Including API documentation in docs built with Jupyter Book
The title is chock full of jargon. Let me break it down. API stands for Application Programming Interface. An API is the user-facing part of a software package. For example, if you use the "numpy" package, "numpy.array" is an API. And APIs need to be documented. A single API can produce different results depending on the inputs so documenting the full capabilities of an API is important. Jupyter Book is a new tool in the Scientific Python community to create and upload documentation easily. The community as a whole seems to be working towards better documenting their projects and some have chosen to go with Jupyter Book instead of relying on Sphinx. I personally don't know why the community felt the need to move away from vanilla rst ( reStructureText ) and Sphinx . One of the advantages of Sphinx is the fact that API documentation for the package can be created automatically (using sphinx-apidoc ) and the API docs can be included in the user-facing documentati