Python signal.html() Examples

def stop(self, signal=None, frame=None):
        """Manage the shutdown process of the worker.

        This function has two purposes:

            1. Cancel all the futures created.
            2. And close all the database connections
               opened by Django. Even though we cancel the connections
               for every execution of the callback, we want to be sure
               that all the database connections are closed
               in this process.

        Exits with code 0 for a clean exit.

        :param signal: Needed for `signal.signal <https://docs.python.org/3/library/signal.html#signal.signal>`_  # noqa
        :param frame: Needed for `signal.signal <https://docs.python.org/3/library/signal.html#signal.signal>`_  # noqa
        """
        run_middleware_hook("pre_worker_stop", self._subscriptions)
        for future in self._futures:
            future.cancel()

        run_middleware_hook("post_worker_stop")
        sys.exit(0) 

def signal_handler(signal, frame=None):
    state_machine_execution_engine = core_singletons.state_machine_execution_engine
    core_singletons.shut_down_signal = signal

    # in this case the print is on purpose to see more easily if the interrupt signal reached the thread
    print(_("Signal '{}' received.\nExecution engine will be stopped and program will be shutdown!").format(
        SIGNALS_TO_NAMES_DICT.get(signal, "[unknown]")))

    # close gui properly
    gui_singletons.main_window_controller.get_controller('menu_bar_controller').on_quit_activate(None)

    post_gui_destruction()

    logging.shutdown()

    # Do not use sys.exit() in signal handler:
    # http://thushw.blogspot.de/2010/12/python-dont-use-sysexit-inside-signal.html
    # noinspection PyProtectedMember
    os._exit(0) 

def command(self):
        setproctitle('taskd')
        self.basic_setup()
        self.keep_running = True
        self.restart_when_done = False
        base.log.info('Starting taskd, pid %s' % os.getpid())
        signal.signal(signal.SIGHUP, self.graceful_restart)
        signal.signal(signal.SIGTERM, self.graceful_stop)
        signal.signal(signal.SIGUSR1, self.log_current_task)
        # restore default behavior of not interrupting system calls
        # see http://docs.python.org/library/signal.html#signal.siginterrupt
        # and http://linux.die.net/man/3/siginterrupt
        signal.siginterrupt(signal.SIGHUP, False)
        signal.siginterrupt(signal.SIGTERM, False)
        signal.siginterrupt(signal.SIGUSR1, False)
        self.worker() 

def _worker_loop(dataset, index_queue, data_queue, collate_fn, seed, init_fn, worker_id):
    global _use_shared_memory
    _use_shared_memory = True

    # Intialize C side signal handlers for SIGBUS and SIGSEGV. Python signal
    # module's handlers are executed after Python returns from C low-level
    # handlers, likely when the same fatal signal happened again already.
    # https://docs.python.org/3/library/signal.html Sec. 18.8.1.1
    _set_worker_signal_handlers()

    torch.set_num_threads(1)
    torch.manual_seed(seed)
    np.random.seed(seed)

    if init_fn is not None:
        init_fn(worker_id)

    while True:
        r = index_queue.get()
        if r is None:
            break
        idx, batch_indices = r
        try:
            samples = collate_fn([dataset[i] for i in batch_indices])
        except Exception:
            data_queue.put((idx, ExceptionWrapper(sys.exc_info())))
        else:
            data_queue.put((idx, samples)) 

def _worker_loop(dataset, index_queue, data_queue, collate_fn, seed, init_fn, worker_id):
    global _use_shared_memory
    _use_shared_memory = True

    # Intialize C side signal handlers for SIGBUS and SIGSEGV. Python signal
    # module's handlers are executed after Python returns from C low-level
    # handlers, likely when the same fatal signal happened again already.
    # https://docs.python.org/3/library/signal.html Sec. 18.8.1.1
    _set_worker_signal_handlers()

    torch.set_num_threads(1)
    torch.manual_seed(seed)
    np.random.seed(seed)

    if init_fn is not None:
        init_fn(worker_id)

    while True:
        r = index_queue.get()
        if r is None:
            break
        idx, batch_indices = r
        try:
            samples = collate_fn([dataset[i] for i in batch_indices])
        except Exception:
            data_queue.put((idx, ExceptionWrapper(sys.exc_info())))
        else:
            data_queue.put((idx, samples)) 

def init():
    """Register cleanup handler."""
    logger.debug("Registering cleanup handler")

    global __cleanup_done
    __cleanup_done = False

    # Will be OS-specific, see https://docs.python.org/2/library/signal.html
    atexit.register(cleanup_handler)
    signal.signal(signal.SIGTERM, cleanup_handler)
    if sys.platform == "darwin" or "linux" in sys.platform:
        # SIGHUP is not available on Windows
        signal.signal(signal.SIGHUP, cleanup_handler) 

def _worker_loop(
    dataset, index_queue, data_queue, collate_fn, seed, init_fn, worker_id
):
    global _use_shared_memory
    _use_shared_memory = True

    # Intialize C side signal handlers for SIGBUS and SIGSEGV. Python signal
    # module's handlers are executed after Python returns from C low-level
    # handlers, likely when the same fatal signal happened again already.
    # https://docs.python.org/3/library/signal.html Sec. 18.8.1.1
    #  C._set_worker_signal_handlers()

    torch.set_num_threads(1)
    torch.manual_seed(seed)

    if init_fn is not None:
        init_fn(worker_id)

    try:
        dataset.init()
    except AttributeError:
        pass

    while True:
        r = index_queue.get()

        if r is None:
            break

        idx, batch_indices = r
        try:
            samples = collate_fn([dataset[i] for i in batch_indices])
        except Exception:
            data_queue.put((idx, ExceptionWrapper(sys.exc_info())))
        else:
            data_queue.put((idx, samples)) 

def _worker_loop(
        dataset, index_queue, data_queue, collate_fn, seed, init_fn, worker_id
):
    global _use_shared_memory
    _use_shared_memory = True

    # Intialize C side signal handlers for SIGBUS and SIGSEGV. Python signal
    # module's handlers are executed after Python returns from C low-level
    # handlers, likely when the same fatal signal happened again already.
    # https://docs.python.org/3/library/signal.html Sec. 18.8.1.1
    #  C._set_worker_signal_handlers()

    torch.set_num_threads(1)
    torch.manual_seed(seed)

    if init_fn is not None:
        init_fn(worker_id)

    try:
        dataset.init()
    except AttributeError:
        pass

    while True:
        r = index_queue.get()

        if r is None:
            break

        idx, batch_indices = r
        try:
            samples = collate_fn([dataset[i] for i in batch_indices])
        except Exception:
            data_queue.put((idx, ExceptionWrapper(sys.exc_info())))
        else:
            data_queue.put((idx, samples)) 

def init():
    """Register cleanup handler"""

    # print "Registering cleanup handler"

    global __cleanup_done
    __cleanup_done = False

    # Will be OS-specific, see https://docs.python.org/2/library/signal.html
    atexit.register(cleanup_handler)
    signal.signal(signal.SIGTERM, cleanup_handler)
    if sys.platform == "darwin" or "linux" in sys.platform:
        # SIGHUP is not available on Windows
        signal.signal(signal.SIGHUP, cleanup_handler) 

def _worker_loop(dataset, index_queue, data_queue, collate_fn, seed, init_fn, worker_id):
    global _use_shared_memory
    _use_shared_memory = True

    # Intialize C side signal handlers for SIGBUS and SIGSEGV. Python signal
    # module's handlers are executed after Python returns from C low-level
    # handlers, likely when the same fatal signal happened again already.
    # https://docs.python.org/3/library/signal.html Sec. 18.8.1.1
    _set_worker_signal_handlers()

    torch.set_num_threads(1)
    random.seed(seed)
    torch.manual_seed(seed)

    if init_fn is not None:
        init_fn(worker_id)

    while True:
        r = index_queue.get()
        if r is None:
            break
        idx, batch_indices = r
        try:
            samples = collate_fn([dataset[i] for i in batch_indices])
        except Exception:
            data_queue.put((idx, ExceptionWrapper(sys.exc_info())))
        else:
            data_queue.put((idx, samples)) 

def _worker_loop(dataset, index_queue, data_queue, collate_fn, init_fn, worker_id):
    global _use_shared_memory
    _use_shared_memory = True

    # Intialize C side signal handlers for SIGBUS and SIGSEGV. Python signal
    # module's handlers are executed after Python returns from C low-level
    # handlers, likely when the same fatal signal happened again already.
    # https://docs.python.org/3/library/signal.html Sec. 18.8.1.1
    _set_worker_signal_handlers()

    torch.set_num_threads(1)

    if init_fn is not None:
        init_fn(worker_id)

    watchdog = ManagerWatchdog()

    while True:
        try:
            r = index_queue.get(timeout=MANAGER_STATUS_CHECK_INTERVAL)
        except queue.Empty:
            if watchdog.is_alive():
                continue
            else:
                break
        if r is None:
            break
        idx, batch_indices = r
        try:
            samples = collate_fn([dataset[i] for i in batch_indices])
        except Exception:
            data_queue.put((idx, ExceptionWrapper(sys.exc_info())))
        else:
            data_queue.put((idx, samples))
            del samples 

def parse_args() -> Tuple[argparse.Namespace, List[str]]:
    usage = dedent(
        """Scalene: a high-precision CPU and memory profiler.
        https://github.com/emeryberger/scalene
        % scalene yourprogram.py
        """
    )
    parser = argparse.ArgumentParser(
        prog="scalene",
        description=usage,
        formatter_class=argparse.RawTextHelpFormatter,
        allow_abbrev=False,
    )
    parser.add_argument("prog", type=str, help="program to be profiled")
    parser.add_argument(
        "--outfile",
        type=str,
        default=None,
        help="file to hold profiler output (default: stdout)",
    )
    parser.add_argument(
        "--html",
        dest="html",
        action="store_const",
        const=True,
        default=False,
        help="output as HTML (default: text)",
    )
    parser.add_argument(
        "--profile-interval",
        type=float,
        default=float("inf"),
        help="output profiles every so many seconds.",
    )
    parser.add_argument(
        "--wallclock",
        dest="wallclock",
        action="store_const",
        const=True,
        default=False,
        help="use wall clock time (default: virtual time)",
    )
    parser.add_argument(
        "--cpu-only",
        dest="cpuonly",
        action="store_const",
        const=True,
        default=False,
        help="only profile CPU time (default: profile CPU, memory, and copying)",
    )
    # the PID of the profiling process (for internal use only)
    parser.add_argument(
        "--pid", type=int, default=int(os.getpid()), help=argparse.SUPPRESS
    )
    # Parse out all Scalene arguments and jam the remaining ones into argv.
    # https://stackoverflow.com/questions/35733262/is-there-any-way-to-instruct-argparse-python-2-7-to-remove-found-arguments-fro
    args, left = parser.parse_known_args()
    return args, left