diff --git a/python/pyspark/sql/datasource.py b/python/pyspark/sql/datasource.py
index bb73a7a9206b1..5547150349388 100644
--- a/python/pyspark/sql/datasource.py
+++ b/python/pyspark/sql/datasource.py
@@ -588,8 +588,8 @@ def partitions(self) -> Sequence[InputPartition]:
         partition value to read the data.
 
         This method is called once during query planning. By default, it returns a
-        single partition with the value ``None``. Subclasses can override this method
-        to return multiple partitions.
+        single partition with the value `InputPartition(None)`. Subclasses can override
+        this method to return multiple partitions.
 
         It's recommended to override this method for better performance when reading
         large datasets.
@@ -626,10 +626,7 @@ def partitions(self) -> Sequence[InputPartition]:
         >>> def partitions(self):
         ...     return [RangeInputPartition(1, 3), RangeInputPartition(5, 10)]
         """
-        raise PySparkNotImplementedError(
-            errorClass="NOT_IMPLEMENTED",
-            messageParameters={"feature": "partitions"},
-        )
+        return [InputPartition(None)]
 
     @abstractmethod
     def read(self, partition: InputPartition) -> Union[Iterator[Tuple], Iterator["RecordBatch"]]:
@@ -643,7 +640,7 @@ def read(self, partition: InputPartition) -> Union[Iterator[Tuple], Iterator["Re
 
         Parameters
         ----------
-        partition : object
+        partition : InputPartition
             The partition to read. It must be one of the partition values returned by
             :meth:`DataSourceReader.partitions`.
 
diff --git a/python/pyspark/sql/tests/test_python_datasource.py b/python/pyspark/sql/tests/test_python_datasource.py
index 9d90082c654d7..e8776c2887209 100644
--- a/python/pyspark/sql/tests/test_python_datasource.py
+++ b/python/pyspark/sql/tests/test_python_datasource.py
@@ -162,7 +162,7 @@ def partitions(self):
                 if partition_func is not None:
                     return partition_func()
                 else:
-                    raise NotImplementedError
+                    return [InputPartition(None)]
 
             def read(self, partition):
                 return read_func(self.schema, partition)
@@ -1040,7 +1040,7 @@ def reader(self, schema) -> "DataSourceReader":
                             {"class_name": "TestJsonReader", "func_name": "partitions"},
                         ),
                         (
-                            "TestJsonReader.read: None",
+                            "TestJsonReader.read: InputPartition(value=None)",
                             {"class_name": "TestJsonReader", "func_name": "read"},
                         ),
                     ]
@@ -1151,7 +1151,7 @@ def reader(self, schema) -> "DataSourceReader":
                             {"class_name": "TestJsonReader", "func_name": "partitions"},
                         ),
                         (
-                            "TestJsonReader.read: None",
+                            "TestJsonReader.read: InputPartition(value=None)",
                             {"class_name": "TestJsonReader", "func_name": "read"},
                         ),
                     ]
diff --git a/python/pyspark/sql/worker/plan_data_source_read.py b/python/pyspark/sql/worker/plan_data_source_read.py
index cded42031b0cc..d736df6084c61 100644
--- a/python/pyspark/sql/worker/plan_data_source_read.py
+++ b/python/pyspark/sql/worker/plan_data_source_read.py
@@ -210,12 +210,12 @@ def data_source_read_func(iterator: Iterable[pa.RecordBatch]) -> Iterable[pa.Rec
         # Deserialize the partition value.
         partition = pickleSer.loads(partition_bytes)
 
-        assert partition is None or isinstance(partition, InputPartition), (
+        assert isinstance(partition, InputPartition), (
             "Expected the partition value to be of type 'InputPartition', "
             f"but found '{type(partition).__name__}'."
         )
 
-        output_iter = reader.read(partition)  # type: ignore[arg-type]
+        output_iter = reader.read(partition)
 
         # Validate the output iterator.
         if not isinstance(output_iter, Iterator):
@@ -240,29 +240,26 @@ def data_source_read_func(iterator: Iterable[pa.RecordBatch]) -> Iterable[pa.Rec
 
     if not is_streaming:
         # The partitioning of python batch source read is determined before query execution.
-        try:
-            partitions = reader.partitions()  # type: ignore[call-arg]
-            if not isinstance(partitions, list):
-                raise PySparkRuntimeError(
-                    errorClass="DATA_SOURCE_TYPE_MISMATCH",
-                    messageParameters={
-                        "expected": "'partitions' to return a list",
-                        "actual": f"'{type(partitions).__name__}'",
-                    },
-                )
-            if not all(isinstance(p, InputPartition) for p in partitions):
-                partition_types = ", ".join([f"'{type(p).__name__}'" for p in partitions])
-                raise PySparkRuntimeError(
-                    errorClass="DATA_SOURCE_TYPE_MISMATCH",
-                    messageParameters={
-                        "expected": "elements in 'partitions' to be of type 'InputPartition'",
-                        "actual": partition_types,
-                    },
-                )
-            if len(partitions) == 0:
-                partitions = [None]  # type: ignore[list-item]
-        except NotImplementedError:
-            partitions = [None]  # type: ignore[list-item]
+        partitions = reader.partitions()  # type: ignore[call-arg]
+        if not isinstance(partitions, list):
+            raise PySparkRuntimeError(
+                errorClass="DATA_SOURCE_TYPE_MISMATCH",
+                messageParameters={
+                    "expected": "'partitions' to return a list",
+                    "actual": f"'{type(partitions).__name__}'",
+                },
+            )
+        if not all(isinstance(p, InputPartition) for p in partitions):
+            partition_types = ", ".join([f"'{type(p).__name__}'" for p in partitions])
+            raise PySparkRuntimeError(
+                errorClass="DATA_SOURCE_TYPE_MISMATCH",
+                messageParameters={
+                    "expected": "elements in 'partitions' to be of type 'InputPartition'",
+                    "actual": partition_types,
+                },
+            )
+        if len(partitions) == 0:
+            partitions = [InputPartition(None)]
 
         # Return the serialized partition values.
         write_int(len(partitions), outfile)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/python/PythonDataSourceSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/python/PythonDataSourceSuite.scala
index bac9849381a3f..a712607f18e41 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/python/PythonDataSourceSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/python/PythonDataSourceSuite.scala
@@ -533,7 +533,7 @@ class PythonDataSourceSuite extends PythonDataSourceSuiteBase {
          |        return []
          |
          |    def read(self, partition):
-         |        if partition is None:
+         |        if partition.value is None:
          |            yield ("success", )
          |        else:
          |            yield ("failed", )