zloop 0.0.1

An asyncio event loop with a Zig core.

zloop

[!WARNING] zloop is experimental. The API and behaviour may change at any time, and it is not yet ready for production use.

A drop-in asyncio event loop whose engine is written in Zig. It's to asyncio what uvloop is - a real asyncio.AbstractEventLoop - except the engine is hand-written in Zig (a kqueue/epoll reactor, plus an opt-in io_uring backend on Linux) rather than libuv wrapped in Cython.

import asyncio
import zloop

print(asyncio.run(asyncio.sleep(0, "hello from a Zig loop"), loop_factory=zloop.new_event_loop))

With uvicorn:

uvicorn app:app --loop zloop:new_event_loop

Why

• Drop-in. A genuine AbstractEventLoop, so the asyncio ecosystem - uvicorn, FastAPI, AnyIO, HTTPX2 - runs on it unchanged.
• Correct. Passes uvicorn's entire test suite (1048 tests), identical to stock asyncio, plus its own suite at 100% coverage.
• Fast. The hot paths - scheduling, timers, and socket I/O - run in Zig, not Python. See Performance for benchmarks against asyncio and uvloop, including an opt-in io_uring backend for free-threaded CPython.

Performance

The fairest comparison is uvloop's own echo benchmark, run unchanged except for a --zloop server flag mirroring --uvloop (the client is byte-for-byte uvloop's). Requests/sec, higher is better.

zloop has two backends: the default readiness reactor (epoll/kqueue) and an opt-in io_uring completion backend (ZLOOP_IO_URING=completion, Linux only). Both are shown below; the fastest in each row is bold.

Single loop (the default, GIL on)

Linux, CPython 3.14, 3 workers, best of 3, requests/sec:

mode	size	asyncio	uvloop	zloop epoll	zloop io_uring
proto	1 KB	135,393	127,872	132,223	138,778
proto	100 KiB	61,441	57,158	66,188	22,280
streams	1 KB	105,250	116,043	122,236	116,720
streams	100 KiB	43,312	40,582	46,862	19,679

For a single GIL-bound loop the default epoll backend beats uvloop. The io_uring completion backend is slower here - its submit/reap overhead and the 64 KiB buffer-ring copy aren't amortized when one serialized loop is the bottleneck (it fragments 100 KiB messages badly). Completion's win is parallel free-threaded loops, below.

Free-threaded parallel loops (GIL off)

Under free-threaded CPython (3.14t), N independent loops on N threads stop being serialized by the GIL - and the leaner completion path (batched submits, multishot recv, ring writes, cached data_received) beats uvloop at every thread count. 1 KB messages, 8 conns/thread, requests/sec:

loops	uvloop	zloop epoll	zloop io_uring
1	174,185	163,900	209,071
4	606,261	535,556	742,847
8	934,289	783,205	1,142,655
16	1,148,609	815,971	1,182,234

(Linux io_uring kernel 6.10, 3-sample medians on a 12-CPU host; directional - measured in a VM, not bare metal. The 16-loop margin is thin: 16 loops oversubscribe 12 cores.)

Reproduce the single-loop matrix with scripts/bench; the free-threaded numbers come from bench_uvloop/ft_parallel_bench.py on a python3.14t build. Full tables and caveats are in the performance docs.

How it works

The loop engine lives in Zig; CPython is reused only where reimplementing would be reckless: driving coroutines (asyncio.Future / asyncio.Task) and the TLS state machine (asyncio.sslproto). That's exactly uvloop's boundary.

zloop/            Python edge - new_event_loop() factory, connection setup
src/python/*.zig  CPython C-API adapter - Loop, Handle, Transport
src/core/*.zig    pure-Zig domain - run-once engine, kqueue/epoll reactor, timer heap