12.1 Description

In Chapter 8, Project 2.5: Schema and Metadata, we used Pydantic to generate a schema for the analysis data model. This schema provides a formal, language-independent definition of the available data. This can then be shared widely to describe the data and resolve questions or ambiguities about the data, the processing provenance, the meaning of coded values, internal relationships, and other topics.

This specification for the schema can be extended to create a complete specification for a RESTful API that provides the data that meets the schema. The purpose of this API is to allow multiple users — via the requests module — to query the API for the analytical data as well as the results of the analysis. This can help users to avoid working with out-of-date data. An organization creates large JupyterLab servers to facilitate doing analysis processing on machines far larger than an ordinary laptop.

Further, an API provides a handy wrapper around the...