Python time.sleep（）与event.wait（）

Question

我想在我的多线程Python应用程序中定期执行操作。我已经看到了两种不同的方法

exit = False
def thread_func(): 
    while not exit:
       action()
       time.sleep(DELAY)

要么

exit_flag = threading.Event()
def thread_func(): 
    while not exit_flag.wait(timeout=DELAY):
       action()

一种方法比另一种方法有优势吗？是使用更少的资源还是与其他线程和GIL更好地协作？哪一个使我的应用程序中的其余线程响应更快？

（假设有一些外部事件集exit或exit_flag，我愿意在关闭时等待完整的延迟）

Answer 1

使用exit_flag.wait(timeout=DELAY)将具有更高的响应速度，因为在exit_flag设置时，您将立即退出while循环。使用time.sleep，即使在设置了事件之后，您也将在time.sleep通话中等待直到睡了DELAY几秒钟。

在实现方面，Python 2.x和Python 3.x具有非常不同的行为。在Python
2.xEvent.wait中，使用大量的小time.sleep调用在纯Python中实现：

from time import time as _time, sleep as _sleep

....
# This is inside the Condition class (Event.wait calls Condition.wait).
def wait(self, timeout=None):
    if not self._is_owned():
        raise RuntimeError("cannot wait on un-acquired lock")
    waiter = _allocate_lock()
    waiter.acquire()
    self.__waiters.append(waiter)
    saved_state = self._release_save()
    try:    # restore state no matter what (e.g., KeyboardInterrupt)
        if timeout is None:
            waiter.acquire()
            if __debug__:
                self._note("%s.wait(): got it", self)
        else:
            # Balancing act:  We can't afford a pure busy loop, so we
            # have to sleep; but if we sleep the whole timeout time,
            # we'll be unresponsive.  The scheme here sleeps very
            # little at first, longer as time goes on, but never longer
            # than 20 times per second (or the timeout time remaining).
            endtime = _time() + timeout
            delay = 0.0005 # 500 us -> initial delay of 1 ms
            while True:
                gotit = waiter.acquire(0)
                if gotit:
                    break
                remaining = endtime - _time()
                if remaining <= 0:
                    break
                delay = min(delay * 2, remaining, .05)
                _sleep(delay)
            if not gotit:
                if __debug__:
                    self._note("%s.wait(%s): timed out", self, timeout)
                try:
                    self.__waiters.remove(waiter)
                except ValueError:
                    pass
            else:
                if __debug__:
                    self._note("%s.wait(%s): got it", self, timeout)
    finally:
        self._acquire_restore(saved_state)

实际上，这意味着使用wait它可能比仅DELAY无条件地休眠整个计算机要消耗更多的CPU
，但这样做的好处是（DELAY响应时间长很多，取决于时间长短）。这也意味着需要经常重新获取GIL，以便可以安排下一次睡眠，同时time.sleep可以完全释放GIL
DELAY。现在，更频繁地获取GIL是否会对您应用程序中的其他线程产生明显影响？也许不是。这取决于正在运行的其他线程数以及它们承担的工作量。我的猜测是，除非您有大量线程，或者另一个线程正在执行大量CPU限制工作，否则它不会特别引人注目，但是它很容易同时尝试和观察。

在Python 3.x中，大部分实现都移至纯C代码：

import _thread # C-module
_allocate_lock = _thread.allocate_lock

class Condition:
    ...
    def wait(self, timeout=None):
        if not self._is_owned():
            raise RuntimeError("cannot wait on un-acquired lock")
        waiter = _allocate_lock()
        waiter.acquire()
        self._waiters.append(waiter)
        saved_state = self._release_save()
        gotit = False
        try:    # restore state no matter what (e.g., KeyboardInterrupt)
            if timeout is None:
                waiter.acquire()
                gotit = True
            else:
                if timeout > 0:
                    gotit = waiter.acquire(True, timeout)  # This calls C code
                else:
                    gotit = waiter.acquire(False)
            return gotit
        finally:
            self._acquire_restore(saved_state)
            if not gotit:
                try:
                    self._waiters.remove(waiter)
                except ValueError:
                    pass

class Event:
    def __init__(self):
        self._cond = Condition(Lock())
        self._flag = False

    def wait(self, timeout=None):
        self._cond.acquire()
        try:
            signaled = self._flag
            if not signaled:
                signaled = self._cond.wait(timeout)
            return signaled
        finally:
            self._cond.release()

和获得锁的C代码：

/* Helper to acquire an interruptible lock with a timeout.  If the lock acquire
 * is interrupted, signal handlers are run, and if they raise an exception,
 * PY_LOCK_INTR is returned.  Otherwise, PY_LOCK_ACQUIRED or PY_LOCK_FAILURE
 * are returned, depending on whether the lock can be acquired withing the
 * timeout.
 */
static PyLockStatus
acquire_timed(PyThread_type_lock lock, PY_TIMEOUT_T microseconds)
{
    PyLockStatus r;
    _PyTime_timeval curtime;
    _PyTime_timeval endtime;


    if (microseconds > 0) {
        _PyTime_gettimeofday(&endtime);
        endtime.tv_sec += microseconds / (1000 * 1000);
        endtime.tv_usec += microseconds % (1000 * 1000);
    }


    do {
        /* first a simple non-blocking try without releasing the GIL */
        r = PyThread_acquire_lock_timed(lock, 0, 0);
        if (r == PY_LOCK_FAILURE && microseconds != 0) {
            Py_BEGIN_ALLOW_THREADS  // GIL is released here
            r = PyThread_acquire_lock_timed(lock, microseconds, 1);
            Py_END_ALLOW_THREADS
        }

        if (r == PY_LOCK_INTR) {
            /* Run signal handlers if we were interrupted.  Propagate
             * exceptions from signal handlers, such as KeyboardInterrupt, by
             * passing up PY_LOCK_INTR.  */
            if (Py_MakePendingCalls() < 0) {
                return PY_LOCK_INTR;
            }

            /* If we're using a timeout, recompute the timeout after processing
             * signals, since those can take time.  */
            if (microseconds > 0) {
                _PyTime_gettimeofday(&curtime);
                microseconds = ((endtime.tv_sec - curtime.tv_sec) * 1000000 +
                                (endtime.tv_usec - curtime.tv_usec));

                /* Check for negative values, since those mean block forever.
                 */
                if (microseconds <= 0) {
                    r = PY_LOCK_FAILURE;
                }
            }
        }
    } while (r == PY_LOCK_INTR);  /* Retry if we were interrupted. */

    return r;
}

该实现是响应式的，不需要频繁唤醒就可以重新获取GIL，因此您可以两全其美。