Date Between

Date Between#

Check: date-between-check

Purpose: Checks whether values in the specified date columns are within a defined range between min_value and max_value. A row fails the check if any of the selected columns contains a date before min_value or after max_value.

You can control boundary inclusivity using the inclusive parameter:

  • inclusive: [False, False] (default): strictly between min < value < max

  • inclusive: [True, False]: include only the lower bound min <= value < max

  • inclusive: [False, True]: include only the upper bound min < value <= max

  • inclusive: [True, True]: include both bounds min <= value <= max

Python Configuration#

from sparkdq.checks import DateBetweenCheckConfig
from sparkdq.core import Severity

DateBetweenCheckConfig(
    check_id="allowed_record_date_range",
    columns=["record_date"],
    min_value="2020-01-01",
    max_value="2023-12-31",
    inclusive=(True, True),
    severity=Severity.CRITICAL
)

Declarative Configuration#

- check: date-between-check
  check-id: allowed_record_date_range
  columns:
    - record_date
  min-value: "2020-01-01"
  max-value: "2023-12-31"
  inclusive: [true, true]
  severity: critical

Typical Use Cases#

  • ✅ Ensure that transaction or event dates fall within a valid business period (e.g., fiscal year).

  • ✅ Validate that data entries only contain dates within a specific reporting window.

  • ✅ Prevent the processing of outdated or future-dated records outside of the allowed range.

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