Pydantic Data Validation

<aside> 📚 📁 Category: Python

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Overview

Pydantic provides data validation and settings management using Python type hints. It's the foundation for FastAPI and enables robust data parsing.

<aside> ℹ️ Why It Matters: Understanding Pydantic Data Validation is essential for building robust, scalable, and secure modern applications.

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Key Concepts

[x] BaseModel - Define data models
[x] Type Validation - Automatic type checking
[x] Field Validators - Custom validation
[x] Nested Models - Complex structures
[x] Config Class - Model configuration
[x] JSON Serialization - To/from JSON
[x] Settings Management - Environment variables
[x] Data Classes - Alternative to dataclasses

Common Use Cases

<aside> 💡 Where to Apply Pydantic Data Validation

                        API request/response validation
                        Configuration management
                        Data parsing and serialization
                        Form validation
                        Database model validation
                        Environment variable parsing

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Best Practices

[x] Use type hints consistently
[x] Define validators for complex logic
[x] Use Field for metadata
[x] Leverage Config for customization