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Unlock the full power of Python data validation with Pydantic — the library trusted by FastAPI, SQLModel, and modern Python projects worldwide.

Whether you’re building APIs, cleaning messy datasets, managing environment configurations, or structuring ML workflows, this book gives you the practical skills and deep understanding to write safer, cleaner, and more reliable Python code.

Inside, you’ll discover:

Foundations of Pydantic and runtime data validation.
Advanced techniques: custom validators, nested models, and performance tuning.
Real-world projects: integrating APIs, ETL pipelines, and environment settings.
A thorough comparison of alternatives like Marshmallow, attrs, dataclasses, TypedDict, and more.
Expert guidance on choosing the right tool for your project.
Full Source Code repository for the examples and solutions for the exercises.

Packed with examples, exercises, and actionable advice, this ebook is perfect for Python developers, data engineers, FastAPI users, and anyone who wants to level up their code quality.

Stop guessing whether your data is safe — trust Pydantic, and write Python code with confidence.

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