Skip to main content

Slippy-map tile geometry: WKB decoding, zoom bands, and MVT encoding in application code (no PostGIS)

Project description

3tears-geo

Slippy-map tile geometry for the 3tears platform: WKB decoding, zoom bands, and MVT encoding — all in application code.

Why this exists in Python rather than in SQL

Every off-the-shelf tile server (Martin, pg_tileserv, Tegola) assumes PostGIS in the database and calls ST_AsMVT. YugabyteDB ships no postgis extension — verified empirically against yugabytedb/yugabyte:2025.2.1.0-b141, where CREATE EXTENSION postgis fails outright with no control file on the image. There is therefore no ST_Intersects, no ST_Simplify, and no ST_AsMVT to call.

So this package does that work: shapely for the geometry, and mapbox-vector-tile for the encoding. The relevant prior art is Tippecanoe and supercluster, not the Postgres tile servers.

The tiling scheme, stated explicitly

Leaving this implicit guarantees a defect, because the two common conventions differ only in the direction of one axis:

  • Web Mercator (EPSG:3857)
  • XYZ orientationy increases southward from the top-left origin. OpenStreetMap / MapLibre / Google. Not TMS, whose y increases northward.
  • Source coordinates are WGS84 (EPSG:4326), projected at build time.
  • MVT geometry uses tile-local integer coordinates over a 4096-unit extent, the format default, not varied per layer.

Latitude clamps to ±85.0511287798066°, the bound of the Mercator square.

Public surface

Imported via from threetears.geo import …:

  • tilesTileId, BoundingBox, tile_for_point, tile_bounds, bounds_to_tile_range, TILE_EXTENT, MAX_MERCATOR_LATITUDE.
  • attributescoerce_attribute, coerce_attributes, validate_attribute_value, UnsupportedAttributeError.
  • geometrydecode_geometry, geometry_bounds, point_geometry.
  • bandsfeature_band, aggregate_band, FeatureSpec, AggregateSpec, TileFeature, simplification_tolerance.
  • mvtencode_tile, project_to_tile.
  • featuresFeatureCache (per-pod source cache + R-Tree).
  • collectionTileCollection, LayerDefinition, ViewportRequest.

Zoom bands: aggregate below, features above

Low zoom is not simplified high zoom. A z4 tile spans a large fraction of a country; rendering it by simplifying and dropping individual features leaves an arbitrary sample of whichever survived. A national view showing 4,000 of 180,000 precincts is not a coarse view of the data — it is a different and misleading dataset.

So each layer declares a crossover. Below it, rows roll up to a coarser declared geography and each bucket becomes one feature carrying real totals. Above it, individual features are simplified per zoom and capped in count. bl-ds-ai-lcv-registration reached the same split independently: its precomputed z4–z10 band holds cluster aggregates, with individual features only from z11.

The cap is a hard limit, not advice. An uncapped tile in a dense metro reaches tens of megabytes, which exceeds the NATS payload ceiling, defeats the L2 hot band, and renders badly. When it binds, features drop by a declared ranking column so the survivors are the important ones, and the result records that it was truncated — a silently capped tile reads as "this is all the data there is".

Feature ids are not MVT ids

MVT feature ids are uint64 by specification. A census geoid or a UUID is silently coerced to 0 by the encoder — no error — which would collapse every feature in a tile onto one id and break any client-side join. So only genuine integers reach the wire-level id; everything else travels as a property, which is exactly what MapLibre's promoteId is for. The id is always present as a property either way, so a client has one place to look.

The R-Tree earns its place via chunk coverage

FeatureCache indexes cached source features in a SQLite R-Tree (built in, unlike SpatiaLite) on the same connection pool as its own managed table, as a BaseCollection subclass rather than a bespoke SQLiteBackend wrapper.

An index alone cannot answer "which features are in this rectangle": it can say what a pod holds, never whether it holds all of them, and a tile built from a partial set is wrong rather than slow — then cached as immutable. So the cache tracks coverage by chunk: it loads the coarse tile containing a request and records that chunk as covered. A run of neighbouring tiles, which overlap almost entirely in source features, then pays one L3 read between them instead of one each.

Attribute coercion is fixed, not per-caller

MVT carries only strings, numbers and booleans, so every other SQL type needs a declared mapping. Two cases are quietly lossy if chosen badly:

SQL MVT Note
integer / numeric / double number doubles are IEEE754
text / varchar string
boolean bool checked before int, since bool subclasses it
NULL key omitted MVT has no null
timestamp / date string ISO-8601 UTC; naive stamps read as UTC
JSONB / array / bytes rejected project a scalar column instead

Omitting the key for NULL is the only faithful encoding, and it puts a real obligation on the client: a style expression reading that attribute must supply its own fallback. The upside is that "no data" and "a genuine zero" stay distinguishable in the tile — which matters most on a choropleth, where collapsing them shades unmeasured regions as though they were measured.

Versioning policy

3tears-geo versions in lockstep with the rest of the 3tears monorepo: every package shares one version, tracking the framework git tag. All packages move together.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

3tears_geo-0.19.3.tar.gz (42.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

3tears_geo-0.19.3-py3-none-any.whl (29.4 kB view details)

Uploaded Python 3

File details

Details for the file 3tears_geo-0.19.3.tar.gz.

File metadata

  • Download URL: 3tears_geo-0.19.3.tar.gz
  • Upload date:
  • Size: 42.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.14

File hashes

Hashes for 3tears_geo-0.19.3.tar.gz
Algorithm Hash digest
SHA256 13adeb70f0634da3a9896a625039752bd8cf5d9023e4a58c6471698366a832a1
MD5 8b21e04f1dbf50b27da5dc9f5320402c
BLAKE2b-256 3d1f4c2010da8a267bb94bc05e949b6ed0e1a96892e0bdb9f520abec930442fc

See more details on using hashes here.

Provenance

The following attestation bundles were made for 3tears_geo-0.19.3.tar.gz:

Publisher: release.yml on pacepace/3tears

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file 3tears_geo-0.19.3-py3-none-any.whl.

File metadata

  • Download URL: 3tears_geo-0.19.3-py3-none-any.whl
  • Upload date:
  • Size: 29.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.14

File hashes

Hashes for 3tears_geo-0.19.3-py3-none-any.whl
Algorithm Hash digest
SHA256 33d80875bfafa9c64ef2c561887faec5469a5296d2b9e2d00f77c2b1fb46ca2e
MD5 b5425b6887a10bb163a31246ff7e8eea
BLAKE2b-256 231e010363ac1d81c4232efc594ad92b0644660ec69b2172e94a7d4a2c470669

See more details on using hashes here.

Provenance

The following attestation bundles were made for 3tears_geo-0.19.3-py3-none-any.whl:

Publisher: release.yml on pacepace/3tears

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page