Address comments

superset-core/src/superset_core/semantic_layers/layer.py

@@ -21,7 +21,7 @@ from abc import ABC, abstractmethod
 from typing import Any, Generic, TypeVar
 
 from pydantic import BaseModel
-from superset_core.semantic_layers.semantic_view import SemanticView
+from superset_core.semantic_layers.view import SemanticView
 
 ConfigT = TypeVar("ConfigT", bound=BaseModel)
 SemanticViewT = TypeVar("SemanticViewT", bound="SemanticView")

superset-core/src/superset_core/semantic_layers/types.py

@@ -25,29 +25,6 @@ from typing import Type as TypeOf
 
 import pyarrow as pa
 
-__all__ = [
-    "BINARY",
-    "BOOLEAN",
-    "DATE",
-    "DATETIME",
-    "DECIMAL",
-    "Day",
-    "Dimension",
-    "Hour",
-    "INTEGER",
-    "INTERVAL",
-    "Minute",
-    "Month",
-    "NUMBER",
-    "OBJECT",
-    "Quarter",
-    "Second",
-    "STRING",
-    "TIME",
-    "Week",
-    "Year",
-]
-
 
 class Type:
     """
@@ -216,7 +193,7 @@ class Metric:
     name: str
     type: TypeOf[Type]
 
-    definition: str | None
+    definition: str | None = None
     description: str | None = None
 
 

superset-core/src/superset_core/semantic_layers/view.py

@@ -77,7 +77,7 @@ class SemanticView(ABC):
         """
 
     @abstractmethod
-    def get_dataframe(
+    def get_table(
         self,
         metrics: list[Metric],
         dimensions: list[Dimension],
@@ -107,3 +107,23 @@ class SemanticView(ABC):
         """
         Execute a query and return the number of rows the result would have.
         """
+
+    @abstractmethod
+    def get_compatible_metrics(
+        self,
+        selected_metrics: set[Metric],
+        selected_dimensions: set[Dimension],
+    ) -> set[Metric]:
+        """
+        Return metrics compatible with the selected dimensions.
+        """
+
+    @abstractmethod
+    def get_compatible_dimensions(
+        self,
+        selected_metrics: set[Metric],
+        selected_dimensions: set[Dimension],
+    ) -> set[Dimension]:
+        """
+        Return dimensions compatible with the selected metrics.
+        """

superset/semantic_layers/mapper.py

@@ -30,7 +30,6 @@ from typing import Any, cast, Sequence, TypeGuard
 
 import numpy as np
 import pyarrow as pa
-from superset_core.semantic_layers.semantic_view import SemanticViewFeature
 from superset_core.semantic_layers.types import (
     AdhocExpression,
     Day,
@@ -54,6 +53,7 @@ from superset_core.semantic_layers.types import (
     Week,
     Year,
 )
+from superset_core.semantic_layers.view import SemanticViewFeature
 
 from superset.common.db_query_status import QueryStatus
 from superset.common.query_object import QueryObject
@@ -348,8 +348,6 @@ def map_query_object(query_object: ValidatedQueryObject) -> list[SemanticQuery]:
             time_offset,
             all_dimensions,
         )
-        print(">>", filters)
-
         queries.append(
             SemanticQuery(
                 metrics=metrics,
@@ -603,8 +601,8 @@ def _convert_query_object_filter(
 
     operator = operator_mapping.get(operator_str)
     if not operator:
-        # Unknown operator - create adhoc filter
-        return None
+        # Unknown operator - raise error to prevent unauthorized access
+        raise ValueError(f"Unsupported filter operator: {operator_str}")
 
     return {
         Filter(

tests/unit_tests/semantic_layers/mapper_test.py

@@ -22,7 +22,6 @@ import pandas as pd
 import pyarrow as pa
 import pytest
 from pytest_mock import MockerFixture
-from superset_core.semantic_layers.semantic_view import SemanticViewFeature
 from superset_core.semantic_layers.types import (
     AdhocExpression,
     Day,
@@ -48,6 +47,7 @@ from superset_core.semantic_layers.types import (
     Week,
     Year,
 )
+from superset_core.semantic_layers.view import SemanticViewFeature
 
 from superset.semantic_layers.mapper import (
     _convert_query_object_filter,
@@ -59,12 +59,18 @@ from superset.semantic_layers.mapper import (
     _get_order_from_query_object,
     _get_time_bounds,
     _get_time_filter,
+    _normalize_column,
+    _validate_filters,
+    _validate_granularity,
+    _validate_group_limit,
+    _validate_metrics,
     get_results,
     map_query_object,
     validate_query_object,
     ValidatedQueryObject,
     ValidatedQueryObjectFilterClause,
 )
+from superset.superset_typing import AdhocColumn
 from superset.utils.core import FilterOperator
 
 # Alias for convenience
@@ -1717,9 +1723,6 @@ def test_normalize_column_adhoc_not_in_dimensions() -> None:
     """
     Test _normalize_column raises error for AdhocColumn with sqlExpression not in dims.
     """
-    from superset.semantic_layers.mapper import _normalize_column
-    from superset.superset_typing import AdhocColumn
-
     dimension_names = {"category", "region"}
     adhoc_column: AdhocColumn = {
         "isColumnReference": True,
@@ -1734,9 +1737,6 @@ def test_normalize_column_adhoc_missing_sql_expression() -> None:
     """
     Test _normalize_column raises error for AdhocColumn without sqlExpression.
     """
-    from superset.semantic_layers.mapper import _normalize_column
-    from superset.superset_typing import AdhocColumn
-
     dimension_names = {"category", "region"}
     adhoc_column: AdhocColumn = {
         "isColumnReference": True,
@@ -1750,9 +1750,6 @@ def test_normalize_column_adhoc_valid(mock_datasource: MagicMock) -> None:
     """
     Test _normalize_column with valid AdhocColumn reference.
     """
-    from superset.semantic_layers.mapper import _normalize_column
-    from superset.superset_typing import AdhocColumn
-
     dimension_names = {"category", "region"}
     adhoc_column: AdhocColumn = {
         "isColumnReference": True,
@@ -2115,8 +2112,6 @@ def test_validate_metrics_adhoc_error(
     """
     Test validation error for adhoc metrics.
     """
-    from superset.semantic_layers.mapper import _validate_metrics
-
     mock_datasource = mocker.Mock()
     category_dim = Dimension("category", "category", STRING, "category", "Category")
     sales_metric = Metric("total_sales", "total_sales", NUMBER, "SUM(amount)", "Sales")
@@ -2139,7 +2134,6 @@ def test_validate_filters_adhoc_column_error(
     """
     Test validation error for adhoc column in filter.
     """
-    from superset.semantic_layers.mapper import _validate_filters
 
     query_object = mocker.Mock()
     query_object.filter = [
@@ -2160,7 +2154,6 @@ def test_validate_filters_missing_operator_error(
     """
     Test validation error for filter without operator.
     """
-    from superset.semantic_layers.mapper import _validate_filters
 
     query_object = mocker.Mock()
     query_object.filter = [
@@ -2481,7 +2474,6 @@ def test_validate_filters_empty(mocker: MockerFixture) -> None:
     """
     Test _validate_filters with empty filter list (the loop doesn't run).
     """
-    from superset.semantic_layers.mapper import _validate_filters
 
     query_object = mocker.Mock()
     query_object.filter = []  # Empty filter list
@@ -2494,7 +2486,6 @@ def test_validate_granularity_valid(mocker: MockerFixture) -> None:
     """
     Test _validate_granularity with valid granularity and time grain.
     """
-    from superset.semantic_layers.mapper import _validate_granularity
 
     mock_datasource = mocker.Mock()
     time_dim = Dimension("order_date", "order_date", STRING, "order_date", "Date", Day)
@@ -2514,7 +2505,6 @@ def test_validate_group_limit_valid(mocker: MockerFixture) -> None:
     """
     Test _validate_group_limit with valid group limit settings.
     """
-    from superset.semantic_layers.mapper import _validate_group_limit
 
     mock_datasource = mocker.Mock()
     category_dim = Dimension("category", "category", STRING, "category", "Category")
@@ -2647,7 +2637,6 @@ def test_validate_filters_with_valid_filters(mocker: MockerFixture) -> None:
     Test _validate_filters with valid filters that pass validation.
     This covers the branch where the loop completes without raising.
     """
-    from superset.semantic_layers.mapper import _validate_filters
 
     query_object = mocker.Mock()
     query_object.filter = [