fix(spark): reject bool type as CPU in _validate_cpu_value

kubeflow/spark/backends/kubernetes/utils.py

@@ -114,8 +114,8 @@ def _resolve_driver_resources(
         Tuple of (cores, memory).
 
     Raises:
-        ValueError:
-            If the configured CPU or memory values are invalid.
+        ValueError: If the configured CPU or memory values are invalid.
+        TypeError: If an unsupported CPU type (such as bool) is passed.
     """
 
     cores = constants.DEFAULT_DRIVER_CPU
@@ -136,7 +136,7 @@ def _resolve_driver_resources(
 def _resolve_executor_resources(
     executor: Executor | None = None,
     num_executors: int | None = None,
-    resources_per_executor: dict[str, str] | None = None,
+    resources_per_executor: dict[str, str | int] | None = None,
 ) -> tuple[int, int, str]:
     """Resolve executor configuration.
 
@@ -154,8 +154,8 @@ def _resolve_executor_resources(
         Tuple containing ``(instances, cores, memory)``.
 
     Raises:
-        ValueError:
-            If the configured CPU or memory values are invalid.
+        ValueError: If the configured CPU or memory values are invalid.
+        TypeError: If an unsupported CPU type (such as bool) is passed.
     """
 
     if executor and executor.num_instances is not None:
@@ -257,11 +257,15 @@ def _validate_cpu_value(cpu: str | int | None) -> int:
         Integer CPU core value.
 
     Raises:
-        ValueError: If CPU value is invalid.
+        ValueError: If CPU value is invalid or non-positive.
+        TypeError: If an unsupported type (such as bool) is passed.
     """
     if cpu is None:
         raise ValueError("CPU value cannot be None")
 
+    if isinstance(cpu, bool):
+        raise TypeError("Invalid CPU type 'bool'. Expected str or int.")
+
     if isinstance(cpu, int):
         cores = float(cpu)
 
@@ -279,13 +283,19 @@ def _validate_cpu_value(cpu: str | int | None) -> int:
                     f"Invalid CPU value '{cpu}'. Decimal milli-CPU values are not supported."
                 )
 
-            cores = int(milli_cpu) / 1000
+            try:
+                cores = int(milli_cpu) / 1000
+            except ValueError as e:
+                raise ValueError(f"Invalid CPU value '{cpu}'.") from e
 
         else:
-            cores = float(cpu)
+            try:
+                cores = float(cpu)
+            except ValueError as e:
+                raise ValueError(f"Invalid CPU value '{cpu}'.") from e
 
     else:
-        raise ValueError(f"Invalid CPU type '{type(cpu)}'. Expected str or int.")
+        raise TypeError(f"Invalid CPU type '{type(cpu).__name__}'. Expected str or int.")
 
     if not math.isfinite(cores) or cores <= 0:
         raise ValueError(f"Invalid CPU value: {cpu!r}")
@@ -473,7 +483,7 @@ def get_spark_connect_driver_spec(
 def get_spark_connect_executor_spec(
     executor: Executor | None = None,
     num_executors: int | None = None,
-    resources_per_executor: dict[str, str] | None = None,
+    resources_per_executor: dict[str, str | int] | None = None,
 ) -> models.SparkV1alpha1ExecutorSpec:
     """Convert SDK Executor to API ExecutorSpec.
 
@@ -490,8 +500,8 @@ def get_spark_connect_executor_spec(
         API ExecutorSpec model.
 
     Raises:
-        ValueError:
-            If the configured executor resources are invalid.
+        ValueError: If the configured executor resources are invalid.
+        TypeError: If an unsupported CPU type (such as bool) is passed.
     """
     instances, cores, memory = _resolve_executor_resources(
         executor,
@@ -511,7 +521,7 @@ def build_spark_connect_cr(
     namespace: str,
     spark_version: str | None = None,
     num_executors: int | None = None,
-    resources_per_executor: dict[str, str] | None = None,
+    resources_per_executor: dict[str, str | int] | None = None,
     spark_conf: dict[str, str] | None = None,
     driver: Driver | None = None,
     executor: Executor | None = None,
@@ -542,8 +552,8 @@ def build_spark_connect_cr(
         SparkConnect CR as typed Pydantic model.
 
     Raises:
-        ValueError:
-            If the provided driver or executor resource configuration is invalid.
+        ValueError: If the provided driver or executor resource configuration is invalid.
+        TypeError: If an unsupported CPU type (such as bool) is passed.
     """
     _validate_spark_conf(spark_conf)
 
@@ -688,7 +698,7 @@ def get_spark_job_driver_spec(
 
 def get_spark_job_executor_spec(
     num_executors: int | None = None,
-    resources_per_executor: dict[str, str] | None = None,
+    resources_per_executor: dict[str, str | int] | None = None,
 ) -> models.SparkV1beta2ExecutorSpec:
     """Build ExecutorSpec for SparkApplication.
 
@@ -802,7 +812,7 @@ def get_spark_application_cr_from_file_job(
     main_file: str,
     arguments: list[str] | None = None,
     num_executors: int | None = None,
-    resources_per_executor: dict[str, str] | None = None,
+    resources_per_executor: dict[str, str | int] | None = None,
     options: list | None = None,
     backend: Any | None = None,
     spark_conf: dict[str, str] | None = None,
@@ -865,7 +875,7 @@ def get_spark_application_cr_from_func_job(
     func: Callable,
     func_args: dict[str, Any] | None = None,
     num_executors: int | None = None,
-    resources_per_executor: dict[str, str] | None = None,
+    resources_per_executor: dict[str, str | int] | None = None,
     options: list | None = None,
     backend: Any | None = None,
     spark_conf: dict[str, str] | None = None,

kubeflow/spark/backends/kubernetes/utils_test.py

@@ -39,6 +39,7 @@
     get_spark_application_cr_from_file_job,
     get_spark_application_cr_from_func_job,
     get_spark_application_info_from_cr,
+    get_spark_connect_executor_spec,
     get_spark_connect_info_from_cr,
     get_spark_job_driver_spec,
     get_spark_job_executor_spec,
@@ -98,11 +99,6 @@ def mock_k8s_backend():
     backend.__class__ = KubernetesBackend
     return backend
 
-    def test_missing_hostname(self):
-        """U16: Missing hostname raises ValueError."""
-        with pytest.raises(ValueError, match="Host is required"):
-            validate_spark_connect_url("sc://:15002")
-
 
 @pytest.fixture
 def spark_connect_resource(minimal_spec):
@@ -966,6 +962,19 @@ def test_generate_job_name(test_case: TestCase) -> None:
             },
             expected_error=ValueError,
         ),
+        TestCase(
+            name="invalid cpu types",
+            expected_status=FAILED,
+            config={
+                "cases": [
+                    True,
+                    False,
+                    [1],
+                    {"cpu": 1},
+                ],
+            },
+            expected_error=TypeError,
+        ),
     ],
 )
 def test_validate_cpu_value(test_case: TestCase) -> None:
@@ -1892,4 +1901,10 @@ def test_get_spark_application_info_from_cr(
         assert job.creation_timestamp == creation_timestamp
         assert job.num_executors == 5
 
+
+def test_get_spark_connect_executor_spec_bool_cpu_raises_type_error():
+    """Verify that boolean CPU values raise TypeError via public construction path."""
+    with pytest.raises(TypeError):
+        get_spark_connect_executor_spec(resources_per_executor={"cpu": True})
+
     print("test execution complete")

kubeflow/spark/types/types.py

@@ -87,7 +87,7 @@ class Driver:
     """
 
     image: str | None = None
-    resources: dict[str, str] | None = None
+    resources: dict[str, str | int] | None = None
     java_options: str | None = None
     service_account: str | None = None
 
@@ -121,7 +121,7 @@ class Executor:
     """
 
     num_instances: int | None = None
-    resources_per_executor: dict[str, str] | None = None
+    resources_per_executor: dict[str, str | int] | None = None
     java_options: str | None = None