This project has successfully verified the use of Jupyter backend for code execution and file writing solution, looking forward to the final implementation on jupyverse
Thanks @matthewwiese !
Jupyter extension for http cell execute
This extension is composed of a Python package named jupyter_kernel_executor
for the server extension and a NPM package named jupyter_kernel_executor
for the frontend extension.(NPM package is not ready yet)
- JupyterLab >= 3.0
To install the extension, execute:
pip install jupyter_kernel_executor
In Linux systems, it is common to use ext
or similar file systems, and through the ino
attributes provided by such
file systems, we can track the movement of files.
If your system meets these requirements, it is recommended that you also install jupyter_server_fileid and configure it according to this document
pip install jupyter_kernel_executor[fileid]
To remove the extension, execute:
pip uninstall jupyter_kernel_executor
If you are seeing the frontend extension, but it is not working, check that the server extension is enabled:
jupyter server extension list
If the server extension is installed and enabled, but you are not seeing the frontend extension, check the frontend extension is installed:
jupyter labextension list
API docs in OpenAPI3, using Swagger Editor can view it online
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 jupyter_kernel_executor directory
# Install package in development mode
pip install -e .
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Server extension must be manually installed in develop mode
jupyter server extension enable jupyter_kernel_executor
# 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
# Server extension must be manually disabled in develop mode
jupyter server extension disable jupyter_kernel_executor
pip uninstall jupyter_kernel_executor
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 jupyter_kernel_executor
within that folder.
This extension is using Pytest for Python code testing.
Install test dependencies (needed only once):
pip install -e ".[test]"
To execute them, run:
pytest -vv -r ap --cov jupyter_kernel_executor
This extension is using Jest for JavaScript code testing.
To execute them, execute:
jlpm
jlpm test
This extension uses Playwright for the integration tests (aka user level tests). More precisely, the JupyterLab helper Galata is used to handle testing the extension in JupyterLab.
More information are provided within the ui-tests README.
See RELEASE