GraphQL with Python: From First Query to Production
GraphQL gives clients the power to request exactly the data they need in a single round trip -- no over-fetching, no chaining three REST endpoints together. In the Python ecosystem, Strawberry GraphQL has emerged as the modern standard, replacing the older Graphene library with a type-hint-driven approach that feels native to Python. Strawberry generates your entire schema from plain Python classes, so your IDE autocomplete, your type checker, and your GraphQL schema all stay in sync.
This guide is organized as a learning path. Start with the fundamentals of what GraphQL is and how it works in Python, then move into building a real API with Strawberry. From there, tackle the performance challenges that surface at scale: the N+1 query problem, DataLoader batching, pagination patterns, and persisted queries for caching and security. Each article includes working code you can run.
Getting Started
2 articlesGraphQL in Python: What It Is, How It Works, and When to Use It
Understand what GraphQL is, how it compares to REST, and why Python developers are adopting it. Covers schemas, queries, mutations, and when GraphQL is the right choice for your project.
Building a GraphQL API with Strawberry in Python
Build a working GraphQL API from scratch using Strawberry. Define types with Python dataclasses, write resolvers, set up queries and mutations, and serve it all through FastAPI.
Data Loading and Performance
3 articlesThe GraphQL N+1 Problem: Why It Happens and How to Fix It
Learn why nested GraphQL resolvers trigger redundant database queries, how the N+1 problem quietly destroys API performance, and the strategies that eliminate it.
DataLoaders in Python GraphQL: Solving the N+1 Problem
Implement DataLoaders in your Python GraphQL API to batch and deduplicate database queries. Walk through the loader pattern, integration with Strawberry, and real performance benchmarks.
Python DataLoader for GraphQL: Batching and Caching Explained
Go deeper into DataLoader internals: how batching windows work, request-scoped caching, cache invalidation strategies, and building custom loaders for complex data relationships.
Production Patterns
3 articlesGraphQL Pagination in Python: Cursor-Based and Offset Patterns
Implement pagination in your GraphQL API. Compare offset-based and cursor-based approaches, build Relay-style connections in Strawberry, and handle edge cases in real-world datasets.
GraphQL Subscriptions in Python: Real-Time Data with WebSockets
Add real-time capabilities to your GraphQL API. Build WebSocket-based subscriptions in Strawberry, handle connection lifecycle events, and manage concurrent subscribers.
GraphQL Persisted Queries: Caching, Security, and Performance
Lock down and speed up your GraphQL API with persisted queries. Reduce payload sizes, prevent arbitrary query attacks, enable CDN caching, and implement automatic persisted queries (APQ).