@tim.peters yes, a uniform random variable rescaled to two nearby scales N and M will display strong correlations. The CPython randrange() exhibits however orders of magnitude higher such correlations, but only in relation to a common bitlength. A randrange() function should a priori not be so strongly tied to the binary base.

The example you show would not be counted as a hit by my test for the randomseed 12.

>>> s = 0
>>> for t in range(100000):
...     random.seed(t)
...     x = [round(random.random() * 100) for i in range(10)]
...     random.seed(t)
...     y = [round(random.random() * 101) for i in range(10)]
...     if x == y:
...         s += 1
... 
>>> s
94
>>> s = 0
>>> for t in range(100000):
...     random.seed(t)
...     x = [random.randrange(100) for i in range(10)]
...     random.seed(t)
...     y = [random.randrange(101) for i in range(10)]
...     if x == y:
...         s += 1
... 
>>> s
90432