test(athena): add functional test for Spark Connect python model path

Skipped unless DBT_TEST_ATHENA_SPARK_WORK_GROUP points to a Spark 3.5
workgroup. Forces +materialized: table because Spark's
HiveExternalCatalog cannot resolve Athena views (no S3 location).

Author: dtaniwaki

dbt-athena/tests/functional/adapter/test_spark_connect_python_submissions.py

@@ -0,0 +1,52 @@
+import os
+
+import pytest
+
+from dbt.tests.adapter.python_model.test_python_model import (
+    BasePythonModelTests,
+    basic_sql,
+    schema_yml,
+    second_sql,
+)
+
+# spark_engine_version="3.5" routes execution through Spark Connect.
+# DBT_TEST_ATHENA_SPARK_WORK_GROUP must point to a workgroup whose
+# engine version is set to Apache Spark 3.5.
+spark_connect_python = """
+def model(dbt, _):
+    dbt.config(
+        materialized='table',
+        spark_engine_version='3.5',
+    )
+    df = dbt.ref("my_sql_model")
+    df2 = dbt.ref("my_versioned_sql_model", v=1)
+    df3 = dbt.ref("my_versioned_sql_model", version=1)
+    df4 = dbt.ref("test", "my_versioned_sql_model", v=1)
+    df5 = dbt.ref("test", "my_versioned_sql_model", version=1)
+    df6 = dbt.source("test_source", "test_table")
+    df = df.limit(2)
+    return df
+"""
+
+
+@pytest.mark.skipif(
+    not os.getenv("DBT_TEST_ATHENA_SPARK_WORK_GROUP"),
+    reason="DBT_TEST_ATHENA_SPARK_WORK_GROUP must point to a Spark 3.5 workgroup.",
+)
+class TestSparkConnectPythonModel(BasePythonModelTests):
+    @pytest.fixture(scope="class")
+    def project_config_update(self):
+        # Athena defaults SQL models to views, but Spark's HiveExternalCatalog
+        # cannot resolve Athena views (no S3 location), so dbt.ref() blows up
+        # with "Can not create a Path from an empty string".  Force tables.
+        return {"models": {"+materialized": "table"}}
+
+    @pytest.fixture(scope="class")
+    def models(self):
+        return {
+            "schema.yml": schema_yml,
+            "my_sql_model.sql": basic_sql,
+            "my_versioned_sql_model_v1.sql": basic_sql,
+            "my_python_model.py": spark_connect_python,
+            "second_sql_model.sql": second_sql,
+        }