Schema [OSS]
Pydantic Validation
Maps the way
Data validation for Python:
- Most widely used data validation library for Python
- Enforces standard type annotation
- Plays nicely with type checkers, IDEs and your brain
- Fast and extensible
The Pydantic platform gives devs visibility to stay in flow, from local to prod, from AI to API.
Ship robust apps faster, in Python, TypeScript, Rust and others.
Schema [OSS]
Pydantic Validation
Maps the way
Data validation for Python:
Agents [OSS]
Pydantic AI
Speeds the way
Agent framework / LLM library for Python:
Observability [OSS + SAAS]
Pydantic Logfire
Lights the way
OpenTelemetry traces, logs and metrics:
Pydantic Validation is used and trusted by millions of individual developers - and some of the biggest organizations in the world, too.
We use Pydantic across key parts of our research and products, and it has accelerated our work considerably.
Pydantic is incredibly powerful and a must use tool for AI engineers.
We use Pydantic across key parts of our research and products, and it has accelerated our work considerably.
Integrations that run on the Datadog Agent use Pydantic models that are generated from an OpenAPI spec to validate configuration which has drastically reduced customer confusion and support cases that we have to triage.
If you're not using Python yet, you should. If you're not using Pydantic yet with Python, you should. Pydantic is the data backbone of FastAPI, but even if you don't use FastAPI, Pydantic is extremely useful. There's always data, and handling data with Pydantic is several times more efficient and safer than without it and much more enjoyable.