How would you implement a FastAPI endpoint that uses query parameters for department, min_salary, and sort_by, validated via Pydantic?

FastAPI automatically parses query parameters from the URL and can validate them using Pydantic models. Define a Pydantic model that represents the query parameters: department: str, min_salary: int = Field(..., ge=0), sort_by: str = Field(default='salary'). Then declare the endpoint to accept this model via Depends. FastAPI will instantiate the model, perform validation, and inject the validated data into the path operation. Inside the handler you can use the validated values to filter or sort a database query. Example: from fastapi import FastAPI, Depends; from pydantic import BaseModel, Field; app = FastAPI(); class EmployeeQuery(BaseModel): department: str; min_salary: int = Field(..., ge=0); sort_by: str = Field(default='salary'); @app.get('/employees') async def get_employees(q: EmployeeQuery = Depends()): # use q.department, q.min_salary, q.sort_by to query DB return {'msg': 'ok'} The Pydantic model ensures that min_salary is a non-negative integer and that sort_by defaults to 'salary' if not provided. FastAPI will automatically return a 422 Unprocessable Entity response if validation fails, providing clear error messages. This approach keeps the endpoint logic clean and separates validation concerns from business logic.