Three Tools for Executing Jupyter Notebooks

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  1. ploomber

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

    NBClient supports running notebooks via CLI for the most basic use cases. However, for more sophisticated execution options, consider the Ploomber!

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  3. papermill

    📚 Parameterize, execute, and analyze notebooks

    Papermill Documentation

  4. projects

    Sample projects using Ploomber. (by ploomber)

    Ploomber is the complete solution for notebook execution. It builds on top of papermill and extends it to allow writing multi-stage workflows where each task is a notebook. Meanwhile, it automatically manages orchestration. Hence you can run notebooks in parallel without having to write extra code.

  5. nbclient

    A client library for executing notebooks. Formally nbconvert's ExecutePreprocessor

    NBClient Source Code

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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