Tips for using Jupyter Notebooks with GitHub

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

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  • patagonia

  • After creating the "patagonia" Github repository for all the quants at Patagonia Capital, our next task is to setup the patagonia environment.

  • nbstripout

    strip output from Jupyter and IPython notebooks

  • If you'd like to automatically remove empty / tagged cells or retroactively apply this filter to your git history, you can read the nbstripout documentation on GitHub.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • papermill

    📚 Parameterize, execute, and analyze notebooks

  • Papermill can also target cloud storage outputs for hosting rendered notebooks, execute notebooks from custom Python code, and even be used within distributed data pipelines like Dagster (see Dagstermill). For more information, see the papermill documentation.

  • Puts Debuggerer

    Ruby library for improved puts debugging, automatically displaying bonus useful information such as source line number and source code.

  • Version control tools like git are powerful collaboration tools that track changes to source code and synchronize local and remote copies of a shared codebase. They allow developers to work together on the same codebase and seamlessly merge their improvements together. These tools also work out of the box with services like GitHub, which provide hosting for the shared codebase. Unfortunately, most of the user experience of using git and GitHub has been designed around text-based source code, but Jupyter notebooks are saved with embedded output media in a JSON format within .ipynb files.

  • dagster

    An orchestration platform for the development, production, and observation of data assets.

  • Papermill can also target cloud storage outputs for hosting rendered notebooks, execute notebooks from custom Python code, and even be used within distributed data pipelines like Dagster (see Dagstermill). For more information, see the papermill documentation.

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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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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