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

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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!

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

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

Profiles the data, validates the schema and runs data quality checks and produces a report

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.

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

Jupyter Notebook Remote Scheduler for Argo on Kubernetes

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

A simple template for using MLflow from Papermill

Neural style transfer bot for Telegram implemented with Ray Serve, Papermill and AIOGram

Store,Version and Run jupyter notebook via ReST api

Collection of benchmarking code for cta