Advanced Field Validation in FastAPI 5.8 | How to Use @field_validator

Take your FastAPI APIs to the next level by mastering custom data validation! This video dives deep into Pydantic’s powerful @field_validator decorator, showing you how to run code before or after Pydantic’s built-in checks—and how to use root validators for multi-field validation. 👀 What You'll Learn: Why and when to use custom validators for model fields in FastAPI The difference between mode="before" (for preprocessing raw input) and mode="after" (for post-validation business rules) Real-world examples and code walkthroughs ✅ Validator Modes Explained: Before: Transform or check raw input before parsing—great for things like converting strings to integers. python @field_validator('number', mode='before') def coerce_str_to_int(cls, value): ... After: Apply checks after parsing—ideal for business logic, such as range checks on typed values. python @field_validator('number', mode='after') def check_number_positive(cls, value): ... 🔄 Multiple Validators & Root Validators: Layer multiple validators for a single field (with both before/after). Use @root_validator to enforce logic spanning multiple fields of the model. python @root_validator def content_contains_title(cls, values): ... 🚦 See in Action: How automatic errors are triggered (with helpful, precise messages!) How to handle deeply nested or multi-field validation effortlessly Perfect for: API developers who want more control over data integrity Building forms and endpoints with complex logic (think: required patterns, cross-field checks, etc.) Anyone switching from Django/Flask who’s curious about Pydantic’s advanced features Code samples included + live API demos Subscribe for more FastAPI, Pydantic, and Python backend tutorials! #FastAPI #Pydantic #Python #APIDevelopment #Validation #RootValidator #FieldValidator #WebDev