深入解析Python中的多进程

# coding:utf-8
# 导入多进程的包，并重命名为mp
import multiprocessing as mp
# 主要工作
def p1():
    print("zxy")
if __name__ == "__main__":
    # 创建新进程
    new_process = mp.Process(target=p1, name="p1")
    # 启动这个进程
    new_process.start()
    # 阻塞该进程
    new_process.join()

# coding:utf-8
import time
import multiprocessing as mp
"""
    使用多进程时，运行程序所用的时间
"""
def job1(q):
    res = 0
    for i in range(100):
        res += i + i**5 +i**8
        time.sleep(0.1)
    # 将结果放入队列中
    q.put(res)
def job2(q):
    res = 0
    for i in range(100):
        res += i + i**5 +i**8
        time.sleep(0.1)
    q.put(res)
if __name__ == "__main__":
    start_time = time.time()
    # 创建队列
    q = mp.Queue()
    # 创建进程1
    process1 = mp.Process(target=job1, args=(q,))
    # 创建进程2
    process2 = mp.Process(target=job2, args=(q,))
    process1.start()
    process2.start()
    # 通过队列获取值
    res1 = q.get()
    res2 = q.get()
    print("res1为%d,res2为%d" % (res1, res2))
    end_time = time.time()
    print("整个过程所用时间为%s" %(end_time-start_time))

# coding:utf-8
import multiprocessing as mp
import time
import threading as th
"""
    多进程、多线程、普通方法的性能比较
"""
# 多进程工作
def mp_job(res):
    for i in range(10000000):
        res += i**5 + i**6
    print(res)
# 多线程工作
def mt_job(res):
    for i in range(10000000):
        res += i**5 + i**6
    print(res)
# 普通方法工作
def normal_job(res):
    for i in range(10000000):
        res += i ** 5 + i ** 6
    print(res)
if __name__ == "__main__":
    mp_sum = 0
    mp_start = time.time()
    process1 =mp.Process(target=mp_job, args=(mp_sum, ))
    process2 = mp.Process(target=mp_job, args=(mp_sum,))
    process1.start()
    process2.start()
    process1.join()
    process2.join()
    mp_end = time.time()
    print("多进程使用时间为", (mp_end-mp_start))
    mt_start = time.time()
    mt_sum = 0
    thread1 = th.Thread(target=mt_job, args=(mt_sum, ))
    thread2 = th.Thread(target=mt_job, args=(mt_sum, ))
    thread1.start()
    thread2.start()
    thread1.join()
    thread2.join()
    mt_end = time.time()
    print("多线程使用的时间是", (mt_end-mt_start))
    normal_start = time.time()
    normal_sum = 0
    # 进行两次
    normal_job(normal_sum)
    normal_job(normal_sum)
    normal_end = time.time()
    print("普通方法使用的时间是", (normal_end-normal_start))

# coding:utf-8
import time
import multiprocessing as mp
"""
    进程池pool的使用
"""
def job(num):
    time.sleep(1)
    return num * num
if __name__ == "__main__":
    start_time = time.time()
    # 括号里面不加参数时，默认使用进程池中所有进程
    pool = mp.Pool()
    res = pool.map(job, range(10))
    print(res)
    end_time = time.time()
    print("运行时间为", (end_time-start_time))

# coding:utf-8
import time
import multiprocessing as mp
"""
    进程池pool的使用
"""
def job(num):
    time.sleep(1)
    return num * num
if __name__ == "__main__":
    start_time = time.time()
    # 括号里面加参数时，指定两个进程进行处理
    pool = mp.Pool(processes=2)
    res = pool.map(job, range(10))
    print(res)
    end_time = time.time()
    print("运行时间为", (end_time-start_time))

# coding:utf-8
import time
def job(res):
    for i in range(10):
        res.append(i*i)
        time.sleep(1)
if __name__ == "__main__":
    start_time = time.time()
    res = []
    job(res)
    print(res)
    end_time =time.time()
    print("不使用进程池所用时间为", (end_time-start_time))

# coding:utf-8
import multiprocessing as mp
"""
    共享内存
"""
if __name__ == "__main__":
    # 第一个参数是数据类型的代码，i代表整数类型
    # 第二个参数是共享数据的值
    v = mp.Value("i", 0)

# coding:utf-8
import multiprocessing as mp
import time
"""
    进程中的锁lock
"""
def job(v, num):
    for i in range(10):
        v.value += num
        print(v.value)
        time.sleep(0.2)
if __name__ == "__main__":
    # 多进程中的共享内存
    v = mp.Value("i", 0)
    # 进程1让共享变量每次加1
    process1 = mp.Process(target=job, args=(v, 1))
    # 进程2让共享变量每次加3
    process2 = mp.Process(target=job, args=(v, 3))
    process1.start()
    process2.start()

# coding:utf-8
import multiprocessing as mp
import time
"""
    进程中的锁lock
"""
def job(v, num, l):
    # 加锁
    l.acquire()
    for i in range(10):
        v.value += num
        print(v.value)
        time.sleep(0.2)
    # 解锁
    l.release()
if __name__ == "__main__":
    # 创建进程锁
    l = mp.Lock()
    # 多进程中的共享内存
    v = mp.Value("i", 0)
    process1 = mp.Process(target=job, args=(v, 1, l))
    process2 = mp.Process(target=job, args=(v, 3, l))
    process1.start()
    process2.start()