time_field()`function`

Create a time column specification.

USAGE

time_field(
    min_time=None,
    max_time=None,
    nullable=False,
    null_probability=0.0,
    unique=False,
    generator=None,
)

Parameters

min_time : str | time | None = None: Minimum time (inclusive). Can be ISO string or time object.
max_time : str | time | None = None: Maximum time (inclusive). Can be ISO string or time 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

TimeField: A time field specification.

Examples

Define a schema with time fields and generate test data:

import pointblank as pb
from datetime import time

# Define a schema with time field specifications
schema = pb.Schema(
    start_time=pb.time_field(
        min_time=time(9, 0, 0),
        max_time=time(12, 0, 0)
    ),
    end_time=pb.time_field(
        min_time=time(13, 0, 0),
        max_time=time(17, 0, 0)
    ),
)

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

	start_time String	end_time String
PolarsRows100Columns2
1	10:19:09	16:32:49
2	09:22:48	14:19:09
3	09:04:39	16:46:32
4	11:41:39	13:22:48
5	10:23:45	13:04:39
96	10:53:39	15:29:54
97	10:47:25	13:59:36
98	09:06:22	14:10:33
99	09:44:23	13:40:49
100	10:01:36	13:29:15

Time values are uniformly distributed within the specified range.