/NumPy 1.14

# numpy.random.RandomState.randint

`RandomState.randint(low, high=None, size=None, dtype='l')`

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`).

Parameters: low : int Lowest (signed) integer to be drawn from the distribution (unless `high=None`, in which case this parameter is one above the highest such integer). high : int, optional If provided, one above the largest (signed) integer to be drawn from the distribution (see above for behavior if `high=None`). 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. All dtypes are determined by their name, i.e., ‘int64’, ‘int’, etc, so byteorder is not available and a specific precision may have different C types depending on the platform. The default value is ‘np.int’. New in version 1.11.0. 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.

`random.random_integers`
similar to `randint`, only for the closed interval [`low`, `high`], and 1 is the lowest value if `high` is omitted. In particular, this other one is the one to use to generate uniformly distributed discrete non-integers.

#### Examples

```>>> 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]])
```