How to integrate Strawberry GraphQL with Django?

Add 'strawberry.django' to INSTALLED_APPS and use GraphQLView in urls.py, as shown in the README. This provides a seamless way to add GraphQL endpoints to Django projects with minimal boilerplate.

Strawberry GraphQL vs Graphene: which is better for Python?

Strawberry excels with type safety and modern Python syntax using dataclasses, while Graphene has a larger ecosystem and more mature tooling. Choose Strawberry for new projects prioritizing clean, type-annotated code, and Graphene for extensive community support.

How to add authentication to a Strawberry GraphQL API?

Use middleware or framework-specific auth methods, such as Django's authentication system or custom resolvers. Check the examples repository for patterns, as Strawberry allows flexible integration but requires manual setup for security.

Does Strawberry GraphQL support subscriptions?

Yes, but support is experimental or basic compared to other libraries. Refer to the official documentation or GitHub issues for implementation details, as it may lack advanced real-time features out-of-the-box.

How to deploy Strawberry GraphQL in production?

Deploy via ASGI or WSGI integrations with frameworks like Starlette or Django, using production servers like Uvicorn. Ensure proper error handling and logging, as the built-in dev server is for development only.

Why isn't mypy catching errors in my Strawberry schema?

Verify the mypy plugin is enabled in mypy.ini with 'plugins = strawberry.ext.mypy_plugin'. Also, ensure type hints are correctly annotated and mypy is configured properly, as static checking requires additional setup steps.

Open-Awesome

Strawberry GraphQL

MITPython0.336.2

A Python GraphQL library that uses type annotations and dataclasses to define schemas with static type checking.

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4.7k stars669 forks0 contributors

What is Strawberry GraphQL?

Strawberry is a GraphQL library for Python that uses type annotations and dataclasses to define GraphQL schemas. It allows developers to build type-safe GraphQL APIs with a syntax that feels natural in Python, providing static type checking through mypy integration. The library includes a development server, CLI tools, and integrations with popular Python web frameworks.

Target Audience

Python developers building GraphQL APIs who want type safety, clean syntax using dataclasses, and integration with web frameworks like Django or Starlette.

Value Proposition

Developers choose Strawberry for its intuitive type annotation-based schema definition, static type checking capabilities, and seamless framework integrations—offering a modern, type-safe alternative to other Python GraphQL libraries.

Overview

A GraphQL library for Python that leverages type annotations 🍓

Use Cases

Best For

Building type-safe GraphQL APIs in Python with static validation
Integrating GraphQL into Django applications with minimal boilerplate
Creating GraphQL schemas using Python dataclasses and type hints
Developing GraphQL APIs with IDE support and autocompletion
Prototyping GraphQL servers quickly with the built-in dev server
Ensuring schema correctness through mypy-based type checking

Not Ideal For

Projects that prefer schema-first development using GraphQL SDL over code-first approaches
Teams heavily invested in another Python GraphQL library like Graphene, as migration requires reworking schema definitions
Applications requiring extensive real-time capabilities via GraphQL subscriptions, as support is less mature compared to alternatives
Environments stuck on older Python versions without dataclass or type hint support (pre-3.7)

Pros & Cons

Pros

Intuitive Type Annotations

Leverages Python type hints and dataclasses for schema definition, making code clean and familiar, as shown in the getting started example with @strawberry.type decorators.

Static Type Checking

Includes a mypy plugin for static validation during development, allowing early error detection and ensuring schema correctness before runtime.

Framework Integration

Provides built-in integrations with Django, Starlette, and Quart, simplifying GraphQL endpoint setup in existing Python web apps, as detailed in the README.

Developer Tooling

Comes with a CLI and development server (strawberry dev) for rapid prototyping and automatic GraphiQL serving, enhancing the testing and exploration experience.

Cons

Limited Ecosystem

As a newer library, Strawberry has fewer community plugins, extensions, and third-party tools compared to established alternatives like Graphene, which can limit advanced integrations.

Python Version Dependency

Requires Python 3.7+ for dataclass support, excluding legacy systems and adding a barrier for teams on older Python releases without modern type features.

Advanced Feature Gaps

Support for complex GraphQL features such as subscriptions or Apollo Federation is less polished or in development, as the README focuses on core functionalities without deep dives.

Frequently Asked Questions

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