rename TYPE_NAME and VERSION artifact attributes

sdk/python/kfp/compiler/pipeline_spec_builder.py

@@ -915,8 +915,8 @@ def populate_metrics_in_dag_outputs(
             if artifact_spec.artifact_type.WhichOneof(
                     'kind'
             ) == 'schema_title' and artifact_spec.artifact_type.schema_title in [
-                    artifact_types.Metrics.TYPE_NAME,
-                    artifact_types.ClassificationMetrics.TYPE_NAME,
+                    artifact_types.Metrics.schema_title,
+                    artifact_types.ClassificationMetrics.schema_title,
             ]:
                 unique_output_name = '{}-{}'.format(task.name, output_name)
 

sdk/python/kfp/compiler/test_data/pipelines/pipeline_with_gcpc_types.py

@@ -20,7 +20,7 @@
 
 
 class VertexModel(dsl.Artifact):
-    TYPE_NAME = 'google.VertexModel'
+    schema_title = 'google.VertexModel'
 
 
 producer_op = components.load_component_from_text("""

sdk/python/kfp/compiler/test_data/pipelines/pipeline_with_importer_and_gcpc_types.py

@@ -21,7 +21,7 @@
 
 class VertexDataset(dsl.Artifact):
     """An artifact representing a GCPC Vertex Dataset."""
-    TYPE_NAME = 'google.VertexDataset'
+    schema_title = 'google.VertexDataset'
 
 
 consumer_op = components.load_component_from_text("""

sdk/python/kfp/components/component_factory.py

@@ -142,24 +142,24 @@ def _annotation_to_type_struct(annotation):
             return type_struct
 
         if issubclass(annotation, artifact_types.Artifact
-                     ) and not annotation.TYPE_NAME.startswith('system.'):
+                     ) and not annotation.schema_title.startswith('system.'):
             # For artifact classes not under the `system` namespace,
-            # use its TYPE_NAME as-is.
-            type_name = annotation.TYPE_NAME
+            # use its schema_title as-is.
+            schema_title = annotation.schema_title
         else:
-            type_name = str(annotation.__name__)
+            schema_title = str(annotation.__name__)
 
     elif hasattr(annotation,
                  '__forward_arg__'):  # Handling typing.ForwardRef('Type_name')
-        type_name = str(annotation.__forward_arg__)
+        schema_title = str(annotation.__forward_arg__)
     else:
-        type_name = str(annotation)
+        schema_title = str(annotation)
 
     # It's also possible to get the converter by type name
-    type_struct = type_utils.get_canonical_type_name_for_type(type_name)
+    type_struct = type_utils.get_canonical_type_name_for_type(schema_title)
     if type_struct:
         return type_struct
-    return type_name
+    return schema_title
 
 
 def _maybe_make_unique(name: str, names: List[str]):

sdk/python/kfp/components/executor.py

@@ -133,7 +133,7 @@ def _write_output_artifact_payload(self, name: str, value: Any):
 
     # TODO: extract to a util
     @classmethod
-    def _get_short_type_name(cls, type_name: str) -> str:
+    def _get_short_type_name(cls, schema_title: str) -> str:
         """Extracts the short form type name.
 
         This method is used for looking up serializer for a given type.
@@ -146,17 +146,17 @@ def _get_short_type_name(cls, type_name: str) -> str:
           str -> str
 
         Args:
-          type_name: The original type name.
+          schema_title: The original type name.
 
         Returns:
           The short form type name or the original name if pattern doesn't match.
         """
         import re
-        match = re.match('(typing\.)?(?P<type>\w+)(?:\[.+\])?', type_name)
+        match = re.match('(typing\.)?(?P<type>\w+)(?:\[.+\])?', schema_title)
         if match:
             return match.group('type')
         else:
-            return type_name
+            return schema_title
 
     # TODO: merge with type_utils.is_parameter_type
     @classmethod

sdk/python/kfp/components/for_loop.py

@@ -21,7 +21,7 @@
 ItemList = List[Union[int, float, str, Dict[str, Any]]]
 
 
-def _get_loop_item_type(type_name: str) -> Optional[str]:
+def _get_loop_item_type(schema_title: str) -> Optional[str]:
     """Extracts the loop item type.
 
     This method is used for extract the item type from a collection type.
@@ -34,19 +34,20 @@ def _get_loop_item_type(type_name: str) -> Optional[str]:
         str -> None
 
     Args:
-        type_name: The collection type name, like `List`, Sequence`, etc.
+        schema_title: The collection type name, like `List`, Sequence`, etc.
 
     Returns:
         The collection item type or None if no match found.
     """
-    match = re.match('(typing\.)?(?:\w+)(?:\[(?P<item_type>.+)\])', type_name)
+    match = re.match('(typing\.)?(?:\w+)(?:\[(?P<item_type>.+)\])',
+                     schema_title)
     if match:
         return match.group('item_type').lstrip().rstrip()
     else:
         return None
 
 
-def _get_subvar_type(type_name: str) -> Optional[str]:
+def _get_subvar_type(schema_title: str) -> Optional[str]:
     """Extracts the subvar type.
 
     This method is used for extract the value type from a dictionary type.
@@ -56,14 +57,14 @@ def _get_subvar_type(type_name: str) -> Optional[str]:
         typing.Mapping[str, float] -> float
 
     Args:
-        type_name: The dictionary type.
+        schema_title: The dictionary type.
 
     Returns:
         The dictionary value type or None if no match found.
     """
     match = re.match(
         '(typing\.)?(?:\w+)(?:\[\s*(?:\w+)\s*,\s*(?P<value_type>.+)\])',
-        type_name)
+        schema_title)
     if match:
         return match.group('value_type').lstrip().rstrip()
     else:

sdk/python/kfp/components/importer_node.py

@@ -55,24 +55,24 @@ def pipeline_with_importer():
           train(dataset=importer1.output)
     """
     if issubclass(artifact_class, artifact_types.Artifact
-                 ) and not artifact_class.TYPE_NAME.startswith('system.'):
+                 ) and not artifact_class.schema_title.startswith('system.'):
         # For artifact classes not under the `system` namespace,
-        # use its TYPE_NAME as-is.
-        type_name = artifact_class.TYPE_NAME
+        # use its schema_title as-is.
+        schema_title = artifact_class.schema_title
     else:
-        type_name = artifact_class.__name__
+        schema_title = artifact_class.__name__
 
     component_spec = structures.ComponentSpec(
         name='importer',
         implementation=structures.Implementation(
             importer=structures.ImporterSpec(
                 artifact_uri=placeholders.InputValuePlaceholder(
                     INPUT_KEY).to_placeholder_string(),
-                type_schema=artifact_class.TYPE_NAME,
+                type_schema=artifact_class.schema_title,
                 reimport=reimport,
                 metadata=metadata)),
         inputs={INPUT_KEY: structures.InputSpec(type='String')},
-        outputs={OUTPUT_KEY: structures.OutputSpec(type=type_name)},
+        outputs={OUTPUT_KEY: structures.OutputSpec(type=schema_title)},
     )
 
     importer = importer_component.ImporterComponent(

sdk/python/kfp/components/types/artifact_types.py

@@ -16,7 +16,7 @@
 These are only compatible with v2 Pipelines.
 """
 
-from typing import Dict, List, Optional
+from typing import Dict, List, Optional, Type
 
 _GCS_LOCAL_MOUNT_PREFIX = '/gcs/'
 _MINIO_LOCAL_MOUNT_PREFIX = '/minio/'
@@ -63,8 +63,8 @@ def my_pipeline():
 
     Note: Other artifacts are used similarly to the usage of ``Artifact`` in the example above (within ``Input[]`` and ``Output[]``).
     """
-    TYPE_NAME = 'system.Artifact'
-    VERSION = '0.0.1'
+    schema_title = 'system.Artifact'
+    schema_version = '0.0.1'
 
     def __init__(self,
                  name: Optional[str] = None,
@@ -110,7 +110,7 @@ class Model(Artifact):
         uri: The model's location on disk or cloud storage.
         metadata: Arbitrary key-value pairs about the model.
     """
-    TYPE_NAME = 'system.Model'
+    schema_title = 'system.Model'
 
     def __init__(self,
                  name: Optional[str] = None,
@@ -141,7 +141,7 @@ class Dataset(Artifact):
         uri: The dataset's location on disk or cloud storage.
         metadata: Arbitrary key-value pairs about the dataset.
     """
-    TYPE_NAME = 'system.Dataset'
+    schema_title = 'system.Dataset'
 
     def __init__(self,
                  name: Optional[str] = None,
@@ -158,7 +158,7 @@ class Metrics(Artifact):
         uri: The metrics artifact's location on disk or cloud storage.
         metadata: Key-value scalar metrics.
     """
-    TYPE_NAME = 'system.Metrics'
+    schema_title = 'system.Metrics'
 
     def __init__(self,
                  name: Optional[str] = None,
@@ -184,7 +184,7 @@ class ClassificationMetrics(Artifact):
         uri: The metrics artifact's location on disk or cloud storage.
         metadata: The key-value scalar metrics.
     """
-    TYPE_NAME = 'system.ClassificationMetrics'
+    schema_title = 'system.ClassificationMetrics'
 
     def __init__(self,
                  name: Optional[str] = None,
@@ -347,7 +347,7 @@ class SlicedClassificationMetrics(Artifact):
         metadata: Arbitrary key-value pairs about the metrics artifact.
     """
 
-    TYPE_NAME = 'system.SlicedClassificationMetrics'
+    schema_title = 'system.SlicedClassificationMetrics'
 
     def __init__(self,
                  name: Optional[str] = None,
@@ -472,7 +472,7 @@ class HTML(Artifact):
         uri: The HTML file's location on disk or cloud storage.
         metadata: Arbitrary key-value pairs about the HTML file.
     """
-    TYPE_NAME = 'system.HTML'
+    schema_title = 'system.HTML'
 
     def __init__(self,
                  name: Optional[str] = None,
@@ -489,7 +489,7 @@ class Markdown(Artifact):
         uri: The markdown file's location on disk or cloud storage.
         metadata: Arbitrary key-value pairs about the markdown file.
     """
-    TYPE_NAME = 'system.Markdown'
+    schema_title = 'system.Markdown'
 
     def __init__(self,
                  name: Optional[str] = None,
@@ -498,8 +498,8 @@ def __init__(self,
         super().__init__(uri=uri, name=name, metadata=metadata)
 
 
-_SCHEMA_TITLE_TO_TYPE: Dict[str, Artifact] = {
-    x.TYPE_NAME: x for x in [
+_SCHEMA_TITLE_TO_TYPE: Dict[str, Type[Artifact]] = {
+    x.schema_title: x for x in [
         Artifact,
         Model,
         Dataset,

sdk/python/kfp/components/types/type_annotations.py

@@ -229,7 +229,7 @@ def maybe_strip_optional_from_annotation(annotation: T) -> T:
     return annotation
 
 
-def get_short_type_name(type_name: str) -> str:
+def get_short_type_name(schema_title: str) -> str:
     """Extracts the short form type name.
 
     This method is used for looking up serializer for a given type.
@@ -242,13 +242,13 @@ def get_short_type_name(type_name: str) -> str:
       str -> str
 
     Args:
-      type_name: The original type name.
+      schema_title: The original type name.
 
     Returns:
       The short form type name or the original name if pattern doesn't match.
     """
-    match = re.match('(typing\.)?(?P<type>\w+)(?:\[.+\])?', type_name)
+    match = re.match('(typing\.)?(?P<type>\w+)(?:\[.+\])?', schema_title)
     if match:
         return match.group('type')
     else:
-        return type_name
+        return schema_title