Skip to main content

A Python kernel for JupyterLite, powered by Xeus

Project description

jupyterlite-xeus-python

ci-badge docs-badge

The xeus-python Python kernel for JupyterLite running in the browser.

jupyterlite-xeus-python

Install

You can install the kernel with conda/mamba:

mamba install -c conda-forge jupyterlite-xeus-python

Or using pip:

pip install jupyterlite-xeus-python

Then build your JupyterLite site:

jupyter lite build

Pre-installed packages

xeus-python allows you to pre-install packages in the Python runtime. You can pre-install packages by adding an environment.yml file in the JupyterLite build directory, this file will be found automatically by xeus-python which will pre-build the environment when running jupyter lite build.

Furthermore, this automatically installs any labextension that it founds, for example installing ipyleaflet will make ipyleaflet work without the need to manually install the jupyter-leaflet labextension.

Say you want to install NumPy, Matplotlib and ipycanvas, it can be done by creating the environment.yml file with the following content:

name: xeus-python-kernel
channels:
  - https://repo.mamba.pm/emscripten-forge
  - https://repo.mamba.pm/conda-forge
dependencies:
  - numpy
  - matplotlib
  - ipycanvas

Then you only need to build JupyterLite:

jupyter lite build

You can also pick another name for that environment file (e.g. custom.yml), by doing so, you will need to specify that name to xeus-python:

jupyter lite build --XeusPythonEnv.environment_file=custom.yml

Contributing

Development install

Note: You will need NodeJS to build the extension package.

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 jupyterlite_xeus_python directory
# Install package in development mode
python -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 run 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 run 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).

Development uninstall

pip uninstall jupyterlite_xeus_python

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 jupyterlite-xeus-python within that folder.

Packaging the extension

See RELEASE

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

jupyterlite-xeus-python-0.9.2.tar.gz (13.6 MB view details)

Uploaded Source

Built Distribution

jupyterlite_xeus_python-0.9.2-py3-none-any.whl (13.5 MB view details)

Uploaded Python 3

File details

Details for the file jupyterlite-xeus-python-0.9.2.tar.gz.

File metadata

File hashes

Hashes for jupyterlite-xeus-python-0.9.2.tar.gz
Algorithm Hash digest
SHA256 13658c58379fedc05d17127651a81cb6b80252a01e7f897bff078f87f35e13be
MD5 d73035dd8273de381ae8fe707eb29905
BLAKE2b-256 e4860d5b068095b556da4a9997a50daad7b0f95f1b435d75ea57380d54cb4ffd

See more details on using hashes here.

Provenance

File details

Details for the file jupyterlite_xeus_python-0.9.2-py3-none-any.whl.

File metadata

File hashes

Hashes for jupyterlite_xeus_python-0.9.2-py3-none-any.whl
Algorithm Hash digest
SHA256 a58ad762d1bb740a618e1c0f70cbb6617195c5bcd88b95021fe945885d23d3a6
MD5 e6eee8b1004a8509f0319a14a37c1a3f
BLAKE2b-256 808880eb9c9797bcb1f64e922cc8fe5a549acc8b112b69ad9b4e5887e21e1e8c

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page