A Jupyter / Openlayers bridge enabling interactive maps in the Jupyter notebook.
This GIF demonstrates how to add Raster Tile layers to the map and control the zoom functionality.
This GIF shows how to add Vector Tile layers to the map and modify their style.
This image illustrates how to add a GeoJSON layer to the map.
For a real-world example of how to use ipyopenlayers
, check out this electricity dashboard project.
This project showcases the integration of ipyopenlayers
in an electricity dashboard application, demonstrating a use case of the library.
You can install using pip
:
pip install ipyopenlayers
If you are using Jupyter Notebook 5.2 or earlier, you may also need to enable the nbextension:
jupyter nbextension enable --py [--sys-prefix|--user|--system] ipyopenlayers
Create a dev environment:
conda create -n ipyopenlayers-dev -c conda-forge nodejs python jupyterlab=4.0.11
conda activate ipyopenlayers-dev
Install the python. This will also build the TS package.
pip install -e ".[test, examples]"
When developing your extensions, you need to manually enable your extensions with the notebook / lab frontend. For lab, this is done by the command:
jupyter labextension develop --overwrite .
jlpm run build
For classic notebook, you need to run:
jupyter nbextension install --sys-prefix --symlink --overwrite --py ipyopenlayers
jupyter nbextension enable --sys-prefix --py ipyopenlayers
Note that the --symlink
flag doesn't work on Windows, so you will here have to run
the install
command every time that you rebuild your extension. For certain installations
you might also need another flag instead of --sys-prefix
, but we won't cover the meaning
of those flags here.
If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the widget.
# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm run watch
# Run JupyterLab in another terminal
jupyter lab
After a change wait for the build to finish and then refresh your browser and the changes should take effect.
If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.
To get started with using ipyopenlayers
, check out the full documentation
https://ipyopenlayers.readthedocs.io/
You can try ipyopenlayers below, or open many other live examples in a new browser tab with JupyterLite.
To update the version, install tbump and use it to bump the version. By default it will also create a tag.
pip install tbump
tbump <new-version>