Random.random()正是这样做的

>>> import random
>>> for i in range(10):
...     print(random.random())
... 
0.908047338626
0.0199900075962
0.904058545833
0.321508119045
0.657086320195
0.714084413092
0.315924955063
0.696965958019
0.93824013683
0.484207425759

如果你想要真正的随机数，并覆盖范围[0,1]:

>>> import os
>>> int.from_bytes(os.urandom(8), byteorder="big") / ((1 << 64) - 1)
0.7409674234050893

我发现我的变化更灵活。

str_Key           = ""
str_FullKey       = "" 
str_CharacterPool = "01234ABCDEFfghij~-)"
for int_I in range(64): 
    str_Key = random.choice(str_CharacterPool) 
    str_FullKey = str_FullKey + str_Key 

你可以使用random。uniform

import random
random.uniform(0, 1)

Random.random()正是这样做的

>>> import random
>>> for i in range(10):
...     print(random.random())
... 
0.908047338626
0.0199900075962
0.904058545833
0.321508119045
0.657086320195
0.714084413092
0.315924955063
0.696965958019
0.93824013683
0.484207425759

如果你想要真正的随机数，并覆盖范围[0,1]:

>>> import os
>>> int.from_bytes(os.urandom(8), byteorder="big") / ((1 << 64) - 1)
0.7409674234050893

这个解决方案有效!

The random randrange (0, 2)

你可以使用numpy。随机模块，你可以得到你想要的形状的随机数数组

>>> import numpy as np
>>> np.random.random(1)[0]
0.17425892129128229
>>> np.random.random((3,2))
array([[ 0.7978787 ,  0.9784473 ],
       [ 0.49214277,  0.06749958],
       [ 0.12944254,  0.80929816]])
>>> np.random.random((3,1))
array([[ 0.86725993],
       [ 0.36869585],
       [ 0.2601249 ]])
>>> np.random.random((4,1))
array([[ 0.87161403],
       [ 0.41976921],
       [ 0.35714702],
       [ 0.31166808]])
>>> np.random.random_sample()
0.47108547995356098