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How to use kill_workers method in Slash

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reusable_executor.py

Source:reusable_executor.py

1###############################################################################2# Reusable ProcessPoolExecutor3#4# author: Thomas Moreau and Olivier Grisel5#6import time7import warnings8import threading9import multiprocessing as mp10from .process_executor import ProcessPoolExecutor, EXTRA_QUEUED_CALLS11from .backend.context import cpu_count12from .backend import get_context13__all__ = ['get_reusable_executor']14# Python 2 compat helper15STRING_TYPE = type("")16# Singleton executor and id management17_executor_lock = threading.RLock()18_next_executor_id = 019_executor = None20_executor_kwargs = None21def _get_next_executor_id():22    """Ensure that each successive executor instance has a unique, monotonic id.23    The purpose of this monotonic id is to help debug and test automated24    instance creation.25    """26    global _next_executor_id27    with _executor_lock:28        executor_id = _next_executor_id29        _next_executor_id += 130        return executor_id31def get_reusable_executor(max_workers=None, context=None, timeout=10,32                          kill_workers=False, reuse="auto",33                          job_reducers=None, result_reducers=None,34                          initializer=None, initargs=(), env=None):35    """Return the current ReusableExectutor instance.36    Start a new instance if it has not been started already or if the previous37    instance was left in a broken state.38    If the previous instance does not have the requested number of workers, the39    executor is dynamically resized to adjust the number of workers prior to40    returning.41    Reusing a singleton instance spares the overhead of starting new worker42    processes and importing common python packages each time.43    ``max_workers`` controls the maximum number of tasks that can be running in44    parallel in worker processes. By default this is set to the number of45    CPUs on the host.46    Setting ``timeout`` (in seconds) makes idle workers automatically shutdown47    so as to release system resources. New workers are respawn upon submission48    of new tasks so that ``max_workers`` are available to accept the newly49    submitted tasks. Setting ``timeout`` to around 100 times the time required50    to spawn new processes and import packages in them (on the order of 100ms)51    ensures that the overhead of spawning workers is negligible.52    Setting ``kill_workers=True`` makes it possible to forcibly interrupt53    previously spawned jobs to get a new instance of the reusable executor54    with new constructor argument values.55    The ``job_reducers`` and ``result_reducers`` are used to customize the56    pickling of tasks and results send to the executor.57    When provided, the ``initializer`` is run first in newly spawned58    processes with argument ``initargs``.59    The environment variable in the child process are a copy of the values in60    the main process. One can provide a dict ``{ENV: VAL}`` where ``ENV`` and61    ``VAR`` are string literals to overwrite the environment variable ``ENV``62    in the child processes to value ``VAL``. The environment variables are set63    in the children before any module is loaded. This only works with with the64    ``loky`` context and it is unreliable on Windows with Python < 3.6.65    """66    _executor, _ = _ReusablePoolExecutor.get_reusable_executor(67        max_workers=max_workers, context=context, timeout=timeout,68        kill_workers=kill_workers, reuse=reuse, job_reducers=job_reducers,69        result_reducers=result_reducers, initializer=initializer,70        initargs=initargs, env=env71    )72    return _executor73class _ReusablePoolExecutor(ProcessPoolExecutor):74    def __init__(self, submit_resize_lock, max_workers=None, context=None,75                 timeout=None, executor_id=0, job_reducers=None,76                 result_reducers=None, initializer=None, initargs=(),77                 env=None):78        super(_ReusablePoolExecutor, self).__init__(79            max_workers=max_workers, context=context, timeout=timeout,80            job_reducers=job_reducers, result_reducers=result_reducers,81            initializer=initializer, initargs=initargs, env=env)82        self.executor_id = executor_id83        self._submit_resize_lock = submit_resize_lock84    @classmethod85    def get_reusable_executor(cls, max_workers=None, context=None, timeout=10,86                              kill_workers=False, reuse="auto",87                              job_reducers=None, result_reducers=None,88                              initializer=None, initargs=(), env=None):89        with _executor_lock:90            global _executor, _executor_kwargs91            executor = _executor92            if max_workers is None:93                if reuse is True and executor is not None:94                    max_workers = executor._max_workers95                else:96                    max_workers = cpu_count()97            elif max_workers <= 0:98                raise ValueError(99                    "max_workers must be greater than 0, got {}."100                    .format(max_workers))101            if isinstance(context, STRING_TYPE):102                context = get_context(context)103            if context is not None and context.get_start_method() == "fork":104                raise ValueError(105                    "Cannot use reusable executor with the 'fork' context"106                )107            kwargs = dict(context=context, timeout=timeout,108                          job_reducers=job_reducers,109                          result_reducers=result_reducers,110                          initializer=initializer, initargs=initargs,111                          env=env)112            if executor is None:113                is_reused = False114                mp.util.debug("Create a executor with max_workers={}."115                              .format(max_workers))116                executor_id = _get_next_executor_id()117                _executor_kwargs = kwargs118                _executor = executor = cls(119                    _executor_lock, max_workers=max_workers,120                    executor_id=executor_id, **kwargs)121            else:122                if reuse == 'auto':123                    reuse = kwargs == _executor_kwargs124                if (executor._flags.broken or executor._flags.shutdown125                        or not reuse):126                    if executor._flags.broken:127                        reason = "broken"128                    elif executor._flags.shutdown:129                        reason = "shutdown"130                    else:131                        reason = "arguments have changed"132                    mp.util.debug(133                        "Creating a new executor with max_workers={} as the "134                        "previous instance cannot be reused ({})."135                        .format(max_workers, reason))136                    executor.shutdown(wait=True, kill_workers=kill_workers)137                    _executor = executor = _executor_kwargs = None138                    # Recursive call to build a new instance139                    return cls.get_reusable_executor(max_workers=max_workers,140                                                     **kwargs)141                else:142                    mp.util.debug(143                        "Reusing existing executor with max_workers={}."144                        .format(executor._max_workers)145                    )146                    is_reused = True147                    executor._resize(max_workers)148        return executor, is_reused149    def submit(self, fn, *args, **kwargs):150        with self._submit_resize_lock:151            return super(_ReusablePoolExecutor, self).submit(152                fn, *args, **kwargs)153    def _resize(self, max_workers):154        with self._submit_resize_lock:155            if max_workers is None:156                raise ValueError("Trying to resize with max_workers=None")157            elif max_workers == self._max_workers:158                return159            if self._executor_manager_thread is None:160                # If the executor_manager_thread has not been started161                # then no processes have been spawned and we can just162                # update _max_workers and return163                self._max_workers = max_workers164                return165            self._wait_job_completion()166            # Some process might have returned due to timeout so check how many167            # children are still alive. Use the _process_management_lock to168            # ensure that no process are spawned or timeout during the resize.169            with self._processes_management_lock:170                processes = list(self._processes.values())171                nb_children_alive = sum(p.is_alive() for p in processes)172                self._max_workers = max_workers173                for _ in range(max_workers, nb_children_alive):174                    self._call_queue.put(None)175            while (len(self._processes) > max_workers176                   and not self._flags.broken):177                time.sleep(1e-3)178            self._adjust_process_count()179            processes = list(self._processes.values())180            while not all([p.is_alive() for p in processes]):181                time.sleep(1e-3)182    def _wait_job_completion(self):183        """Wait for the cache to be empty before resizing the pool."""184        # Issue a warning to the user about the bad effect of this usage.185        if len(self._pending_work_items) > 0:186            warnings.warn("Trying to resize an executor with running jobs: "187                          "waiting for jobs completion before resizing.",188                          UserWarning)189            mp.util.debug("Executor {} waiting for jobs completion before"190                          " resizing".format(self.executor_id))191        # Wait for the completion of the jobs192        while len(self._pending_work_items) > 0:193            time.sleep(1e-3)194    def _setup_queues(self, job_reducers, result_reducers):195        # As this executor can be resized, use a large queue size to avoid196        # underestimating capacity and introducing overhead197        queue_size = 2 * cpu_count() + EXTRA_QUEUED_CALLS198        super(_ReusablePoolExecutor, self)._setup_queues(...

work_handler.py

Source:work_handler.py

...59                )60            )61            self.workers[-1].start()62    def _build_workers(self, func, n=1, on_kill=None, timeout=1, max_queue_size=-1):63        self.kill_workers(self.workers)64        self.workers = []65        self.queue = Queue(max_queue_size)66        for _ in range(n):67            self.workers.append(68                ThreadWorker(69                    self.queue,70                    func,71                    on_kill=on_kill,72                    on_start=on_start,73                    timeout=timeout,74                )75            )76            self.workers[-1].start()77    def kill_workers(self):78        for worker in self.workers:79            worker.kill()80            worker.join()81    def kill_workers_on_completion(self):82        while True:83            time.sleep(0.2)84            if self.queue.empty():85                break86        self.kill_workers()87class RedisWorker:88    def __init__(self, q, on_kill=None):89        self.queue = q90        self.on_kill = on_kill91    def run(self):92        start_worker_cmd = shlex.split("rq worker " + self.queue.name)93        self.process = Popen(start_worker_cmd)94    def kill(self):95        self.process.kill()96        if self.on_kill:97            self.on_kill()98class RedisManager:99    def __init__(self, n=1, on_kill=None, q_name="default-redis-queue"):100        redis_conn = Redis()101        self.queue = rQueue(q_name, connection=redis_conn)102        start_redis_server_cmd = shlex.split("redis-server")103        self.server = Popen(start_redis_server_cmd)104        self.workers = []105        for _ in range(n):106            self.workers.append(RedisWorker(self.queue, on_kill=on_kill))107            self.workers[-1].run()108    def kill_workers_on_completion(self):109        while True:110            time.sleep(0.2)111            if len(self.queue.job_ids) == 0:112                break113        self.kill_workers()114    def kill_workers(self):115        self.server.kill()116        for worker in self.workers:117            worker.kill()118class ProcessWorker(multiprocessing.Process):119    def __init__(self, q, func, timeout=1, on_kill=None, on_start=None):120        multiprocessing.Process.__init__(self)121        log.info("New Worker Process: {}".format(self.name))122        self._queue = q123        self._function = func124        self._timeout = timeout125        self._kill = False126        self._on_kill = on_kill127        self._on_start = on_start128        if self._on_start:129            self._on_start()130    def run(self):131        while not self._kill:132            try:133                log.debug("{} - Pulling from Queue".format(self.name))134                work = self._queue.get(timeout=self._timeout)135            except queue.Empty:136                log.debug("{} - Timed Out".format(self.name))137                continue138            if work:139                log.debug("{} - Running {}".format(self.name, self._function))140                log.debug("{} - Input: {}".format(self.name, work))141                self._function(work)142        if self._on_kill:143            self._on_kill()144        # print('Worker {} Dying'.format(os.getpid()))145    def kill(self):146        self._kill = True147class ProcessManager:148    def __init__(149        self, func, n=1, on_kill=None, on_start=None, timeout=1, max_queue_size=-1150    ):151        self.queue = mQueue(max_queue_size)152        self._timeout = timeout153        self.workers = []154        for _ in range(n):155            self.workers.append(156                ProcessWorker(157                    self.queue,158                    func,159                    on_kill=on_kill,160                    on_start=on_start,161                    timeout=timeout,162                )163            )164            self.workers[-1].start()165    def _build_workers(self, func, n=1, on_kill=None, timeout=1, max_queue_size=-1):166        self.kill_workers(self.workers)167        self.workers = []168        self.queue = mQueue(max_queue_size)169        for _ in range(n):170            self.workers.append(171                ProcessWorker(172                    self.queue,173                    func,174                    on_kill=on_kill,175                    on_start=on_start,176                    timeout=timeout,177                )178            )179            self.workers[-1].start()180    def kill_workers(self):181        for worker in self.workers:182            worker.kill()183            worker.join()184    def kill_workers_on_completion(self):185        while True:186            time.sleep(0.2)187            if self.queue.empty():188                break189        self.kill_workers()190def WorkerManager(191    func=None,192    n=1,193    on_kill=None,194    on_start=None,195    timeout=1,196    max_queue_size=-1,197    parallelization="thread",198    q_name="default-redis-queue",199):200    if parallelization == "thread":201        assert callable(func)202        return ThreadManager(203            func,...

manage.py

Source:manage.py

...17    logging.info(f"{sender} â {message}")18def get_pid_file():19    pid_file = path.join(utils.project_dir(), WORKER_PIDS)20    return pid_file21def kill_workers():22    pid_file = get_pid_file()23    if not path.exists(pid_file):24        print("Looks like there's no workers to stop. Please verify it manually")25        return26    count = 027    with open(pid_file) as fp:28        for pid in fp:29            try:30                pid = int(pid)31            except ValueError:32                logging.debug(f"kill_workers could not parse pid `{pid}`")33                continue34            _info(f"Stopping worker process: {pid}", "kill_workers")35            outputs = getoutput(f"ps -p {pid}")36            if WORKER in outputs:37                os.kill(pid, signal.SIGTERM)38                count += 139            else:40                logging.debug(41                    f"Looks like process {pid} isn't a worker"42                    f"`ps -p` result: `{outputs}`"43                )44    os.remove(pid_file)45    _info(f"Stopped {count} workers", "kill_workers")46def erase_database():47    database = DatabaseAdapter()48    database.drop_urls_table()49    _info("Database cleaned", "erase_database")50def load_urls_to_database(urls_file: str):51    _info(f"Loading `{urls_file}` into database", "load_urls_to_database")52    count = 053    errors = 054    database = DatabaseAdapter()55    if not path.isfile(urls_file):56        _info(f"Given path: `{urls_file}` is not a file", "load_urls_to_database")57        return58    with open(urls_file) as fp:59        database.create_urls_table()60        with database.connect():61            with database.commit():62                for url in fp:63                    url = url.strip()64                    database.naked_insert_url(url)65                    count += 166    _info(f"Loaded {count} urls into database with {errors} errors", "load_urls_to_database")67def start_workers(count: int, debug: bool):68    _info(f"Starting {count} workers", "start_workers")69    worker_cmd = [path.join(utils.project_dir(), WORKER)]70    if debug:71        worker_cmd.append("-d")72    with open(get_pid_file(), "at") as fp:73        for i in range(count):74            pid = Popen(worker_cmd).pid75            _info(f"Started worker with pid {pid}", "start_workers")76            fp.write(f"{pid}\n")77            # SQLite doesn't allow multi process safe connection78            # This delay is for letting workers at least start safely79            time.sleep(START_DELAY)80            # In general this is a weak decision. That shouldn't be done this way in81            # the Production82            # On the other hand, in the production we would use better DBMS which83            # Could handle row-level locks84def start_threaded_workers(count: int = 1):85    threads = [ThreadedWorker(i) for i in range(count)]86    for t in threads:87        time.sleep(0.3)88        t.start()89    _info(f"Starting {count} threaded workers", "start_threaded_workers")90    for t in threads:91        _info(f"{t.name} â finished it's work", "start_threaded_workers")92        t.join()93    _info(f"All {count} workers are done", "start_threaded_workers")94if __name__ == '__main__':95    parser = argparse.ArgumentParser(96        description="Workers manager.",97        epilog="""98        The above flags could be used simultaneously.99        However, actions would be executed in the certain order: 100        0 â `stop`101        1 â `erase`102        2 â `load`103        3 â `workers` & `debug`104        """)105    parser.add_argument("-s", "--stop", help="Stop all running workers", action="store_true")106    parser.add_argument("-e", "--erase", help="Erase database.", action="store_true")107    parser.add_argument("-l", "--load", help="Path to a file with urls to load into database",108                        type=str)109    parser.add_argument("-w", "--workers", help="Start given number of workers", type=int)110    parser.add_argument("-t", "--threads", help="Start given number of threaded workers",111                        type=int)112    parser.add_argument("-d", "--debug", help="Enable debug logging in workers",113                        action="store_true")114    args = parser.parse_args()115    utils.configure_logger(args.debug)116    if args.workers is not None and args.threads is not None:117        print("You couldn't start both threaded and process based workers simultaneously")118        exit(1)119    if args.stop:120        kill_workers()121    if args.erase:122        erase_database()123    if args.load:124        load_urls_to_database(args.load)125    if args.threads:126        if args.threads < 1:127            print("Please let us start at least 1 thread")128            exit(2)129        if args.threads > 10:130            print(f"We let you start {args.threads} but please reconsider it")131        start_threaded_workers(args.threads)132    if args.workers:...

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