Multi-process data is not synchronized
import multiprocessing,time
'''
测试多进程抢票
并发执行,或导致数据不同步,那么我们需要做的是进程同步,进行加锁
'''
def worker(dict):
while True:
number = dict.get("ticket");
if number > 0:
# 模拟网络延迟
time.sleep(1);
number -= 1;
print("{},ticket = {}".format(multiprocessing.current_process().name,number));
dict.update({
"ticket":number});
else:
break;
def main():
# 创建贡献数据
manager = multiprocessing.Manager();
# 创建共享的字典对象
manager_dict = manager.dict(ticket = 5);
# 创建10个进程模拟操作
job_process = [multiprocessing.Process(target=worker,args=(manager_dict,),name = "售票员:{}".format(item)) for item in range(10)];
# 启动
for process in job_process:
process.start();
for process in job_process:
process.join();
print("所有进程执行完毕,字典最终数据为:{}".format(manager_dict))
if __name__ == '__main__':
main();
The process of using lock for synchronization is the same as that of Java, but if you lock in this way, it will cause performance degradation;
import multiprocessing,time
'''
测试多进程抢票
并发执行,或导致数据不同步,那么我们需要做的是进程同步,进行加锁
使用lock进行加锁和解锁
'''
def worker(dict,lock):
while True:
# 加锁 设置5秒的加锁时间,超时放弃加锁
lock.acquire(timeout = 5);
number = dict.get("ticket");
if number > 0:
# 模拟网络延迟
time.sleep(1);
number -= 1;
print("{},ticket = {}".format(multiprocessing.current_process().name,number));
dict.update({
"ticket":number});
else:
break;
# 解锁
lock.release();
def main():
# 创建锁
lock = multiprocessing.Lock();
# 创建贡献数据
manager = multiprocessing.Manager();
# 创建共享的字典对象
manager_dict = manager.dict(ticket = 5);
# 创建10个进程模拟操作
job_process = [multiprocessing.Process(target=worker,args=(manager_dict,lock,),name = "售票员:{}".format(item)) for item in range(10)];
# 启动
for process in job_process:
process.start();
for process in job_process:
process.join();
print("所有进程执行完毕,字典最终数据为:{}".format(manager_dict))
if __name__ == '__main__':
main();