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.
pip install tarsk
Status: early. The version badge above reads live from PyPI — a number written here went stale twice before this sentence replaced it. Wheels for Linux (glibc and musl, x86_64 and aarch64), macOS universal2 and Windows x64, on Python 3.11 through 3.14 including the free-threaded build. 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
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
- No chord.
chainandgroupare 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, Postgres, RabbitMQ end to end
cargo test --lib # cron, console, socket permissions
The broker tests start their own redis-server and Postgres cluster, use any RabbitMQ
answering on the conventional ports (or TARSK_AMQP_URL), and skip whichever is missing —
loudly, so a skip cannot pass for a pass. 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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