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Regex Match Check

Check: regex-match-check

Purpose: Validates that string values in a column match a given regular expression pattern. Use this to enforce format compliance for structured fields such as email addresses, identifiers, or standardized codes.

!!! note - Null values are skipped by default. Set treat_null_as_failure: true to treat them as invalid. - Pattern matching is case-sensitive by default. Use ignore_case: true for case-insensitive matching.

from sparkdq.checks import RegexMatchCheckConfig
from sparkdq.core import Severity

RegexMatchCheckConfig(
    check_id="valid-email-format",
    column="email",
    pattern=r"^[\w\.-]+@[\w\.-]+\.\w+$",
    ignore_case=True,
    treat_null_as_failure=False,
    severity=Severity.CRITICAL
)

- check: regex-match-check
  check-id: valid-email-format
  column: email
  pattern: "^[\\w\\.-]+@[\\w\\.-]+\\.\\w+$"
  ignore-case: true
  treat-null-as-failure: false
  severity: critical

Typical Use Cases

  • Validate format compliance for email addresses, phone numbers, or postal codes.
  • Enforce structured identifier patterns such as AB-12345 or ISO-8601 date strings.
  • Detect malformed or free-text values in fields that require a standardized format.

← Row-Level Checks