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A skeleton repository for tutorials infrastructure
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scientific-python/executable-tutorials
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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
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 using
pytest
, both locally and on CI.
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
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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