1.使用Pool来创建进程
from multiprocessing import Pool def f(n): return n*n if __name__=="__main__": p=Pool(5) a=range(10) print(p.map(f,a))
p.map会将a列表中的数据依次循环给f函数。但是当函数需要两个参数时,该方法不适用。
2.使用Process来创建进程
def info(title): print title print ‘module name:‘, __name__ if hasattr(os, ‘getppid‘): # only available on Unix print ‘parent process:‘, os.getppid() print ‘process id:‘, os.getpid() def f(name): info(‘function f‘) print ‘hello‘, name if __name__ == ‘__main__‘: info(‘main line‘) p = Process(target=f, args=(‘bob‘,)) p.start() p.join() #串行
3.使用Pool.apply_async(异步)
from multiprocessing import Pool import time def f(n): print n*n time.sleep(1) return n*n if __name__ == ‘__main__‘: p = Pool(processes=5) res_list = [] for i in range(10): res = p.apply_async(f,[i,]) res_list.append(res) for item in res_list: print item.get()
共享内存的三种方法
1.使用multiprocessing中的Queue(将Queue封装了)
from multiprocessing import Process, Queue import Queue as Q2 def f(q,n): q.put([n, ‘hello‘]) print q.get() if __name__ == ‘__main__‘: q = Q2.Queue() for i in range(5): p = Process(target=f, args=(q,i)) p.start() # print q.get() # prints "[42, None, ‘hello‘]" from multiprocessing import Process, Lock import time def f(i): # l.acquire() time.sleep(1) print ‘hello world‘, i # l.release() if __name__ == ‘__main__‘: # lock = Lock() for num in range(10): Process(target=f, args=[num]).start()
2.使用values和array(灵活性较差,不推荐使用)
from multiprocessing import Process, Value, Array def f(n, a): n.value = 3.1415927 for i in range(len(a)): a[i] = -a[i] if __name__ == ‘__main__‘: num = Value(‘d‘, 0.0) arr = Array(‘i‘, range(10)) p = Process(target=f, args=(num, arr)) p.start() p.join() print num.value print arr[:]
3.使用Manager
from multiprocessing import Process, Manager def f(d, l): d[1] = ‘1‘ d[‘2‘] = 2 d[0.25] = None l.reverse() if __name__ == ‘__main__‘: manager = Manager() d = manager.dict() l = manager.list(range(10)) p = Process(target=f, args=(d, l)) p.start() p.join() print d print l
时间: 2024-10-13 16:07:31