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GeoLibre in Jupyter: the full GeoLibre GIS app as an anywidget, with a leafmap-style Python API.

Project description

geolibre

GeoLibre in Jupyter: the full GeoLibre GIS app as an anywidget, with a leafmap-style Python API.

The widget embeds the complete GeoLibre app (menus, panels, processing tools) inside a notebook cell. State syncs both ways through a single .geolibre.json project, so data you add from Python appears in the UI, and edits you make in the UI are readable back from Python.

Install

pip install geolibre

Quickstart

from geolibre import Map

m = Map(center=(-100, 40), zoom=4)
m.add_geojson("https://example.com/data.geojson", name="Data")
m

Add more data and drive the view:

m.add_tile_layer(
    "https://tile.openstreetmap.org/{z}/{x}/{y}.png",
    name="OpenStreetMap",
    attribution="(c) OpenStreetMap contributors",
)
m.add_cog("https://example.com/dem.tif", name="DEM", colormap="terrain")
m.add_basemap("dark")
m.set_center(-120, 47, zoom=8)

Round-trip the project:

m.save_project("my-map.geolibre.json")

m2 = Map()
m2.load_project("my-map.geolibre.json")

# Read state edited in the UI (e.g. after panning/zooming):
m.to_project()["mapView"]["center"]

API

Method Description
Map(center, zoom, basemap=, height=, layout=, theme=) Create a map. layout is "embed", "full", or "maponly".
add_geojson(data, name=, **style) Add GeoJSON (dict, path, URL, JSON, or GeoDataFrame).
add_tile_layer(url, name=, tile_size=, attribution=) Add a raster XYZ tile layer.
add_cog(url, name=, bands=, colormap=, rescale=) Add a Cloud Optimized GeoTIFF.
add_basemap(basemap) Set the background basemap.
set_center(lng, lat, zoom=None) Center (and optionally zoom) the map.
set_center_zoom(lng, lat, zoom=None) Alias of set_center (leafmap compatibility).
remove_layer(layer_id) / clear_layers() Remove layers.
to_project() / load_project(src) / save_project(path) Project I/O.

Notes

  • The bundled app is served from a localhost HTTP server, so the interactive widget works in local Jupyter and VS Code directly. Google Colab routes through its built-in port proxy automatically. JupyterHub routes through jupyter-server-proxy automatically (install it with pip install "geolibre[hub]"). On other remote servers (Binder, remote JupyterLab), pass Map(server_proxy=True) (also needs jupyter-server-proxy); Map(server_proxy=False) forces the direct path.
  • Optional extras: pip install geolibre[all] adds GeoPandas/Shapely support for add_geojson(geodataframe).
  • add_geojson inlines file/URL data into the project (up to 50 MB), so a large dataset is held in memory and re-synced on every project update. For very large layers, prefer a tile or COG source (add_tile_layer/add_cog) the app fetches directly.

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