Pydantic is a data validation library built around declarative model classes that define the expected structure, types, and constraints of data, distinguishing it from plain data-holding structures (like Python's built-in dataclasses) by adding runtime validation, type coercion, and sanitization. Its validation model operates at two levels: field-level validators that check and normalize individual attributes against domain-specific rules, and model-level (root) validators that enforce constraints spanning multiple fields or the record as a whole, either before or after the raw data is coerced into typed values. This belongs to the broader discipline of data modeling and input validation in software engineering, where the goal is to guarantee that external, untrusted, or loosely structured data (e.g., from JSON) conforms to a well-defined schema before it is used in a program.
Pydantic is a data validation library built around declarative model classes that define the expected structure, types, and constraints of data, distinguishing it from plain data-holding structures (…