'''进程'''
from multiprocessing import Process
import os,time
def run(name):
print('运行子进程%s(%s)'%(name,os.getpid()))
def run2(name):
print('运行子进程是%s(%s)'%(name,os.getpid()))
if __name__ == "__main__":
print('当前子进程%s'%os.getpid())
# run('test') # 这行代码仍然在当前进程中执行
# 创建一个新的进程
p = Process(target=run,args=('test',))
print('开始执行子进程')
# 开始执行新进程
p.start()
# time.sleep(1)
# 将子进程加入到主进程中
p.join()
print('子进程执行完毕')
p2 = Process(target=run2,args=('test',))
p2.start()
p2.join()
'''进程池'''
from multiprocessing import Pool
import os,time,random
def task(name):
print('运行任务%s(%s)'%(name,os.getpid()))
start = time.time()
# 随机休眠1-3秒
time.sleep(random.randint(1,3))
end = time.time()
print('任务%s耗时为%.2f'%(name,(end-start)))
if __name__ == '__main__':
print('主进程是%s'%os.getpid())
# 初始化进程池
pool = Pool(4)
for i in range(6):
# 将任务交给进程池去执行
pool.apply_async(task,args=('任务%d'%i,))
pool.close()
pool.join()
'''线程'''
import threading,time
def task(name):
print('线程%s正在运行...'%threading.current_thread().name)
print(name)
if __name__ == '__main__':
print('主线程%s'%threading.current_thread().name)
# task()
# 创建一个新线程
t = threading.Thread(target=task,args=('传入一个参数',))
t.start()
t.join()
print('主线程%s运行结束'%threading.current_thread().name)
'''
多线程安全问题
python 中多任务一般使用多进程来完成
因为在python中多线程并不能真正提高效率
进程可以在不同的电脑上运行——分布式
'''
import threading,time
# 银行账户
balance = 0
# 创建一个锁
lock = threading.Lock()
def change(money):
global balance
# 存钱
balance = balance + money
balance = balance - money
def run(money):
for i in range(100000):
# 上锁
lock.acquire()
try:
change(money)
finally:
# 释放锁
lock.release()
t1 = threading.Thread(target=run,args=(10,))
t2 = threading.Thread(target=run,args=(8,))
t1.start()
t2.start()
t1.join()
t2.join()
print('balance=%d'%balance)
'''
t1:
x1 = balance + 10
balance = x1
x1 = balance - 10
balance = x1
t2:
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