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Pydantic

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May 1, 2024 2 minute read

Understanding Pydantic

Pydantic is a Python library that simplifies data validation and modeling. It enables the creation of type-annotated Python classes that enforce data integrity and ensure that data conforms to predefined schemas. By leveraging Pydantic, developers can build robust and reliable applications with reduced errors and increased code maintainability.

Benefits of Using Pydantic

Using Pydantic comes with several advantages:

Path to Pydantic

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We've curated five courses to help you on your path to Pydantic. Use these to develop your skills, build background knowledge, and put what you learn to practice.

Sorted from most relevant to least relevant:

Learning Pydantic: Advanced Data Validation In Python

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FastAPI for Busy Software Engineers

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Try FastAPI Test Driven Development 2024

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Complete OpenAI API Masterclass for Beginners using Python

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Mastering REST APIs with FastAPI

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Reading list

We've selected four books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Pydantic.

Test-Driven Development with Python

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Combines Pydantic with test-driven development techniques. It covers writing tests for Pydantic models, using mocks and fixtures, and ensuring the reliability of Pydantic-based applications. It good choice for those interested in building robust and testable code with Pydantic.

Architecture Patterns with Python: Enabling Test...

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Test-Driven Development with Python: Obey the...

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(Deutsch) Architekturpatterns mit Python: Test-Driven...

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Implementing QuantLib. Quantitative Finance in C++:...

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Covers a wider range of data validation techniques in Python, including using Pydantic. It discusses best practices, common pitfalls, and advanced techniques for data validation. It good choice for those interested in a comprehensive understanding of data validation beyond Pydantic.

Implementing QuantLib: Quantitative finance in C++:...

Paperback

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