++ codebase that assumes you’ve been living in it for years.

Serving vector tiles from 10-meter resolution land cover data. What breaks when you 100x the input resolution, and how topology-preserving smoothing fixes the ugly parts.

Background

Freddie is our tile server for land cover data. It reads GeoTIFF raster files (pixels classified as wood, grass, built-up, water, etc.) and serves them as vector tiles or raster tiles over HTTP. Nothing fancy. Read pixels, make shapes, encode, serve.

The original setup used ESA WorldCover at ~100m resolution. Native resolution sits around z8 in Web Mercator, so serving z0–z8 tiles was straightforward. Sample pixels, run-length encode, merge adjacent faces of the same class, encode to MVT. Done. It just worked, and I didn’t think much about it.

Every browser has tabs. Linear, flat, disposable. Open thirty of them researching one topic and they sit in a row with no indication that twelve of them came from the same Wikipedia article. Close the wrong one and the context is gone.

Tree is a macOS browser that replaces tabs with a tree. Every page knows its parent. Cmd+Click a link and it becomes a child node of the current page. The sidebar shows the full hierarchy: research paths branch naturally, and you can always trace back to where you started.

We needed rate limiting across all our services: FastAPI, Django, you name it. The usual approach is to grab a library, wire it up per-framework, and accept the slight differences in behavior between them. We went a different way: one Lua script that runs atomically in Redis, with everything else being thin wrappers around it.

This is how the rate limiting system in application-kit works, including per-project overrides, element-based counting, and a monitor mode for gradual rollouts.

Building a vector map renderer in Rust with wgpu. From “everything renders as points” to a full style-driven renderer running on desktop, iOS, and the browser.

Why

We built our maps stack on top of Mapbox GL: the JS SDK, then native SDKs on the C++ core.

For static maps we wrapped the C++ SDK in a Python library (maparazzo). It worked but the C++ renderer leaked memory. OpenGL contexts kept state around after objects were destroyed. We tried pooling Map instances, reusing GL contexts. It helped but never fully solved it.

Our Python services ran on ubuntu:24.04 with pip-installed dependencies. It worked, but the images carried hundreds of packages we never used, Trivy scans were noisy with OS-level CVEs, and builds were slower than they needed to be. Over a couple of months we migrated to Chainguard’s Wolfi base image and uv for dependency management. This is how it went for the maps service, the one that renders static map tiles with a C++/Python hybrid stack.

Rewriting the Woosmap Maps SDK on top of a Mapbox GL JS fork, with a Google Maps-compatible API surface, built with Bun, and an experiment in offscreen rendering.

Why

The Woosmap Maps SDK depended on Mapbox GL JS. Then Mapbox changed the license. Version 2.0 moved to the Business Source License, not open source anymore. The last truly open version was 1.13.1 (December 2020). No more upstream bug fixes, no WebGL2 improvements, no new features. We were stuck on a frozen codebase.

Generating Mapbox GL GL style JSON from Python code instead of editing 3,000-line JSON files by hand. Hierarchical style resolution, a Django-style filter DSL, injection-based layer ordering, and a Go sprite generator called from Python via ctypes.

The problem with style JSON

A Mapbox GL GL style is a single JSON file that describes everything about how a map looks. Background color, road widths at every zoom level, label fonts, icon placement, landcover tints, building extrusion heights. All of it.

iTunes Match worked great for years: you uploaded your library, Apple matched what it could, and you had access to everything from any device. But Apple is clearly moving everyone toward Apple Music, and iTunes Match has been slowly rotting. The writing was on the wall.

I didn’t want to subscribe to Apple Music. I wanted to keep my library, my ratings, my play counts, my playlists, all the metadata accumulated over 20 years. So I built my own streaming setup: a Go backend that serves the library over HTTP, and SwiftUI apps that play it on iOS, macOS, and tvOS.