freestiler for Python
freestiler builds PMTiles vector tile archives from GeoPandas data,
GeoParquet files, and DuckDB spatial queries using a Rust tiling engine.
Features:
- MapLibre Tiles (
mlt) and Mapbox Vector Tiles (mvt) - Multi-layer tilesets
- Point clustering
- Feature coalescing
- Exponential feature dropping for low zoom levels
Why this package exists
- Python-native API backed by the same Rust tiler as the R package
- PMTiles output instead of tile directory trees
- Direct DuckDB SQL tiling
- Streaming point tiling for large DuckDB query results
Installation
Install from PyPI:
pip install freestiler
Published PyPI wheels ship the native feature set for Python 3.9 through 3.14:
- GeoPandas input
- Multi-layer tiling and feature management
- Direct GeoParquet file input
- DuckDB-backed file input
- DuckDB SQL query support
If a wheel is not available for your platform, pip will build from source and
requires a Rust toolchain.
Quick Start
import geopandas as gpd
from freestiler import freestile
gdf = gpd.read_file("counties.shp")
freestile(gdf, "counties.pmtiles", layer_name="counties")
That example is intentionally small. The more interesting path is tiling directly from DuckDB:
from freestiler import freestile_query
freestile_query(
query="SELECT * FROM read_parquet('blocks.parquet') WHERE state = 'NC'",
output="nc_blocks.pmtiles",
layer_name="blocks",
)
For very large point tables, use streaming="always" and prefer
tile_format="mvt" for maximum viewer compatibility.
Hexagonal binning
freestile_h3() aggregates points into H3 hexagons at zoom-appropriate
resolutions, writing a multi-layer archive where low zooms show coarse
hexagons, intermediate zooms show finer ones, and base_zoom and above show
the raw points. It needs the H3 extra (pip install 'freestiler[h3]') for
DuckDB and the DuckDB H3 community extension.
from freestiler import freestile_h3
freestile_h3(
points,
"wind.pmtiles",
agg={"n": "COUNT(*)", "avg_mw": "AVG(capacity_mw)"},
min_zoom=2, max_zoom=12, base_zoom=10,
)
agg also accepts (fn, column) tuples (e.g. {"n": ("count", "*")}) if you
would rather not write SQL.
For a categorical, hex-only archive alongside existing point tiles:
freestile_h3(
"SELECT ST_Point(lon, lat) AS geom, group_id FROM read_parquet('dots/*.parquet')",
"groups.pmtiles", include_points=False,
category="group_id", category_values=list(range(1, 9)),
source_crs="EPSG:4326", min_zoom=3, max_zoom=11,
h3_resolutions=[4, 4, 5, 5, 6, 6, 7, 7, 8], fade=True,
)
The output includes point_count, category counts (group_id:1, etc., plus
group_id:_other for null/unlisted values), modal_category, modal_count,
modal_share, and modal_tie. Ties have no selected category. This avoids a
raw-point GeoDataFrame, but all resulting hex layers still reside in memory;
it is not bounded polygon streaming.
Performance note:
freestile(gdf, ...)is convenient for GeoDataFrames that already fit comfortably in memory.- For larger datasets,
freestile_file()andfreestile_query()are usually faster because they avoid a heavier GeoPandas-to-Rust handoff. - If your GeoDataFrame still needs
to_crs(4326)before tiling, that reprojection step can dominate startup time on large layers.
Source Builds
Published wheels include GeoParquet and DuckDB support by default. To build from a local checkout:
git clone https://github.com/walkerke/freestiler.git
cd freestiler/python
python3 -m venv .venv
source .venv/bin/activate
pip install maturin
python3 -m maturin develop --release
To build an installable wheel instead of using an editable install:
python3 -m maturin build --release --out dist
pip install dist/freestiler-*.whl
Links
1 maintainer
Metadata
1 maintainer
Release files for freestiler 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| freestiler-0.3.0.tar.gz | 819.8 kB | Details |
Built distributions (wheels)
Total release size: 278.0 MB
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Transparency logRelease files / freestiler-0.3.0-cp39-cp39-macosx_11_0_arm64.whl
| Download URL | freestiler-0.3.0-cp39-cp39-macosx_11_0_arm64.whl |
|---|---|
| Size | 14.6 MB |
| Tags | CPython 3.9 macOS 11.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
ea56296dd986f270f6dcf57e54727d423b137c1579cb694c865a715cc0722a89
|
|
BLAKE2b-256 checksum How to use checksums |
1c6f4bafac4c343f4c00ffdebe81bbd46ae51eb97defbff314e63b219f5f72db
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 2, 2026.
Transparency log
