Push spatial data from Python directly into a live QGIS session
Project description
qgis-bridge
Push spatial data from Python directly into a live QGIS session — no file exports, no manual imports, no QGIS-specific knowledge required.
Overview
qgis-bridge eliminates the friction of moving data between Python analysis environments and QGIS for visualization. Run your spatial analysis in a Jupyter notebook or Python script, then send results to QGIS with a single function call.
Usage
Standalone function:
from qgis_bridge import to_qgis
to_qgis(gdf, layer_name="Risk Zones", color_by="risk_score")
GeoDataFrame accessor:
import qgis_bridge # registers the .qgis accessor on GeoDataFrame
gdf.qgis.send(layer_name="Risk Zones", color_by="risk_score")
Cloud raster URIs (streamed directly, no local download):
to_qgis("gs://my-bucket/elevation.tif", layer_name="Elevation")
to_qgis("s3://my-bucket/imagery.tif", layer_name="Imagery")
to_qgis("az://my-container/dem.tif", layer_name="DEM")
Supported Data Types
- Vector: GeoDataFrame with a CRS set
- Raster: Cloud GeoTIFFs via GCS (
gs://), S3 (s3://), or Azure Blob (az://)
Design
- Zero QGIS installation required in the Python environment
- Communicates with an already-running QGIS instance
- No authentication surface — credential resolution handled by QGIS/GDAL
- Works in Jupyter, JupyterLab, VS Code, and plain Python scripts
Installation
pip install qgis-bridge
The QGIS plugin must also be installed separately inside QGIS (Plugins > Install from Zip), using the qgis_plugin/ directory from this repository.
Contributing
This project uses uv for development.
# Install uv (if not already installed)
brew install uv # macOS
pip install uv # any platform
# Clone and set up
git clone https://github.com/R-Repo/qgis-bridge
cd qgis-bridge
uv sync --group dev # creates .venv and installs all dependencies
# Run tests (no QGIS required)
uv run pytest tests/
Status
Early development. API subject to change.
License
MIT
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