Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.
The most straightforward avenue for creating a "Hamilton cookbook" would be to support rendering notebooks as pages via a Sphinx plugin. This would make it easier for people to browse examples from the documentation. Instead of supporting interactivity directly from the docs, notebooks can include a link to launch the page in a Google Colab if appropriate.
The most straightforward avenue for creating a "Hamilton cookbook" would be to support rendering notebooks as pages via a Sphinx plugin. This would make it easier for people to browse examples from the documentation. Instead of supporting interactivity directly from the docs, notebooks can include a link to launch the page in a Google Colab if appropriate.
ref: https://docs.readthedocs.io/en/stable/guides/jupyter.html