📚 Parameterize, execute, and analyze notebooks

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

A site that displays up to date COVID-19 stats, powered by fastpages.

A library for recording and reading data in notebooks.

A web frontend for scheduling Jupyter notebook reports

📝 Pytest plugin for testing notebooks

🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.

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

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

Full-stack asset management for Ruby on Rails. With Paperclip, SWFUpload, jQuery, jgrow, Jcrop and Facebox.

Material for the Jupytext+Papermill blog post

Tools for developing pluvial (excess rainfall) and fluvial scenarios for probabilistic flood risk analyses

A simple script to help schedule Jupyter Notebook execution and storing of the results using Papermill

Learn to run & execute Jupyter Notebooks as a REST API in this series.

Parametrize and run scripts as notebooks with jupytext and papermill

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:

Papermill is a sinatra front-end designed to query and analyze a Bunyan/MongoDB capped collection.

Microservice to generate Jupyter reports combining papermill and nbconvert.

ETL to scrape a real estate website, process house prices and data, and build an ML model of the house prices.

R bindings for papermill

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Jupyter Notebook Remote Scheduler for Argo on Kubernetes

Colab,  MLflow and papermill are individually great. Together they form a dream team.

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

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A papermill engine for running Noteable notebooks

papermill. write once, publish everywhere

Run notebooks on a k8s cluster via pygeoapi

A simple template for using MLflow from Papermill

Batch executor of sos notebooks