Official Python command-line tool of the Overture Maps Foundation
Overture Maps provides free and open geospatial map data, from many different sources and normalized to a common schema. This tool helps to download Overture data within a region of interest and converts it to a few different file formats. For more information about accessing Overture Maps data, see our official documentation site https://docs.overturemaps.org.
Note: This repository and project are experimental. Things are likely change including the user interface until a stable release, but we will keep the documentation here up-to-date.
Download the building footprints for the specific bounding box as GeoJSON and save to a file named "boston.geojson"
overturemaps download --bbox=-71.068,42.353,-71.058,42.363 -f geojson --type=building -o boston.geojsonDownload Overture Maps data with an optional bounding box into the specified file format. When specifying a bounding box, only the minimum data is transferred. The result is streamed out and can handle arbitrarily large bounding boxes.
Command-line options:
--bbox(optional): west, south, east, north longitude and latitude coordinates. When omitted the entire dataset for the specified type will be downloaded-f(required: one of "geojson", "geojsonseq", "geoparquet"): output format--output/-o(optional): Location of output file. When omitted output will be written to stdout.--type/-t(required): The Overture map data type to be downloaded. Examples of types arebuildingfor building footprints,placefor POI places data, etc. Runoverturemaps download --helpfor the complete list of allowed types--connect_timeout(optional): Socket connection timeout, in seconds. If omitted, the AWS SDK default value is used (typically 1 second).--request_timeout(optional): Socket read timeouts on Windows and macOS, in seconds. If omitted, the AWS SDK default value is used (typically 3 seconds). This option is ignored on non-Windows, non-macOS systems.--stac/--no-stac(optional): By default, the reader uses Overture's STAC catalog to speed up queries to the latest release. If the--no-stacflag is present, the CLI will use the S3 path for the latest release directly.
This downloads data directly from Overture's S3 bucket without interacting with any other servers. By including bounding box extents on each row in the Overture distribution, the underlying Parquet readers use the Parquet summary statistics to download the minimum amount of data necessary to extract data from the desired region.
To help find bounding boxes of interest, we like this bounding box tool
from Klokantech. Choose the CSV format and copy the value directly into
the --bbox field here.
Look up an ID in the GERS Registry. If the feature is present in the latest release, it will download the feature and write it out in the specified format.
Command-line options:
-f("geojson", "geojsonseq", "geoparquet"): output format, defaults to geojsonseq for a single feature on one line.--output/-o(optional): Location of output file. When omitted output will be written to stdout.--connect_timeout(optional): Socket connection timeout, in seconds. If omitted, the AWS SDK default value is used (typically 1 second).--request_timeout(optional): Socket read timeouts on Windows and macOS, in seconds. If omitted, the AWS SDK default value is used (typically 3 seconds). This option is ignored on non-Windows, non-macOS systems.
overturemaps is also a Python library. Import directly from overturemaps to query Overture data
without using the CLI.
record_batch_reader returns a pyarrow.RecordBatchReader — a streaming cursor over the data.
This is the lowest-level entry point and works with any Arrow-compatible tool.
from overturemaps import record_batch_reader
bbox = (-71.068, 42.353, -71.058, 42.363) # xmin, ymin, xmax, ymax
reader = record_batch_reader("building", bbox=bbox)
if reader is not None:
table = reader.read_all()
print(table.schema)geodataframe loads data directly into a geopandas.GeoDataFrame. Requires geopandas to be
installed (pip install overturemaps[geopandas] or pip install geopandas).
from overturemaps import geodataframe
bbox = (-71.068, 42.353, -71.058, 42.363)
gdf = geodataframe("building", bbox=bbox)
print(gdf.head())Use get_writer and copy from overturemaps.writers to write data to GeoJSON, GeoJSONSeq, or
GeoParquet without the CLI:
from overturemaps import record_batch_reader
from overturemaps.writers import copy, get_writer
bbox = (-71.068, 42.353, -71.058, 42.363)
reader = record_batch_reader("building", bbox=bbox)
with get_writer("geojson", "boston.geojson", schema=reader.schema) as writer:
copy(reader, writer)Supported format strings: "geojson", "geojsonseq", "geoparquet".
overturemaps is available via Homebrew:
brew install overturemapsTo install overturemaps from PyPi using pip:
pip install overturemapsoverturemaps is also on conda-forge and can be installed using conda, mamba, or pixi. To install overturemaps using conda:
conda install -c conda-forge overturemapsIf 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.parquetBenchmarks using synthetic data on Apple M-series hardware:
| Output format | Geometry | Rows | Time |
|---|---|---|---|
| GeoJSON | Points | 10 000 | 31 ms |
| GeoJSON | Polygons | 10 000 | 44 ms |
| GeoParquet | — | — | network/disk bound |
To run the benchmarks locally:
uv sync --group dev
pytest benchmarks/ -vuv sync
uv run pytest tests/