Best way to revert to a random seed after temporarily fixing it?

Question

Is this the only way to 'unseed' the random number generator:

np.random.seed(int(time.time()))

If you have some code that you want to be repeatable (e.g. a test) in a loop with other code that you want to be random each loop, how do you 'reset' the seed to random number generator after setting it?

The following code illustrates the issue:

import numpy as np

def test():
    np.random.seed(2)
    print("Repeatable test:", [np.random.randint(10) for i in range(3)])

for i in range(4):
    print("Random number:", np.random.randint(10))
    test()

Random number: 8
Repeatable test: [8, 8, 6]
Random number: 2
Repeatable test: [8, 8, 6]
Random number: 2
Repeatable test: [8, 8, 6]
Random number: 2
Repeatable test: [8, 8, 6]

Desired result: I want random number to be random each loop.

I am happy to import the time module if this is the only way to do it but I thought there might be a simpler, more robust way.

(You can't get the current seed according to this post)

Answer 1

You're going down the wrong path. Instead of trying to unseed the global RNG used by numpy.random, use a separate RNG for the parts that need to be repeatable. This RNG can have a completely independent state from the numpy.random default RNG:

def test():
    rng = numpy.random.RandomState(2)
    print("Repeatable test:", [rng.randint(10) for i in range(3)])

---

While it is technically possible to save and restore the state of the global numpy.random RNG, it is a very specialized operation and rarely a good idea. It may be useful, for example, if you're debugging a piece of code and you want to "rewind" the random state after jumping backward through the code, though you need to save the state in advance, and it won't rewind any other random number generators:

# Don't abuse this.
state = numpy.random.get_state()
do_stuff()
numpy.random.set_state(state)

Answer 2

You can instantiate your own Random object.

myrandom = random.Random(myseed)

The random module manages its own instance of Random, which will be unaffected by changes made to myrandom.