Introduction to Python learning multi-process

Basic use of multiple processes

import multiprocessing
import os
import time
 
 
def run():
    print("父进程：%s，子进程：%s" % (os.getppid(), os.getpid()))
    time.sleep(2)
 
if __name__ == "__main__":
        p = multiprocessing.Process(target=run)
        p.start()
        p.join()

Inter-process communication

Memory is not shared between different processes. To achieve data exchange between two processes, you can use the following method

Queue

import multiprocessing
 
 
def f(q):
    q.put(11111)
 
if __name__ == "__main__":
    q = multiprocessing.Queue()
    p = multiprocessing.Process(target=f, args=(q,))
    p.start()
    print(q.get())

Pipe

import multiprocessing
 
 
def f(conn):
    conn.send(1)
    conn.send(2)
    print(conn.recv())
    conn.close()
 
if __name__ == "__main__":
    parent_conn, child_conn = multiprocessing.Pipe()
    p = multiprocessing.Process(target=f, args=(child_conn,))
    p.start()
    print(parent_conn.recv())
    print(parent_conn.recv())
    parent_conn.send(3)
    p.join()

Data sharing between processes

Manager

import multiprocessing
import os
 
 
def func(d, l):
    d[os.getpid()] = os.getpid()
    print(d)
    l.append(os.getpid())
    print(l)
 
if __name__ == "__main__":
    manager = multiprocessing.Manager()
    d = manager.dict()
    l = manager.list()
    p_list = []
    for i in range(5):
        p = multiprocessing.Process(target=func, args=(d, l))
        p.start()
        p_list.append(p)
    for p in p_list:
        p.join()

Process Lock

When multiple processes want to access shared resources, Lock can avoid access conflicts

import multiprocessing
 
 
def f(l, i):
    l.acquire()
    print("hello world", i)
    l.release()
 
if __name__ == "__main__":
    lock = multiprocessing.Lock()
    for num in range(10):
        p = multiprocessing.Process(target=f, args=(lock, num))
        p.start()

Process pool

The process pool maintains a process queue internally. When used, Then go to the process pool to get a process. If there is no usable process in the process pool, then the program will wait until there is a process in the process pool

import multiprocessing
import os
import time
 
 
def foo(i):
    time.sleep(2)
    print("in process", os.getpid())
    return i + 100
 
 
def bar(arg):
    print("==>exec done:", arg)
 
if __name__ == "__main__":
    pool = multiprocessing.Pool(5)
    for i in range(10):
        pool.apply_async(func=foo, args=(i,), callback=bar)
    print("end")
    pool.close()
    pool.join()

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