Pydantic

Define a BaseModel for the shape the application expects, then pass incoming data to model_validate(). The official guide shows that models can validate Python objects and JSON, and can be used as a source for JSON Schema. For example, a request model with name: str and age: int makes those fields explicit before the rest of an application uses them. One choice matters at an input boundary: Pydantic attempts type conversion by default, so a value such as a numeric string may become an integer. If the input must already have the declared type, the strict-mode guide explains how to request stricter validation. This distinction helps when validating data from a configuration file or HTTP payload, where permissive conversion may be convenient in one project and undesirable in another. Pydantic is a library used from Python code, not a hosted endpoint that receives data for you. The validation docs site also links to Pydantic AI and Logfire; this entry is for the core validation library and its MIT-licensed repository, not those separate products or their service terms.