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

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

HyukjinKwon commented on code in PR #41927:
URL: https://github.com/apache/spark/pull/41927#discussion_r1259014832


##########
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):

Review Comment:
   There are some codes to refer to provide a nice message for nested types, e.g., https://github.com/apache/spark/blob/master/python/pyspark/sql/types.py#L1906-L2189



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