ASh*_*lly 62 python multithreading sleep
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)
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要么
exit_flag = threading.Event()
def thread_func():
while not exit_flag.wait(timeout=DELAY):
action()
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一种方式优于另一种方式有优势吗?是否使用更少的资源,或者与其他线程和GIL玩得更好?哪一个使我的应用程序中的剩余线程更具响应性?
(假设一些外部事件集exit或者exit_flag,我愿意在关闭时等待完整的延迟)
dan*_*ano 63
使用exit_flag.wait(timeout=DELAY)将更具响应性,因为您将在exit_flag设置时立即突破while循环.随着time.sleep,该事件被设置即使,你会在附近等待time.sleep电话,直到你已经睡了DELAY秒.
在实现方面,Python 2.x和Python 3.x具有非常不同的行为.在Python中,2.x Event.wait是使用一堆小time.sleep调用在纯Python中实现的:
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)
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这实际上意味着使用wait可能比只是DELAY无条件地完全睡觉时更耗费CPU ,但是具有DELAY更多响应的好处(可能很多,取决于多长时间).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可以释放GIL DELAY.现在,更频繁地获取GIL会对应用程序中的其他线程产生明显影响吗?也许或许没有.这取决于正在运行的其他线程数以及它们具有哪种工作负载.我的猜测是它不会特别明显,除非你有大量的线程,或者可能是另一个线程做了大量的CPU绑定工作,但它很容易尝试两种方式看看.
在Python 3.x中,大部分实现都转移到了纯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()
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以及获取锁的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;
}
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这种实现具有响应性,并且不需要频繁唤醒重新获取GIL,因此您可以获得两全其美的效果.
Python 2.*
就像@dano所说的那样,event.wait更具响应性,
但是当系统时间向后改变时它会很危险,而它正在等待!错误#1607041:Condition.wait超时因时钟更改而失败
看这个样本:
def someHandler():
while not exit_flag.wait(timeout=0.100):
action()
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通常action()会在100ms的内部调用.
但是当你改变时间时.一小时后,两个动作之间暂停一小时.
结论:当允许时间可以改变时,你应该避免 event.wait
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