Python implementation of the Autoinvent Schema, the metadata that Conveyor and Magql use to describe data models.
The schema describes the models making up an application, and the fields belonging to each model. Each model and field has properties describing where and how it should be queried, displayed, or interacted with.
There are two layers to the schema:
The data layer is the JSON-serializable data that can be sent from one program and loaded by another. This contains all the static values for the schema.
The functional layer can return dynamic values based on the static data and the current state of the application. This allows for complex custom behavior.
Typically, the data layer will be generated automatically with another library. Then, the project will override specific values and methods to describe the behavior they want that couldn’t be automatically detected. For example, Autoinvent-Schema-SQLAlchemy will introspect SQLAlchemy models to create schema models and fields describing SQL tables and columns.