Runtime Type Validation with Pydantic¶

Pydantic is a framework for executing runtime type validation - e.g., for validating data sent to an API against a pre-defined data model.

This demo shows how Pydantic can be used to validate a config file (written in YAML), against a pre-defined schema.

Demo Objectives¶

Define a data model.
Use the data model to validate config loaded from a YAML file.
Show the difference between validating data in a dict and as part of data model instatiation.
Demonstrate how validation errors can be handled and reported to Users.

This demo is contained in a single Python module, load_config.py, that can be run using,

$ python -m load_config