[GitHub] [spark] asl3 commented on a diff in pull request #41927: [SPARK-44216] [PYTHON] Make assertSchemaEqual API with ignore_nullable optional flag

["asl3 (via GitHub)" <gi...@apache.org>]

asl3 commented on code in PR #41927:
URL: https://github.com/apache/spark/pull/41927#discussion_r1259848389


##########
python/pyspark/testing/utils.py:
##########
@@ -221,7 +221,130 @@ def check_error(
         )
 
 
-def assertDataFrameEqual(df: DataFrame, expected: DataFrame, check_row_order: bool = False):
+def assertSchemaEqual(
+    df_schema: StructType, expected_schema: StructType, ignore_nullable: bool = False
+):
+    """
+    A util function to assert equality between DataFrame schemas `df_schema`
+    and `expected_schema`, with optional parameter `ignore_nullable`.
+
+    .. versionadded:: 3.5.0
+
+    Parameters
+    ----------
+    df_schema : StructType
+        The DataFrame schema that is being compared or tested.
+
+    expected_schema : StructType
+        The expected schema, for comparison with the actual schema.
+
+    ignore_nullable : bool, optional
+        A flag indicating whether the nullable flag should be ignored in schema comparison.
+        If set to `False` (default), the nullable flag in the schemas is not taken into account.
+        If set to `True`, the nullable flag will be checked during schema comparison.
+
+    Examples
+    --------
+    >>> from pyspark.sql.types import StructType, StructField, ArrayType, IntegerType, DoubleType
+    >>> s1 = StructType([StructField("names", ArrayType(DoubleType(), True), True)])
+    >>> s2 = StructType([StructField("names", ArrayType(DoubleType(), True), True)])
+    >>> assertSchemaEqual(s1, s2) # pass
+    >>> s1 = StructType([StructField("names", ArrayType(IntegerType(), True), True)])
+    >>> s2 = StructType([StructField("names", ArrayType(DoubleType(), False), True)])
+    >>> assertSchemaEqual(s1, s2) # fail  # doctest: +IGNORE_EXCEPTION_DETAIL
+    Traceback (most recent call last):
+    ...
+    PySparkAssertionError: [DIFFERENT_SCHEMA] Schemas do not match:
+    [df]
+    StructField("names", ArrayType(IntegerType(), True), True)
+    <BLANKLINE>
+    [expected]
+    StructField("names", ArrayType(DoubleType(), False), True)
+    <BLANKLINE>
+    """
+
+    def compare_schemas_ignore_nullable(s1, s2):
+        if len(s1) != len(s2):
+            return False
+        zipped = zip_longest(s1, s2)
+        for sf1, sf2 in zipped:
+            if not compare_structfields_ignore_nullable(sf1, sf2):
+                return False
+        return True
+
+    def compare_structfields_ignore_nullable(df_structfield, expected_structfield):
+        if ignore_nullable:
+            if df_structfield is None and expected_structfield is None:
+                return True
+            elif df_structfield is None or expected_structfield is None:
+                return False
+            if df_structfield.name != expected_structfield.name:
+                return False
+            else:
+                return compare_datatypes_ignore_nullable(
+                    df_structfield.dataType, expected_structfield.dataType
+                )
+        else:
+            return df_structfield == expected_structfield
+
+    def compare_datatypes_ignore_nullable(dt1, dt2):
+        # checks datatype equality, using recursion to ignore nullable
+        if dt1.typeName() == dt2.typeName():
+            if dt1.typeName() == "array":
+                return compare_datatypes_ignore_nullable(dt1.elementType, dt2.elementType)
+            elif dt1.typeName() == "struct":
+                return compare_schemas_ignore_nullable(dt1, dt2)
+            else:
+                return True
+        else:
+            return False
+
+    schemas_equal = True
+    error_msg = "Schemas do not match: \n"
+
+    if ignore_nullable:
+        if not compare_schemas_ignore_nullable(df_schema, expected_schema):
+            zipped = zip_longest(df_schema, expected_schema)
+            for df_structfield, expected_structfield in zipped:
+                if not compare_structfields_ignore_nullable(df_structfield, expected_structfield):
+                    schemas_equal = False
+                    error_msg += (
+                        "[df]"
+                        + "\n"
+                        + str(df_structfield)
+                        + "\n\n"
+                        + "[expected]"
+                        + "\n"
+                        + str(expected_structfield)
+                        + "\n\n"
+                    )
+    else:
+        if df_schema != expected_schema:
+            schemas_equal = False
+            zipped = zip_longest(df_schema, expected_schema)
+            for df_structfield, expected_structfield in zipped:
+                if df_structfield != expected_structfield:
+                    error_msg += (
+                        "[df]"
+                        + "\n"
+                        + str(df_structfield)
+                        + "\n\n"
+                        + "[expected]"
+                        + "\n"
+                        + str(expected_structfield)
+                        + "\n\n"
+                    )
+
+    if not schemas_equal:
+        raise PySparkAssertionError(
+            error_class="DIFFERENT_SCHEMA",
+            message_parameters={"error_msg": error_msg},
+        )
+
+
+def assertDataFrameEqual(
+    df: DataFrame, expected: DataFrame, check_row_order: bool = False, ignore_nullable: bool = False

Review Comment:
   sounds good, how about `check_nullability` -- if set to False, it also will ignore nullable flag in Maps, Arrays, and Structs



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