np.random

numpy.random.randint

numpy.random.randint(low, high=None, size=None, dtype='l')

>>> np.random.randint(2, size=10)
array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0])
>>> np.random.randint(1, size=10)
array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])

Generate a 2 x 4 array of ints between 0 and 4, inclusive:
>>> np.random.randint(5, size=(2, 4))
array([[4, 0, 2, 1],
[3, 2, 2, 0]])

numpy.random.random

numpy.random.random(size=None)

>>> numpy.random.random()
0.3619044878607339
>>> numpy.random.random()-2
-1.3074864277635
>>> numpy.random.random((1,10))
array([[ 0.23640074,  0.19227714,  0.94424091,  0.67545432,  0.91937884,
0.06127973,  0.50797509,  0.68498703,  0.40482353,  0.76130972]])

numpy.random.randn

numpy.random.randn(d0, d1, ..., dn)

>>> np.random.randn()
2.1923875335537315 #random

Two-by-four array of samples from N(3, 6.25):
>>> 2.5 * np.random.randn(2, 4) + 3
array([[-4.49401501,  4.00950034, -1.81814867,  7.29718677],
[ 0.39924804,  4.68456316,  4.99394529,  4.84057254]])