Pydantic: Data Validation the Right Way
Every non-trivial Python program has a boundary where untrusted data enters: an API request body, a config file, an environment variable, a row from a CSV. The naive approach is to trust the shape of that data and let KeyError or TypeError surface deep inside your business logic when it doesn’t match. Pydantic moves that failure to the boundary, where it belongs, and gives you a typed, validated object instead of a bag of dicts and hope. ...