Master FastAPI Interview Preparation

Preparing for a FastAPI interview, backend development assessment, or Python API engineering role? This course is designed to help you strengthen your FastAPI knowledge, identify skill gaps, and prepare with confidence for technical interviews.

FastAPI is a modern Python framework designed for building high-performance, scalable, and production-ready APIs. To work effectively with FastAPI, developers need more than basic Python knowledge. Modern API development requires an understanding of async programming, dependency injection, data validation, authentication, databases, testing, deployment, API documentation, error handling, and software architecture.

This course provides structured practice across these areas, helping you review both fundamental and advanced FastAPI concepts used in real-world backend development.

The course covers important areas of FastAPI development, including:

FastAPI fundamentals
API endpoint design
Path operations
Request and response handling
Dependency injection
Data validation
Pydantic models
Async/await programming
Concurrency and asynchronous endpoints
API performance optimization
Authentication and authorization
Password hashing
CORS and security headers
Database integration
Database connection pooling
SQLAlchemy and ORM concepts
Database modeling
Data serialization
Unit and integration testing
Docker containerization
CI/CD pipelines
FastAPI deployment strategies
Automatic API documentation
OpenAPI schema generation
Exception and error handling
Logging strategies
API error responses
Code organization
API architecture
Design patterns
Backend coding standards and best practices

Sample Practice Question

Question: What is the main benefit of using async and await in FastAPI endpoints?

A. They allow asynchronous operations to be handled efficiently without blocking the event loop

B. They automatically make every CPU-intensive operation run on multiple processors

C. They eliminate the need for database connections

D. They automatically convert synchronous Python code into machine code

Correct Answer: A. They allow asynchronous operations to be handled efficiently without blocking the event loop

Detailed Explanation

Option A — Correct

FastAPI supports Python's asynchronous programming model, allowing developers to use async and await for operations that spend time waiting, such as database queries, network requests, file operations, and calls to external services.

For example:

@app.get("/users")

async def get_users():

users = await fetch_users()

return users

While an asynchronous operation is waiting to complete, the event loop can work on other tasks instead of unnecessarily blocking the application.

This can be particularly useful for I/O-bound applications and high-concurrency APIs, where many requests may be waiting for external resources at the same time.

Option B — Incorrect

Using async and await does not automatically make CPU-intensive work run across multiple processors.

CPU-bound workloads may require other approaches, such as multiprocessing, worker processes, or specialized background processing strategies.

Asynchronous programming is primarily useful for efficiently handling I/O-bound operations.

Option C — Incorrect

Async programming does not eliminate the need for database connections. FastAPI applications can still connect to databases and use connection pools, ORMs, or database drivers.

Async database libraries can help applications handle database I/O efficiently, but a database connection is still required when the application needs to access a database.

Option D — Incorrect

async and await are language features used to define and coordinate asynchronous operations. They do not convert Python code into machine code.

Python execution and compilation involve different mechanisms, while asynchronous programming concerns how tasks are scheduled and executed.

You'll review concepts related to:

FastAPI API development
REST API design
Python asynchronous programming
Performance and concurrency
Dependency injection
Pydantic and data validation
Authentication and API security
SQLAlchemy and database integration
Testing and deployment
Docker and CI/CD
OpenAPI and automatic documentation
Error handling and logging
Backend architecture and design patterns
Production API development best practices

Strengthen your FastAPI skills, understand modern backend development practices, and prepare with confidence for your next technical interview.