我有一个问题,这个问题与我的问题并没有真正的关系,而是为什么它不是一个问题。也许有点傻,但我对课程不太熟悉,我正在努力学习。假设我有一个定义如下的类:
import numpy as np
import multiprocessing as mp
class Foo(object):
def __init__(self, a):
self.a = a
def Sum(self, b):
self.a = np.random.randint(10)
return self.a + b, self.a我创建了一个对象:
foo = Foo(1)然后,在不同进程之间并行计算b的不同值的求和结果:
def Calc(b):
return foo.Sum(b)
pool = mp.Pool(processes=2)
b = [0, 1, 2, 3]
out = pool.map(Calc, b)
print(out)哪种打印(在一种情况下是随机的):
[(8, 8), (5, 4), (3, 1), (7, 4)]这是正确的。我的问题是,不同的进程如何能够同时修改类属性a(在本例中,操作相当快,但在我的实际示例中,操作需要几秒钟,如果不是分钟,那么并行化)而不影响彼此?
发布于 2020-10-30 15:57:47
每个过程都是独立的,它们之间没有任何交流。当您将foo对象发送到不同的进程时,它们不再是同一件事了--它们中有许多是自己做的事情。您的问题实际上不是关于类或类实例,而是关于在不同进程中发生的事情。
打印实例的id及其a属性可以说明。
import multiprocessing as mp
import numpy as np
class Foo(object):
def __init__(self, a):
self.a = a
def Sum(self, b):
s = f'I am {id(self)}, a before={self.a}'
self.a = np.random.randint(10)
print(f'{s} | a after={self.a}')
return self.a + b, self.a
foo = Foo(1)
def Calc(b):
return foo.Sum(b)
if __name__ == '__main__':
print(f'original foo id:{id(foo)}')
pool = mp.Pool(processes=2)
b = [0, 1, 2, 3, 5, 6, 7, 8]
out = pool.map(Calc, b)
print(out)
print(f'{id(foo)}.a is still {foo.a}')
# not sure why this is necessary
pool.terminate()然后从命令提示符运行:
PS C:\pyprojects> py -m tmp
original foo id:2235026702928
I am 1850261105632, a before=1 | a after=4
I am 1905926138848, a before=1 | a after=1
I am 1850261105632, a before=4 | a after=8
I am 1905926138848, a before=1 | a after=9
I am 1850261105632, a before=8 | a after=2
I am 1905926138848, a before=9 | a after=9
I am 1850261105632, a before=2 | a after=7
I am 1905926138848, a before=9 | a after=3
[(4, 4), (2, 1), (10, 8), (12, 9), (7, 2), (15, 9), (14, 7), (11, 3)]
2235026702928.a is still 1播放打印字符串:
import multiprocessing as mp
import numpy as np
import os
class Foo(object):
def __init__(self, a):
self.a = a
def Sum(self, b):
s = f'I am {id(self)}, a: before={self.a}'
self.a = np.random.randint(10)
s = f'{s} | after={self.a}'
return os.getpid(),s,(self.a + b, self.a),b
foo = Foo(1)
def Calc(b):
return foo.Sum(b)
if __name__ == '__main__':
print(f'original foo id:{id(foo)}')
pool = mp.Pool(processes=2)
b = [0, 1, 2, 3, 5, 6, 7, 8]
out = pool.map(Calc, b)
out.sort(key=lambda x: (x[0],x[-1]))
for result in out:
print(f'pid:{result[0]} b:{result[-1]} {result[1]} {result[2]}')
print(f'{id(foo)}.a is still {foo.a}')
pool.terminate()..。
PS C:\pyprojects> py -m tmp
original foo id:2466513417648
pid:10460 b:1 I am 2729330535728, a: before=1 | after=2 (3, 2)
pid:10460 b:3 I am 2729330535728, a: before=2 | after=5 (8, 5)
pid:10460 b:6 I am 2729330535728, a: before=5 | after=2 (8, 2)
pid:10460 b:8 I am 2729330535728, a: before=2 | after=2 (10, 2)
pid:13100 b:0 I am 2799588470064, a: before=1 | after=1 (1, 1)
pid:13100 b:2 I am 2799588470064, a: before=1 | after=6 (8, 6)
pid:13100 b:5 I am 2799588470064, a: before=6 | after=8 (13, 8)
pid:13100 b:7 I am 2799588470064, a: before=8 | after=0 (7, 0)
2466513417648.a is still 1
PS C:\pyprojects>发布于 2020-10-30 15:17:04
每个进程都使用自己的内存,因此它们不能修改另一个进程的类属性。另一方面,如果您要对线程执行同样的操作,则会遇到争用条件的问题。
https://stackoverflow.com/questions/64610930
复制相似问题