Source code for fennel.worker.executor

import asyncio
import logging
import signal
from concurrent.futures import ThreadPoolExecutor
from contextlib import asynccontextmanager
from dataclasses import asdict
from functools import partial
from logging.handlers import QueueHandler
from multiprocessing import Queue
from typing import Optional

import anyio
import structlog
import uvloop

from fennel.exceptions import Completed, UnknownTask
from fennel.job import Job
from fennel.utils import base64uuid, duration
from import Broker

logger = structlog.get_logger("fennel.worker")

EXIT_SIGNAL = "signal"
EXIT_COMPLETE = "complete"

[docs]class Executor: def __init__(self, app): """ The `Executor` is responsible for reading jobs from the Redis queue and executing them. Heartbeats are sent from the executor periodically (controlled by :attr:`fennel.settings.Settings.heartbeat_interval`). If they are missing for more than :attr:`fennel.settings.Settings.heartbeat_timeout` seconds, the executor will be assumed dead and all of its pending messages will be reinserted to the stream by another worker's maintenance function. Parameters ---------- app : fennel.App The application instance for which to start an `Executor`. """ = app self.settings = app.settings self.executor_id: str = base64uuid() Optional[Broker] = None self.threadpool = ThreadPoolExecutor(max_workers=app.settings.concurrency) self.must_stop: bool = False self.running: int = 0 self.done: = None
[docs] def start(self, exit: str = EXIT_SIGNAL, queue: Queue = None) -> None: """ Begin the main executor loop. Parameters ---------- exit : str The exit strategy. `EXIT_SIGNAL` is used when the worker should only stop on receipt of a interrupt or termination signal. `EXIT_COMPLETE` is used in tests to exit when all tasks from the queue have completed. queue : multiprocessing.Queue A `QueueHandler` will be used to send logs to this queue to avoid interleaving from multiple processes. Notes ----- Intended to run via :func:`fennel.worker.worker.start` which will supervise multiple `Executor` processes. `signal.SIGINT` and `signal.SIGTERM` are handled by gracefully shutting down, which means giving the executor processes a chance to finish their current tasks. """ if queue: # To prevent interleaved logging. logging.getLogger("fennel.worker").addHandler(QueueHandler(queue)) uvloop.install(), exit)
async def _start(self, exit) -> None: = await Broker.for_app( self.done = anyio.create_event() try: logger.warning("executor-started", executor=self.executor_id) await self._supervise(exit) except Completed: pass finally: logger.warning("executor-stopped", executor=self.executor_id) async def _supervise(self, exit): async with anyio.open_signal_receiver(signal.SIGINT, signal.SIGTERM) as signals: async with anyio.create_task_group() as tg: await tg.spawn(self._heartbeat) await tg.spawn(self._scheduler) await tg.spawn(self._maintenance) for i in range(self.settings.concurrency): await tg.spawn(self._loop, f"{self.executor_id}:{i}", exit) async for signum in signals: logger.critical("shutting-down") async with anyio.move_on_after(self.settings.grace_period) as scope: self.must_stop = True await self.done.wait() if scope.cancel_called: logger.warning("grace-period-exceeded") await tg.cancel_scope.cancel() return
[docs] @asynccontextmanager async def is_running(self): self.running += 1 try: yield finally: self.running -= 1 if self.running == 0: await self.done.set()
async def _loop(self, consumer_id: str, exit: str) -> None: """ The main consumer loop: read data from the stream and handle processing. """ async with self.is_running(): while not self.must_stop: await anyio.sleep(0) # Check for cancellation. results = await consumer=consumer_id, count=self.settings.prefetch_count, recover=False, timeout=self.settings.read_timeout, ) if exit == EXIT_COMPLETE and not results: raise Completed for xid, fields in results: job = await["uuid"]) await self._handle(xid, job, consumer_id) async def _handle(self, xid: str, job: Job, consumer_id: str) -> None: """ Handle the given job. All jobs are acknowledged and deleted after processing. Depending on the outcome, they will also be scheduled for reprocessing, their result will be stored, or they will be put in the dead-letter queue. """ with duration(logger, "executing", xid=xid, job=asdict(job), con=consumer_id): job = await self._execute(job) job = job.increment() if job.exception: if job.tries <= job.max_retries: await, job) logger.debug("ack-schedule", xid=xid, job=asdict(job)) else: await, job) logger.debug("ack-dead", xid=xid, job=asdict(job)) else: if not self.settings.results_enabled: await, job) logger.debug("ack", xid=xid, job=asdict(job)) else: await, job) logger.debug("ack-store", xid=xid, job=asdict(job)) async def _execute(self, job: Job) -> Job: """ Attempt execution of a task. If the task is a coroutine function, then await it in our current event loop, otherwise run the task in a thread pool executor so as not to block the loop. """ try: f =[job.task] args, kwargs = job.args, job.kwargs except KeyError: raise UnknownTask(f"Could not find function: {job.task}") try: if asyncio.iscoroutinefunction(f): val = await f(*args, **kwargs) else: loop = asyncio.get_running_loop() val = await loop.run_in_executor(self.threadpool, partial(f, *args, **kwargs)) except BaseException as e: logger.exception("execution-failed", job=asdict(job)) return job.replace( exception={ "original_type": type(e).__name__, "original_args": list(e.args), }, return_value=None, ) else: return job.replace(exception={}, return_value=val) async def _heartbeat(self) -> None: """ Publish a heartbeat for this executor. If heartbeats are missing for more than settings.heartbeat_timeout seconds, the executor will be considered dead and all its consumers' messages will be deleted and added to the stream for reprocessing. """ while True: await"heartbeat", executor=self.executor_id) await anyio.sleep(self.settings.heartbeat_interval) async def _scheduler(self) -> None: """ Find any jobs whose ETA has passed and add them to the stream. Jobs are stored in a sorted set by their expected time of arrival and we find tasks whose value is less than 'now'. """ while True: results = await"poll-schedule", executor=self.executor_id, results=results) await anyio.sleep(self.settings.schedule_interval) async def _maintenance(self) -> None: """ The maintenance script performs the following: 1. Find dead consumers (their executor heartbeats are missing for greater than settings.heartbeat_timeout). 2. Delete their pending messages and put them back in the stream for other consumers to process. 3. Delete the dead consumers (and the executor's last heartbeat). """ while True: results = await"maintenance", executor=self.executor_id, results=results) await anyio.sleep(self.settings.maintenance_interval)