wof-explorer 0.5.0a1

WhosOnFirst geographic data explorer with cursor-based navigation and hierarchical queries

WOF Explorer

A Python library for exploring WhosOnFirst geographic data with cursor-based navigation and hierarchical queries.

Features

• Cursor-based navigation for memory-efficient exploration of large datasets
• Hierarchical traversal (country → region → city → neighborhood)
• Spatial queries with bounding box support
• Multiple export formats: GeoJSON, CSV, WKT
• Async-first API with clean, intuitive interface

Installation

pip install wof-explorer

For development:

git clone https://github.com/dugspi/wof-explorer.git
cd wof-explorer
pip install -e ".[dev]"

CLI Tool

The package includes a command-line tool for downloading WhosOnFirst databases:

# Download US and Canada databases (downloads, extracts, and merges automatically)
wof-explore download us,ca

# Download multiple countries
wof-explore download us ca mx gb

# Specify output directory
wof-explore download us,ca -o ./data

# Keep individual database files after merge
wof-explore download us,ca --keep

# List available country codes
wof-explore countries

# Validate installation
wof-explore validate

The downloader fetches compressed databases from geocode.earth, extracts them, and merges multiple countries into a single whosonfirst-combined.db file.

Quick Start

import asyncio
from wof_explorer import WOFConnector, WOFSearchFilters, PlaceCollection

async def main():
    connector = WOFConnector('whosonfirst-data-admin-us-latest.db')
    await connector.connect()

    # Search for neighborhoods in Chicago
    cursor = await connector.search(
        WOFSearchFilters(
            placetype="neighbourhood",
            ancestor_name="Chicago",
            is_current=True
        )
    )

    # Fetch results with geometry
    places = await cursor.fetch_all(include_geometry=True)
    print(f"Found {len(places)} neighborhoods")

    # Export to GeoJSON
    collection = PlaceCollection(places=places)
    geojson = collection.to_geojson_string()

    await connector.disconnect()

asyncio.run(main())

Database Setup

WOF Explorer works with WhosOnFirst SQLite databases. Download one to get started:

# US administrative data (~1.5GB)
curl -O https://data.whosonfirst.org/sqlite/whosonfirst-data-admin-us-latest.db

# Or choose a smaller region
curl -O https://data.whosonfirst.org/sqlite/whosonfirst-data-admin-ca-latest.db  # Canada
curl -O https://data.whosonfirst.org/sqlite/whosonfirst-data-admin-gb-latest.db  # Great Britain

See data.whosonfirst.org/sqlite for all available databases.

Core Concepts

Two-Phase Exploration

WOF Explorer uses a two-phase pattern optimized for large datasets:

Phase 1: Navigate (lightweight)

# Search returns a cursor with minimal data loaded
cursor = await connector.search(WOFSearchFilters(placetype="locality"))
print(f"Found {cursor.total_count} cities")

# Iterate without loading geometry
for place in cursor.places:
    print(f"{place.name} ({place.id})")

Phase 2: Fetch (selective)

# Only fetch full details for what you need
places = await cursor.fetch_all(include_geometry=True)

Hierarchical Navigation

from wof_explorer import WOFConnector, WOFSearchFilters, WOFHierarchyCursor

async def explore_hierarchy():
    connector = WOFConnector('database.db')
    await connector.connect()

    # Find San Francisco
    cursor = await connector.search(WOFSearchFilters(name="San Francisco"))
    sf = cursor.places[0]

    # Navigate the hierarchy
    hierarchy = WOFHierarchyCursor(sf, connector)

    # Get ancestors (city → county → state → country)
    ancestors = await hierarchy.fetch_ancestors()

    # Get descendants (neighborhoods within SF)
    neighborhoods = await hierarchy.fetch_descendants(
        filters=WOFSearchFilters(placetype="neighbourhood")
    )

    await connector.disconnect()

Spatial Queries

from wof_explorer.models import BBox

# Search within a bounding box
bbox = BBox(min_lat=37.7, max_lat=37.8, min_lon=-122.5, max_lon=-122.4)
cursor = await connector.search(
    WOFSearchFilters(placetype="locality", bbox=bbox)
)

Export Formats

collection = PlaceCollection(places=places)

# GeoJSON (for mapping tools)
geojson = collection.to_geojson_string()

# CSV (for spreadsheets)
csv_data = collection.to_csv_string()

# WKT (for GIS software)
wkt_data = collection.to_wkt_string()

API Reference

Core Classes

Class	Description
WOFConnector	Database connection and query interface
WOFSearchFilters	Query builder for search operations
PlaceCollection	Container for batch operations and export
WOFSearchCursor	Iterate search results efficiently
WOFHierarchyCursor	Navigate geographic hierarchies
WOFBatchCursor	Process multiple places by ID

Search Filters

WOFSearchFilters(
    name="Chicago",              # Exact name match
    name_contains="New",         # Partial name match
    placetype="locality",        # Place type filter
    placetype=["locality", "neighbourhood"],  # Multiple types (OR)
    ancestor_name="California",  # Within ancestor hierarchy
    country="US",                # Country code
    is_current=True,             # Only current records
    bbox=BBox(...),              # Bounding box
    limit=100                    # Result limit
)

Examples

See the examples/ directory:

• basic_usage.py - Getting started
• hierarchical_search.py - Navigate hierarchies
• spatial_queries.py - Bounding box searches
• batch_processing.py - Handle large datasets

Requirements

• Python 3.9+
• SQLite database with WhosOnFirst data

License

MIT License - see LICENSE for details.

Links

• WhosOnFirst - The underlying geographic data project
• WhosOnFirst Data - Download databases
• GitHub Issues - Report bugs or request features