The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️

A library for recording and reading data in notebooks.

A web frontend for scheduling Jupyter notebook reports

📝 Pytest plugin for testing notebooks

Cell-by-cell testing for production Jupyter notebooks in JupyterLab

A toolbox 🧰 for Jupyter notebooks 📙: testing, experiment tracking, debugging, profiling, and more!

Python library to run ML/data pipelines on stateless compute infrastructure (that may be ephemeral or serverless). Please see the documentation site with more details and demo:

Microservice to generate Jupyter reports combining papermill and nbconvert.

Jupyter Notebook Remote Scheduler for Argo on Kubernetes

Example project with a CNN to train a Pokémon type classifier.

Store,Version and Run jupyter notebook via ReST api

Run and publish parameterised Jupyter notebooks using Faculty platform

A papermill engine and CLI tool that posts success/failure of notebook execution to Slack.

pre-commit hooks for papermill (https://github.com/nteract/papermill)

Example MLOps/ML-training pipeline running with no cloud infrastructure except a public personal (free) Github acount.

A Flask Server to run and store notebooks asynchronously using huey workers.

Integrate Papermill (IPython/Jupyter notebook API) with Sopel (IRC bot) to run your notebooks from IRC