Toronto Addresses Layer

Turns the City of Toronto Address Points dataset (~525,000 addresses) into map-tile layers (interactive vector + labelled raster) that OpenStreetMap mappers can add to the iD and JOSM editors as a reference overlay.

Live layer and how to add it: https://skfd.github.io/toronto-addresses-layer/

This is a thin repo: the whole pipeline is the address-layerist engine. All that lives here is layer.toml (the data source + field map + site settings) and a run.py shim.

Setup

pip install -r requirements.txt          # the engine + its deps

The vector-tile step needs WSL2 + tippecanoe once -- see ../address-layerist/wsl-setup.md.

Usage

addressvault pull toronto --wait   # acquire data into the vault (separate tool; --wait coalesces)
python run.py slim       # slim the latest toronto dump into a GeoJSONL + meta
python run.py vector     # vector (MVT) tiles via WSL tippecanoe
python run.py raster     # labelled raster (PNG) tiles
python run.py site       # render the landing page

python run.py build      # slim + vector + raster + site
python run.py update     # build + publish (the daily entry point)

Build output lands in build/site/; that directory is what gets published to an orphan gh-pages branch (history never grows).

Scheduling (Windows)

Run as Administrator:

.\schedule-add.ps1       # registers a daily task "TorontoAddressLayer" at 14:00
.\schedule-remove.ps1    # unregisters it

The task runs python run.py update. It is set for 14:00 -- about two hours after the sibling toronto-addresses-import task -- so fresh city data is available before tiles are built.

Licence / attribution

Address data is © City of Toronto, published under the Open Government Licence – Toronto. Tiles and the landing page carry that attribution.