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Python Pydantic Tutorial: Complete Data Validation Course (Used by FastAPI)

81.7K views on YouTube

In this video, we’ll be learning how to use Pydantic, Python’s most popular data validation library. Pydantic uses type hints to validate data at runtime, ensuring that the data coming into your application meets your expectations. We’ll cover everything from basic model creation and field validation to custom validators, type coercion, nested models, and model configurations. We’ll also see why Pydantic is so widely used in libraries like FastAPI, data processing pipelines, and AI tools. If you’ve ever struggled with messy manual validation code or data that isn’t the right type or format, Pydantic will make your life much easier. Let’s get started…

The code from this video can be found here:
https://gist.github.com/26fbfae9fb2ad293cc431530e8932855

Type Hinting tutorial – https://youtu.be/RwH2UzC2rIo
UV tutorial – https://youtu.be/AMdG7IjgSPM
Mutable Default Arguments video: https://youtu.be/_JGmemuINww
Regular Expressions tutorial: https://youtu.be/K8L6KVGG-7o
Python Object-Oriented playlist: https://www.youtube.com/playlist?list=PL-osiE80TeTsqhIuOqKhwlXsIBIdSeYtc

Pydantic documentation: https://docs.pydantic.dev/
Pydantic types reference: https://docs.pydantic.dev/latest/api/types/
More Pydantic types: https://docs.pydantic.dev/latest/api/networks/

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