ml_prov

JupyterLab extension for visual hyperparamter tuning.

🚀 Try it out on Binder:

This extension is composed of a Python package named ml_prov for the server extension and a NPM package named ml-prov for the frontend extension.

This extension was created with the TypeScript cookiecutter based on the official extension tutorial.

Requirements

• JupyterLab >= 3.0

You can also use the environment.yml file with conda. The nbclassic version is pinned there due to version conflicts.

Install

Install JupyterLab if you haven't already.

To install the extension, execute: 🟥 not yet available, please refer to the Development Install section below.

pip install ml_prov

Uninstall

To remove the extension, execute:

pip uninstall ml_prov

Troubleshoot

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

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 ml_prov 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 ml_prov
# 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).

By default, the jlpm run 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

# Server extension must be manually disabled in develop mode
jupyter server extension disable ml_prov
pip uninstall ml_prov

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 ml-prov within that folder.

Publish

1. Make code changes
2. Update version in package.json
3. Make sure to npm login
4. Build the extension: jlpm run build:prod
5. Verify files to be published npm pack --dry-run
6. Publish npm publish