Build Python GraphQL APIs with FastAPI and Strawberry

The Modern Stack for Productivity and Performance

Photo by Isaac Smith on Unsplash

While REST dominated the API landscape for years, development headaches constantly surfaced around performance, documentation and strongly typed interfaces for robust frontends to consume.

Thankfully, GraphQL emerged solving many frequent pain points through self-documenting schema designs, flexible nested queries and runtime performance gains.

For Python coders, integrating these modern capabilities frequently posed configuration and boilerplate burdens. But with the intuitive templating of FastAPI and schema declarations from Strawberry, even newcomer backends engineers can craft production-ready GraphQL services rapidly.

In this tutorial, you’ll learn:

• Core GraphQL strengths and how it improves over REST
• Defining Strawberry schema building blocks
• Constructing interactive GraphQL APIs with FastAPI
• Optimizing through DataLoader, gevent and asyncio
• Deployment options for production needs

Let’s explore how Python again leads in innovative developer experiences!

Upgrading from REST to GraphQL APIs