multiprocessing.Value不能正确存储浮点数 [英] multiprocessing.Value doesn't store float correctly

问题描述

我尝试将浮点数分配给multiprocessing.Value共享ctype，如下所示:

I try to asign a float to the multiprocessing.Value shared ctype as follows:

import multiprocessing
import random

test_float = multiprocessing.Value('f', 0)
i = random.randint(1,10000)/(random.randint(1,10000))
test_float.value = i
print("i: type = {}, value = {}".format(type(i), i))
print("test_float: type = {}, value = {}".format(type(test_float.value), test_float.value))
print("i == test_float: {}".format(i == test_float.value))

但是，存储在multiprocessing.Value中的float是！=输入float:

However, the float stored in multiprocessing.Value is != the input float:

>>> i: type = <class 'float'>, value = 1.480021216407355
>>> test_float: type = <class 'float'>, value = 1.4800212383270264
>>> i == test_float: False

这是什么问题?

找到了解决方案(请参阅答案)但是，我不明白，为什么这里的"double"是正确的类型而不是"float".如果有人可以详细说明并提供解决方案，则将其标记为正确答案.

Found the solution (see answers) However, I do not understand, why a "double" is the correct type here and not a "float". If someone can elaborate on that and include the solution, I will mark it as the correct answer.

推荐答案

Python浮点数是double-precision floats，或其他语言称为double的浮点数.这就是为什么您需要使用'd'的原因:'f'与python用于float的精度级别不符

Python floats are double-precision floats, or what other languages would call double's. That is why you need to use 'd': 'f' does not correspond to the precision level python uses for float's

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