Python Client

Overture's Python client provides a command-line interface and a Python library for downloading data within a bounding box and converting it to common geospatial file formats. It reads directly from Overture's cloud-hosted GeoParquet and uses the STAC catalog to target the latest release automatically.

Installation

pip install overturemaps

The package is also available on conda-forge:

conda install -c conda-forge overturemaps

If you have uv installed, you can run overturemaps with uvx without installing it:

uvx overturemaps download --bbox=-71.068,42.353,-71.058,42.363 -f geojson --type=building -o boston.geojson

Usage

download

The overturemaps download command downloads Overture data with an optional bounding box into the specified file format. When a bounding box is specified, only the minimum data is transferred. Results are streamed, so arbitrarily large areas work.

overturemaps download \
  --bbox=-71.068,42.353,-71.058,42.363 \
  -f geojson \
  --type=building \
  -o boston_buildings.geojson

Options:

Flag	Description
--bbox	West, south, east, north coordinates. Omit to download the entire type.
-f	Output format: geojson, geojsonseq, or geoparquet
--type/-t	Feature type to download, e.g. building, place, segment, address. Run overturemaps download --help for the complete list.
--output/-o	Output file path. Omit to write to stdout.
--stac/--no-stac	Use Overture's STAC catalog to speed up queries (default: on).

tip

Use this bounding box tool to find coordinates for your area of interest. Choose CSV format and copy the value directly into the --bbox field.

gers

The overturemaps gers command looks up a GERS ID in the registry. If the feature is present in the latest release, it downloads the feature and writes it in the specified format.

overturemaps gers d4e59dbf-fda4-47eb-bf05-f7576f17e2c1 -f geojson -o feature.geojson

Options:

Flag	Description
-f	Output format: geojson, geojsonseq, or geoparquet. Defaults to geojsonseq.
--output/-o	Output file path. Omit to write to stdout.

Next steps

• Visualize the data in QGIS or kepler.gl
• Make an interactive map
• Explore the schema reference