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Co-authored-by: Isaac
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✅ 738/738 passed, 41 skipped, 4h43m32s total Running from acceptance #4562 |
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## main #1092 +/- ##
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- Coverage 92.11% 72.64% -19.47%
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Files 101 101
Lines 9546 9557 +11
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- Misses 753 2614 +1861
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…eholders
The custom-message field is renamed to message_expr and now accepts either a
Spark SQL expression string or a Spark Column object. The expression is
evaluated as-is — DQX no longer substitutes {rule_name}, {check_func_name}, or
{column_value} placeholders. Callers reference columns and identifiers directly
inside the expression.
- DQRule / DQForEachColRule: rename message -> message_expr (str | Column | None)
- to_dict serialises message_expr only when it is a string (Column is in-process)
- DQRuleManager._build_message_col simplified: F.expr(str) or use Column directly
- checks_serializer: read message_expr key from metadata, pass to constructors
- Unit tests rewritten for the new attribute name and Column variant
- Integration tests rewritten without placeholders; the existing
test_apply_checks_without_custom_message_unchanged is dropped (the Engine's
no-message default path is already covered by surrounding tests)
- Docs (quality_checks.mdx) rewritten to drop the placeholder section, add a
Column-based Python example, and annotate each example with the rendered
message string
Co-authored-by: Isaac
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Changes
Add an optional
messagecallable parameter toDQRule,DQRowRule,DQDatasetRule, andDQForEachColRulethat allows users to define custom check failure messages. The callable receives rule context (rule_name,check_func_name,check_func_args,column_value) and returns a Spark Column expression, enabling dynamic messages that can include column values.When
messageisNone(the default), the existing auto-generated message behavior is preserved. When provided, the custom message replaces the default message for failed rows while maintaining null/non-null semantics for passing rows.Linked issues
Resolves #958
Tests