# FastAPI - Data APIs (Data Engineering)

> Routes, Pydantic models, dependencies, middleware, OpenAPI documentation, deployment

- 20 interview questions
- Mid-Level
- [Interview Questions: Data Engineering](https://sharpskill.dev/en/technologies/data-engineering/interview-questions.md)

## 1. What is FastAPI?

**Answer**

FastAPI is a modern, high-performance Python web framework for building APIs. It uses standard Python type hints for automatic data validation and documentation generation. FastAPI is built on Starlette for web functionality and Pydantic for data validation, offering performance comparable to Node.js and Go.

## 2. Which decorator should be used to define a GET route in FastAPI?

**Answer**

FastAPI uses HTTP method decorators directly on the application instance. The @app.get("/path") decorator defines a GET route. Each HTTP method has its corresponding decorator: @app.post(), @app.put(), @app.delete(), etc. This syntax is inspired by Flask but with automatic validation added.

## 3. What is the role of Pydantic in FastAPI?

**Answer**

Pydantic is the data validation library used by FastAPI. It allows defining data models with Python types and automatically validates incoming data. Pydantic also generates the JSON schema for OpenAPI documentation and provides detailed error messages when data is invalid.

## 17 more questions available

- How to define a path parameter in a FastAPI route?
- How does FastAPI distinguish a query parameter from a path parameter?

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