feat(mcp): add pie, pivot table, and mixed timeseries chart creation support (#38375)

tests/unit_tests/mcp_service/chart/test_new_chart_types.py

@@ -0,0 +1,929 @@
+# 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.
+
+"""
+Unit tests for new MCP chart types: pie, pivot_table, mixed_timeseries.
+
+Tests cover schema validation, form_data mapping, chart name generation,
+and schema validator pre-validation for all three new chart types.
+"""
+
+from unittest.mock import patch
+
+import pytest
+from pydantic import ValidationError
+
+from superset.mcp_service.chart.chart_utils import (
+    generate_chart_name,
+    map_config_to_form_data,
+    map_mixed_timeseries_config,
+    map_pie_config,
+    map_pivot_table_config,
+)
+from superset.mcp_service.chart.schemas import (
+    AxisConfig,
+    ColumnRef,
+    FilterConfig,
+    MixedTimeseriesChartConfig,
+    PieChartConfig,
+    PivotTableChartConfig,
+)
+from superset.mcp_service.chart.validation.schema_validator import SchemaValidator
+
+# ============================================================
+# Pie Chart Schema Tests
+# ============================================================
+
+
+class TestPieChartConfigSchema:
+    """Test PieChartConfig Pydantic schema validation."""
+
+    def test_basic_pie_config(self) -> None:
+        config = PieChartConfig(
+            chart_type="pie",
+            dimension=ColumnRef(name="product"),
+            metric=ColumnRef(name="revenue", aggregate="SUM"),
+        )
+        assert config.chart_type == "pie"
+        assert config.dimension.name == "product"
+        assert config.metric.aggregate == "SUM"
+        assert config.donut is False
+        assert config.show_labels is True
+        assert config.label_type == "key_value_percent"
+
+    def test_donut_chart_config(self) -> None:
+        config = PieChartConfig(
+            chart_type="pie",
+            dimension=ColumnRef(name="category"),
+            metric=ColumnRef(name="count", aggregate="COUNT"),
+            donut=True,
+            inner_radius=40,
+            outer_radius=80,
+        )
+        assert config.donut is True
+        assert config.inner_radius == 40
+        assert config.outer_radius == 80
+
+    def test_pie_config_with_all_options(self) -> None:
+        config = PieChartConfig(
+            chart_type="pie",
+            dimension=ColumnRef(name="region"),
+            metric=ColumnRef(name="sales", aggregate="SUM", label="Total Sales"),
+            donut=True,
+            show_labels=False,
+            label_type="percent",
+            sort_by_metric=False,
+            show_legend=False,
+            row_limit=50,
+            number_format="$,.2f",
+            show_total=True,
+            labels_outside=False,
+            outer_radius=90,
+            inner_radius=50,
+            filters=[FilterConfig(column="status", op="=", value="active")],
+        )
+        assert config.show_labels is False
+        assert config.label_type == "percent"
+        assert config.row_limit == 50
+        assert config.show_total is True
+        assert config.filters is not None
+        assert len(config.filters) == 1
+
+    def test_pie_config_rejects_extra_fields(self) -> None:
+        with pytest.raises(ValidationError):
+            PieChartConfig(
+                chart_type="pie",
+                dimension=ColumnRef(name="product"),
+                metric=ColumnRef(name="revenue", aggregate="SUM"),
+                unknown_field="bad",
+            )
+
+    def test_pie_config_missing_dimension(self) -> None:
+        with pytest.raises(ValidationError):
+            PieChartConfig(
+                chart_type="pie",
+                metric=ColumnRef(name="revenue", aggregate="SUM"),
+            )
+
+    def test_pie_config_missing_metric(self) -> None:
+        with pytest.raises(ValidationError):
+            PieChartConfig(
+                chart_type="pie",
+                dimension=ColumnRef(name="product"),
+            )
+
+    def test_pie_config_row_limit_bounds(self) -> None:
+        with pytest.raises(ValidationError):
+            PieChartConfig(
+                chart_type="pie",
+                dimension=ColumnRef(name="product"),
+                metric=ColumnRef(name="revenue", aggregate="SUM"),
+                row_limit=0,
+            )
+
+    def test_pie_config_valid_label_types(self) -> None:
+        for label_type in [
+            "key",
+            "value",
+            "percent",
+            "key_value",
+            "key_percent",
+            "key_value_percent",
+            "value_percent",
+        ]:
+            config = PieChartConfig(
+                chart_type="pie",
+                dimension=ColumnRef(name="product"),
+                metric=ColumnRef(name="revenue", aggregate="SUM"),
+                label_type=label_type,
+            )
+            assert config.label_type == label_type
+
+
+# ============================================================
+# Pie Chart Form Data Mapping Tests
+# ============================================================
+
+
+class TestMapPieConfig:
+    """Test map_pie_config form_data generation."""
+
+    def test_basic_pie_form_data(self) -> None:
+        config = PieChartConfig(
+            chart_type="pie",
+            dimension=ColumnRef(name="product"),
+            metric=ColumnRef(name="revenue", aggregate="SUM"),
+        )
+        result = map_pie_config(config)
+
+        assert result["viz_type"] == "pie"
+        assert result["groupby"] == ["product"]
+        assert result["metric"]["aggregate"] == "SUM"
+        assert result["metric"]["column"]["column_name"] == "revenue"
+        assert result["show_labels"] is True
+        assert result["show_legend"] is True
+        assert result["label_type"] == "key_value_percent"
+        assert result["sort_by_metric"] is True
+        assert result["row_limit"] == 100
+        assert result["donut"] is False
+        assert result["color_scheme"] == "supersetColors"
+
+    def test_donut_form_data(self) -> None:
+        config = PieChartConfig(
+            chart_type="pie",
+            dimension=ColumnRef(name="category"),
+            metric=ColumnRef(name="count", aggregate="COUNT"),
+            donut=True,
+            inner_radius=40,
+            outer_radius=80,
+        )
+        result = map_pie_config(config)
+
+        assert result["donut"] is True
+        assert result["innerRadius"] == 40
+        assert result["outerRadius"] == 80
+
+    def test_pie_form_data_with_filters(self) -> None:
+        config = PieChartConfig(
+            chart_type="pie",
+            dimension=ColumnRef(name="product"),
+            metric=ColumnRef(name="revenue", aggregate="SUM"),
+            filters=[FilterConfig(column="region", op="=", value="US")],
+        )
+        result = map_pie_config(config)
+
+        assert "adhoc_filters" in result
+        assert len(result["adhoc_filters"]) == 1
+        assert result["adhoc_filters"][0]["subject"] == "region"
+        assert result["adhoc_filters"][0]["operator"] == "=="
+        assert result["adhoc_filters"][0]["comparator"] == "US"
+
+    def test_pie_form_data_custom_options(self) -> None:
+        config = PieChartConfig(
+            chart_type="pie",
+            dimension=ColumnRef(name="status"),
+            metric=ColumnRef(name="count", aggregate="COUNT"),
+            show_labels=False,
+            label_type="percent",
+            show_legend=False,
+            number_format="$,.2f",
+            show_total=True,
+            labels_outside=False,
+        )
+        result = map_pie_config(config)
+
+        assert result["show_labels"] is False
+        assert result["label_type"] == "percent"
+        assert result["show_legend"] is False
+        assert result["number_format"] == "$,.2f"
+        assert result["show_total"] is True
+        assert result["labels_outside"] is False
+
+    def test_pie_form_data_custom_metric_label(self) -> None:
+        config = PieChartConfig(
+            chart_type="pie",
+            dimension=ColumnRef(name="product"),
+            metric=ColumnRef(name="revenue", aggregate="SUM", label="Total Revenue"),
+        )
+        result = map_pie_config(config)
+
+        assert result["metric"]["label"] == "Total Revenue"
+        assert result["metric"]["hasCustomLabel"] is True
+
+
+# ============================================================
+# Pivot Table Schema Tests
+# ============================================================
+
+
+class TestPivotTableChartConfigSchema:
+    """Test PivotTableChartConfig Pydantic schema validation."""
+
+    def test_basic_pivot_table_config(self) -> None:
+        config = PivotTableChartConfig(
+            chart_type="pivot_table",
+            rows=[ColumnRef(name="product")],
+            metrics=[ColumnRef(name="revenue", aggregate="SUM")],
+        )
+        assert config.chart_type == "pivot_table"
+        assert len(config.rows) == 1
+        assert len(config.metrics) == 1
+        assert config.aggregate_function == "Sum"
+        assert config.show_row_totals is True
+        assert config.show_column_totals is True
+
+    def test_pivot_table_with_columns(self) -> None:
+        config = PivotTableChartConfig(
+            chart_type="pivot_table",
+            rows=[ColumnRef(name="product")],
+            columns=[ColumnRef(name="region")],
+            metrics=[ColumnRef(name="revenue", aggregate="SUM")],
+        )
+        assert config.columns is not None
+        assert len(config.columns) == 1
+        assert config.columns[0].name == "region"
+
+    def test_pivot_table_with_all_options(self) -> None:
+        config = PivotTableChartConfig(
+            chart_type="pivot_table",
+            rows=[ColumnRef(name="product"), ColumnRef(name="category")],
+            columns=[ColumnRef(name="region")],
+            metrics=[
+                ColumnRef(name="revenue", aggregate="SUM"),
+                ColumnRef(name="orders", aggregate="COUNT"),
+            ],
+            aggregate_function="Average",
+            show_row_totals=False,
+            show_column_totals=False,
+            transpose=True,
+            combine_metric=True,
+            row_limit=5000,
+            value_format="$,.2f",
+            filters=[FilterConfig(column="year", op="=", value=2024)],
+        )
+        assert config.aggregate_function == "Average"
+        assert config.show_row_totals is False
+        assert config.transpose is True
+        assert config.combine_metric is True
+        assert config.row_limit == 5000
+
+    def test_pivot_table_missing_rows(self) -> None:
+        with pytest.raises(ValidationError):
+            PivotTableChartConfig(
+                chart_type="pivot_table",
+                metrics=[ColumnRef(name="revenue", aggregate="SUM")],
+            )
+
+    def test_pivot_table_missing_metrics(self) -> None:
+        with pytest.raises(ValidationError):
+            PivotTableChartConfig(
+                chart_type="pivot_table",
+                rows=[ColumnRef(name="product")],
+            )
+
+    def test_pivot_table_empty_rows(self) -> None:
+        with pytest.raises(ValidationError):
+            PivotTableChartConfig(
+                chart_type="pivot_table",
+                rows=[],
+                metrics=[ColumnRef(name="revenue", aggregate="SUM")],
+            )
+
+    def test_pivot_table_rejects_extra_fields(self) -> None:
+        with pytest.raises(ValidationError):
+            PivotTableChartConfig(
+                chart_type="pivot_table",
+                rows=[ColumnRef(name="product")],
+                metrics=[ColumnRef(name="revenue", aggregate="SUM")],
+                unknown_field="bad",
+            )
+
+    def test_pivot_table_valid_aggregate_functions(self) -> None:
+        for agg in ["Sum", "Average", "Median", "Count", "Minimum", "Maximum"]:
+            config = PivotTableChartConfig(
+                chart_type="pivot_table",
+                rows=[ColumnRef(name="product")],
+                metrics=[ColumnRef(name="revenue", aggregate="SUM")],
+                aggregate_function=agg,
+            )
+            assert config.aggregate_function == agg
+
+
+# ============================================================
+# Pivot Table Form Data Mapping Tests
+# ============================================================
+
+
+class TestMapPivotTableConfig:
+    """Test map_pivot_table_config form_data generation."""
+
+    def test_basic_pivot_form_data(self) -> None:
+        config = PivotTableChartConfig(
+            chart_type="pivot_table",
+            rows=[ColumnRef(name="product")],
+            metrics=[ColumnRef(name="revenue", aggregate="SUM")],
+        )
+        result = map_pivot_table_config(config)
+
+        assert result["viz_type"] == "pivot_table_v2"
+        assert result["groupbyRows"] == ["product"]
+        assert result["groupbyColumns"] == []
+        assert len(result["metrics"]) == 1
+        assert result["metrics"][0]["aggregate"] == "SUM"
+        assert result["aggregateFunction"] == "Sum"
+        assert result["rowTotals"] is True
+        assert result["colTotals"] is True
+        assert result["metricsLayout"] == "COLUMNS"
+
+    def test_pivot_form_data_with_columns(self) -> None:
+        config = PivotTableChartConfig(
+            chart_type="pivot_table",
+            rows=[ColumnRef(name="product")],
+            columns=[ColumnRef(name="region"), ColumnRef(name="quarter")],
+            metrics=[ColumnRef(name="revenue", aggregate="SUM")],
+        )
+        result = map_pivot_table_config(config)
+
+        assert result["groupbyRows"] == ["product"]
+        assert result["groupbyColumns"] == ["region", "quarter"]
+
+    def test_pivot_form_data_with_filters(self) -> None:
+        config = PivotTableChartConfig(
+            chart_type="pivot_table",
+            rows=[ColumnRef(name="product")],
+            metrics=[ColumnRef(name="revenue", aggregate="SUM")],
+            filters=[FilterConfig(column="year", op="=", value=2024)],
+        )
+        result = map_pivot_table_config(config)
+
+        assert "adhoc_filters" in result
+        assert len(result["adhoc_filters"]) == 1
+        assert result["adhoc_filters"][0]["subject"] == "year"
+
+    def test_pivot_form_data_custom_options(self) -> None:
+        config = PivotTableChartConfig(
+            chart_type="pivot_table",
+            rows=[ColumnRef(name="product")],
+            metrics=[ColumnRef(name="revenue", aggregate="SUM")],
+            aggregate_function="Average",
+            show_row_totals=False,
+            show_column_totals=False,
+            transpose=True,
+            combine_metric=True,
+            value_format="$,.2f",
+        )
+        result = map_pivot_table_config(config)
+
+        assert result["aggregateFunction"] == "Average"
+        assert result["rowTotals"] is False
+        assert result["colTotals"] is False
+        assert result["transposePivot"] is True
+        assert result["combineMetric"] is True
+        assert result["valueFormat"] == "$,.2f"
+
+    def test_pivot_form_data_multiple_metrics(self) -> None:
+        config = PivotTableChartConfig(
+            chart_type="pivot_table",
+            rows=[ColumnRef(name="product")],
+            metrics=[
+                ColumnRef(name="revenue", aggregate="SUM", label="Total Revenue"),
+                ColumnRef(name="orders", aggregate="COUNT", label="Order Count"),
+            ],
+        )
+        result = map_pivot_table_config(config)
+
+        assert len(result["metrics"]) == 2
+        assert result["metrics"][0]["label"] == "Total Revenue"
+        assert result["metrics"][1]["label"] == "Order Count"
+
+
+# ============================================================
+# Mixed Timeseries Schema Tests
+# ============================================================
+
+
+class TestMixedTimeseriesChartConfigSchema:
+    """Test MixedTimeseriesChartConfig Pydantic schema validation."""
+
+    def test_basic_mixed_timeseries_config(self) -> None:
+        config = MixedTimeseriesChartConfig(
+            chart_type="mixed_timeseries",
+            x=ColumnRef(name="order_date"),
+            y=[ColumnRef(name="revenue", aggregate="SUM")],
+            y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+        )
+        assert config.chart_type == "mixed_timeseries"
+        assert config.x.name == "order_date"
+        assert config.primary_kind == "line"
+        assert config.secondary_kind == "bar"
+        assert config.show_legend is True
+
+    def test_mixed_timeseries_with_all_options(self) -> None:
+        config = MixedTimeseriesChartConfig(
+            chart_type="mixed_timeseries",
+            x=ColumnRef(name="date"),
+            time_grain="P1M",
+            y=[ColumnRef(name="revenue", aggregate="SUM")],
+            primary_kind="area",
+            group_by=ColumnRef(name="region"),
+            y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+            secondary_kind="scatter",
+            group_by_secondary=ColumnRef(name="channel"),
+            show_legend=False,
+            x_axis=AxisConfig(title="Date"),
+            y_axis=AxisConfig(title="Revenue", format="$,.2f"),
+            y_axis_secondary=AxisConfig(title="Orders", scale="log"),
+            filters=[FilterConfig(column="status", op="=", value="complete")],
+        )
+        assert config.primary_kind == "area"
+        assert config.secondary_kind == "scatter"
+        assert config.time_grain == "P1M"
+        assert config.group_by is not None
+        assert config.group_by.name == "region"
+        assert config.group_by_secondary is not None
+        assert config.group_by_secondary.name == "channel"
+
+    def test_mixed_timeseries_missing_y(self) -> None:
+        with pytest.raises(ValidationError):
+            MixedTimeseriesChartConfig(
+                chart_type="mixed_timeseries",
+                x=ColumnRef(name="date"),
+                y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+            )
+
+    def test_mixed_timeseries_missing_y_secondary(self) -> None:
+        with pytest.raises(ValidationError):
+            MixedTimeseriesChartConfig(
+                chart_type="mixed_timeseries",
+                x=ColumnRef(name="date"),
+                y=[ColumnRef(name="revenue", aggregate="SUM")],
+            )
+
+    def test_mixed_timeseries_empty_y(self) -> None:
+        with pytest.raises(ValidationError):
+            MixedTimeseriesChartConfig(
+                chart_type="mixed_timeseries",
+                x=ColumnRef(name="date"),
+                y=[],
+                y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+            )
+
+    def test_mixed_timeseries_rejects_extra_fields(self) -> None:
+        with pytest.raises(ValidationError):
+            MixedTimeseriesChartConfig(
+                chart_type="mixed_timeseries",
+                x=ColumnRef(name="date"),
+                y=[ColumnRef(name="revenue", aggregate="SUM")],
+                y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+                unknown_field="bad",
+            )
+
+
+# ============================================================
+# Mixed Timeseries Form Data Mapping Tests
+# ============================================================
+
+
+class TestMapMixedTimeseriesConfig:
+    """Test map_mixed_timeseries_config form_data generation."""
+
+    @patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
+    def test_basic_mixed_form_data(self, mock_is_temporal) -> None:
+        mock_is_temporal.return_value = True
+
+        config = MixedTimeseriesChartConfig(
+            chart_type="mixed_timeseries",
+            x=ColumnRef(name="order_date"),
+            y=[ColumnRef(name="revenue", aggregate="SUM")],
+            y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+        )
+        result = map_mixed_timeseries_config(config, dataset_id=1)
+
+        assert result["viz_type"] == "mixed_timeseries"
+        assert result["x_axis"] == "order_date"
+        assert len(result["metrics"]) == 1
+        assert result["metrics"][0]["aggregate"] == "SUM"
+        assert len(result["metrics_b"]) == 1
+        assert result["metrics_b"][0]["aggregate"] == "COUNT"
+        assert result["seriesType"] == "line"
+        assert result["seriesTypeB"] == "bar"
+        assert result["yAxisIndex"] == 0
+        assert result["yAxisIndexB"] == 1
+        assert result["show_legend"] is True
+
+    @patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
+    def test_mixed_form_data_with_time_grain(self, mock_is_temporal) -> None:
+        mock_is_temporal.return_value = True
+
+        config = MixedTimeseriesChartConfig(
+            chart_type="mixed_timeseries",
+            x=ColumnRef(name="date"),
+            time_grain="P1W",
+            y=[ColumnRef(name="revenue", aggregate="SUM")],
+            y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+        )
+        result = map_mixed_timeseries_config(config, dataset_id=1)
+
+        assert result["time_grain_sqla"] == "P1W"
+
+    @patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
+    def test_mixed_form_data_area_series(self, mock_is_temporal) -> None:
+        mock_is_temporal.return_value = True
+
+        config = MixedTimeseriesChartConfig(
+            chart_type="mixed_timeseries",
+            x=ColumnRef(name="date"),
+            y=[ColumnRef(name="revenue", aggregate="SUM")],
+            primary_kind="area",
+            y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+            secondary_kind="area",
+        )
+        result = map_mixed_timeseries_config(config, dataset_id=1)
+
+        assert result["seriesType"] == "line"
+        assert result["area"] is True
+        assert result["seriesTypeB"] == "line"
+        assert result["areaB"] is True
+
+    @patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
+    def test_mixed_form_data_with_groupby(self, mock_is_temporal) -> None:
+        mock_is_temporal.return_value = True
+
+        config = MixedTimeseriesChartConfig(
+            chart_type="mixed_timeseries",
+            x=ColumnRef(name="date"),
+            y=[ColumnRef(name="revenue", aggregate="SUM")],
+            group_by=ColumnRef(name="region"),
+            y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+            group_by_secondary=ColumnRef(name="channel"),
+        )
+        result = map_mixed_timeseries_config(config, dataset_id=1)
+
+        assert result["groupby"] == ["region"]
+        assert result["groupby_b"] == ["channel"]
+
+    @patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
+    def test_mixed_form_data_groupby_same_as_x_ignored(self, mock_is_temporal) -> None:
+        mock_is_temporal.return_value = True
+
+        config = MixedTimeseriesChartConfig(
+            chart_type="mixed_timeseries",
+            x=ColumnRef(name="date"),
+            y=[ColumnRef(name="revenue", aggregate="SUM")],
+            group_by=ColumnRef(name="date"),  # same as x
+            y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+            group_by_secondary=ColumnRef(name="date"),  # same as x
+        )
+        result = map_mixed_timeseries_config(config, dataset_id=1)
+
+        assert "groupby" not in result
+        assert "groupby_b" not in result
+
+    @patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
+    def test_mixed_form_data_with_axis_config(self, mock_is_temporal) -> None:
+        mock_is_temporal.return_value = True
+
+        config = MixedTimeseriesChartConfig(
+            chart_type="mixed_timeseries",
+            x=ColumnRef(name="date"),
+            y=[ColumnRef(name="revenue", aggregate="SUM")],
+            y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+            x_axis=AxisConfig(title="Date"),
+            y_axis=AxisConfig(title="Revenue", format="$,.2f", scale="log"),
+            y_axis_secondary=AxisConfig(title="Orders", format=",d", scale="log"),
+        )
+        result = map_mixed_timeseries_config(config, dataset_id=1)
+
+        assert result["xAxisTitle"] == "Date"
+        assert result["yAxisTitle"] == "Revenue"
+        assert result["y_axis_format"] == "$,.2f"
+        assert result["logAxis"] is True
+        assert result["yAxisTitleSecondary"] == "Orders"
+        assert result["y_axis_format_secondary"] == ",d"
+        assert result["logAxisSecondary"] is True
+
+    @patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
+    def test_mixed_form_data_with_filters(self, mock_is_temporal) -> None:
+        mock_is_temporal.return_value = True
+
+        config = MixedTimeseriesChartConfig(
+            chart_type="mixed_timeseries",
+            x=ColumnRef(name="date"),
+            y=[ColumnRef(name="revenue", aggregate="SUM")],
+            y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+            filters=[FilterConfig(column="status", op="=", value="complete")],
+        )
+        result = map_mixed_timeseries_config(config, dataset_id=1)
+
+        assert "adhoc_filters" in result
+        assert len(result["adhoc_filters"]) == 1
+
+    @patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
+    def test_mixed_form_data_non_temporal_x(self, mock_is_temporal) -> None:
+        mock_is_temporal.return_value = False
+
+        config = MixedTimeseriesChartConfig(
+            chart_type="mixed_timeseries",
+            x=ColumnRef(name="year"),
+            y=[ColumnRef(name="revenue", aggregate="SUM")],
+            y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+        )
+        result = map_mixed_timeseries_config(config, dataset_id=1)
+
+        assert result["time_grain_sqla"] is None
+        assert result["granularity_sqla"] is None
+        assert result["x_axis_sort_series_type"] == "name"
+
+
+# ============================================================
+# map_config_to_form_data Dispatch Tests
+# ============================================================
+
+
+class TestMapConfigToFormDataDispatch:
+    """Test map_config_to_form_data dispatches to correct mapping function."""
+
+    def test_dispatches_pie_config(self) -> None:
+        config = PieChartConfig(
+            chart_type="pie",
+            dimension=ColumnRef(name="product"),
+            metric=ColumnRef(name="revenue", aggregate="SUM"),
+        )
+        result = map_config_to_form_data(config)
+        assert result["viz_type"] == "pie"
+
+    def test_dispatches_pivot_table_config(self) -> None:
+        config = PivotTableChartConfig(
+            chart_type="pivot_table",
+            rows=[ColumnRef(name="product")],
+            metrics=[ColumnRef(name="revenue", aggregate="SUM")],
+        )
+        result = map_config_to_form_data(config)
+        assert result["viz_type"] == "pivot_table_v2"
+
+    @patch("superset.mcp_service.chart.chart_utils.is_column_truly_temporal")
+    def test_dispatches_mixed_timeseries_config(self, mock_is_temporal) -> None:
+        mock_is_temporal.return_value = True
+        config = MixedTimeseriesChartConfig(
+            chart_type="mixed_timeseries",
+            x=ColumnRef(name="date"),
+            y=[ColumnRef(name="revenue", aggregate="SUM")],
+            y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+        )
+        result = map_config_to_form_data(config, dataset_id=1)
+        assert result["viz_type"] == "mixed_timeseries"
+
+
+# ============================================================
+# Chart Name Generation Tests
+# ============================================================
+
+
+class TestGenerateChartNameNewTypes:
+    """Test generate_chart_name for new chart types."""
+
+    def test_pie_chart_name(self) -> None:
+        config = PieChartConfig(
+            chart_type="pie",
+            dimension=ColumnRef(name="product"),
+            metric=ColumnRef(name="revenue", aggregate="SUM"),
+        )
+        result = generate_chart_name(config)
+        assert result == "Pie Chart - product by revenue"
+
+    def test_pie_chart_name_with_custom_label(self) -> None:
+        config = PieChartConfig(
+            chart_type="pie",
+            dimension=ColumnRef(name="product"),
+            metric=ColumnRef(name="revenue", aggregate="SUM", label="Total Revenue"),
+        )
+        result = generate_chart_name(config)
+        assert result == "Pie Chart - product by Total Revenue"
+
+    def test_pivot_table_chart_name(self) -> None:
+        config = PivotTableChartConfig(
+            chart_type="pivot_table",
+            rows=[ColumnRef(name="product"), ColumnRef(name="region")],
+            metrics=[ColumnRef(name="revenue", aggregate="SUM")],
+        )
+        result = generate_chart_name(config)
+        assert result == "Pivot Table - product, region"
+
+    def test_mixed_timeseries_chart_name(self) -> None:
+        config = MixedTimeseriesChartConfig(
+            chart_type="mixed_timeseries",
+            x=ColumnRef(name="date"),
+            y=[ColumnRef(name="revenue", aggregate="SUM")],
+            y_secondary=[ColumnRef(name="orders", aggregate="COUNT")],
+        )
+        result = generate_chart_name(config)
+        assert result == "Mixed Chart - revenue + orders"
+
+
+# ============================================================
+# Schema Validator Pre-Validation Tests
+# ============================================================
+
+
+class TestSchemaValidatorNewTypes:
+    """Test SchemaValidator pre-validation for new chart types."""
+
+    def test_pie_chart_type_accepted(self) -> None:
+        data = {
+            "dataset_id": 1,
+            "config": {
+                "chart_type": "pie",
+                "dimension": {"name": "product"},
+                "metric": {"name": "revenue", "aggregate": "SUM"},
+            },
+        }
+        is_valid, request, error = SchemaValidator.validate_request(data)
+        assert is_valid is True
+        assert error is None
+
+    def test_pivot_table_chart_type_accepted(self) -> None:
+        data = {
+            "dataset_id": 1,
+            "config": {
+                "chart_type": "pivot_table",
+                "rows": [{"name": "product"}],
+                "metrics": [{"name": "revenue", "aggregate": "SUM"}],
+            },
+        }
+        is_valid, request, error = SchemaValidator.validate_request(data)
+        assert is_valid is True
+        assert error is None
+
+    def test_mixed_timeseries_chart_type_accepted(self) -> None:
+        data = {
+            "dataset_id": 1,
+            "config": {
+                "chart_type": "mixed_timeseries",
+                "x": {"name": "date"},
+                "y": [{"name": "revenue", "aggregate": "SUM"}],
+                "y_secondary": [{"name": "orders", "aggregate": "COUNT"}],
+            },
+        }
+        is_valid, request, error = SchemaValidator.validate_request(data)
+        assert is_valid is True
+        assert error is None
+
+    def test_pie_missing_dimension_rejected(self) -> None:
+        data = {
+            "dataset_id": 1,
+            "config": {
+                "chart_type": "pie",
+                "metric": {"name": "revenue", "aggregate": "SUM"},
+            },
+        }
+        is_valid, _, error = SchemaValidator.validate_request(data)
+        assert is_valid is False
+        assert error is not None
+        assert (
+            "dimension" in error.message.lower()
+            or "dimension" in (error.details or "").lower()
+        )
+
+    def test_pie_missing_metric_rejected(self) -> None:
+        data = {
+            "dataset_id": 1,
+            "config": {
+                "chart_type": "pie",
+                "dimension": {"name": "product"},
+            },
+        }
+        is_valid, _, error = SchemaValidator.validate_request(data)
+        assert is_valid is False
+        assert error is not None
+
+    def test_pivot_table_missing_rows_rejected(self) -> None:
+        data = {
+            "dataset_id": 1,
+            "config": {
+                "chart_type": "pivot_table",
+                "metrics": [{"name": "revenue", "aggregate": "SUM"}],
+            },
+        }
+        is_valid, _, error = SchemaValidator.validate_request(data)
+        assert is_valid is False
+        assert error is not None
+        assert (
+            "rows" in error.message.lower() or "rows" in (error.details or "").lower()
+        )
+
+    def test_pivot_table_missing_metrics_rejected(self) -> None:
+        data = {
+            "dataset_id": 1,
+            "config": {
+                "chart_type": "pivot_table",
+                "rows": [{"name": "product"}],
+            },
+        }
+        is_valid, _, error = SchemaValidator.validate_request(data)
+        assert is_valid is False
+        assert error is not None
+
+    def test_mixed_timeseries_missing_y_rejected(self) -> None:
+        data = {
+            "dataset_id": 1,
+            "config": {
+                "chart_type": "mixed_timeseries",
+                "x": {"name": "date"},
+                "y_secondary": [{"name": "orders", "aggregate": "COUNT"}],
+            },
+        }
+        is_valid, _, error = SchemaValidator.validate_request(data)
+        assert is_valid is False
+        assert error is not None
+
+    def test_mixed_timeseries_missing_y_secondary_rejected(self) -> None:
+        data = {
+            "dataset_id": 1,
+            "config": {
+                "chart_type": "mixed_timeseries",
+                "x": {"name": "date"},
+                "y": [{"name": "revenue", "aggregate": "SUM"}],
+            },
+        }
+        is_valid, _, error = SchemaValidator.validate_request(data)
+        assert is_valid is False
+        assert error is not None
+
+    def test_mixed_timeseries_missing_x_rejected(self) -> None:
+        data = {
+            "dataset_id": 1,
+            "config": {
+                "chart_type": "mixed_timeseries",
+                "y": [{"name": "revenue", "aggregate": "SUM"}],
+                "y_secondary": [{"name": "orders", "aggregate": "COUNT"}],
+            },
+        }
+        is_valid, _, error = SchemaValidator.validate_request(data)
+        assert is_valid is False
+        assert error is not None
+
+    def test_invalid_chart_type_lists_all_options(self) -> None:
+        data = {
+            "dataset_id": 1,
+            "config": {
+                "chart_type": "invalid_type",
+            },
+        }
+        is_valid, _, error = SchemaValidator.validate_request(data)
+        assert is_valid is False
+        assert error is not None
+        assert "pie" in (error.details or "").lower()
+        assert "pivot_table" in (error.details or "").lower()
+        assert "mixed_timeseries" in (error.details or "").lower()
+
+    @pytest.mark.parametrize(
+        "bad_chart_type",
+        [["xy"], {"type": "xy"}, 123, True],
+    )
+    def test_non_string_chart_type_rejected_gracefully(
+        self, bad_chart_type: object
+    ) -> None:
+        data = {
+            "dataset_id": 1,
+            "config": {
+                "chart_type": bad_chart_type,
+            },
+        }
+        is_valid, _, error = SchemaValidator.validate_request(data)
+        assert is_valid is False
+        assert error is not None
+        assert error.error_code == "INVALID_CHART_TYPE"