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opengeos/leafmap
A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment
leafmap is a Python wrapper that unifies ipyleaflet, folium, MapLibre, kepler.gl, and several other mapping backends behind a single API, so you can swap renderers without rewriting your map code. It targets GIS analysts and data scientists working in Jupyter who want interactive maps without wrestling with each backend's quirks. WhiteboxTools integration gives it 500+ geospatial analysis tools accessible from the same interface.
The pluggable backend design is genuinely useful — switching between ipyleaflet and folium is a one-liner, which matters when you're deciding between notebook interactivity and static HTML export. Cloud-Optimized GeoTIFF and STAC support is first-class, not bolted on; loading a COG from S3 works with one call. The MapLibre integration (added relatively recently) unlocks 3D terrain, PMTiles, and GPU-accelerated rendering that ipyleaflet can't touch. Documentation is unusually thorough for an academic-adjacent project — 100+ runnable notebooks covering real workflows, not toy examples.
The abstraction leaks constantly: once you need anything non-trivial, you're reaching into the underlying backend's API anyway, at which point the wrapper adds indirection without value. Dependency footprint is enormous — installing leafmap pulls in folium, ipyleaflet, whiteboxtools, and optional extras that each carry their own transitive deps; environment conflicts in conda are a regular community complaint. The WhiteboxTools GUI is a separate widget that only works in classic Jupyter Notebook, not JupyterLab or VS Code notebooks, which is where most people actually work now. Performance with large vector datasets is limited by the browser-side rendering of ipyleaflet; there's no server-side tile generation built in, so anything over ~50k features needs a workaround.