Skip to main content

Easy access to global administrative boundaries and geometries via Overture Maps data

Project description

wkls: Well-Known Locations

License: Apache 2.0

wkls makes it easy to find global administrative boundaries — from countries to cities — using readable, chainable Python syntax.

It reads Overture Maps Foundation GeoParquet data (version 2025-09-24.0) directly from the AWS Open Data Registry.

It reads directly from GeoParquet data (version 2025-09-24.0) hosted on the AWS Open Data Registry.

You can instantly get geometries in formats like Well-known Text (WKT), Well-known Binaries (WKB), HexWKB, GeoJSON, and SVG:

import wkls

# prints "MULTIPOLYGON (((-122.9915659 37.7672733...)))"
print(wkls.us.ca.sanfrancisco.wkt())

#prints "2025-09-24.0"
print(wkls.overture_version())

Installation

pip install wkls

This command alsoloads DuckDB with its related spatial extension.

Quick Start

After installing wkls, run the following commands to get started:

import wkls

# Get country geometry
usa_wkt = wkls.us.wkt()
print(f"USA geometry: {usa_wkt[:50]}...")

# Get state/region geometry  
california_geojson = wkls.us.ca.geojson()

# Get city geometry
sf_svg = wkls.us.ca.sanfrancisco.svg()

# Check dataset version
print(f"Using Overture Maps data: {wkls.overture_version()}")

# Explore available data
print(f"Countries: {len(wkls.countries())}")
print(f"US regions: {len(wkls.us.regions())}")
print(f"CA counties: {len(wkls.us.ca.counties())}")

Usage

Accessing geometry

wkls supports up to 3 chained attributes:

  1. Country (required) – must be a 2-letter ISO 3166-1 alpha-2 code (e.g. us, de, fr)
  2. Region (optional) – must be a valid region ISO code suffix (e.g. ca for US-CA, ny for US-NY)
  3. Place (optional) – a name match against subtypes: county, locality, or neighborhood

Examples:

wkls.us.wkt()                          # country: United States
wkls.us.ca.wkt()                       # region: California
wkls.us.ca.sanfrancisco.wkt()          # city/county: San Francisco
wkls["us"]["ca"]["sanfrancisco"].wkt() # dictionary-style access

Supported formats

wkls supports the following formats:

  • .wkt() – Well-Known Text
  • .wkb() – Raw binary WKB
  • .hexwkb() – Hex-encoded WKB
  • .geojson() – GeoJSON string
  • .svg() – SVG path string

Example: Find the administrative boundary of San Francisco, California

Chained expressions like wkls.us.ca.sanfrancisco return a WKL object. Internally, this holds a Pandas DataFrame containing one or more rows that match the given chain.

        id           country    region   subtype       name           division_id
0  085718963fffff...   US       US-CA    county    San Francisco  085718963fffff...

In most cases, wkls resolves to a single administrative boundary. But if there are name collisions (e.g., both a county and a locality called “San Francisco”), multiple rows may be returned.

By default, geometry methods like .wkt() will use the first matching row.

Helper methods

The following methods return Pandas DataFrames for easy exploration:

Method Description
wkls.countries() List all countries
wkls.us.regions() List regions in the US
wkls.us.ca.counties() List counties in California
wkls.us.ca.cities() List cities in California
wkls.subtypes() Show all distinct division subtypes

Dataset information

You can check which version of the Overture Maps dataset is being used:

print(wkls.overture_version())  
> "2025-09-24.0"

Note: The overture_version() method is only available at the root level, not on chained objects like wkls.us.overture_version().

How It Works

wkls works in two stages:

1. In-memory GERS ID resolution

Your chained attributes — up to 3 levels — are parsed in this order:

  1. country → matched by ISO 2-letter code (e.g. "us")
  2. region → matched using region ISO code suffix (e.g. "ca""US-CA")
  3. place → fuzzy-matched against names in subtypes: county, locality, or neighborhood

This resolves to a Pandas DataFrame containing one or more rows from the in-memory wkls metadata table. At this stage, no geometry is loaded yet — only metadata (like id, name, region, subtype, etc.).

2. Geometry lookup using DuckDB

The geometry lookup is triggered only when you call one of the geometry methods:

  • .wkt()
  • .wkb()
  • .hexwkb()
  • .geojson()
  • .svg()

At that point, wkls uses the previously resolved GERS ID to query the Overture division_area GeoParquet directly from S3.

The current Overture Maps dataset version can be checked with wkls.overture_version().

Contributing

We welcome contributions! Please see our Contributing Guide for details on how to get started, development setup, and submission guidelines.

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Acknowledgments

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

wkls-0.4.3.tar.gz (15.5 MB view details)

Uploaded Source

Built Distribution

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

wkls-0.4.3-py3-none-any.whl (15.4 MB view details)

Uploaded Python 3

File details

Details for the file wkls-0.4.3.tar.gz.

File metadata

  • Download URL: wkls-0.4.3.tar.gz
  • Upload date:
  • Size: 15.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for wkls-0.4.3.tar.gz
Algorithm Hash digest
SHA256 94f19d7edc8a55088569668ca7ec6054616026da33b90264bf06fbeee0fd23ba
MD5 5beefa71bd52ecb6299ab2b745be2950
BLAKE2b-256 e149a35d5d787a067956bb742a705445c9c2749498bca83892481af122eb14a9

See more details on using hashes here.

Provenance

The following attestation bundles were made for wkls-0.4.3.tar.gz:

Publisher: pypi-publish.yaml on wherobots/wkls

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

File details

Details for the file wkls-0.4.3-py3-none-any.whl.

File metadata

  • Download URL: wkls-0.4.3-py3-none-any.whl
  • Upload date:
  • Size: 15.4 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for wkls-0.4.3-py3-none-any.whl
Algorithm Hash digest
SHA256 93f78a8368c0a85b55e1445bed533ed3ce8edf6dcf8abaf4623d76411509d13c
MD5 afdaec20ce541f789a20112b9632f0ad
BLAKE2b-256 d4fc4b903762ba245aba1b377273cb409e1ec619086e181bee4d59fd641411cd

See more details on using hashes here.

Provenance

The following attestation bundles were made for wkls-0.4.3-py3-none-any.whl:

Publisher: pypi-publish.yaml on wherobots/wkls

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