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A skeleton repository for tutorials infrastructure

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scientific-python/executable-tutorials

Use Cases

Many organizations maintain collections of tutorials addressing realisticproblems in a science domain, with runnable code examples written andkept current by experts in the tools. They are useful as:

  • A trove of working snippets to copy and paste
  • A maintained resource for self-guided learning
  • A ready-to-use curriculum for hands-on workshops
  • A suite of science domain-specific "integration tests" for the showcased libraries

Key Features

This repository demonstrates one way to configure a collection of tutorials,covering some core features:

  • Source is inMyST Markdown which is easy for humans to edit and review.
  • The executed examples—code and results—are published as astatic site.
  • The examples can be opened as Jupyter notebooks to run and edit:
    • In a user's local environment
    • In the cloud usingBinder
    • (Experimental) In the user's browser via aJupyter Lite app
  • The examples can be tested usingpytest, both locally and on CI.

Try It Out

  • Read thepublished examples.

  • Open it onBinder to run the examples in the cloud.

  • Download and run the examples locally.

    git clone https://github.com/scientific-python/executable-tutorials

    For users ofpixi:

    pixi run start

    Alternatively, install the requirements with pip and start JupyterLab.

    pip install -r requirements.txtjupyter lab

Make Your Own

See theGuide for Maintainers to create your own collection of tutorials.

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A skeleton repository for tutorials infrastructure

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