멀티 프로세싱, 멀티 스레딩
목차
기초개념
1. 멀티 프로세싱(Multi Processing) #process #concurrent
- multiprocessing 모듈
- concurrent 모듈
2. 멀티 스레딩(Multi Threading) #threading #concurrent
- threading 모듈
- concurrent 모듈
기초 개념
프로세스(process) = 실행중인 프로그램 : 멀티코어 시스템에서 병렬 실행 가능
스레드(thread) = 동일한 프로세스 내에서 실행되는 작은 실행 단위
1. 멀티 프로세싱(Multi Processing) #process #concurrent
- cpu 집약적인 처리에 유용
multiprocessing 모듈
import multiprocessing
import time
def worker(num):
"""스레드가 실행할 함수"""
print(f'Worker {num} 시작')
time.sleep(2)
print(f'Worker {num} 완료')
if __name__ == "__main__":
processes = []
for i in range(5):
process = multiprocessing.Process(target=worker, args=(i,))
processes.append(process)
process.start()
for process in processes:
process.join()
print("모든 작업 완료")
concurrent 모듈
from concurrent.futures import ProcessPoolExecutor
import time
def square(n):
time.sleep(1)
return n * n
if __name__ == '__main__':
with ProcessPoolExecutor(max_workers=4) as executor:
numbers = [1, 2, 3, 4, 5]
results = list(executor.map(square, numbers))
print(results)
2. 멀티 스레딩(Multi Threading) #threading #concurrent
- IO바운드에 유용(네트워크 통신 등)
- GIL(Global Interpreter Lock) : 하나의 스레드만 사용가능하게끔 제한해서 cpu연산 집약에선 성능향상X
threading 모듈
import threading
import time
def worker(num):
"""스레드가 실행할 함수"""
print(f'Worker {num} 시작')
time.sleep(2)
print(f'Worker {num} 완료')
if __name__ == "__main__":
threads = []
for i in range(5):
thread = threading.Thread(target=worker, args=(i,))
threads.append(thread)
thread.start()
for thread in threads:
thread.join()
print("모든 작업 완료")
concurrent 모듈
from concurrent.futures import ThreadPoolExecutor
import time
def square(n):
time.sleep(1)
return n * n
if __name__ == '__main__':
with ThreadPoolExecutor(max_workers=4) as executor:
numbers = [1, 2, 3, 4, 5]
results = list(executor.map(square, numbers))
print(results)
