[BUGFIX] Metric table.column_type should properly evaluate for Post…

…gres (#10793)

Co-authored-by: Thu Pham <thu.pham@greatexpectations.io>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

docs/docusaurus/docs/reference/learn/data_quality_use_cases/schema_resources/schema_strict_and_relaxed.py

@@ -63,7 +63,7 @@
 )
 
 strict_suite.add_expectation(
-    gxe.ExpectColumnValuesToBeOfType(column="transfer_amount", type_="DOUBLE_PRECISION")
+    gxe.ExpectColumnValuesToBeOfType(column="transfer_amount", type_="DOUBLE PRECISION")
 )
 
 strict_results = batch.validate(strict_suite)
@@ -85,7 +85,7 @@
 
 relaxed_suite.add_expectation(
     gxe.ExpectColumnValuesToBeInTypeList(
-        column="transfer_amount", type_list=["DOUBLE_PRECISION", "STRING"]
+        column="transfer_amount", type_list=["DOUBLE PRECISION", "STRING"]
     )
 )
 

great_expectations/compatibility/postgresql.py

@@ -0,0 +1,78 @@
+from __future__ import annotations
+
+from great_expectations.compatibility.not_imported import NotImported
+
+POSTGRESQL_NOT_IMPORTED = NotImported(
+    "postgresql connection components are not installed, please 'pip install psycopg2'"
+)
+
+try:
+    import psycopg2  # noqa: F401
+    import sqlalchemy.dialects.postgresql as postgresqltypes
+except ImportError:
+    postgresqltypes = POSTGRESQL_NOT_IMPORTED  # type: ignore[assignment]
+
+try:
+    from sqlalchemy.dialects.postgresql import TEXT
+except (ImportError, AttributeError):
+    TEXT = POSTGRESQL_NOT_IMPORTED  # type: ignore[misc, assignment]
+
+try:
+    from sqlalchemy.dialects.postgresql import CHAR
+except (ImportError, AttributeError):
+    CHAR = POSTGRESQL_NOT_IMPORTED  # type: ignore[misc, assignment]
+
+try:
+    from sqlalchemy.dialects.postgresql import INTEGER
+except (ImportError, AttributeError):
+    INTEGER = POSTGRESQL_NOT_IMPORTED  # type: ignore[misc, assignment]
+
+try:
+    from sqlalchemy.dialects.postgresql import SMALLINT
+except (ImportError, AttributeError):
+    SMALLINT = POSTGRESQL_NOT_IMPORTED  # type: ignore[misc, assignment]
+
+try:
+    from sqlalchemy.dialects.postgresql import BIGINT
+except (ImportError, AttributeError):
+    BIGINT = POSTGRESQL_NOT_IMPORTED  # type: ignore[misc, assignment]
+
+try:
+    from sqlalchemy.dialects.postgresql import TIMESTAMP
+except (ImportError, AttributeError):
+    TIMESTAMP = POSTGRESQL_NOT_IMPORTED  # type: ignore[misc, assignment]
+
+try:
+    from sqlalchemy.dialects.postgresql import DATE
+except (ImportError, AttributeError):
+    DATE = POSTGRESQL_NOT_IMPORTED  # type: ignore[misc, assignment]
+
+try:
+    from sqlalchemy.dialects.postgresql import DOUBLE_PRECISION
+except (ImportError, AttributeError):
+    DOUBLE_PRECISION = POSTGRESQL_NOT_IMPORTED  # type: ignore[misc, assignment]
+
+try:
+    from sqlalchemy.dialects.postgresql import BOOLEAN
+except (ImportError, AttributeError):
+    BOOLEAN = POSTGRESQL_NOT_IMPORTED  # type: ignore[misc, assignment]
+
+try:
+    from sqlalchemy.dialects.postgresql import NUMERIC
+except (ImportError, AttributeError):
+    NUMERIC = POSTGRESQL_NOT_IMPORTED  # type: ignore[misc, assignment]
+
+
+class POSTGRESQL_TYPES:
+    """Namespace for PostgreSQL dialect types."""
+
+    TEXT = TEXT
+    CHAR = CHAR
+    INTEGER = INTEGER
+    SMALLINT = SMALLINT
+    BIGINT = BIGINT
+    TIMESTAMP = TIMESTAMP
+    DATE = DATE
+    DOUBLE_PRECISION = DOUBLE_PRECISION
+    BOOLEAN = BOOLEAN
+    NUMERIC = NUMERIC

great_expectations/expectations/core/expect_column_values_to_be_in_type_list.py

@@ -458,7 +458,11 @@ def _validate_pandas(  # noqa: C901, PLR0912
     def _validate_sqlalchemy(self, actual_column_type, expected_types_list, execution_engine):
         if expected_types_list is None:
             success = True
-        elif execution_engine.dialect_name in [GXSqlDialect.SNOWFLAKE, GXSqlDialect.DATABRICKS]:
+        elif execution_engine.dialect_name in [
+            GXSqlDialect.DATABRICKS,
+            GXSqlDialect.POSTGRESQL,
+            GXSqlDialect.SNOWFLAKE,
+        ]:
             success = isinstance(actual_column_type, str) and any(
                 actual_column_type.lower() == expected_type.lower()
                 for expected_type in expected_types_list

great_expectations/expectations/core/expect_column_values_to_be_of_type.py

@@ -412,7 +412,11 @@ def _validate_sqlalchemy(self, actual_column_type, expected_type, execution_engi
 
         if expected_type is None:
             success = True
-        elif execution_engine.dialect_name in [GXSqlDialect.SNOWFLAKE, GXSqlDialect.DATABRICKS]:
+        elif execution_engine.dialect_name in [
+            GXSqlDialect.DATABRICKS,
+            GXSqlDialect.POSTGRESQL,
+            GXSqlDialect.SNOWFLAKE,
+        ]:
             success = (
                 isinstance(actual_column_type, str)
                 and actual_column_type.lower() == expected_type.lower()

great_expectations/expectations/metrics/util.py

@@ -360,7 +360,7 @@ def __getitem__(self, key: Any) -> Any:
         return item
 
 
-def get_sqlalchemy_column_metadata(  # noqa: C901
+def get_sqlalchemy_column_metadata(  # noqa: C901, PLR0912
     execution_engine: SqlAlchemyExecutionEngine,
     table_selectable: sqlalchemy.Select,
     schema_name: Optional[str] = None,
@@ -414,11 +414,18 @@ def get_sqlalchemy_column_metadata(  # noqa: C901
             )
 
         dialect_name = execution_engine.dialect.name
-        if dialect_name in [GXSqlDialect.SNOWFLAKE, GXSqlDialect.DATABRICKS]:
+        if dialect_name in [
+            GXSqlDialect.DATABRICKS,
+            GXSqlDialect.POSTGRESQL,
+            GXSqlDialect.SNOWFLAKE,
+        ]:
             # WARNING: Do not alter columns in place, as they are cached on the inspector
             columns_copy = [column.copy() for column in columns]
             for column in columns_copy:
-                column["type"] = column["type"].compile(dialect=execution_engine.dialect)
+                if column.get("type"):
+                    # When using column_reflection_fallback, we might not be able to
+                    # extract the column type, and only have the column name
+                    column["type"] = column["type"].compile(dialect=execution_engine.dialect)
             if dialect_name == GXSqlDialect.SNOWFLAKE:
                 return [
                     # TODO: SmartColumn should know the dialect and do lookups based on that

tests/integration/data_sources_and_expectations/expectations/test_expect_column_values_to_be_in_type_list.py

@@ -5,6 +5,7 @@
 
 import great_expectations.expectations as gxe
 from great_expectations.compatibility.databricks import DATABRICKS_TYPES
+from great_expectations.compatibility.postgresql import POSTGRESQL_TYPES
 from great_expectations.compatibility.snowflake import SNOWFLAKE_TYPES
 from great_expectations.compatibility.sqlalchemy import (
     sqlalchemy as sa,
@@ -19,6 +20,7 @@
 from tests.integration.test_utils.data_source_config import (
     DatabricksDatasourceTestConfig,
     PandasDataFrameDatasourceTestConfig,
+    PostgreSQLDatasourceTestConfig,
     SnowflakeDatasourceTestConfig,
 )
 
@@ -386,6 +388,110 @@ def test_success_complete_snowflake(
     assert result_dict["observed_value"] in expectation.type_list
 
 
+@pytest.mark.parametrize(
+    "expectation",
+    [
+        pytest.param(
+            gxe.ExpectColumnValuesToBeInTypeList(column="CHAR", type_list=["CHAR", "CHAR(1)"]),
+            id="CHAR",
+        ),
+        pytest.param(
+            gxe.ExpectColumnValuesToBeInTypeList(column="TEXT", type_list=["TEXT"]),
+            id="TEXT",
+        ),
+        pytest.param(
+            gxe.ExpectColumnValuesToBeInTypeList(column="INTEGER", type_list=["INTEGER"]),
+            id="INTEGER",
+        ),
+        pytest.param(
+            gxe.ExpectColumnValuesToBeInTypeList(column="SMALLINT", type_list=["SMALLINT"]),
+            id="SMALLINT",
+        ),
+        pytest.param(
+            gxe.ExpectColumnValuesToBeInTypeList(column="BIGINT", type_list=["BIGINT"]),
+            id="BIGINT",
+        ),
+        pytest.param(
+            gxe.ExpectColumnValuesToBeInTypeList(
+                column="TIMESTAMP", type_list=["TIMESTAMP", "TIMESTAMP WITHOUT TIME ZONE"]
+            ),
+            id="TIMESTAMP",
+        ),
+        pytest.param(
+            gxe.ExpectColumnValuesToBeInTypeList(column="DATE", type_list=["DATE"]),
+            id="DATE",
+        ),
+        pytest.param(
+            gxe.ExpectColumnValuesToBeInTypeList(
+                column="DOUBLE_PRECISION", type_list=["DOUBLE PRECISION"]
+            ),
+            id="DOUBLE_PRECISION",
+        ),
+        pytest.param(
+            gxe.ExpectColumnValuesToBeInTypeList(column="BOOLEAN", type_list=["BOOLEAN"]),
+            id="BOOLEAN",
+        ),
+        pytest.param(
+            gxe.ExpectColumnValuesToBeInTypeList(column="NUMERIC", type_list=["NUMERIC"]),
+            id="NUMERIC",
+        ),
+    ],
+)
+@parameterize_batch_for_data_sources(
+    data_source_configs=[
+        PostgreSQLDatasourceTestConfig(
+            column_types={
+                "CHAR": POSTGRESQL_TYPES.CHAR,
+                "TEXT": POSTGRESQL_TYPES.TEXT,
+                "INTEGER": POSTGRESQL_TYPES.INTEGER,
+                "SMALLINT": POSTGRESQL_TYPES.SMALLINT,
+                "BIGINT": POSTGRESQL_TYPES.BIGINT,
+                "TIMESTAMP": POSTGRESQL_TYPES.TIMESTAMP,
+                "DATE": POSTGRESQL_TYPES.DATE,
+                "DOUBLE_PRECISION": POSTGRESQL_TYPES.DOUBLE_PRECISION,
+                "BOOLEAN": POSTGRESQL_TYPES.BOOLEAN,
+                "NUMERIC": POSTGRESQL_TYPES.NUMERIC,
+            }
+        ),
+    ],
+    data=pd.DataFrame(
+        {
+            "CHAR": ["a", "b", "c"],
+            "TEXT": ["a", "b", "c"],
+            "INTEGER": [1, 2, 3],
+            "SMALLINT": [1, 2, 3],
+            "BIGINT": [1, 2, 3],
+            "TIMESTAMP": [
+                "2021-01-01 00:00:00",
+                "2021-01-02 00:00:00",
+                "2021-01-03 00:00:00",
+            ],
+            "DATE": [
+                # Date in isoformat
+                "2021-01-01",
+                "2021-01-02",
+                "2021-01-03",
+            ],
+            "DOUBLE_PRECISION": [1.0, 2.0, 3.0],
+            "BOOLEAN": [False, False, True],
+            "NUMERIC": [1, 2, 3],
+        },
+        dtype="object",
+    ),
+)
+def test_success_complete_postgres(
+    batch_for_datasource: Batch, expectation: gxe.ExpectColumnValuesToBeInTypeList
+) -> None:
+    result = batch_for_datasource.validate(expectation, result_format=ResultFormat.COMPLETE)
+    result_dict = result.to_json_dict()["result"]
+
+    assert result.success
+    assert isinstance(result_dict, dict)
+    assert isinstance(result_dict["observed_value"], str)
+    assert isinstance(expectation.type_list, list)
+    assert result_dict["observed_value"] in expectation.type_list
+
+
 @pytest.mark.parametrize(
     "expectation",
     [