tarsk

A Python task queue whose workers hold a memory ceiling you set — without losing a task.

task with rust through the middle. The scheduler, retry state machine, lease tracking and child supervision are Rust; the only Python in the hot path is your handler.

Status: 0.1.0, not yet on PyPI. The core works and is tested; the wheel builds and installs. See What is missing.

📖 Documentation — everything below the fold lives there: how it works, writing tasks, routing and scheduling, operating, benchmarks.

from tarsk import App

app = App(broker="redis://localhost:6379/0")

@app.task(retries=3, timeout=30, queue="heavy")
def embed_document(doc_id: str) -> dict:
    ...

task_id = embed_document.send("abc")

tarsk worker --app myapp:app --broker redis://localhost:6379/0 \
             --queues heavy --children 4 --max-rss 400MB --metrics 0.0.0.0:9090

Handlers must be idempotent. Delivery is at-least-once. This is a contract, not a footnote: a worker killed mid-task will run that task again.

What it does that others do not

child RSS over one hour under a leaky handler, and the supervisor holding it

One hour, 72,001 tasks, a handler that never frees anything. 66 recycles, peak 400 MB against a 400 MB ceiling, no sample over it, nothing killed, nothing lost. The flat line beneath the sawtooth, on the same axis, is the supervisor doing the holding: 28.32 to 28.40 MB across the hour, a drift of 82 KB. A ceiling enforced from inside a process with the same problem would only defer it.

Every Python task queue leaks, because leaks come from the code they run rather than from the queue. The difference is what the runtime does about it.

--max-rss is a byte budget. Celery's --max-tasks-per-child is a task count, which only bounds bytes if you already know how many bytes a task costs — and stays wrong once that changes. Same configuration, different workloads:

	leak 20MB/task	leak 40MB/task	payload-dependent 2–80MB
celery `--max-tasks-per-child=6`	162 MB	282 MB	327 MB
tarsk `--max-rss=200MB`	183 MB	183 MB	187 MB

Celery wins the first column, and that is the honest result: when the leak per task is known and constant, dividing the budget by it works — someone divided 200 by 20 and typed 6. It is the other two columns tarsk was built for: nothing was reconfigured between them, the workload moved, and the guess encoded in that 6 went with it.

The worker that runs your code is 27 MB against Celery's 41 MB and taskiq's 44 MB, because it imports your tasks and nothing else — no broker driver, no scheduler. Recycling costs 7 ms at the 99th percentile against Celery's 139 ms, because the replacement child starts before the trigger fires and the slot never goes empty.

What it does not claim

Not faster. With a 50 ms handler tarsk, Celery and taskiq all reach 19–20 tasks/s. Draining 10,000 no-op tasks across four processes: Celery 10.0s, taskiq 2.3s, tarsk 2.2s — ahead in every run and by 4%, which this project's own benchmark rules call a tie. It starts in half the time and runs in half the memory; that is the claim, and speed is not.

This file claimed a 1.45× lead until the numbers were checked on more than one machine. The full retraction, and every column where tarsk loses, is in the benchmarks.

Not a hard ceiling regardless of task size. The ceiling is read while a child is idle, so a child never starts a task it cannot afford — but a handler that allocates 300 MB will allocate it. Overshoot is bounded by one task's peak, not by zero.

Not durable execution. That is Temporal's category, and it is much heavier.

What is missing

Not on PyPI yet — the wheel builds and installs, it just has not been uploaded
No chord. chain and group are here; fanning back in to a callback is not
Windows runs the suites that need no broker, since neither Redis nor Postgres ships for it. Everything else — the channel, recycling, the memory ceiling — is tested there

Running the tests

The toolchain is pinned in mise.toml — Rust 1.94.0 and Python 3.14.3, the versions the published numbers were produced with. With mise installed, mise install fetches both and entering the directory creates .venv from the pinned Python. Without it, any Python 3.11+ and a recent stable Rust will build: the wheel is abi3-py311.

python -m venv .venv && .venv/bin/pip install maturin msgpack
.venv/bin/maturin develop --release

.venv/bin/python tests/test_ipc.py       # protocol, timeouts, retries
.venv/bin/python tests/test_recycle.py   # the ceiling, soft timeouts, middleware
.venv/bin/python tests/test_brokers.py   # Redis and Postgres end to end
cargo test --lib                         # cron, console, socket permissions

The broker tests start their own redis-server and Postgres cluster and skip whichever is not installed. python demo/run.py --minutes 1 --ceiling 150MB --rate 30 is the definition of done in miniature: it exits non-zero if a task goes missing or the supervisor drifts.

License

MIT — see LICENSE.

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0.1.3

Aug 17, 2026 11 files

0.1.2

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0.1.1

Aug 16, 2026 11 files

This release

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Aug 15, 2026 11 files

tarsk 0.1.0

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