iPython is an interactive python shell. It was renamed to Jupyter.
“Turn a GitHub repo into a collection of interactive notebooks Have a repository full of Jupyter notebooks? With Binder, you can add a badge that opens those notebooks in an executable environment, making your code immediately reproducible by anyone, anywhere.”
- npsphinx - Jupyter Notebook Tools for Sphinx
nbsphinx is a Sphinx extension that provides a source parser for
*.ipynbfiles. Custom Sphinx directives are used to show Jupyter Notebook code cells (and of course their results) in both HTML and LaTeX output. Un-evaluated notebooks – i.e. notebooks without stored output cells – will be automatically executed during the Sphinx build process.
- The magic notebook for exploring data / Observable
“Observable is the magic notebook for exploring data and thinking with code.”
- Live code
- Code that runs automatically for instant feedback.
- Effortlessly add interaction and animation thanks to dataflow.
- All your favorite libraries and web technologies at your fingertips.
- Wikipedia scraping functions (IMO, this is a case for how not to use ipython notebooks)
- Some early experience in teaching using ipython notebook
- Pronto Cycle Share data analysis by Jake Vanderplas. He also has a number of tutorials, talks etc., on ipython and datascience on his github.
- Peter Norvig’s notebooks
- ipython uses pandoc to export the notebooks to latex, rst, html etc.,
See also: Python, Python 3