1. 多進(jìn)程實(shí)現(xiàn)斐波那契

對于耗費(fèi)cpu的操作，多進(jìn)程由于多線程, 我拿斐波那契進(jìn)行比較發(fā)現(xiàn)多進(jìn)程速度遠(yuǎn)遠(yuǎn)高于多線程

# 多線程
import time
from concurrent.futures import ThreadPoolExecutor, as_completed

def fib(n):
    if n<=2:
        return 1
    return fib(n-1)+fib(n-2)

if __name__ == "__main__":
    with ThreadPoolExecutor(2) as executor:
        all_task = [executor.submit(fib, (num)) for num in range(38)]      # 39s
        start_time = time.time()
        for future in as_completed(all_task):
            data = future.result()
            print("exe result: {}".format(data))

        print("last time is: {}".format(time.time()-start_time))

# 多進(jìn)程
import time
from concurrent.futures import ThreadPoolExecutor, as_completed


def fib(n):
    if n<=2:
        return 1
    return fib(n-1)+fib(n-2)

if __name__ == "__main__":
    with ProcessPoolExecutor(2) as executor:
        all_task = [executor.submit(fib, (num)) for num in range(38)]      # 19
        start_time = time.time()
        for future in as_completed(all_task):
            data = future.result()
            print("exe result: {}".format(data))

        print("last time is: {}".format(time.time()-start_time))
    start_time = time.time()

2. 使用進(jìn)程池

import multiprocessing

#多進(jìn)程編程
import time
def get_html(n):
    time.sleep(n)
    print("sub_progress success")
    return n

if __name__ == "__main__":
pool = multiprocessing.Pool(multiprocessing.cpu_count())
 #使用線程池**********************************************************
    result = pool.apply_async(get_html, args=(3,))
    #等待所有任務(wù)完成
    pool.close()
    pool.join()

    print(result.get())   # sub_progress success
                          #3
# ********************************************************************
# imap 會(huì)按順序打印
    for result in pool.imap(get_html, [1,5,3]):
        print("{} sleep success".format(result))
# sub_progress success
# 1 sleep success
# sub_progress success
# sub_progress success
# 5 sleep success
# 3 sleep success
# ********************************************************************
# imap_unordered 按時(shí)間順序打印
    for result in pool.imap_unordered(get_html, [1,5,3]):
        print("{} sleep success".format(result))

# sub_progress success
# 1 sleep success
# sub_progress success
# 3 sleep success
# sub_progress success
# 5 sleep success

3. 進(jìn)程使用Queue

進(jìn)程的Queue在multiprocessing下才好用

import time
from multiprocessing import Process, Queue, Manager, Pool, Pipe
def producer(queue):
    queue.put("a")
    time.sleep(2)

def consumer(queue):
    time.sleep(2)
    data = queue.get()
    print(data)

if __name__=="__main__":
    queue = Queue(10)
    my_producter = Process(target=producer, args=(queue,))
    my_consumer = Process(target=consumer, args=(queue,))
    my_producter.start()
    my_consumer.start()
    my_producter.join()
    my_consumer.join()  # a

4. 共享變量不適用于多進(jìn)程

#共享全局變量不能適用于多進(jìn)程編程，可以適用于多線程
import time
from multiprocessing import Process, Queue, Manager, Pool, Pipe

def producer(a):
    a += 100
    time.sleep(2)

def consumer(a):
    time.sleep(2)
    print(a)

if __name__ == "__main__":
    a = 1
    my_producer = Process(target=producer, args=(a,))
    my_consumer = Process(target=consumer, args=(a,))
    my_producer.start()
    my_consumer.start()
    my_producer.join()
    my_consumer.join()  
    # 1

5. 通過pipe實(shí)現(xiàn)進(jìn)程間通信

# pipe性能高于queue

def producer(pipe):
    pipe.send("fz")


def consumer(pipe):
    print(pipe.recv())


if __name__== "__main__":
    receice_pipe, send_pipe = Pipe()
    # pipe只能適用于兩個(gè)進(jìn)程
    my_producer = Process(target=producer, args=(send_pipe,))
    my_consumer = Process(target=consumer, args=(receice_pipe,))

    my_producer.start()
    my_consumer.start()
    my_producer.join()
    my_consumer.join()
    # fz

6. 兩個(gè)進(jìn)程共同操作一個(gè)dict

除了dict managers包下包含了所有python的類型可以選擇

import time
from multiprocessing import Process, Queue, Manager, Pool, Pipe

def add_data(p_dict, key, value):
    p_dict[key]=value

if __name__=="__main__":
    progress_dict = Manager().dict()

    first_progress = Process(target=add_data, args=(progress_dict, "fz",21))
    second_progress = Process(target=add_data, args=(progress_dict, "xk",19))

    first_progress.start()
    second_progress.start()
    first_progress.join()
    second_progress.join()
    print(progress_dict)