rsloop 0.1.9

An event loop for asyncio written in Rust

An event loop for asyncio written in Rust

rsloop is a PyO3-based asyncio event loop implemented in Rust.

Each rsloop.Loop owns a dedicated Rust runtime thread for loop coordination and I/O work. On Linux, low-level fd watchers plus plain TCP / Unix socket readiness, socket reads, and non-TLS server accepts are driven from that thread through compio with io_uring support enabled. Python callbacks, tasks, and coroutines still run on the thread that calls run_forever() or run_until_complete() (usually the main Python thread).

The package exposes:

• a native extension module at rsloop._loop
• a Python wrapper in python/rsloop/__init__.py
• rsloop.Loop, rsloop.new_event_loop(), and rsloop.run(...)

Repository metadata currently targets Python >=3.8. The packaged project now supports the core event-loop surface on Linux, macOS, and Windows, including Windows pipe transports and subprocess workflows.

Install

From PyPI:

pip install rsloop

With uv:

uv add rsloop

Usage

Simple entry point:

import rsloop

async def main():
    ...

rsloop.run(main())

Manual loop creation also works:

import asyncio
import rsloop

loop = rsloop.new_event_loop()
asyncio.set_event_loop(loop)
try:
    loop.run_until_complete(...)
finally:
    asyncio.set_event_loop(None)
    loop.close()

Importing rsloop also patches asyncio.set_event_loop() so Python 3.8 can accept an rsloop.Loop instance, matching the behavior exercised by tests/test_run.py.

Verified Surface Area

The current codebase implements these user-facing areas.

Loop lifecycle and scheduling:

• run_forever, run_until_complete, stop, close
• time, is_running, is_closed
• get_debug, set_debug
• call_soon, call_soon_threadsafe, call_later, call_at
• returned Handle and TimerHandle objects with cancel() / cancelled()

Tasks, futures, and execution helpers:

• create_future, create_task
• set_task_factory, get_task_factory
• set_exception_handler, get_exception_handler, call_exception_handler, default_exception_handler
• set_default_executor, run_in_executor
• shutdown_asyncgens, shutdown_default_executor
• callback execution under captured contextvars.Context
• asyncio.get_running_loop() support while running on rsloop
• rsloop.run(...) helper, with asyncio.run(..., loop_factory=...) integration on Python 3.12+

I/O and networking:

• add_reader, remove_reader, add_writer, remove_writer
• sock_recv, sock_recv_into, sock_sendall, sock_accept, sock_connect
• getaddrinfo, getnameinfo
• create_server, create_connection
• create_unix_server, create_unix_connection
• connect_accepted_socket
• returned Server objects with close(), is_serving(), get_loop(), and sockets()
• returned StreamTransport objects with write(), writelines(), close(), abort(), is_closing(), write_eof(), can_write_eof(), get_extra_info(), get_protocol(), set_protocol(), pause_reading(), resume_reading(), is_reading()

Pipes, subprocesses, and signals:

• connect_read_pipe, connect_write_pipe
• subprocess_exec, subprocess_shell
• returned ProcessTransport and ProcessPipeTransport objects
• higher-level compatibility with asyncio.create_subprocess_exec() and asyncio.create_subprocess_shell()
• Unix subprocess options including cwd, env, executable, pass_fds, start_new_session, process_group, user, group, extra_groups, umask, and restore_signals
• add_signal_handler, remove_signal_handler

Profiling:

• profile(...), profiler_running(), start_profiler(), stop_profiler()

Fast Streams

Importing rsloop patches asyncio.open_connection() and asyncio.start_server() by default.

That import-time behavior is controlled by RSLOOP_USE_FAST_STREAMS and can be disabled with:

export RSLOOP_USE_FAST_STREAMS=0

The native fast-stream path is used only when:

• the running loop is an rsloop.Loop
• ssl is unset or None

Otherwise rsloop falls back to the stdlib asyncio.streams helpers.

The implementation lives in src/fast_streams.rs and is backed by the lower level transport code in src/stream_transport.rs.

Runtime Model

Today the runtime is hybrid rather than fully single-threaded:

• the loop coordination thread is always the central scheduler
• on Linux, add_reader / add_writer, plain socket reads, and non-TLS socket accept loops use the compio runtime on that thread
• some transport paths still fall back to helper threads, especially TLS I/O, TLS server accept, and parts of the legacy transport write path

That means the codebase has started the move toward a single-runtime-thread I/O model, but has not finished eliminating every helper thread yet.

Current Limitations

These gaps are visible in the current implementation.

• TLS uses a rustls backend with a narrower compatibility surface than CPython's OpenSSL-backed ssl module. In particular, encrypted private keys are not supported yet, and the fast-stream monkeypatch still falls back to stdlib helpers whenever ssl is enabled. TLS transport internals also still use helper-thread paths instead of the newer runtime-thread compio socket path.
• Subprocess support still has one notable gap: preexec_fn remains unsupported because running arbitrary Python between fork() and exec() is unsafe in this runtime model.
• Unix-specific APIs remain Unix-specific: create_unix_server, create_unix_connection, add_signal_handler, remove_signal_handler.
• Platform-specific limitations still apply: Unix socket APIs and Unix signal handlers remain Unix-only, and several subprocess options such as pass_fds, user, group, and umask are still specific to Unix process spawning.
• The transport runtime model is still in transition: plain socket reads and non-TLS accepts now run on the loop runtime thread on Linux, but writes and TLS-heavy paths are not fully collapsed onto that same single-threaded I/O path yet.

Build

Quick check:

cargo check

Release build and editable install:

cargo build --release
uv run --with maturin maturin develop --release

Build release wheels into dist/wheels:

scripts/build-wheels.sh

scripts/build-wheels.sh currently defaults to CPython 3.8 3.9 3.10 3.11 3.12 3.13 3.14 plus free-threaded 3.14t, and uses uv python install / uv python find to locate interpreters.

Profiling

Profiling is behind the Cargo feature profiler and is disabled by default. Build or install with that feature first:

cargo build --release --features profiler
uv run --with maturin maturin develop --release --features profiler

Then wrap the code you want to inspect:

import rsloop

with rsloop.profile():
    rsloop.run(main())

Or manage the session manually:

import rsloop

rsloop.start_profiler()
try:
    rsloop.run(main())
finally:
    rsloop.stop_profiler()

This starts a Tracy client inside the process. Build a release binary, open tracy-profiler.exe, then connect to the running process while the profiled code is executing.

The current Tracy feature set is aimed at local Windows profiling: enable, only-localhost, sampling, and flush-on-exit. The last one helps short-lived runs flush data before exit.

If the extension was built without --features profiler, profile() and start_profiler() raise a runtime error.

Examples

Run the repository examples from the project root:

uv run python examples/01_basics.py
uv run python examples/02_fd_and_sockets.py
uv run python examples/03_streams.py
uv run python examples/04_unix_and_accepted_socket.py
uv run python examples/05_pipes_signals_subprocesses.py

Example files: examples/01_basics.py, examples/02_fd_and_sockets.py, examples/03_streams.py, examples/04_unix_and_accepted_socket.py, examples/05_pipes_signals_subprocesses.py.

The repository also includes:

• demo/fastapi_service.py for running the same FastAPI app on stdlib asyncio, uvloop, or rsloop
• benchmarks/compare_event_loops.py for callback, task, and TCP stream comparisons

Benchmark

uv run --with maturin maturin develop --release
uv run --with uvloop python benchmarks/compare_event_loops.py

An example output from that script on Linux with CPython 3.14.0:

callbacks (200,000 ops)
loop           median_s       best_s      ops_per_s   vs_fastest
rsloop         0.041608     0.040585      4,806,807        1.00x
uvloop         0.087539     0.086690      2,284,707        2.10x
asyncio        0.229563     0.221348        871,222        5.52x

tasks (50,000 ops)
loop           median_s       best_s      ops_per_s   vs_fastest
uvloop         0.084425     0.083497        592,239        1.00x
rsloop         0.091845     0.090982        544,397        1.09x
asyncio        0.138782     0.137716        360,276        1.64x

tcp_streams (5,000 ops)
loop           median_s       best_s      ops_per_s   vs_fastest
rsloop         0.119483     0.118451         41,847        1.00x
uvloop         0.119582     0.116446         41,812        1.00x
asyncio        0.138408     0.134438         36,125        1.16x

See benchmarks/README.md for workload details and extra flags, and demo/README.md for the FastAPI loop comparison demo.

Acknowledgements

rsloop builds on the Python asyncio model and is implemented with PyO3 on the Rust side. The runtime and I/O work in the current implementation rely in part on compio. On Windows, parts of the runtime also rely on vibeio.

License

This project is licensed under the Apache License, Version 2.0. See LICENSE for the full text.