fix(ontology): accept datatype on DatasetField and Metric

converters/ontology/src/ossie_ontology/spec.py

@@ -134,6 +134,7 @@ class DatasetField(OssieObject):
     dimension: Dimension | None = None
     label: str | None = None
     description: str | None = None
+    datatype: str | None = None
     ai_context: AiContext | None = None
     custom_extensions: list[CustomExtension] = Field(default_factory=list)
 
@@ -170,6 +171,7 @@ class Metric(OssieObject):
     name: str
     expression: Expression
     description: str | None = None
+    datatype: str | None = None
     ai_context: AiContext | None = None
     custom_extensions: list[CustomExtension] = Field(default_factory=list)
 

converters/ontology/tests/test_spec.py

@@ -0,0 +1,65 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+"""Tests for the spec DTOs in ossie_ontology.spec."""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+import pytest
+import yaml
+
+from ossie_ontology.spec import DatasetField, Metric, SemanticModel
+
+# tests/ -> ontology -> converters -> <repo root>
+_EXAMPLES_DIR = Path(__file__).resolve().parents[3] / "examples"
+
+
+def test_dataset_field_accepts_datatype():
+    field = DatasetField.model_validate({
+        "name": "ss_quantity",
+        "expression": {"dialects": [{"dialect": "ANSI_SQL", "expression": "ss_quantity"}]},
+        "datatype": "Integer",
+    })
+    assert field.datatype == "Integer"
+
+
+def test_metric_accepts_datatype():
+    metric = Metric.model_validate({
+        "name": "total_sales",
+        "expression": {"dialects": [{"dialect": "ANSI_SQL", "expression": "SUM(ss_sales_price)"}]},
+        "datatype": "Decimal",
+    })
+    assert metric.datatype == "Decimal"
+
+
+def test_tpcds_example_parses():
+    example_path = _EXAMPLES_DIR / "tpcds_semantic_model.yaml"
+    if not example_path.is_file():
+        pytest.skip(f"canonical example not present at {example_path}")
+
+    doc = yaml.safe_load(example_path.read_text(encoding="utf-8"))
+    # A standalone core document carries `version` at the root alongside the
+    # semantic model contents. Keep it once SemanticModel declares it (#441).
+    if "version" not in SemanticModel.model_fields:
+        doc.pop("version", None)
+    model = SemanticModel.model_validate(doc)
+
+    assert model.name == "tpcds_retail_model"
+    assert any(f.datatype for d in model.datasets for f in d.fields)
+    assert any(m.datatype for m in model.metrics)