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JupyterLab Logtalk CodeMirror Extension

A JupyterLab extension providing a Logtalk CodeMirror mode based on A JupyterLab extension providing a Prolog CodeMirror and extension-cookiecutter-ts.

Also see the Jupyter kernel for Logtalk.

Requirements

Contributing

Development install

Notes:

The jlpm command is JupyterLab's pinned version of yarn that is installed with JupyterLab. You may use yarn or npm in lieu of jlpm below.

# Clone the repo to your local environment
# Change directory to the jupyterlab_logtalk_codemirror_extension directory
# Install package in development mode
python3 -m pip install -e .
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Rebuild extension Typescript source after making changes
jlpm build

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 extension.

# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm watch
# Run JupyterLab in another terminal
jupyter lab

With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).

By default, the jlpm build command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:

jupyter lab build --minimize=False

Development uninstall

python3 -m pip uninstall jupyterlab_logtalk_codemirror_extension

In development mode, you will also need to remove the symlink created by jupyter labextension develop command. To find its location, you can run jupyter labextension list to figure out where the labextensions folder is located. Then you can remove the symlink named jupyterlab_logtalk_codemirror_extension within that folder.

Upload to PyPI

This extension is available as a Python package on the Python Package Index. A new version of the package can be published in the following way:

  1. Install the requirements build and twine: python3 -m pip install --upgrade build twine
  2. Increase the version in package.json
  3. Create the distribution files: python3 -m build
  4. Upload the package to PyPI: twine upload dist/*

For further information, see the Packaging Python Projects Tutorial.