datetime_field()`function`

Create a datetime column specification.

USAGE

datetime_field(
    min_date=None,
    max_date=None,
    nullable=False,
    null_probability=0.0,
    unique=False,
    generator=None,
)

Parameters

min_date : str | datetime | None = None: Minimum datetime (inclusive). Can be ISO string or datetime object.
max_date : str | datetime | None = None: Maximum datetime (inclusive). Can be ISO string or datetime object.
nullable : bool = False: Whether the column can contain null values. Default is False.
null_probability : float = 0.0: Probability of generating null when nullable=True. Default is 0.0.
unique : bool = False: Whether all values must be unique. Default is False.
generator : Callable[[], Any] | None = None: Custom callable that generates values. Overrides other settings.

Returns

DatetimeField: A datetime field specification.

Examples

Define a schema with datetime fields and generate test data:

import pointblank as pb
from datetime import datetime

# Define a schema with datetime field specifications
schema = pb.Schema(
    created_at=pb.datetime_field(
        min_date=datetime(2024, 1, 1),
        max_date=datetime(2024, 12, 31)
    ),
    updated_at=pb.datetime_field(
        min_date=datetime(2024, 6, 1),
        max_date=datetime(2024, 12, 31)
    ),
)

# Generate 100 rows of test data
pb.preview(pb.generate_dataset(schema, n=100, seed=23))

	created_at Datetime	updated_at Datetime
PolarsRows100Columns2
1	2024-12-25 04:22:08	2024-09-21 14:13:08
2	2024-10-29 16:22:23	2024-07-03 10:44:55
3	2024-04-22 14:13:08	2024-06-07 15:09:55
4	2024-12-12 14:04:53	2024-09-28 03:03:37
5	2024-11-18 04:49:47	2024-11-12 13:36:43
96	2024-07-29 13:15:44	2024-11-28 23:02:29
97	2024-04-28 08:49:29	2024-12-30 22:17:11
98	2024-12-13 09:42:37	2024-08-16 08:51:48
99	2024-10-28 23:35:39	2024-11-26 06:03:26
100	2024-06-25 14:22:27	2024-09-23 19:35:59

Datetime values are uniformly distributed within the specified range.