python之multiprocessing
2021-05-23 16:29
标签：manage man 通过 lis 字典 join 解释 进程间 run multiprocessing模块提供本地和远程并发性，通过使用子进程而不是线程来有效地避开全局解释器锁。由于这个原因，多处理模块允许程序员在给定的机器上充分利用多个处理器。它在Unix和Windows上运行。 输出结果： 输出结果： 不同进程间内存是不共享的，要实现两个进程间的数据交换，可以使用一下方法：Queue,Pipes,Manager python之multiprocessing 标签：manage man 通过 lis 字典 join 解释 进程间 run 原文地址：https://www.cnblogs.com/bad-robot/p/9734493.html1、multiprocessing简介
2、进程的创建
2.1、创建一个进程
import multiprocessing,time
def run(name):
time.sleep(2)
print("hello", name)
if __name__ == "__main__":
p = multiprocessing.Process(target=run, args=(‘bob‘,))
p.start()
p.join()
2.2、创建多个进程
import multiprocessing,time
def run(name):
time.sleep(2)
print("hello", name)
if __name__ == "__main__":
for i in range(10):
p = multiprocessing.Process(target=run, args=(‘bob %s‘ % i,))
p.start()
# p.join()
2.3、进程中创建线程
import multiprocessing,time,threading
def thread_run():
print("threading id :%s" %threading.get_ident())
def run(name):
time.sleep(2)
print("hello", name)
t = threading.Thread(target=thread_run,)
t.start()
if __name__ == "__main__":
for i in range(10):
p = multiprocessing.Process(target=run, args=(‘bob %s‘ % i,))
p.start()
2.4、获取进程id
from multiprocessing import Process
import os
def info(title):
print(title)
print(‘module name:‘, __name__)
print(‘parent process:‘, os.getppid())
print(‘process id:‘, os.getpid())
print("\n\n")
def f(name):
info(‘\033[31;1mcalled from child process function f\033[0m‘)
print(‘hello‘, name)
if __name__ == ‘__main__‘:
info(‘\033[32;1mmain process line\033[0m‘)
main process line
module name: __main__
parent process: 6024
process id: 30756
2.5、获取进程id和子进程id
from multiprocessing import Process
import os
def info(title):
print(title)
print(‘module name:‘, __name__)
print(‘parent process:‘, os.getppid())
print(‘process id:‘, os.getpid())
print("\n\n")
def f(name):
info(‘\033[31;1mcalled from child process function f\033[0m‘)
print(‘hello‘, name)
if __name__ == ‘__main__‘:
info(‘\033[32;1mmain process line\033[0m‘)
p = Process(target=f, args=(‘bob‘,))
p.start()
# p.join()
main process line
module name: __main__
parent process: 6024
process id: 30756
3、进程间通信
3.1、Queue
from multiprocessing import Process, Queue
def f(q):
q.put([42, None, ‘hello‘])
if __name__ == ‘__main__‘:
q = Queue()
p = Process(target=f, args=(q,))
p.start()
print(q.get())
3.2、Pipes
from multiprocessing import Process, Pipe
def f(conn):
conn.send([42, None, ‘hello from child‘])
conn.send([42, None, ‘hello from child3‘])
print("",conn.recv())
conn.close()
if __name__ == ‘__main__‘:
parent_conn, child_conn = Pipe()
p = Process(target=f, args=(child_conn,))
p.start()
print("parent",parent_conn.recv()) # prints "[42, None, ‘hello‘]"
print("parent",parent_conn.recv()) # prints "[42, None, ‘hello‘]"
parent_conn.send(" from hshs") # prints "[42, None, ‘hello‘]"
p.join()
3.3、Manager
from multiprocessing import Process, Manager
import os
def f(d, l):
d[os.getpid()] =os.getpid()
l.append(os.getpid())
print(l)
if __name__ == ‘__main__‘:
with Manager() as manager:
d = manager.dict() #{} #生成一个字典，可在多个进程间共享和传递
l = manager.list(range(5))#生成一个列表，可在多个进程间共享和传递
p_list = []
for i in range(10):
p = Process(target=f, args=(d, l))
p.start()
p_list.append(p)
for res in p_list: #等待结果
res.join()
print(d)
print(l)
3.4、进程同步
from multiprocessing import Process, Lock
def f(l, i):
l.acquire()
print(‘hello world‘, i)
l.release()
if __name__ == ‘__main__‘:
lock = Lock()
for num in range(100):
Process(target=f, args=(lock, num)).start()
4、进程池
4.1、串行：apply
from multiprocessing import Process, Pool,freeze_support
import time
import os
def Foo(i):
time.sleep(2)
print("in process",os.getpid())
return i + 100
def Bar(arg):
print(‘-->exec done:‘, arg,os.getpid())
if __name__ == ‘__main__‘:
#freeze_support()
pool = Pool(processes=3) #允许进程池同时放入5个进程
print("主进程",os.getpid())
for i in range(10):
pool.apply(func=Foo, args=(i,)) #串行
print(‘end‘)
pool.close()
pool.join() #进程池中进程执行完毕后再关闭，如果注释，那么程序直接关闭。.join()
4.2、并行：apply_async
from multiprocessing import Process, Pool,freeze_support
import time
import os
def Foo(i):
time.sleep(2)
print("in process",os.getpid())
return i + 100
def Bar(arg):
print(‘-->exec done:‘, arg,os.getpid())
if __name__ == ‘__main__‘:
#freeze_support()
pool = Pool(processes=3) #允许进程池同时放入5个进程
print("主进程",os.getpid())
for i in range(10):
pool.apply_async(func=Foo, args=(i,), callback=Bar) #callback=回调
#pool.apply_async(func=Foo, args=(i,)) #串行
print(‘end‘)
pool.close()
pool.join() #进程池中进程执行完毕后再关闭，如果注释，那么程序直接关闭。.join()
文章标题：python之multiprocessing
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