Blazeio

TIL about blazeio. blazeio: https://github.com/anonyxbiz/Blazeio TechEmpower Framework Benchmarks > Round 23 (2025-02) > Data Updates: https://www.techempower.com/benchmarks/#section=data-r23&tes... TechEmpower/FrameworkBenchmarks > wiki > Project-Information-Framework-Tests-Overview: https://github.com/TechEmpower/FrameworkBenchmarks/wiki/Proj... TechEmpower/FrameworkBenchmarks > Python: https://github.com/TechEmpower/FrameworkBenchmarks/tree/mast...

I’ve been working on a Python async library ([Blazeio](https://github.com/anonyxbiz/Blazeio)) and stumbled into a shockingly simple optimization that makes `asyncio.Event` look like a relic. ### *The Problem* `asyncio.Event` (and similar constructs in other languages) has two nasty scaling flaws: 1. *Memory*: It allocates one future per waiter → 1M waiters = 48MB wasted.. 2. *Latency*: It wakes waiters one-by-one - O(N) syscalls under the GIL. ### *The Fix: `SharpEvent`* A drop-in replacement that: - *Uses one shared future* for all waiters - *O(1) memory*. - *Wakes every waiter in a single operation* - *O(1) latency*. ### *Benchmarks* | Metric | `asyncio.Event` | `SharpEvent` | |----------------|-----------------|--------------| | 1K waiters | ~1ms wakeup | *~1µs* | | 1M waiters | *Crashes* | *Still ~1µs*| | Memory (1M)

I built Blazeio ([https://github.com/anonyxbiz/Blazeio]) because aiohttp let me down in production. I needed a framework I could trust to support high-concurrency web apps, and rather than just complain, I decided to build it myself. It’s not about coding pointlessly, it’s about solving real problems. I update it for me, but since others have faced similar challenges, they can benefit from it too. I designed to be efficient, scalable, and lightweight, capable of handling hundreds of thousands of requests on a single server with minimal resources. Sometimes, creating something is motivated by necessity, not just by a paycheck.

I'm building and maintaining Blazeio: https://github.com/anonyxbiz/Blazeio. Blazeio is designed to handle massive concurrency with low response times and high requests per second. It utilizes a perishable buffer, discarding chunks as they are received, and operates with a single task throughout the entire request/response cycle. In theory, Blazeio can scale to handle infinite concurrency. While Black Sheep crashes under heavy load, Blazeio continues to scale seamlessly and outperform it.