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Pydantic
Pydantic is a Python library for data validation, type enforcement, and serialization using standard Python type hints.
It ensures the data coming into your app (like API requests, configs, or ML inputs) is valid, typed, and clean — automatically.
Key Features
Automatic validation: Converts and checks input types (e.g., “5” → int(5)).
BaseModel class: Define data schemas by subclassing BaseModel.
Error messages: Tells you exactly which field is invalid and why.
Data parsing: Converts JSON or dicts into Python objects you can use directly.
Integration with FastAPI: FastAPI uses Pydantic models to validate request bodies and auto-generate documentation.
Why It Matters in MLOps
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Ensures model inputs (e.g., features in an API request) are validated before prediction.
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Prevents serving errors due to missing or wrong data types.
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Makes your FastAPI endpoints self-documenting via OpenAPI and /docs.
Example: Google colab
https://colab.research.google.com/drive/1IkROILidYV8iY9HchMGv2EAqQNK5o8d5?usp=sharing