Create Schema for Validation in FastAPI | Use Pydantic Models for Data Validation

Description

Welcome to this video in the FastAPI Database Tutorial series! In this video, we will learn how to create schemas in FastAPI using Pydantic models to validate and structure our data. Schemas in FastAPI act as blueprints for how data should look when it is sent to or received from the API. They help make sure the data is in the correct format and follows the right rules — for example, checking if a field is required, has the right data type, or meets certain conditions. You will learn how to create separate schemas.py files, define request and response schemas, and understand how they differ from database models. We’ll also discuss how schemas improve data consistency, security, and overall code readability. By the end of this video, you’ll have a strong understanding of how FastAPI uses Pydantic models for validation and how to design schemas that make your APIs more reliable and professional. #FastAPI #FastAPITutorial #FastAPISchema #Pydantic #DataValidation #PythonBackend #FastAPIDatabase #BackendDevelopment #WebDevelopment #LearnFastAPI