您可以检查它的功能：def shuffle(self, x, random=None):

"""Shuffle list x in place, and return None.

Optional argument random is a 0-argument function returning a

random float in [0.0, 1.0); if it is the default None, the

standard random.random will be used.

"""

if random is None:

randbelow = self._randbelow

for i in reversed(range(1, len(x))):

# pick an element in x[:i+1] with which to exchange x[i]

j = randbelow(i+1)

x[i], x[j] = x[j], x[i]

else:

_int = int

for i in reversed(range(1, len(x))):

# pick an element in x[:i+1] with which to exchange x[i]

j = _int(random() * (i+1))

x[i], x[j] = x[j], x[i]

else分支在这里应用，尤其是j = _int(random() * (i+1))行。这是经典的Fisher-Yates shuffle

所以随机值的“使用粒度”通常取决于列表的长度，尤其是当前元素的索引。在

哦，顺便说一句：你不是在提供一个种子，而是在提供随机值——最终每个迭代都是一个值。

相反，您可以使用随机值进行一次随机洗牌：

^{pr2}$

或者，您也可以使用seed-s，但实际上它们不应该是介于0和1之间的浮点数，请参阅def seed(self, a=None, version=2):

"""Initialize internal state from hashable object.

None or no argument seeds from current time or from an operating

system specific randomness source if available.

If *a* is an int, all bits are used.

For version 2 (the default), all of the bits are used if *a* is a str,

bytes, or bytearray. For version 1 (provided for reproducing random

sequences from older versions of Python), the algorithm for str and

bytes generates a narrower range of seeds.

"""

if version == 1 and isinstance(a, (str, bytes)):

x = ord(a[0]) << 7 if a else 0

for c in a:

x = ((1000003 * x) ^ ord(c)) & 0xFFFFFFFFFFFFFFFF

x ^= len(a)

a = -2 if x == -1 else x

if version == 2 and isinstance(a, (str, bytes, bytearray)):

if isinstance(a, str):

a = a.encode()

a += _sha512(a).digest()

a = int.from_bytes(a, 'big')

super().seed(a)

self.gauss_next = None

父类(其中a结束，有或没有这些损坏过程)是本机代码：NUMBA_EXPORT_FUNC(PyObject *)

_numba_rnd_seed(PyObject *self, PyObject *args)

{

unsigned int seed;

rnd_state_t *state;

if (!PyArg_ParseTuple(args, "O&I:rnd_seed",

rnd_state_converter, &state, &seed)) {

/* rnd_seed_*(bytes-like object) */

Py_buffer buf;

PyErr_Clear();

if (!PyArg_ParseTuple(args, "O&s*:rnd_seed",

rnd_state_converter, &state, &buf))

return NULL;

if (rnd_seed_with_bytes(state, &buf))

return NULL;

else

Py_RETURN_NONE;

}

else {

/* rnd_seed_*(int32) */

numba_rnd_init(state, seed);

Py_RETURN_NONE;

}

}

甚至可能发生这样的情况：传递一个浮点值会导致在这里运行最后一个分支，在这里使用未初始化的seed值，导致行为一致，这仅仅是因为在调用这个_numba_rnd_seed之前的函数调用使堆栈处于相同的状态。在