taskforeman 0.1.1

A bounded, fault-tolerant async worker pipeline.

taskforeman

A bounded, fault-tolerant async worker pipeline for Python 3.10+.

Designed for workloads that require stateful, long-lived workers — browser automation, API clients, database connection pools, or any workload where the worker itself needs lifecycle management. Failures escalate automatically through three levels: retry → error accumulation → circuit breaker.

---

Installation

pip install taskforeman

---

Quick start

import asyncio
from taskforeman import BaseWorker, WorkerManager, WorkerPoolSettings, WorkerException

class MyWorker(BaseWorker):
    async def start(self) -> None:
        self.driver = await launch_my_engine()
        self._running = True

    async def stop(self) -> None:
        await self.driver.close()
        self._running = False

async def my_task(worker: MyWorker, url: str) -> None:
    page = await worker.driver.goto(url)
    if page.status == 429:
        raise WorkerException("rate limited", error=True)
    await db.insert(page.content)

async def main():
    settings = WorkerPoolSettings(max_size=4, rpm=60)
    async with WorkerManager(MyWorker, settings) as manager:
        for url in urls:
            await manager.enqueue(my_task, url)
        await manager.join()

if __name__ == "__main__":
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        pass

---

Construction styles

Managed lifecycle

The manager instantiates and owns all workers. Use this when all workers are identical:

async with WorkerManager(MyWorker, pool_settings) as manager:
    await manager.enqueue(my_task, item)
    await manager.join()

Bring your own workers

Pre-construct workers with individual configuration, then hand them to the manager. Use this when workers need different proxies, credentials, or profiles:

from dataclasses import dataclass
from taskforeman import WorkerSettings

@dataclass
class MyWorkerSettings(WorkerSettings):
    proxy: str = ""
    name: str = "worker"

workers = [
    MyWorker(MyWorkerSettings(proxy="residential-1.example.com", name="worker-0")),
    MyWorker(MyWorkerSettings(proxy="residential-2.example.com", name="worker-1")),
]

async with WorkerManager.from_workers(workers, pool_settings) as manager:
    await manager.enqueue(my_task, item)
    await manager.join()

Worker indices are assigned automatically by the manager. Access them via worker.index and worker.worker_settings inside your task callables.

---

Settings

Settings can be provided as nested dataclasses (recommended for production) or as flat keyword arguments (convenient for scripts).

Nested

from taskforeman import (
    WorkerPoolSettings,
    PoolSettings,
    RetrySettings,
    ErrorSettings,
    RateLimitSettings,
    CircuitBreakerSettings,
)

settings = WorkerPoolSettings(
    task_timeout    = 30.0,
    queue_maxsize   = 100,
    pool            = PoolSettings(max_size=4, restart_every=50),
    retry           = RetrySettings(max_attempts=3, timeout=5.0, backoff=2.0),
    error           = ErrorSettings(max_accumulated=3),
    rate_limit      = RateLimitSettings(requests_per_minute=120, burst=5),
    circuit_breaker = CircuitBreakerSettings(max_attempts=3, timeout=10.0, backoff=2.0),
)

Flat

settings = WorkerPoolSettings(
    max_size           = 4,
    restart_every      = 50,
    retry_max_attempts = 3,
    retry_timeout      = 5.0,
    retry_backoff      = 2.0,
    max_accumulated    = 3,
    rpm                = 120,
    burst              = 5,
    cb_max_attempts    = 3,
    cb_timeout         = 10.0,
    cb_backoff         = 2.0,
)

Reference

Setting	Default	Description
task_timeout	30.0	Per-task execution timeout in seconds
queue_maxsize	100	Max tasks held in queue; callers block when full
worker_start_delay	2.0	Seconds between starting successive workers
pool.max_size	4	Number of concurrent workers
pool.restart_every	None	Restart worker after N completed tasks; None disables
retry.max_attempts	3	Max attempts before escalating to error accumulation
retry.timeout	5.0	Base wait in seconds between retry attempts
retry.backoff	2.0	Multiplier applied to timeout on each attempt
error.max_accumulated	3	Retry exhaustions before a circuit breaker trip fires
rate_limit.requests_per_minute	120.0	Sustained RPM per worker; None disables
rate_limit.burst	1	Token bucket capacity; controls burst after idle periods
circuit_breaker.max_attempts	3	Trips allowed before the program exits
circuit_breaker.timeout	10.0	Base pause in seconds when the breaker opens
circuit_breaker.backoff	2.0	Multiplier applied to timeout on each trip

---

Flow control

Raise WorkerException from inside any task callable to control how the worker handles the outcome.

from taskforeman import WorkerException

# Retry the task (counts against retry budget)
raise WorkerException("busy", retry=True)

# Restart the worker, then retry
raise WorkerException("session expired", restart=True, retry=True)

# Discard the task silently (no error accumulation)
raise WorkerException("not found", skip=True)

# Force one error accumulation, discard task
raise WorkerException("rate limited", error=True)

# Force an immediate circuit breaker trip, discard task
raise WorkerException("proxy dead", circuit_breaker=True)

# Exit the program immediately
raise WorkerException("unrecoverable", quit=True)

Flag priority

circuit_breaker > error > quit > skip > retry

restart is honoured alongside any primary flag.

Subclassing for readability

class SessionExpired(WorkerException):
    def __init__(self, message=None):
        super().__init__(message, restart=True, retry=True)

class RateLimited(WorkerException):
    def __init__(self, message=None):
        super().__init__(message, error=True)

class ProxyDead(WorkerException):
    def __init__(self, message=None):
        super().__init__(message, circuit_breaker=True)

---

Escalation model

retry → error accumulation → circuit breaker

1. Retry — the task is retried up to retry.max_attempts times with exponential backoff between attempts.

2. Error accumulation — once the retry budget is exhausted, the failure is accumulated. When error.max_accumulated failures accumulate, a circuit breaker trip fires and the accumulator resets.

3. Circuit breaker — all workers pause for circuit_breaker.timeout seconds (with exponential backoff on each trip) and the task is re-enqueued. After circuit_breaker.max_attempts trips, the program exits.

---

Rate limiting

Each worker maintains its own independent token bucket. Tokens refill at requests_per_minute / 60 per second up to a maximum of burst. The first task always fires immediately. Subsequent tasks are throttled to the configured rate. If a worker sits idle, tokens accumulate up to burst, allowing a short burst of back-to-back tasks when work resumes.

Set rpm=None to disable rate limiting entirely.

---

Keyboard interrupt

Wrap your entry point to handle Ctrl+C cleanly:

if __name__ == "__main__":
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        pass

asyncio.run() cancels all tasks and calls __aexit__ on the manager before raising KeyboardInterrupt, closing all workers cleanly.

---

Project structure

src/
  taskforeman/
    __init__.py
    config/
      settings.py
    core/
      exceptions.py
      manager.py
      worker.py
tests/
  conftest.py
  test_manager.py
  test_settings.py
  test_worker.py
examples/
  basic_usage.py
pyproject.toml
README.md

---

Running tests

pip install -e ".[dev]"
pytest

---

License

MIT