cronoq for Python

An elastic, priority-aware task scheduler for asyncio, powered by a Rust engine. cronoq decides when your coroutines run, in what order and with how much concurrency: priorities with aging, deadlines, fixed start times and cron, dependencies, retries with backoff, shared rate limits, and autoscaling, all in-process, without extra infrastructure.

pip install cronoq

Why

• Important work first, nothing starves. Four priority classes with aging; deadlines raise urgency as they approach.
• Respect rate limits. Token buckets and semaphores shared across pools gate dispatch, so a burst never turns into a 429 storm; Retryable(retry_after=...) honours Retry-After.
• Scheduled jobs that start on time. Fixed-start tasks reserve capacity and get a worker held for them; cron schedules with time zones.
• Pipelines without glue code. Dependencies by key with success/failure/completion edges, atomic batches, idempotent keys.
• Elastic concurrency. Pools scale between min and max from queue pressure and wait-time objectives.
• Fast. The engine makes about a million scheduling decisions per second; payloads stay Python objects in memory, and are serialized only when a durable store is configured.

Quickstart

import asyncio
import cronoq

async def call_llm(ctx: cronoq.TaskContext, prompt: str) -> str:
    # raise cronoq.Retryable("429", retry_after=2.0) to back off,
    # raise cronoq.Permanent("bad input") to fail without retrying
    await asyncio.sleep(0.1)
    return f"answer to {prompt!r}"

async def main() -> None:
    pools = [cronoq.Pool("llm", call_llm, min=1, max=16)]
    limits = [cronoq.Resource.token_bucket("openai", rate=50.0, burst=100)]
    async with cronoq.Scheduler(pools, resources=limits) as sched:
        chat = await sched.submit("hi", pool="llm", priority="high", deadline_in=2.0,
                                  resources={"openai": 1})
        batch = [await sched.submit(f"doc {i}", pool="llm", priority="low",
                                    resources={"openai": 1}) for i in range(10)]
        print(await chat)
        print(len([await h for h in batch]), "batch items done")
        print((await sched.snapshot()).pool("llm"))

asyncio.run(main())

• A scheduler is bound to the event loop that started it: use async with cronoq.Scheduler(...) (or await sched.start() / await sched.shutdown()) inside that loop. If the loop closes without a shutdown, the scheduler stops and further calls raise cronoq.SchedulerError. Leaving async with waits up to shutdown_grace seconds (default 5) for running attempts.
• Executors are async def run(ctx, payload) coroutines and run on that loop. ctx has id, attempt, kind, key, pool, tags, timeout, deadline (Unix seconds), is_cancelled() and heartbeat().
• Plain (sync) functions are accepted too and run in the loop's default thread pool. A thread cannot be interrupted: on timeout or cancellation the attempt is aborted, but the function keeps running until it returns, and the next attempt may overlap with it. Check ctx.is_cancelled() in long-running sync executors.
• Payloads and results are arbitrary Python objects. They are serialized only when the scheduler has a durable store (see Durable state).
• Tasks without pool= go to the scheduler's default_pool: the pool named "default", or the first pool.
• cronoq.Retryable / cronoq.Permanent control retries; any other exception is retryable. Awaiting a task that did not succeed raises cronoq.TaskFailed (.status, .message). All cronoq exceptions can be pickled.
• Cancelling a task, a timeout, or a lost lease cancels the executor's asyncio task. A CancelledError the executor raises on its own (not caused by cronoq) is a retryable failure. An executor that swallows CancelledError keeps running and may overlap with the retry.
• Invalid durations or configuration (negative, NaN, out of range) raise ValueError.
• cronoq.compat.ElasticPriorityScheduler is a synchronous, thread-safe API for code written against ElasticPriorityScheduler.
• Wheels use the stable ABI (abi3, CPython 3.14+). Free-threaded (no-GIL) CPython builds are not supported.

Status events

sched.events() is an async iterator of cronoq.StatusEvent (id, pool, key, status, attempt, at in Unix seconds, message). It delivers terminal events (succeeded, failed, dead_lettered, cancelled, ...) by default, and every transition (ready, running, retrying, ...) when the scheduler is created with emit_transitions=True.

async with sched.events() as events:          # or: events = sched.events(); ...; events.close()
    async for e in events:
        print(e.id, e.status, e.message)

• Each stream buffers up to event_capacity events (a Scheduler argument, default 1024). When the consumer falls behind, the oldest events are dropped and counted in events.lagged. With sched.events(on_lag="raise") the next iteration raises cronoq.EventsLagged (.skipped); iterating again continues with the buffered events.
• A stream ends (StopAsyncIteration) when the scheduler shuts down or the stream is closed.

Durable state

Scheduler(pools, store=cronoq.SqliteStore("state.db")) keeps queued work, schedules and results in a SQLite file across restarts. Payloads and results are stored as JSON unless you pass codec=; several processes can share the file, with one leading and the others standing by.

More: Python quickstart · use cases · API reference.

Client and remote workers for cronoq-server

pip install "cronoq[client]"

The extra installs grpcio, which has no prebuilt wheel for Windows on arm64.

import os
from cronoq.client import CancelTask, Client, Reject, Worker, task

# Submit and inspect (client token; the server requires tokens of at least 16 characters).
async with Client("localhost:7070", token=os.environ["CRONOQ_CLIENT_TOKEN"]) as c:
    sub = await c.submit({"prompt": "hi"}, pool="llm", priority="high",
                         deadline_in=30, timeout=60, key="job-1")
    result = await c.wait(sub.id, timeout=120)        # Result(id, status, output, message, ...)
    print(result.status, result.json())

    done = await c.submit("quick", wait=True, wait_timeout=10)   # submit and wait in one call
    info = await c.get("job-1")      # TaskInfo: status, pool, key, kind, attempt, timestamps, ...

    await c.submit_batch([task("a", key="a"), task("b", key="b", after=["a"])])
    async for event in c.watch(pools=["llm"], keys=["job-1"], all_transitions=True):
        ...                          # every transition of job-1 (default: terminal statuses only)

# Serve a pool (worker token).
async def handle(lease):  # lease.payload / .json() / .text(), .attempt, .pool, .tags, .cancelled
    if not can_handle(lease):
        raise Reject("missing model")    # hand the lease back unrun
    if obsolete(lease):
        raise CancelTask("superseded")   # end the task as cancelled
    return {"answer": 42}                # bytes, str, JSON-serialisable value or None

worker = Worker("localhost:7070", "llm", handle, slots=8,
                token=os.environ["CRONOQ_WORKER_TOKEN"])
await worker.run()                  # reconnects with backoff; `await worker.stop()` drains

• Payloads: bytes are sent as-is, str as UTF-8 text, other values as JSON (application/json). Outputs are encoded the same way and carry their content type.
• Handlers raise cronoq.Retryable(msg, retry_after=...) or cronoq.Permanent(msg); any other exception is a retryable failure. An output larger than the server's max_message_bytes is a permanent failure.
• Reject(reason) gives the lease back: the server offers it, within the same attempt, to another worker of the pool with a free slot; if there is none, the attempt fails as retryable and counts against the retry budget. CancelTask(reason) ends the task as cancelled.
• The worker speaks protocol version 3. The server may grant fewer slots than requested (worker.granted_slots, capped by limits.max_slots_per_worker); leases beyond the grant are handed back. When the server announces it is shutting down (worker.last_shutdown) the worker reconnects with backoff, or immediately when leadership moved to another node.
• Each running lease is heartbeated every lease.lease_ttl / 3; when the server aborts an attempt (timeout, cancellation, lease expiry) the handler task is cancelled and lease.cancelled is set.
• Failed calls raise cronoq.client.ClientError with the gRPC status name in .code (e.g. unauthenticated, not_found from get/wait on an unknown task, resource_exhausted when a pool is full, unavailable when the server is not the leader or is shutting down); .retryable is true for the last two. Client.wait and Client.submit(..., wait=True) raise TimeoutError when the wait times out (the server caps waits at limits.max_wait_s), as does Client.submit(..., call_timeout=...).
• Client.snapshot() (metrics or admin token) returns per-pool figures, totals and workers_connected.
• Client and Worker can be created outside a running loop; they connect on first use. Worker.stop() can be called more than once (callers wait for the same drain), and a stopped worker can be run again. A handler that swallows CancelledError keeps running after an abort and may overlap with the retry of the same task.

Migrating from ElasticPriorityScheduler

from cronoq.compat import ElasticPriorityScheduler, Priority, Task

A synchronous, thread-safe drop-in for the original API. See the migration guide.

Development

python3 -m venv .venv
.venv/bin/pip install maturin pytest pytest-asyncio grpcio protobuf mypy
.venv/bin/maturin develop -m crates/cronoq-py/Cargo.toml
cd crates/cronoq-py && ../../.venv/bin/python -m pytest
../../.venv/bin/python -m mypy.stubtest cronoq._cronoq   # stubs match the extension

python/tests/test_client.py starts a real cronoq-server (building it with cargo if needed, or using CRONOQ_SERVER_BIN). The stubs in cronoq/_proto are generated by scripts/gen_proto.sh. See CONTRIBUTING.md.

License

MIT OR Apache-2.0.