# numpy.random.randint#

random.randint(low, high=None, size=None, dtype=int)#

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

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).

Note

New code should use the `integers` method of a `default_rng()` instance instead; please see the Quick Start.

Parameters
lowint 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).

highint 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

sizeint 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.

dtypedtype, optional

Desired dtype of the result. Byteorder must be native. The default value is int.

New in version 1.11.0.

Returns
outint or ndarray of ints

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

`random_integers`

similar to `randint`, only for the closed interval [low, high], and 1 is the lowest value if high is omitted.

`random.Generator.integers`

which should be used for new code.

Examples

```>>> np.random.randint(2, size=10)
array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0]) # random
>>> 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], # random
[3, 2, 2, 0]])
```

Generate a 1 x 3 array with 3 different upper bounds

```>>> np.random.randint(1, [3, 5, 10])
array([2, 2, 9]) # random
```

Generate a 1 by 3 array with 3 different lower bounds

```>>> np.random.randint([1, 5, 7], 10)
array([9, 8, 7]) # random
```

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([[ 8,  6,  9,  7], # random
[ 1, 16,  9, 12]], dtype=uint8)
```