feat: add Model.transform_columns property

google/cloud/bigquery/model.py

@@ -16,6 +16,8 @@
 
 """Define resources for the BigQuery ML Models API."""
 
+from __future__ import annotations
+
 import copy
 import datetime
 import typing
@@ -184,6 +186,22 @@ def feature_columns(self) -> Sequence[standard_sql.StandardSqlField]:
             standard_sql.StandardSqlField.from_api_repr(column) for column in resource
         ]
 
+    @property
+    def transform_columns(self) -> Sequence[TransformColumn]:
+        """The input feature columns that were used to train this model.
+        The output transform columns used to train this model.
+
+        See REST API:
+        https://cloud.google.com/bigquery/docs/reference/rest/v2/models#transformcolumn
+
+        Read-only.
+        """
+        resources = self._properties.get("transformColumns",[])
+        return [
+            TransformColumn(resource)
+            for resource in resources
+        ]
+
     @property
     def label_columns(self) -> Sequence[standard_sql.StandardSqlField]:
         """Label columns that were used to train this model.
@@ -433,6 +451,49 @@ def __repr__(self):
             self.project, self.dataset_id, self.model_id
         )
 
+class TransformColumn:
+    """TransformColumn represents a transform column feature.
+
+    See
+    https://cloud.google.com/bigquery/docs/reference/rest/v2/models#transformcolumn
+
+    Args:
+        resource:
+            A dictionary representing a transform column feature.
+    """
+    def __init__(self,resource: Dict[str, Any]):
+        self._properties = resource
+
+    @property
+    def name(self) -> Optional[str]:
+        return self._properties.get("name")
+
+    @property
+    def type_(self) -> Optional[str]:
+        type_json = self._properties.get("type")
+        if type_json is None:
+            return None
+        return standard_sql.StandardSqlDataType.from_api_repr(type_json)
+
+    @property
+    def transform_sql(self) -> Optional[str]:
+        return self._properties.get("transformSql")
+
+    @classmethod
+    def from_api_repr(cls, resource: Dict[str, Any]) -> "TransformColumn":
+        """Constructs a transform column feature given its API representation
+
+        Args:
+            resource:
+                Transform column feature representation from the API
+
+        Returns:
+            Transform column feature parsed from ``resource``.
+        """
+        this = cls(None)
+        resource = copy.deepcopy(resource)
+        this._properties = resource
+        return this
 
 def _model_arg_to_model_ref(value, default_project=None):
     """Helper to convert a string or Model to ModelReference.

tests/unit/model/test_model.py

@@ -18,7 +18,9 @@
 
 import pytest
 
+
 import google.cloud._helpers
+import google.cloud.bigquery.model
 
 KMS_KEY_NAME = "projects/1/locations/us/keyRings/1/cryptoKeys/1"
 
@@ -136,7 +138,7 @@ def test_from_api_repr(target_class):
         google.cloud._helpers._rfc3339_to_datetime(got.training_runs[2]["startTime"])
         == expiration_time
     )
-
+    assert got.transform_columns == []
 
 def test_from_api_repr_w_minimal_resource(target_class):
     from google.cloud.bigquery import ModelReference
@@ -293,6 +295,49 @@ def test_feature_columns(object_under_test):
     assert object_under_test.feature_columns == expected
 
 
+def test_from_api_repr_w_transform_columns(target_class):
+    resource = {
+    "modelReference": {
+            "projectId": "my-project",
+            "datasetId": "my_dataset",
+            "modelId": "my_model",
+
+        },
+    "transformColumns": [{
+                "name": "transform_name" ,
+                "type": {"typeKind": "INT64"},
+                "transformSql": "transform_sql"
+}]
+}
+    got = target_class.from_api_repr(resource)
+    assert len(got.transform_columns) == 1
+    transform_column = got.transform_columns[0]
+    assert isinstance(transform_column, google.cloud.bigquery.model.TransformColumn)
+    assert transform_column.name == "transform_name"
+
+def test_transform_column_name():
+    transform_columns = google.cloud.bigquery.model.TransformColumn({"name":"is_female"})
+    assert transform_columns.name == "is_female"
+
+def test_transform_column_transform_sql():
+    transform_columns = google.cloud.bigquery.model.TransformColumn({"transformSql": "is_female"})
+    assert transform_columns.transform_sql == "is_female"
+
+def test_transform_column_type():
+    transform_columns = google.cloud.bigquery.model.TransformColumn({"type":{"typeKind": "BOOL"}})
+    assert transform_columns.type_.type_kind == "BOOL"
+
+def test_transform_column_type_none():
+    transform_columns = google.cloud.bigquery.model.TransformColumn({})
+    assert transform_columns.type_ is None
+
+def test_transform_column_properties():
+    transform_column = google.cloud.bigquery.model.TransformColumn({"name": "is_female","type": {
+        "typeKind": "BOOL"},"transformSql":"is_female"})
+    assert transform_column._properties == {"name": "is_female","type": {
+    "typeKind":"BOOL"},"transformSql":"is_female"}
+
+
 def test_label_columns(object_under_test):
     from google.cloud.bigquery import standard_sql