# Do this (new version)
from numpy.random import default_rng

rng = default_rng()
vals = rng.standard_normal(10)
more_vals = rng.standard_normal(10)
numbers = rng.integers(high, size=5)

# instead of this (legacy version)
from numpy import random

vals = random.standard_normal(10)
more_vals = random.standard_normal(10)
numbers = random.integers(high, size=5)

import numpy

numpy.random.seed()
numpy.random.get_state()
numpy.random.set_state()
numpy.random.rand()
numpy.random.ranf()
numpy.random.sample()
numpy.random.randn()
numpy.random.randint()
numpy.random.random()
numpy.random.random_integers()
numpy.random.random_sample()
numpy.random.choice()
numpy.random.bytes()
numpy.random.shuffle()
numpy.random.permutation()
numpy.random.beta()
numpy.random.binomial()
numpy.random.chisquare()
numpy.random.dirichlet()
numpy.random.exponential()
numpy.random.f()
numpy.random.gamma()
numpy.random.geometric()
numpy.random.gumbel()
numpy.random.hypergeometric()
numpy.random.laplace()
numpy.random.logistic()
numpy.random.lognormal()
numpy.random.logseries()
numpy.random.multinomial()
numpy.random.multivariate_normal()
numpy.random.negative_binomial()
numpy.random.noncentral_chisquare()
numpy.random.noncentral_f()
numpy.random.normal()
numpy.random.pareto()
numpy.random.poisson()
numpy.random.power()
numpy.random.rayleigh()
numpy.random.standard_cauchy()
numpy.random.standard_exponential()
numpy.random.standard_gamma()
numpy.random.standard_normal()
numpy.random.standard_t()
numpy.random.triangular()
numpy.random.uniform()
numpy.random.vonmises()
numpy.random.wald()
numpy.random.weibull()
numpy.random.zipf()
