`numpy.random:RandomState.randint`

Signature

def randint(low, high = None, size = None, dtype = <class 'int'>)

Summary

Return random integers from low (inclusive) to high (exclusive).

Extended Summary

Return random integers from the "discrete uniform" distribution of the specified dtype in the "half-open" interval [low, high). If high is None (the default), then results are from [0, low).

Parameters

low : int or array-like of ints: Lowest (signed) integers to be drawn from the distribution (unless high=None, in which case this parameter is one above the highest such integer).
high : int or array-like of ints, optional: If provided, one above the largest (signed) integer to be drawn from the distribution (see above for behavior if high=None). If array-like, must contain integer values
size : int or tuple of ints, optional: Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned.
dtype : dtype, optional: Desired dtype of the result. Byteorder must be native. The default value is long.
warning
This function defaults to the C-long dtype, which is 32bit on windows and otherwise 64bit on 64bit platforms (and 32bit on 32bit ones). Since NumPy 2.0, NumPy's default integer is 32bit on 32bit platforms and 64bit on 64bit platforms. Which corresponds to np.intp. (dtype=int is not the same as in most NumPy functions.)

Returns

out : int or ndarray of ints: size-shaped array of random integers from the appropriate distribution, or a single such random int if size not provided.

Examples

np.random.randint(2, size=10)

✗

array([1, 1, 0, 0, 0, 1, 1, 0, 0, 1])

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([[3, 0, 2, 2],
       [2, 3, 0, 1]])

Generate a 1 x 3 array with 3 different upper bounds

np.random.randint(1, [3, 5, 10])

✗

array([2, 4, 6])

Generate a 1 by 3 array with 3 different lower bounds

np.random.randint([1, 5, 7], 10)

✗

array([9, 8, 7])

Generate a 2 by 4 array using broadcasting with dtype of uint8

np.random.randint([1, 3, 5, 7], [[10], [20]], dtype=np.uint8)

✗

array([[ 2,  7,  6,  8],
       [ 6, 17, 10, 14]], dtype=uint8)

Aliases

numpy.random.randint
numpy.random.RandomState.randint