To install Python, I recommend pyenv. After installing pyenv, install a Python version with e.g.:
pyenv install 3.11.4
then set that as your global Python version with
pyenv global 3.11.4
This project uses Poetry to manage Python dependencies.
After installing Poetry, run
poetry install
to install all dependencies.
To register the current Poetry-managed Python environment with JupyterLab, run
poetry run python -m ipykernel install --user --name "lonboard"
JupyterLab is an included dev dependency, so to start JupyterLab you can run
ANYWIDGET_HMR=1 poetry run jupyter lab
Then you should see a tile on the home screen that lets you open a Jupyter Notebook in the lonboard
environment. You should also be able to open up an example notebook from the examples/
folder.
Requirements:
Install module dependencies:
npm install
We use ESBuild to bundle into an ES Module, which the Jupyter Widget will then load at runtime. The configuration for ESBuild can be found in build.mjs
. To start watching for changes in the /src
folder and automatically generate a new build, use:
npm run build:watch
All models on the TypeScript side are combined into a single entry point, which is compiled by ESBuild and loaded by the Python Map
class. (Refer to the _esm
key on the Map
class, which tells Jupyter/ipywidgets where to load the JavaScript bundle.)
Anywidget and its dependency ipywidgets handles the serialization from Python into JS, automatically keeping each side in sync.
Push a new tag to the main branch of the format v*
. A new version will be published to PyPI automatically.
The documentation website is generated with mkdocs
and mkdocs-material
. After poetry install
, you can serve the docs website locally with
poetry run mkdocs serve
Publishing documentation happens automatically via CI when a new tag is published of the format v*
. It can also be triggered manually through the Github Actions dashboard on this page. Note that publishing docs manually is not advised if there have been new code additions since the last release as the new functionality will be associated in the documentation with the tag of the previous release. In this case, prefer publishing a new patch or minor release, which will publish both a new Python package and the new documentation for it.