다음 코드를 사용하여 threading을 사용하고 현재 카운트를 인쇄합니다.파이썬 : 특정 횟수의 스레딩
import threading
count = 0
def worker():
"""thread worker function"""
global count
count += 1
print(count)
threads = []
for i in range(5):
t = threading.Thread(target=worker)
threads.append(t)
t.start()
현재 5 개의 스레드로 설정되어 있습니다. 스레드가 특정 #에 도달 할 때까지 스레드를 계속 실행하려면 어떻게합니까? worker()이 100 번 실행될 때까지 5 스레드에서 실행됩니다.
while 루프를 반복하되 카운터와 테스트를 잠금으로 보호하십시오. 그렇지 않으면 테스트 된 값이 방금 증가시킨 값과 다릅니다.
스레드 ID를 추가 했으므로 어느 스레드가 실제로 카운터를 늘리는 지 확인할 수 있습니다.
또한 확인 : 이후에 증가합니다.
마지막에 스레드를 기다립니다.
import threading
lck = threading.Lock()
count = 0
def worker():
global count
"""thread worker function"""
while True:
lck.acquire()
if count==100:
lck.release()
break
count += 1
print(threading.current_thread() ,count)
lck.release()
threads = []
for i in range(5):
t = threading.Thread(target=worker)
threads.append(t)
t.start()
for t in threads:
t.join()
결과 :
(<Thread(Thread-1, started 5868)>, 1)
(<Thread(Thread-2, started 7152)>, 2)
(<Thread(Thread-3, started 6348)>, 3)
(<Thread(Thread-4, started 6056)>, 4)
(<Thread(Thread-1, started 5868)>, 5)
(<Thread(Thread-5, started 5748)>, 6)
(<Thread(Thread-2, started 7152)>, 7)
(<Thread(Thread-3, started 6348)>, 8)
(<Thread(Thread-4, started 6056)>, 9)
(<Thread(Thread-1, started 5868)>, 10)
(<Thread(Thread-5, started 5748)>, 11)
(<Thread(Thread-2, started 7152)>, 12)
(<Thread(Thread-3, started 6348)>, 13)
(<Thread(Thread-4, started 6056)>, 14)
(<Thread(Thread-1, started 5868)>, 15)
(<Thread(Thread-5, started 5748)>, 16)
(<Thread(Thread-2, started 7152)>, 17)
(<Thread(Thread-3, started 6348)>, 18)
(<Thread(Thread-4, started 6056)>, 19)
(<Thread(Thread-1, started 5868)>, 20)
(<Thread(Thread-5, started 5748)>, 21)
(<Thread(Thread-2, started 7152)>, 22)
(<Thread(Thread-3, started 6348)>, 23)
(<Thread(Thread-4, started 6056)>, 24)
(<Thread(Thread-1, started 5868)>, 25)
(<Thread(Thread-5, started 5748)>, 26)
(<Thread(Thread-2, started 7152)>, 27)
(<Thread(Thread-3, started 6348)>, 28)
(<Thread(Thread-4, started 6056)>, 29)
(<Thread(Thread-1, started 5868)>, 30)
(<Thread(Thread-5, started 5748)>, 31)
(<Thread(Thread-2, started 7152)>, 32)
(<Thread(Thread-3, started 6348)>, 33)
(<Thread(Thread-4, started 6056)>, 34)
(<Thread(Thread-1, started 5868)>, 35)
(<Thread(Thread-5, started 5748)>, 36)
(<Thread(Thread-2, started 7152)>, 37)
(<Thread(Thread-3, started 6348)>, 38)
(<Thread(Thread-4, started 6056)>, 39)
(<Thread(Thread-1, started 5868)>, 40)
(<Thread(Thread-5, started 5748)>, 41)
(<Thread(Thread-2, started 7152)>, 42)
(<Thread(Thread-3, started 6348)>, 43)
(<Thread(Thread-4, started 6056)>, 44)
(<Thread(Thread-1, started 5868)>, 45)
(<Thread(Thread-5, started 5748)>, 46)
(<Thread(Thread-2, started 7152)>, 47)
(<Thread(Thread-3, started 6348)>, 48)
(<Thread(Thread-4, started 6056)>, 49)
(<Thread(Thread-1, started 5868)>, 50)
(<Thread(Thread-5, started 5748)>, 51)
(<Thread(Thread-2, started 7152)>, 52)
(<Thread(Thread-3, started 6348)>, 53)
(<Thread(Thread-4, started 6056)>, 54)
(<Thread(Thread-1, started 5868)>, 55)
(<Thread(Thread-5, started 5748)>, 56)
(<Thread(Thread-2, started 7152)>, 57)
(<Thread(Thread-3, started 6348)>, 58)
(<Thread(Thread-4, started 6056)>, 59)
(<Thread(Thread-1, started 5868)>, 60)
(<Thread(Thread-5, started 5748)>, 61)
(<Thread(Thread-2, started 7152)>, 62)
(<Thread(Thread-3, started 6348)>, 63)
(<Thread(Thread-4, started 6056)>, 64)
(<Thread(Thread-1, started 5868)>, 65)
(<Thread(Thread-5, started 5748)>, 66)
(<Thread(Thread-2, started 7152)>, 67)
(<Thread(Thread-3, started 6348)>, 68)
(<Thread(Thread-4, started 6056)>, 69)
(<Thread(Thread-1, started 5868)>, 70)
(<Thread(Thread-5, started 5748)>, 71)
(<Thread(Thread-2, started 7152)>, 72)
(<Thread(Thread-3, started 6348)>, 73)
(<Thread(Thread-4, started 6056)>, 74)
(<Thread(Thread-1, started 5868)>, 75)
(<Thread(Thread-5, started 5748)>, 76)
(<Thread(Thread-2, started 7152)>, 77)
(<Thread(Thread-3, started 6348)>, 78)
(<Thread(Thread-4, started 6056)>, 79)
(<Thread(Thread-1, started 5868)>, 80)
(<Thread(Thread-5, started 5748)>, 81)
(<Thread(Thread-2, started 7152)>, 82)
(<Thread(Thread-3, started 6348)>, 83)
(<Thread(Thread-4, started 6056)>, 84)
(<Thread(Thread-1, started 5868)>, 85)
(<Thread(Thread-5, started 5748)>, 86)
(<Thread(Thread-2, started 7152)>, 87)
(<Thread(Thread-3, started 6348)>, 88)
(<Thread(Thread-4, started 6056)>, 89)
(<Thread(Thread-1, started 5868)>, 90)
(<Thread(Thread-5, started 5748)>, 91)
(<Thread(Thread-2, started 7152)>, 92)
(<Thread(Thread-3, started 6348)>, 93)
(<Thread(Thread-4, started 6056)>, 94)
(<Thread(Thread-1, started 5868)>, 95)
(<Thread(Thread-5, started 5748)>, 96)
(<Thread(Thread-2, started 7152)>, 97)
(<Thread(Thread-3, started 6348)>, 98)
(<Thread(Thread-4, started 6056)>, 99)
(<Thread(Thread-1, started 5868)>, 100)
루프 그것은, 물론.
lock = threading.Lock()
count = 0
def worker():
"""thread worker function"""
global count
while True:
with lock:
if count >= 100: break
count += 1
print(count)
공지 사항 threading.Lock와 count에 보호 액세스; GIL에 의존하는 것은 간단합니다.
솔직히 말해서 이와 같은 것을 원하면 잘못된 방향으로 가고 있음을 의미합니다. 이 코드는 stateful이고 stateful이므로 실제 병렬 실행과 멀리 떨어져 있습니다. 또한 보통 Python에서 코드를 병렬로 실행하려면 multiprocessing 모듈을 사용해야합니다.
당신의 목표는 총 100 번을 체크하는 경우 그래서, 기본적으로, 그것은 비 저장 방식으로 코드를 다시 작성하는 것이 좋습니다 :
import multiprocessing as mp
def worker_1(x):
for i in range(x)
print i
def worker_2(y):
print y
if __name__ == '__main__':
p = mp.Pool(5)
for x in p.pool(worker_1, [25, 25, 25, 25]):
// process result
pass
for y in p.pool(worker_2, range(100)):
// process result
pass