I want to generate a random seed in a predictable way.
I was hoping to do this
seed = 12345
prng_0 = random.Random(seed)
prng_1 = random.Random(prng_0.rand_int(0))
There, 0
is the lower bound, but it turns out I need to give it an upper bound as well. I don't want to set a fixed upper bound.
I'm doing this because I need reproducibility when testing. Namely, this is a function receiving a seed and building its prng, prng_0
, then calling multiple times another function that needs to receive a different seed every time.
def funct_a(seed=None):
prng_1 = random.Random(seed)
prng_2 = numpy.random.RandomState(prng_1.randint(0, 4294967296))
print(prng_1.random())
print(prng_2.random())
def funct_b(seed=None):
prng_0 = random.Random(seed)
for i in range(0, 5):
seed = prng_0.randint(0) # not working, needs upper bound
funct_a(seed)
funct_b(12345) # test call
Interestingly enough, numpy has a definite upper seed value, as testified by the doc and by this error
ValueError: Seed must be between 0 and 4294967295
When I don't want an upper bound I'll often use
sys.maxint
for the upper bound as an approximation