Skip to main content

Automatically insert docstring templates in JupyterLab notebooks.

Project description

jupyterlab_autodocstring

Github Actions Status Binder

Automatically insert docstring template after writing function header. After writing a function header, type the triple quotes (autocomplete will make it 6) and hit tab.

Requirements

  • JupyterLab >= 4.0.0

Install

To install the extension, execute:

pip install jupyterlab_autodocstring

Uninstall

To remove the extension, execute:

pip uninstall jupyterlab_autodocstring

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 jupyterlab_autodocstring directory
# Install package in development mode
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

pip uninstall jupyterlab_autodocstring

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_autodocstring within that folder.

Testing the extension

Frontend tests

This extension is using Jest for JavaScript code testing.

To execute them, execute:

jlpm
jlpm test

Integration tests

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.

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

jupyterlab_autodocstring-0.1.0.tar.gz (34.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

jupyterlab_autodocstring-0.1.0-py3-none-any.whl (40.7 kB view details)

Uploaded Python 3

File details

Details for the file jupyterlab_autodocstring-0.1.0.tar.gz.

File metadata

  • Download URL: jupyterlab_autodocstring-0.1.0.tar.gz
  • Upload date:
  • Size: 34.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.2

File hashes

Hashes for jupyterlab_autodocstring-0.1.0.tar.gz
Algorithm Hash digest
SHA256 3aadcf081634552e2b7ab09fddda531f72f672aa04a60a5dcffc72b1e3713b13
MD5 e716ee464ef21c5f121881a6fd328257
BLAKE2b-256 85f9096f4e79ab0563aa5fa26da9a2ba2261c594a49db4aeb7730d65ca3442c6

See more details on using hashes here.

File details

Details for the file jupyterlab_autodocstring-0.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for jupyterlab_autodocstring-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 236b964405a11654790ee57c3067530e3e3b7ad552f547a29ad661ba94476229
MD5 01bf82ad73a714c464b0d0d33ceb3b45
BLAKE2b-256 4068cf3afe9d5b5b4acf8d102e664cfca239d7c34254cfdca58f3825cd480c1c

See more details on using hashes here.

Supported by

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