Loading...
The Mapbox API provides mapping and location-based services for developers to integrate customizable maps, geocoding, routing and navigation features into their applications.
Engineers use the Mapbox Python SDK or direct `requests` calls to the REST APIs for geocoding, directions, and static map image generation. Geocoding results are joined with business datasets in pandas, while routing data feeds into OR-Tools optimization models.
Mapbox APIs power location-aware AI agents that reason about physical space. Expose the Geocoding and Directions APIs as MCP tools so LLM agents can plan routes, estimate travel times, and answer geographic questions. The Isochrone API helps AI systems reason about accessibility and coverage areas.
# pip install requests
import requests
resp = requests.get(
"https://api.mapbox.com/geocoding/v5/mapbox.places/San%20Francisco.json",
params={"access_token": "YOUR_ACCESS_TOKEN"}
)
coords = resp.json()["features"][0]["center"]
print("lon:", coords[0], "lat:", coords[1])Official dataset source
More datasets used by Python data engineers.
A suite of APIs covering Maps, Places, Geocoding, Distance Matrix, and Directions from Google. Used in data engineering for geocoding address data, calculating logistics routes, enriching datasets with place attributes, and building geospatial pipelines using the googlemaps Python client.
Access current weather conditions, hourly and 16-day forecasts, historical weather data, and air pollution metrics for any location on Earth. Widely used in Python data engineering pipelines for enriching datasets with weather context, building weather dashboards, and integrating climate signals into machine learning features via the pyowm library.
Access open-source global map data including roads, buildings, points of interest, land use, and administrative boundaries from OpenStreetMap. Used in geospatial data engineering pipelines for routing analysis, map enrichment, address geocoding, and building location-aware datasets with Python using the OSMnx library.