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Yes. Powered by Rust and Axum, FastrAPI outperforms FastAPI by up to 33x in real-world benchmarks, with no compromises on usability.In benchmark tests with 20 virtual users over 30 seconds:
  • FastrAPI: 31,360 requests/sec with 0.59ms average latency
  • FastAPI + Gunicorn (1 worker): 937 requests/sec with 21.08ms average latency
  • FastAPI + Gunicorn (16 workers): 3,882 requests/sec with 4.84ms average latency
That’s approximately 33x faster than FastAPI with a single worker, and 8x faster even when FastAPI uses 16 workers.
Nope. FastrAPI lets you write 100% Python code while leveraging Rust’s performance under the hood.You use the same familiar Python syntax and decorators you’re used to from FastAPI. The Rust integration is completely transparent - you don’t need to write or understand any Rust code to use FastrAPI.
Absolutely. With full Pydantic integration and async support, FastrAPI scales effortlessly for small projects and enterprise-grade APIs alike.FastrAPI supports:
  • Complex Pydantic models with validation
  • Async/await for concurrent request handling
  • Dependency injection for clean code organization
  • Middleware for cross-cutting concerns
  • WebSockets for real-time communication
  • Multiple response types (JSON, HTML, custom)
Yes. FastrAPI mirrors FastAPI’s decorator-based syntax, ensuring compatibility and instant access to familiar workflows.While FastrAPI is not a direct fork, it maintains API compatibility with FastAPI’s core features, making it a true drop-in replacement for most use cases.
Switching is as simple as changing your import:
# Before
from fastapi import FastAPI

# After
from fastrapi import FastrAPI
Most FastAPI code will work without modification. Some advanced features may not be available yet - check the roadmap for details.
FastrAPI is still in active development. Some advanced features are not yet implemented:
  • APIRouter and include_router()
  • app.mount() for static files and sub-apps
  • Lifespan events (@app.on_startup / @app.on_shutdown)
  • Built-in TestClient
  • GraphQL support
  • Hot reloading
Check the roadmap for the full list of planned features.
FastrAPI achieves its performance through several architectural improvements:
  1. Rust-powered core - Built on Axum and Tokio for native async performance
  2. O(1) route lookup - Uses papaya concurrent hashmap instead of regex matching
  3. Pre-computed dependency injection - One-time parsing at decorator time, not per request
  4. Fast-path optimization - Trivial endpoints skip unnecessary validation and kwargs processing
  5. Efficient JSON serialization - Easy integration with fast serializers like orjson
  6. Memory safety - Rust’s ownership model prevents common performance pitfalls
  7. Native async runtime - Tokio provides better concurrency than Python’s asyncio
FastrAPI requires Python 3.8 or higher.It works with both CPython and PyPy implementations.
It depends. FastrAPI maintains API compatibility with FastAPI’s core features, so many extensions should work.However, extensions that rely on FastAPI’s internal architecture or advanced features may not work yet. Test your specific extensions to verify compatibility.
You can install FastrAPI using pip or uv:
# Using pip
pip install fastrapi

# Using uv
uv install fastrapi
FastrAPI is still in active development (version 0.2.8). While it’s stable and performant for many use cases, some advanced features are not yet implemented.For production use:
  • Verify that all features you need are available
  • Test thoroughly with your specific workload
  • Monitor the roadmap for upcoming features
  • Join the community and report any issues you encounter
Many users are already successfully using FastrAPI in production for high-performance APIs.
Contributions are welcome! Check out the contributing guide to get started.You can contribute by:
  • Reporting bugs and issues
  • Submitting pull requests for new features
  • Improving documentation
  • Sharing your FastrAPI projects
  • Helping other users in discussions
If you need help with FastrAPI:

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