Set numpy.random.seed on a global scale [closed]

Question

How can I set numpy.random.seed(0) on a global scale? It seems I have to reset the seed every time I call a np.random function.

import numpy as np

np.random.seed(0)
print(np.random.randint(0,10,2))
np.random.seed(0)
print(np.random.randint(0,10,2))
print(np.random.randint(0,10,2))

np.random.seed(0)
print(np.random.rand())
np.random.seed(0)
print(np.random.rand())
print(np.random.rand())


[5 0]
[5 0]
[3 3]
0.5488135039273248
0.5488135039273248
0.7151893663724195

Answer 1

That is how seeds actually work. You set a 'seed' value which determines all following generated random numbers. You can think of the seed as a starting point for randomly generated numbers. Every time you set the seed you set a starting point for generating a random sequence.

Every time the code generates a random number, it steps 'forward' from the seed/starting point in a random (but deterministic) way. Setting the seed puts the random number generator in a specific state from which it will follow the same random path every time (due to the is the deterministic character).