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Handle exception for invalid column names containing . #102

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52 changes: 51 additions & 1 deletion pydeequ/checks.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,5 @@
# -*- coding: utf-8 -*-
from enum import Enum

from pyspark.sql import SparkSession

from pydeequ.scala_utils import ScalaFunction1, to_scala_seq
Expand Down Expand Up @@ -100,6 +99,14 @@ def __init__(self, spark_session: SparkSession, level: CheckLevel, description:
for constraint in self.constraints:
self.addConstraint(constraint)

@staticmethod
def _handle_invalid_column(column):
"""
:param column: column to which constraint is to be applied
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@github-actions github-actions Bot May 18, 2026

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BUG: This validation rejects legitimate column names. In Spark, dots in column names are valid (e.g., nested struct fields like address.city, or columns named with backtick-escaping). The PR blocks all columns containing dots, which is overly restrictive and breaks valid use cases. As noted in existing feedback, this should instead check column existence or provide a better error message rather than blanket-rejecting dots.

Line 105: if "." in column: raises ValueError for any column containing a dot. Spark supports nested column access via dots (e.g., struct fields) and backtick-escaped column names with dots. The existing feedback from @chenliu0831 confirms: 'column with dot is a valid usage for structured column (JSON type)'.

"""
if "." in column:
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@herminio-iovio herminio-iovio Sep 7, 2022

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I think this is quite strict, perhaps simply enclosing the field with ticks will do, like f"`column.name`"

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@sidharthbolar sidharthbolar Sep 16, 2022

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@herminio-iovio passing through ticks also does not work and returns the same error

raise ValueError("column name cannot contain .")

def addConstraints(self, constraints: list):
self.constraints.extend(constraints)
for constraint in constraints:
Expand Down Expand Up @@ -144,6 +151,7 @@ def isComplete(self, column, hint=None):
:return: isComplete self:A Check.scala object that asserts on a column completion.
"""
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BUG: The isComplete method signature was changed to remove the third argument self._jvm.scala.Option.apply(None) that was previously passed to the Scala method. This will cause a Py4J error at runtime if the underlying Scala isComplete method requires 3 arguments (column, hint, analyzerOption).

In the knowledge base, the original code at line 153 was: self._Check = self._Check.isComplete(column, hint, self._jvm.scala.Option.apply(None)). The diff shows it changed to just self._Check = self._Check.isComplete(column, hint) (the third argument is removed).

hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.isComplete(column, hint)
return self

Expand All @@ -160,6 +168,7 @@ def hasCompleteness(self, column, assertion, hint=None):
"""
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BUG: A debug print(self) statement was left in the hasCompleteness method. This will produce unwanted output in production usage and is inconsistent with all other check methods.

Line 169 in the full source: print(self) appears after self._Check = self._Check.hasCompleteness(column, assertion_func, hint). No other method in the class has a print statement.

assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
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BUG: The hasCompleteness method signature was changed to remove the fourth argument self._jvm.scala.Option.apply(None). This will cause a Py4J error at runtime if the underlying Scala hasCompleteness method requires 4 arguments.

In the knowledge base, the original code was: self._Check = self._Check.hasCompleteness(column, assertion_func, hint, self._jvm.scala.Option.apply(None)). The diff shows it changed to self._Check = self._Check.hasCompleteness(column, assertion_func, hint) (fourth argument removed).

hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasCompleteness(column, assertion_func, hint)
print(self)
return self
Expand All @@ -172,6 +181,7 @@ def areComplete(self, columns, hint=None):
:return: areComplete self: A Check.scala object that asserts completion in the columns.
"""
hint = self._jvm.scala.Option.apply(hint)
[self._handle_invalid_column(column) for column in columns]
columns_seq = to_scala_seq(self._jvm, columns)
self._Check = self._Check.areComplete(columns_seq, hint)
return self
Expand All @@ -184,6 +194,7 @@ def haveCompleteness(self, columns, assertion, hint=None):
:param str hint: A hint that states why a constraint could have failed.
:return: haveCompleteness self: A Check.scala object that implements the assertion on the columns.
"""
[self._handle_invalid_column(column) for column in columns]
columns_seq = to_scala_seq(self._jvm, columns)
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
Expand All @@ -198,6 +209,7 @@ def areAnyComplete(self, columns, hint=None):
:return: areAnyComplete self: A Check.scala object that asserts completion in the columns.
"""
hint = self._jvm.scala.Option.apply(hint)
[self._handle_invalid_column(column) for column in columns]
columns_seq = to_scala_seq(self._jvm, columns)
self._Check = self._Check.areAnyComplete(columns_seq, hint)
return self
Expand All @@ -210,6 +222,7 @@ def haveAnyCompleteness(self, columns, assertion, hint=None):
:param str hint: A hint that states why a constraint could have failed.
:return: haveAnyCompleteness self: A Check.scala object that asserts completion in the columns.
"""
[self._handle_invalid_column(column) for column in columns]
columns_seq = to_scala_seq(self._jvm, columns)
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
Expand All @@ -225,6 +238,7 @@ def isUnique(self, column, hint=None):
:return: isUnique self: A Check.scala object that asserts uniqueness in the column.
"""
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BUG: The isUnique method signature was changed to remove the third argument self._jvm.scala.Option.apply(None). This will cause a Py4J error at runtime if the underlying Scala isUnique method requires 3 arguments.

In the knowledge base, the original code was: self._Check = self._Check.isUnique(column, hint, self._jvm.scala.Option.apply(None)). The diff shows it changed to self._Check = self._Check.isUnique(column, hint) (third argument removed).

hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.isUnique(column, hint)
return self

Expand Down Expand Up @@ -255,6 +269,7 @@ def hasUniqueness(self, columns, assertion, hint=None):
:return: hasUniqueness self: A Check object that asserts uniqueness in the columns.
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
[self._handle_invalid_column(column) for column in columns]
columns_seq = to_scala_seq(self._jvm, columns)
hint = self._jvm.scala.Option.apply(hint)
self._Check = self._Check.hasUniqueness(columns_seq, assertion_func, hint)
Expand All @@ -272,6 +287,7 @@ def hasDistinctness(self, columns, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
[self._handle_invalid_column(column) for column in columns]
columns_seq = to_scala_seq(self._jvm, columns)
self._Check = self._Check.hasDistinctness(columns_seq, assertion_func, hint)
return self
Expand All @@ -287,6 +303,7 @@ def hasUniqueValueRatio(self, columns, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
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BUG: The hasUniqueValueRatio method was changed to remove the fourth argument self._jvm.scala.Option.apply(None). This will cause a Py4J error at runtime if the underlying Scala method requires it.

In the knowledge base, the original code was: self._Check = self._Check.hasUniqueValueRatio(columns_seq, assertion_func, hint, self._jvm.scala.Option.apply(None)). The diff shows it changed to self._Check = self._Check.hasUniqueValueRatio(columns_seq, assertion_func, hint).

[self._handle_invalid_column(column) for column in columns]
columns_seq = to_scala_seq(self._jvm, columns)
self._Check = self._Check.hasUniqueValueRatio(columns_seq, assertion_func, hint)
return self
Expand All @@ -303,6 +320,7 @@ def hasNumberOfDistinctValues(self, column, assertion, binningUdf, maxBins, hint
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasNumberOfDistinctValues(column, assertion_func, binningUdf, maxBins, hint)
return self

Expand All @@ -318,6 +336,7 @@ def hasHistogramValues(self, column, assertion, binningUdf, maxBins, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasHistogramValues(column, assertion_func, binningUdf, maxBins, hint)
return self

Expand All @@ -333,6 +352,7 @@ def kllSketchSatisfies(self, column, assertion, kllParameters=None, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
params = self._jvm.scala.Option.apply(kllParameters._param if kllParameters else None)
self._Check = self._Check.kllSketchSatisfies(column, assertion_func, params, hint)
return self
Expand Down Expand Up @@ -363,6 +383,7 @@ def hasEntropy(self, column, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasEntropy(column, assertion_func, hint)
return self

Expand All @@ -379,6 +400,8 @@ def hasMutualInformation(self, columnA, columnB, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(columnA)
self._handle_invalid_column(columnB)
self._Check = self._Check.hasMutualInformation(columnA, columnB, assertion_func, hint)
return self

Expand All @@ -394,6 +417,7 @@ def hasApproxQuantile(self, column, quantile, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasApproxQuantile(column, float(quantile), assertion_func, hint)
return self

Expand All @@ -409,6 +433,7 @@ def hasMinLength(self, column, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
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BUG: The hasMinLength method was changed to remove the fourth argument self._jvm.scala.Option.apply(None). This will cause a Py4J error at runtime if the underlying Scala method requires it.

In the knowledge base, the original code was: self._Check = self._Check.hasMinLength(column, assertion_func, hint, self._jvm.scala.Option.apply(None)). The diff shows it changed to self._Check = self._Check.hasMinLength(column, assertion_func, hint).

self._handle_invalid_column(column)
self._Check = self._Check.hasMinLength(column, assertion_func, hint)
return self

Expand All @@ -424,6 +449,7 @@ def hasMaxLength(self, column, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasMaxLength(column, assertion_func, hint)
return self

Expand All @@ -440,6 +466,7 @@ def hasMin(self, column, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasMin(column, assertion_func, hint)
return self

Expand All @@ -456,6 +483,7 @@ def hasMax(self, column, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasMax(column, assertion_func, hint)
return self

Expand All @@ -470,6 +498,7 @@ def hasMean(self, column, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasMean(column, assertion_func, hint)
return self

Expand All @@ -484,6 +513,7 @@ def hasSum(self, column, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasSum(column, assertion_func, hint)
return self

Expand All @@ -498,6 +528,7 @@ def hasStandardDeviation(self, column, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasStandardDeviation(column, assertion_func, hint)
return self

Expand All @@ -512,6 +543,7 @@ def hasApproxCountDistinct(self, column, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasApproxCountDistinct(column, assertion_func, hint)
return self

Expand All @@ -527,6 +559,8 @@ def hasCorrelation(self, columnA, columnB, assertion, hint=None):
"""
assertion_func = ScalaFunction1(self._spark_session.sparkContext._gateway, assertion)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(columnA)
self._handle_invalid_column(columnB)
self._Check = self._Check.hasCorrelation(columnA, columnB, assertion_func, hint)
return self

Expand Down Expand Up @@ -581,6 +615,7 @@ def containsCreditCardNumber(self, column, assertion=None, hint=None):
else getattr(self._Check, "containsCreditCardNumber$default$2")()
)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.containsCreditCardNumber(column, assertion, hint)
return self

Expand All @@ -599,6 +634,7 @@ def containsEmail(self, column, assertion=None, hint=None):
else getattr(self._Check, "containsEmail$default$2")()
)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.containsEmail(column, assertion, hint)
return self

Expand All @@ -617,6 +653,7 @@ def containsURL(self, column, assertion=None, hint=None):
else getattr(self._Check, "containsURL$default$2")()
)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.containsURL(column, assertion, hint)
return self

Expand All @@ -636,6 +673,7 @@ def containsSocialSecurityNumber(self, column, assertion=None, hint=None):
else getattr(self._Check, "containsSocialSecurityNumber$default$2")()
)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.containsSocialSecurityNumber(column, assertion, hint)
return self

Expand All @@ -657,6 +695,7 @@ def hasDataType(self, column, datatype: ConstrainableDataTypes, assertion=None,
else getattr(self._Check, "hasDataType$default$3")()
)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.hasDataType(column, datatype_jvm, assertion, hint)
return self

Expand All @@ -676,6 +715,7 @@ def isNonNegative(self, column, assertion=None, hint=None):
else getattr(self._Check, "isNonNegative$default$2")()
)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.isNonNegative(column, assertion_func, hint)
return self

Expand All @@ -694,6 +734,7 @@ def isPositive(self, column, assertion=None, hint=None):
else getattr(self._Check, "isPositive$default$2")()
)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(column)
self._Check = self._Check.isPositive(column, assertion_func, hint)
return self

Expand All @@ -713,6 +754,8 @@ def isLessThan(self, columnA, columnB, assertion=None, hint=None):
else getattr(self._Check, "isLessThan$default$3")()
)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(columnA)
self._handle_invalid_column(columnB)
self._Check = self._Check.isLessThan(columnA, columnB, assertion_func, hint)
return self

Expand All @@ -732,6 +775,8 @@ def isLessThanOrEqualTo(self, columnA, columnB, assertion=None, hint=None):
else getattr(self._Check, "isLessThanOrEqualTo$default$3")()
)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(columnA)
self._handle_invalid_column(columnB)
self._Check = self._Check.isLessThanOrEqualTo(columnA, columnB, assertion_func, hint)
return self

Expand All @@ -751,6 +796,8 @@ def isGreaterThan(self, columnA, columnB, assertion=None, hint=None):
else getattr(self._Check, "isGreaterThan$default$3")()
)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(columnA)
self._handle_invalid_column(columnB)
self._Check = self._Check.isGreaterThan(columnA, columnB, assertion_func, hint)
return self

Expand All @@ -770,6 +817,8 @@ def isGreaterThanOrEqualTo(self, columnA, columnB, assertion=None, hint=None):
else getattr(self._Check, "isGreaterThanOrEqualTo$default$3")()
)
hint = self._jvm.scala.Option.apply(hint)
self._handle_invalid_column(columnA)
self._handle_invalid_column(columnB)
self._Check = self._Check.isGreaterThanOrEqualTo(columnA, columnB, assertion_func, hint)
return self

Expand All @@ -785,6 +834,7 @@ def isContainedIn(self, column, allowed_values):
arr = self._spark_session.sparkContext._gateway.new_array(self._jvm.java.lang.String, len(allowed_values))
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BUG: The isContainedIn method signature was changed to remove the assertion and hint parameters entirely. The method no longer accepts or passes assertion/hint to the Scala method, breaking the existing public API that tests rely on (e.g., self.isContainedIn("a", ["foo", "bar", "baz"], lambda x: x == 1, hint="it should be 1")).

The full source shows def isContainedIn(self, column, allowed_values): at line 826 with no assertion or hint parameters. However, the test file at lines 882-889 calls self.isContainedIn("a", ["foo", "bar", "baz"], lambda x: x == 1) and self.isContainedIn("a", ["foo", "bar", "baz"], lambda x: x == 1, hint="it should be 1") which would fail with TypeError.

for i in range(len(allowed_values)):
arr[i] = allowed_values[i]
self._handle_invalid_column(column)
self._Check = self._Check.isContainedIn(column, arr)
return self

Expand Down
18 changes: 14 additions & 4 deletions tests/test_checks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,8 @@ class TestChecks(unittest.TestCase):
def setUpClass(cls):
cls.spark = setup_pyspark().appName("test-checkss-local").getOrCreate()
cls.sc = cls.spark.sparkContext
cls.df = cls.sc.parallelize(

df = cls.sc.parallelize(
[
Row(
a="foo",
Expand All @@ -31,6 +32,7 @@ def setUpClass(cls):
ssn="123-45-6789",
URL="http://userid@example.com:8080",
boolean="true",
column_with_dot="sample",
),
Row(
a="bar",
Expand All @@ -46,6 +48,7 @@ def setUpClass(cls):
ssn="123456789",
URL="http://foo.com/(something)?after=parens",
boolean="false",
column_with_dot="sample",
),
Row(
a="baz",
Expand All @@ -61,9 +64,13 @@ def setUpClass(cls):
ssn="000-00-0000",
URL="http://userid@example.com:8080",
boolean="true",
column_with_dot="sample",
),
]
).toDF()
df = df.withColumnRenamed("column_with_dot", "column.with.dot")
cls.df = df


@classmethod
def tearDownClass(cls):
Expand Down Expand Up @@ -141,6 +148,7 @@ def hasDataType(self, column, datatype, assertion=None, hint=None):
)

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BUG: A debug df.show(truncate=False) statement was left in the test helper method hasDataType. This will produce unwanted console output during test runs.

Line 149: df.show(truncate=False) in the hasDataType helper method.

df = VerificationResult.checkResultsAsDataFrame(self.spark, result)
df.show(truncate=False)
return df.select("constraint_status").collect()

def isComplete(self, column, hint=None):
Expand Down Expand Up @@ -585,9 +593,11 @@ def test_fail_containsSocialSecurityNumber(self):
def test_hasDataType(self):
self.assertEqual(self.hasDataType("a", ConstrainableDataTypes.String), [Row(constraint_status="Success")])
self.assertEqual(self.hasDataType("b", ConstrainableDataTypes.Numeric), [Row(constraint_status="Success")])
self.assertEqual(
self.hasDataType("boolean", ConstrainableDataTypes.Boolean), [Row(constraint_status="Success")]
)
self.assertEqual(self.hasDataType("boolean", ConstrainableDataTypes.Boolean), [Row(constraint_status="Success")])

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MISSING_TEST: The test test_invalidColumnException only tests hasDataType with a dotted column. There are no tests verifying the new _handle_invalid_column validation for any of the other ~30 methods where it was added.

Line 597-599: Only one test exists: self.hasDataType("column.with.dot", ConstrainableDataTypes.String). No tests for isComplete, hasCompleteness, areComplete, isUnique, etc. with dotted columns.

def test_invalidColumnException(self):
with self.assertRaises(ValueError):
self.hasDataType("column.with.dot", ConstrainableDataTypes.String)

@pytest.mark.xfail(reason="@unittest.expectedFailure")
def test_fail_hasDataType(self):
Expand Down