import asyncio
import inspect
import logging
import signal
from dataclasses import dataclass
from datetime import datetime, timedelta
from functools import partial
from signal import Signals
from time import time
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Sequence, Set, Tuple, Union, cast
from aioredis.exceptions import ResponseError, WatchError
from pydantic.utils import import_string
from arku.cron import CronJob
from arku.jobs import Deserializer, JobResult, SerializationError, Serializer, deserialize_job_raw, serialize_result
from .connections import ArkuRedis, RedisSettings, create_pool, log_redis_info
from .constants import (
abort_job_max_age,
abort_jobs_ss,
default_queue_name,
health_check_key_suffix,
in_progress_key_prefix,
job_key_prefix,
keep_cronjob_progress,
result_key_prefix,
retry_key_prefix,
)
from .utils import args_to_string, ms_to_datetime, poll, timestamp_ms, to_ms, to_seconds, to_unix_ms, truncate
if TYPE_CHECKING:
from .typing import SecondsTimedelta, StartupShutdown, WorkerCoroutine, WorkerSettingsType # noqa F401
logger = logging.getLogger('arku.worker')
no_result = object()
@dataclass
class Function:
name: str
coroutine: 'WorkerCoroutine'
timeout_s: Optional[float]
keep_result_s: Optional[float]
keep_result_forever: Optional[bool]
max_tries: Optional[int]
[docs]def func(
coroutine: Union[str, Function, 'WorkerCoroutine'],
*,
name: Optional[str] = None,
keep_result: Optional['SecondsTimedelta'] = None,
timeout: Optional['SecondsTimedelta'] = None,
keep_result_forever: Optional[bool] = None,
max_tries: Optional[int] = None,
) -> Function:
"""
Wrapper for a job function which lets you configure more settings.
:param coroutine: coroutine function to call, can be a string to import
:param name: name for function, if None, ``coroutine.__qualname__`` is used
:param keep_result: duration to keep the result for, if 0 the result is not kept
:param keep_result_forever: whether to keep results forever, if None use Worker default, wins over ``keep_result``
:param timeout: maximum time the job should take
:param max_tries: maximum number of tries allowed for the function, use 1 to prevent retrying
"""
if isinstance(coroutine, Function):
return coroutine
if isinstance(coroutine, str):
name = name or coroutine
coroutine_: 'WorkerCoroutine' = import_string(coroutine)
else:
coroutine_ = coroutine
assert asyncio.iscoroutinefunction(coroutine_), f'{coroutine_} is not a coroutine function'
timeout = to_seconds(timeout)
keep_result = to_seconds(keep_result)
return Function(name or coroutine_.__qualname__, coroutine_, timeout, keep_result, keep_result_forever, max_tries)
[docs]class Retry(RuntimeError):
"""
Special exception to retry the job (if ``max_retries`` hasn't been reached).
:param defer: duration to wait before rerunning the job
"""
def __init__(self, defer: Optional['SecondsTimedelta'] = None):
self.defer_score: Optional[int] = to_ms(defer)
def __repr__(self) -> str:
return f'<Retry defer {(self.defer_score or 0) / 1000:0.2f}s>'
def __str__(self) -> str:
return repr(self)
class JobExecutionFailed(RuntimeError):
def __eq__(self, other: Any) -> bool:
if isinstance(other, JobExecutionFailed):
return self.args == other.args
return False
class FailedJobs(RuntimeError):
def __init__(self, count: int, job_results: List[JobResult]):
self.count = count
self.job_results = job_results
def __str__(self) -> str:
if self.count == 1 and self.job_results:
exc = self.job_results[0].result
return f'1 job failed {exc!r}'
else:
return f'{self.count} jobs failed:\n' + '\n'.join(repr(r.result) for r in self.job_results)
def __repr__(self) -> str:
return f'<{str(self)}>'
class RetryJob(RuntimeError):
pass
[docs]class Worker:
"""
Main class for running jobs.
:param functions: list of functions to register, can either be raw coroutine functions or the
result of :func:`arku.worker.func`.
:param queue_name: queue name to get jobs from
:param cron_jobs: list of cron jobs to run, use :func:`arku.cron.cron` to create them
:param redis_settings: settings for creating a redis connection
:param redis_pool: existing redis pool, generally None
:param burst: whether to stop the worker once all jobs have been run
:param on_startup: coroutine function to run at startup
:param on_shutdown: coroutine function to run at shutdown
:param handle_signals: default true, register signal handlers,
set to false when running inside other async framework
:param max_jobs: maximum number of jobs to run at a time
:param job_timeout: default job timeout (max run time)
:param keep_result: default duration to keep job results for
:param keep_result_forever: whether to keep results forever
:param poll_delay: duration between polling the queue for new jobs
:param queue_read_limit: the maximum number of jobs to pull from the queue each time it's polled; by default it
equals ``max_jobs``
:param max_tries: default maximum number of times to retry a job
:param health_check_interval: how often to set the health check key
:param health_check_key: redis key under which health check is set
:param ctx: dictionary to hold extra user defined state
:param retry_jobs: whether to retry jobs on Retry or CancelledError or not
:param allow_abort_jobs: whether to abort jobs on a call to :func:`arku.jobs.Job.abort`
:param max_burst_jobs: the maximum number of jobs to process in burst mode (disabled with negative values)
:param job_serializer: a function that serializes Python objects to bytes, defaults to pickle.dumps
:param job_deserializer: a function that deserializes bytes into Python objects, defaults to pickle.loads
"""
def __init__(
self,
functions: Sequence[Union[Function, 'WorkerCoroutine']] = (),
*,
queue_name: Optional[str] = default_queue_name,
cron_jobs: Optional[Sequence[CronJob]] = None,
redis_settings: RedisSettings = None,
redis_pool: ArkuRedis = None,
burst: bool = False,
on_startup: Optional['StartupShutdown'] = None,
on_shutdown: Optional['StartupShutdown'] = None,
handle_signals: bool = True,
max_jobs: int = 10,
job_timeout: 'SecondsTimedelta' = 300,
keep_result: 'SecondsTimedelta' = 3600,
keep_result_forever: bool = False,
poll_delay: 'SecondsTimedelta' = 0.5,
queue_read_limit: Optional[int] = None,
max_tries: int = 5,
health_check_interval: 'SecondsTimedelta' = 3600,
health_check_key: Optional[str] = None,
ctx: Optional[Dict[Any, Any]] = None,
retry_jobs: bool = True,
allow_abort_jobs: bool = False,
max_burst_jobs: int = -1,
job_serializer: Optional[Serializer] = None,
job_deserializer: Optional[Deserializer] = None,
):
self.functions: Dict[str, Union[Function, CronJob]] = {f.name: f for f in map(func, functions)}
if queue_name is None:
if redis_pool is not None:
queue_name = redis_pool.default_queue_name
else:
raise ValueError('If queue_name is absent, redis_pool must be present.')
self.queue_name = queue_name
self.cron_jobs: List[CronJob] = []
if cron_jobs is not None:
assert all(isinstance(cj, CronJob) for cj in cron_jobs), 'cron_jobs, must be instances of CronJob'
self.cron_jobs = list(cron_jobs)
self.functions.update({cj.name: cj for cj in self.cron_jobs})
assert len(self.functions) > 0, 'at least one function or cron_job must be registered'
self.burst = burst
self.on_startup = on_startup
self.on_shutdown = on_shutdown
self.sem = asyncio.BoundedSemaphore(max_jobs)
self.job_timeout_s = to_seconds(job_timeout)
self.keep_result_s = to_seconds(keep_result)
self.keep_result_forever = keep_result_forever
self.poll_delay_s = to_seconds(poll_delay)
self.queue_read_limit = queue_read_limit or max(max_jobs * 5, 100)
self._queue_read_offset = 0
self.max_tries = max_tries
self.health_check_interval = to_seconds(health_check_interval)
if health_check_key is None:
self.health_check_key = self.queue_name + health_check_key_suffix
else:
self.health_check_key = health_check_key
self._pool = redis_pool
if self._pool is None:
self.redis_settings: Optional[RedisSettings] = redis_settings or RedisSettings()
else:
self.redis_settings = None
# self.tasks holds references to run_job coroutines currently running
self.tasks: Dict[str, asyncio.Task[Any]] = {}
# self.job_tasks holds references the actual jobs running
self.job_tasks: Dict[str, asyncio.Task[Any]] = {}
self.main_task: Optional[asyncio.Task[None]] = None
self.loop = asyncio.get_event_loop()
self.ctx = ctx or {}
max_timeout = max(f.timeout_s or self.job_timeout_s for f in self.functions.values())
self.in_progress_timeout_s = (max_timeout or 0) + 10
self.jobs_complete = 0
self.jobs_retried = 0
self.jobs_failed = 0
self._last_health_check: float = 0
self._last_health_check_log: Optional[str] = None
self._handle_signals = handle_signals
if self._handle_signals:
self._add_signal_handler(signal.SIGINT, self.handle_sig)
self._add_signal_handler(signal.SIGTERM, self.handle_sig)
self.on_stop: Optional[Callable[[Signals], None]] = None
# whether or not to retry jobs on Retry and CancelledError
self.retry_jobs = retry_jobs
self.allow_abort_jobs = allow_abort_jobs
self.aborting_tasks: Set[str] = set()
self.max_burst_jobs = max_burst_jobs
self.job_serializer = job_serializer
self.job_deserializer = job_deserializer
[docs] def run(self) -> None:
"""
Sync function to run the worker, finally closes worker connections.
"""
self.main_task = self.loop.create_task(self.main())
try:
self.loop.run_until_complete(self.main_task)
except asyncio.CancelledError: # pragma: no cover
# happens on shutdown, fine
pass
finally:
self.loop.run_until_complete(self.close())
[docs] async def async_run(self) -> None:
"""
Asynchronously run the worker, does not close connections. Useful when testing.
"""
self.main_task = self.loop.create_task(self.main())
await self.main_task
[docs] async def run_check(self, retry_jobs: Optional[bool] = None, max_burst_jobs: Optional[int] = None) -> int:
"""
Run :func:`arku.worker.Worker.async_run`, check for failed jobs and raise :class:`arku.worker.FailedJobs`
if any jobs have failed.
:return: number of completed jobs
"""
if retry_jobs is not None:
self.retry_jobs = retry_jobs
if max_burst_jobs is not None:
self.max_burst_jobs = max_burst_jobs
await self.async_run()
if self.jobs_failed:
failed_job_results = [r for r in await self.pool.all_job_results() if not r.success]
raise FailedJobs(self.jobs_failed, failed_job_results)
else:
return self.jobs_complete
@property
def pool(self) -> ArkuRedis:
return cast(ArkuRedis, self._pool)
async def main(self) -> None:
if self._pool is None:
self._pool = await create_pool(
self.redis_settings,
job_deserializer=self.job_deserializer,
job_serializer=self.job_serializer,
default_queue_name=self.queue_name,
)
logger.info('Starting worker for %d functions: %s', len(self.functions), ', '.join(self.functions))
await log_redis_info(self.pool, logger.info)
self.ctx['redis'] = self.pool
if self.on_startup:
await self.on_startup(self.ctx)
async for _ in poll(self.poll_delay_s): # noqa F841
await self._poll_iteration()
if self.burst:
if 0 <= self.max_burst_jobs <= self._jobs_started():
await asyncio.gather(*self.tasks.values())
return None
queued_jobs = await self.pool.zcard(self.queue_name)
if queued_jobs == 0:
await asyncio.gather(*self.tasks.values())
return None
async def _poll_iteration(self) -> None:
"""
Get ids of pending jobs from the main queue sorted-set data structure and start those jobs, remove
any finished tasks from self.tasks.
"""
count = self.queue_read_limit
if self.burst and self.max_burst_jobs >= 0:
burst_jobs_remaining = self.max_burst_jobs - self._jobs_started()
if burst_jobs_remaining < 1:
return
count = min(burst_jobs_remaining, count)
async with self.sem: # don't bother with zrangebyscore until we have "space" to run the jobs
with self.pool.encoder_context(decode_responses=True):
now = timestamp_ms()
job_ids = await self.pool.zrangebyscore(
self.queue_name, min=float('-inf'), start=self._queue_read_offset, num=count, max=now
)
await self.start_jobs(job_ids)
if self.allow_abort_jobs:
await self._cancel_aborted_jobs()
for job_id, t in list(self.tasks.items()):
if t.done():
del self.tasks[job_id]
# required to make sure errors in run_job get propagated
t.result()
await self.heart_beat()
async def _cancel_aborted_jobs(self) -> None:
"""
Go through job_ids in the abort_jobs_ss sorted set and cancel those tasks.
"""
async with self.pool as conn:
with conn.encoder_context(decode_responses=True):
pipe = conn.pipeline()
pipe.zrange(abort_jobs_ss, start=0, end=-1)
pipe.zremrangebyscore(abort_jobs_ss, min=timestamp_ms() + abort_job_max_age, max=float('inf'))
abort_job_ids, _ = await pipe.execute()
aborted: Set[str] = set()
for job_id in abort_job_ids:
try:
task = self.job_tasks[job_id]
except KeyError:
pass
else:
aborted.add(job_id)
task.cancel()
if aborted:
self.aborting_tasks.update(aborted)
await self.pool.zrem(abort_jobs_ss, *aborted)
[docs] async def start_jobs(self, job_ids: List[str]) -> None:
"""
For each job id, get the job definition, check it's not running and start it in a task
"""
for job_id in job_ids:
await self.sem.acquire()
in_progress_key = in_progress_key_prefix + job_id
async with self.pool as conn:
pipe = conn.pipeline()
await pipe.unwatch()
await pipe.watch(in_progress_key)
ongoing_exists = await pipe.exists(in_progress_key)
score = await pipe.zscore(self.queue_name, job_id)
if ongoing_exists or not score:
# job already started elsewhere, or already finished and removed from queue
await pipe.reset()
self.sem.release()
logger.debug('job %s already running elsewhere', job_id)
continue
pipe.multi()
pipe.psetex(in_progress_key, int(self.in_progress_timeout_s * 1000), b'1')
try:
await pipe.execute()
except (ResponseError, WatchError):
# job already started elsewhere since we got 'existing'
self.sem.release()
logger.debug('multi-exec error, job %s already started elsewhere', job_id)
else:
t = self.loop.create_task(self.run_job(job_id, score))
t.add_done_callback(lambda _: self.sem.release())
self.tasks[job_id] = t
async def run_job(self, job_id: str, score: int) -> None: # noqa: C901
start_ms = timestamp_ms()
coros = (
self.pool.get(job_key_prefix + job_id),
self.pool.incr(retry_key_prefix + job_id),
self.pool.expire(retry_key_prefix + job_id, 88400),
)
if self.allow_abort_jobs:
abort_job, v, job_try, _ = await asyncio.gather(self.pool.zrem(abort_jobs_ss, job_id), *coros)
else:
v, job_try, _ = await asyncio.gather(*coros)
abort_job = False
function_name, enqueue_time_ms = '<unknown>', 0
args: Tuple[Any, ...] = ()
kwargs: Dict[Any, Any] = {}
async def job_failed(exc: BaseException) -> None:
self.jobs_failed += 1
result_data_ = serialize_result(
function=function_name,
args=args,
kwargs=kwargs,
job_try=job_try,
enqueue_time_ms=enqueue_time_ms,
success=False,
result=exc,
start_ms=start_ms,
finished_ms=timestamp_ms(),
ref=f'{job_id}:{function_name}',
serializer=self.job_serializer,
queue_name=self.queue_name,
)
await asyncio.shield(self.finish_failed_job(job_id, result_data_))
if not v:
logger.warning('job %s expired', job_id)
return await job_failed(JobExecutionFailed('job expired'))
try:
function_name, args, kwargs, enqueue_job_try, enqueue_time_ms = deserialize_job_raw(
v, deserializer=self.job_deserializer
)
except SerializationError as e:
logger.exception('deserializing job %s failed', job_id)
return await job_failed(e)
if abort_job:
t = (timestamp_ms() - enqueue_time_ms) / 1000
logger.info('%6.2fs ⊘ %s:%s aborted before start', t, job_id, function_name)
return await job_failed(asyncio.CancelledError())
try:
function: Union[Function, CronJob] = self.functions[function_name]
except KeyError:
logger.warning('job %s, function %r not found', job_id, function_name)
return await job_failed(JobExecutionFailed(f'function {function_name!r} not found'))
if hasattr(function, 'next_run'):
# cron_job
ref = function_name
keep_in_progress: Optional[float] = keep_cronjob_progress
else:
ref = f'{job_id}:{function_name}'
keep_in_progress = None
if enqueue_job_try and enqueue_job_try > job_try:
job_try = enqueue_job_try
await self.pool.setex(retry_key_prefix + job_id, 88400, str(job_try))
max_tries = self.max_tries if function.max_tries is None else function.max_tries
if job_try > max_tries:
t = (timestamp_ms() - enqueue_time_ms) / 1000
logger.warning('%6.2fs ! %s max retries %d exceeded', t, ref, max_tries)
self.jobs_failed += 1
result_data = serialize_result(
function_name,
args,
kwargs,
job_try,
enqueue_time_ms,
False,
JobExecutionFailed(f'max {max_tries} retries exceeded'),
start_ms,
timestamp_ms(),
ref,
self.queue_name,
serializer=self.job_serializer,
)
return await asyncio.shield(self.finish_failed_job(job_id, result_data))
result = no_result
exc_extra = None
finish = False
timeout_s = self.job_timeout_s if function.timeout_s is None else function.timeout_s
incr_score: Optional[int] = None
job_ctx = {
'job_id': job_id,
'job_try': job_try,
'enqueue_time': ms_to_datetime(enqueue_time_ms),
'score': score,
}
ctx = {**self.ctx, **job_ctx}
start_ms = timestamp_ms()
success = False
try:
s = args_to_string(args, kwargs)
extra = f' try={job_try}' if job_try > 1 else ''
if (start_ms - score) > 1200:
extra += f' delayed={(start_ms - score) / 1000:0.2f}s'
logger.info('%6.2fs → %s(%s)%s', (start_ms - enqueue_time_ms) / 1000, ref, s, extra)
self.job_tasks[job_id] = task = self.loop.create_task(function.coroutine(ctx, *args, **kwargs))
# run repr(result) and extra inside try/except as they can raise exceptions
try:
result = await asyncio.wait_for(task, timeout_s)
except (Exception, asyncio.CancelledError) as e:
exc_extra = getattr(e, 'extra', None)
if callable(exc_extra):
exc_extra = exc_extra()
raise
else:
result_str = '' if result is None else truncate(repr(result))
finally:
del self.job_tasks[job_id]
except (Exception, asyncio.CancelledError) as e:
finished_ms = timestamp_ms()
t = (finished_ms - start_ms) / 1000
if self.retry_jobs and isinstance(e, Retry):
incr_score = e.defer_score
logger.info('%6.2fs ↻ %s retrying job in %0.2fs', t, ref, (e.defer_score or 0) / 1000)
if e.defer_score:
incr_score = e.defer_score + (timestamp_ms() - score)
self.jobs_retried += 1
elif job_id in self.aborting_tasks and isinstance(e, asyncio.CancelledError):
logger.info('%6.2fs ⊘ %s aborted', t, ref)
result = e
finish = True
self.aborting_tasks.remove(job_id)
self.jobs_failed += 1
elif self.retry_jobs and isinstance(e, (asyncio.CancelledError, RetryJob)):
logger.info('%6.2fs ↻ %s cancelled, will be run again', t, ref)
self.jobs_retried += 1
else:
logger.exception(
'%6.2fs ! %s failed, %s: %s', t, ref, e.__class__.__name__, e, extra={'extra': exc_extra}
)
result = e
finish = True
self.jobs_failed += 1
else:
success = True
finished_ms = timestamp_ms()
logger.info('%6.2fs ← %s ● %s', (finished_ms - start_ms) / 1000, ref, result_str)
finish = True
self.jobs_complete += 1
keep_result_forever = (
self.keep_result_forever if function.keep_result_forever is None else function.keep_result_forever
)
result_timeout_s = self.keep_result_s if function.keep_result_s is None else function.keep_result_s
result_data = None
if result is not no_result and (keep_result_forever or result_timeout_s > 0):
result_data = serialize_result(
function_name,
args,
kwargs,
job_try,
enqueue_time_ms,
success,
result,
start_ms,
finished_ms,
ref,
self.queue_name,
serializer=self.job_serializer,
)
await asyncio.shield(
self.finish_job(
job_id,
finish,
result_data,
result_timeout_s,
keep_result_forever,
incr_score,
keep_in_progress,
)
)
async def finish_job(
self,
job_id: str,
finish: bool,
result_data: Optional[bytes],
result_timeout_s: Optional[float],
keep_result_forever: bool,
incr_score: Optional[int],
keep_in_progress: Optional[float],
) -> None:
async with self.pool as conn:
tr = conn.pipeline()
tr.multi()
delete_keys = []
in_progress_key = in_progress_key_prefix + job_id
if keep_in_progress is None:
delete_keys += [in_progress_key]
else:
tr.expire(in_progress_key, keep_in_progress)
if finish:
if result_data:
expire = None if keep_result_forever else result_timeout_s
tr.set(result_key_prefix + job_id, result_data, ex=expire)
delete_keys += [retry_key_prefix + job_id, job_key_prefix + job_id]
tr.zrem(abort_jobs_ss, job_id)
tr.zrem(self.queue_name, job_id)
elif incr_score:
tr.zincrby(self.queue_name, incr_score, job_id)
tr.delete(*delete_keys)
await tr.execute()
async def finish_failed_job(self, job_id: str, result_data: Optional[bytes]) -> None:
async with self.pool as conn:
tr = conn.pipeline()
tr.multi()
tr.delete(
retry_key_prefix + job_id,
in_progress_key_prefix + job_id,
job_key_prefix + job_id,
)
tr.zrem(abort_jobs_ss, job_id)
tr.zrem(self.queue_name, job_id)
# result_data would only be None if serializing the result fails
keep_result = self.keep_result_forever or self.keep_result_s > 0
if result_data is not None and keep_result: # pragma: no branch
expire = 0 if self.keep_result_forever else self.keep_result_s
tr.set(result_key_prefix + job_id, result_data, ex=expire)
await tr.execute()
async def heart_beat(self) -> None:
now = datetime.now()
await self.record_health()
cron_window_size = max(self.poll_delay_s, 0.5) # Clamp the cron delay to 0.5
await self.run_cron(now, cron_window_size)
async def run_cron(self, n: datetime, delay: float, num_windows: int = 2) -> None:
job_futures = set()
cron_delay = timedelta(seconds=delay * num_windows)
this_hb_cutoff = n + cron_delay
for cron_job in self.cron_jobs:
if cron_job.next_run is None:
if cron_job.run_at_startup:
cron_job.next_run = n
else:
cron_job.calculate_next(n)
# This isn't getting run this iteration in any case.
continue
# We queue up the cron if the next execution time is in the next
# delay * num_windows (by default 0.5 * 2 = 1 second).
if cron_job.next_run < this_hb_cutoff:
job_id = f'{cron_job.name}:{to_unix_ms(cron_job.next_run)}' if cron_job.unique else None
job_futures.add(
self.pool.enqueue_job(
cron_job.name, _job_id=job_id, _queue_name=self.queue_name, _defer_until=cron_job.next_run
)
)
cron_job.calculate_next(cron_job.next_run)
job_futures and await asyncio.gather(*job_futures)
async def record_health(self) -> None:
now_ts = time()
if (now_ts - self._last_health_check) < self.health_check_interval:
return
self._last_health_check = now_ts
pending_tasks = sum(not t.done() for t in self.tasks.values())
with self.pool.encoder_context(decode_responses=True):
queued = await self.pool.zcard(self.queue_name)
info = (
f'{datetime.now():%b-%d %H:%M:%S} j_complete={self.jobs_complete} j_failed={self.jobs_failed} '
f'j_retried={self.jobs_retried} j_ongoing={pending_tasks} queued={queued}'
)
await self.pool.psetex(self.health_check_key, int((self.health_check_interval + 1) * 1000), info.encode())
log_suffix = info[info.index('j_complete=') :]
if self._last_health_check_log and log_suffix != self._last_health_check_log:
logger.info('recording health: %s', info)
self._last_health_check_log = log_suffix
elif not self._last_health_check_log:
self._last_health_check_log = log_suffix
def _add_signal_handler(self, signum: Signals, handler: Callable[[Signals], None]) -> None:
try:
self.loop.add_signal_handler(signum, partial(handler, signum))
except NotImplementedError: # pragma: no cover
logger.debug('Windows does not support adding a signal handler to an eventloop')
def _jobs_started(self) -> int:
return self.jobs_complete + self.jobs_retried + self.jobs_failed + len(self.tasks)
def handle_sig(self, signum: Signals) -> None:
sig = Signals(signum)
logger.info(
'shutdown on %s ◆ %d jobs complete ◆ %d failed ◆ %d retries ◆ %d ongoing to cancel',
sig.name,
self.jobs_complete,
self.jobs_failed,
self.jobs_retried,
len(self.tasks),
)
for t in self.tasks.values():
if not t.done():
t.cancel()
self.main_task and self.main_task.cancel()
self.on_stop and self.on_stop(sig)
async def close(self) -> None:
if not self._handle_signals:
self.handle_sig(signal.SIGUSR1)
if not self._pool:
return
await asyncio.gather(*self.tasks.values())
await self.pool.delete(self.health_check_key)
if self.on_shutdown:
await self.on_shutdown(self.ctx)
if self._handle_signals:
await self.close_pool()
async def close_pool(self) -> None:
await self.pool.close() # type: ignore
self._pool = None
def __repr__(self) -> str:
return (
f'<Worker j_complete={self.jobs_complete} j_failed={self.jobs_failed} j_retried={self.jobs_retried} '
f'j_ongoing={sum(not t.done() for t in self.tasks.values())}>'
)
def get_kwargs(settings_cls: 'WorkerSettingsType') -> Dict[str, NameError]:
worker_args = set(inspect.signature(Worker).parameters.keys())
d = settings_cls if isinstance(settings_cls, dict) else settings_cls.__dict__
return {k: v for k, v in d.items() if k in worker_args}
def create_worker(settings_cls: 'WorkerSettingsType', **kwargs: Any) -> Worker:
return Worker(**{**get_kwargs(settings_cls), **kwargs}) # type: ignore
def run_worker(settings_cls: 'WorkerSettingsType', **kwargs: Any) -> Worker:
worker = create_worker(settings_cls, **kwargs)
worker.run()
return worker
async def async_check_health(
redis_settings: Optional[RedisSettings], health_check_key: Optional[str] = None, queue_name: Optional[str] = None
) -> int:
redis_settings = redis_settings or RedisSettings()
redis: ArkuRedis = await create_pool(redis_settings)
queue_name = queue_name or default_queue_name
health_check_key = health_check_key or (queue_name + health_check_key_suffix)
data = await redis.get(health_check_key)
if not data:
logger.warning('Health check failed: no health check sentinel value found')
r = 1
else:
logger.info('Health check successful: %s', data)
r = 0
await redis.close() # type: ignore
return r
def check_health(settings_cls: 'WorkerSettingsType') -> int:
"""
Run a health check on the worker and return the appropriate exit code.
:return: 0 if successful, 1 if not
"""
cls_kwargs = get_kwargs(settings_cls)
redis_settings = cast(Optional[RedisSettings], cls_kwargs.get('redis_settings'))
health_check_key = cast(Optional[str], cls_kwargs.get('health_check_key'))
queue_name = cast(Optional[str], cls_kwargs.get('queue_name'))
loop = asyncio.get_event_loop()
return loop.run_until_complete(async_check_health(redis_settings, health_check_key, queue_name))
