Skip to main content

JupyterLab as a Digital Audio Workstation

Project description

logo

JupyterLab-DAW

Github Actions Status

Audio and music in JupyterLab.

This JupyterLab extension provides features that should be familiar to those who are working with Digital Audio Workstations (DAWs) for editing and producing audio.

All audio processing is done entirely in the front-end (browser) with the help of the Tone.js library. Interaction from within Python notebooks is possible via ipytone.

Note: this is very much work in progress (nothing much to see yet)!

Requirements

  • JupyterLab >= 3.0

Install

To install the extension, execute:

pip install jupyterlab_daw

Uninstall

To remove the extension, execute:

pip uninstall jupyterlab_daw

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_daw 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_daw

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-daw 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_daw-0.2.1.tar.gz (314.9 kB view details)

Uploaded Source

Built Distribution

jupyterlab_daw-0.2.1-py3-none-any.whl (98.5 kB view details)

Uploaded Python 3

File details

Details for the file jupyterlab_daw-0.2.1.tar.gz.

File metadata

  • Download URL: jupyterlab_daw-0.2.1.tar.gz
  • Upload date:
  • Size: 314.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.0

File hashes

Hashes for jupyterlab_daw-0.2.1.tar.gz
Algorithm Hash digest
SHA256 755d1ddb29b4577b4e5650638563d00125f09f76ad26b1828d0be0af291a9e08
MD5 6f4c43c377a142393c8492e88c89ecea
BLAKE2b-256 4311edc4d71d8b6ff7d0ad7c42b96216ce62c2eebe4e4602d5b7c47d43bd71b7

See more details on using hashes here.

Provenance

File details

Details for the file jupyterlab_daw-0.2.1-py3-none-any.whl.

File metadata

File hashes

Hashes for jupyterlab_daw-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 71eacc6cec76eb0cd8f39edb6c3350b63d6f37d46d8ddcb1d64e6d6f7f36d953
MD5 5767e7e67b795eda71d0ac9519e2da9e
BLAKE2b-256 57013bdec12497c70b13f243a51c600ab2cf916bb4ea7e07bfb0ac3261060ceb

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