Coder Social home page Coder Social logo

zitryss / jupyterpads Goto Github PK

View Code? Open in Web Editor NEW
2.0 0.0 0.0 171 KB

PyPads companion extension for JupyterLab

License: BSD 3-Clause "New" or "Revised" License

JavaScript 2.10% Python 8.28% TypeScript 59.22% CSS 0.63% Jupyter Notebook 24.91% Dockerfile 4.86%

jupyterpads's Introduction

JupyterPads

JupyterPads is an extension for the Jupyter Notebook which helps to integrate machine learning pipeline into interactive computing.

Because the data science process is research-oriented, it is usual to have multiple experiments running simultaneously, with many of them never making it to production. This requires a method that keeps track of all the different experiments and hyperparameters that have been attempted. Your data science process will need to support tracking, comparing results from different runs, visualizing, as well as support for moving models that prove to be valid to the next stage of the life cycle. Experiment management in the machine learning field can be a very time-consuming activity for developers. The project’s goal was to create an extension for an interactive notebook that will take care of all the overhead associated with the experiment management and potentially improve human-computer interaction.

1 2

This extension is composed of a Python package named jupyterpads for the server extension and a NPM package named jupyterpads for the frontend extension.

Requirements

  • JupyterLab >= 2.0

Install

Note: You will need NodeJS to install the extension.

pip install jupyterpads
jupyter lab build

Troubleshoot

If you are seeing the frontend extension but it is not working, check that the server extension is enabled:

jupyter serverextension list

If the server extension is installed and enabled but you are not seeing the frontend, check the frontend is installed:

jupyter labextension list

If it is installed, try:

jupyter lab clean
jupyter lab build

Contributing

Install

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
# Move to jupyterpads directory

# Install server extension
pip install -e .
# Register server extension
jupyter serverextension enable --py jupyterpads --sys-prefix

# Install dependencies
jlpm
# Build Typescript source
jlpm build
# Link your development version of the extension with JupyterLab
jupyter labextension install .
# Rebuild Typescript source after making changes
jlpm build
# Rebuild JupyterLab after making any changes
jupyter lab build

You can watch the source directory and run JupyterLab in watch mode to watch for changes in the extension's source and automatically rebuild the extension and application.

# Watch the source directory in another terminal tab
jlpm watch
# Run jupyterlab in watch mode in one terminal tab
jupyter lab --watch

Now every change will be built locally and bundled into JupyterLab. Be sure to refresh your browser page after saving file changes to reload the extension (note: you'll need to wait for webpack to finish, which can take 10s+ at times).

Uninstall

pip uninstall jupyterpads
jupyter labextension uninstall jupyterpads

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.