Copilot commented on code in PR #43573:
URL: https://github.com/apache/superset/pull/43573#discussion_r3890440806
##########
superset/mcp_service/chart/chart_helpers.py:
##########
@@ -489,6 +489,13 @@ def _build_single_query_dict(
qd["row_limit"] = effective_row_limit
if order_desc is not None:
qd["order_desc"] = order_desc
+ # sort_by_metric charts (pie/funnel/treemap/sankey) order by the metric
+ # descending. buildQuery derives this on the frontend; the MCP path builds
+ # the query dict directly and never reads a top-level form_data['orderby'],
+ # so translate the flag here or a row_limit truncates an unordered result
+ # (dropping the heaviest rows rather than the top-N by the metric).
Review Comment:
The comment mentions funnel/treemap, but the MCP chart plugins/schemas in
this module currently only expose `sort_by_metric` for pie and sankey. This
makes the comment misleading for future maintainers; please update it to match
the actual supported chart types (or phrase it generically).
##########
superset/mcp_service/chart/plugins/sankey.py:
##########
@@ -0,0 +1,148 @@
+# 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.
+
+"""Sankey chart type plugin."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from typing import Any, ClassVar
+
+from superset.mcp_service.chart.chart_utils import (
+ _sankey_chart_what,
+ _summarize_filters,
+ map_sankey_config,
+)
+from superset.mcp_service.chart.plugin import BaseChartPlugin
+from superset.mcp_service.chart.schemas import ColumnRef, SankeyChartConfig
+from superset.mcp_service.chart.validation.dataset_validator import
DatasetValidator
+from superset.mcp_service.common.error_schemas import ChartGenerationError
+
+
+class SankeyChartPlugin(BaseChartPlugin):
+ """Plugin for sankey chart type."""
+
+ chart_type = "sankey_v2"
+ display_name = "Sankey Diagram"
+ native_viz_types: ClassVar[Mapping[str, str]] = {
+ "sankey_v2": "Sankey Diagram",
+ }
+
+ def pre_validate(
+ self,
+ config: dict[str, Any],
+ ) -> ChartGenerationError | None:
+ missing_fields = []
+
+ if "source" not in config:
+ missing_fields.append("'source' (origin node column)")
+ if "target" not in config:
+ missing_fields.append("'target' (destination node column)")
+ if "metric" not in config:
+ missing_fields.append("'metric' (edge weight)")
+
+ if missing_fields:
+ return ChartGenerationError(
+ error_type="missing_sankey_fields",
+ message=(
+ f"Sankey chart missing required fields: {',
'.join(missing_fields)}"
+ ),
+ details=(
+ "Sankey diagrams draw weighted flows from a source node to
"
+ "a target node; the metric sets each edge's width"
+ ),
+ suggestions=[
+ "Add 'source': {'name': 'from_stage'}",
+ "Add 'target': {'name': 'to_stage'}",
+ "Add 'metric': {'name': 'users', 'aggregate': 'SUM'}",
+ "Example: {'chart_type': 'sankey_v2', "
+ "'source': {'name': 'from_stage'}, "
+ "'target': {'name': 'to_stage'}, "
+ "'metric': {'name': 'users', 'aggregate': 'SUM'}}",
+ ],
+ error_code="MISSING_SANKEY_FIELDS",
+ )
+
+ return None
+
+ def extract_column_refs(self, config: Any) -> list[ColumnRef]:
+ if not isinstance(config, SankeyChartConfig):
+ return []
+ refs: list[ColumnRef] = [config.source, config.target, config.metric]
+ if config.filters:
+ for f in config.filters:
+ refs.append(ColumnRef(name=f.column))
+ return refs
+
+ def to_form_data(
+ self, config: Any, dataset_id: int | str | None = None
+ ) -> dict[str, Any]:
+ return map_sankey_config(config)
+
+ def generate_name(self, config: Any, dataset_name: str | None = None) ->
str:
+ what = _sankey_chart_what(config)
+ context = _summarize_filters(config.filters)
+ return self._with_context(what, context)
+
+ def resolve_viz_type(self, config: Any) -> str:
+ return "sankey_v2"
+
+ def normalize_column_refs(self, config: Any, dataset_context: Any) -> Any:
+ config_dict = config.model_dump()
+
+ for key in ("source", "target"):
+ col = config_dict.get(key)
+ if col and not col.get("sql_expression") and not
col.get("saved_metric"):
+ col["name"] = DatasetValidator.get_canonical_column_name(
+ col["name"], dataset_context
+ )
+ if config_dict.get("metric"):
+ if config_dict["metric"].get("sql_expression"):
+ pass
+ elif config_dict["metric"].get("saved_metric"):
+ config_dict["metric"]["name"] = (
+ DatasetValidator.get_canonical_metric_name(
+ config_dict["metric"]["name"], dataset_context
+ )
+ )
+ else:
+ config_dict["metric"]["name"] = (
+ DatasetValidator.get_canonical_column_name(
+ config_dict["metric"]["name"], dataset_context
+ )
+ )
+ DatasetValidator.normalize_filters(config_dict, dataset_context)
+ return SankeyChartConfig.model_validate(config_dict)
+
+ def schema_error_hint(self) -> ChartGenerationError | None:
+ return ChartGenerationError(
+ error_type="sankey_validation_error",
+ message="Sankey chart configuration validation failed",
+ details=(
+ "The sankey chart configuration is missing required "
+ "fields or has invalid structure"
+ ),
+ suggestions=[
+ "Ensure 'source' and 'target' each have a 'name'",
+ "Ensure 'metric' field has 'name' and 'aggregate'",
+ "Example: {'chart_type': 'sankey_v2', "
+ "'source': {'name': 'from_stage'}, "
+ "'target': {'name': 'to_stage'}, "
+ "'metric': {'name': 'users', 'aggregate': 'SUM'}}",
+ ],
Review Comment:
`schema_error_hint()` suggests that `metric` must include an `aggregate`,
but the schema also allows saved metrics (`saved_metric=True`) and SQL metrics
(`sql_expression` + `label`). As written, the suggestions can mislead callers
into providing invalid or unnecessary fields.
##########
tests/unit_tests/mcp_service/chart/test_sankey_chart.py:
##########
@@ -0,0 +1,270 @@
+# 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 sankey chart type plugin.
+
+Schema validation, form_data mapping (matching the frontend Sankey buildQuery
+contract for viz_type ``sankey_v2`` — a ``source`` and ``target`` column plus
+one ``metric`` weighting each edge), and registry integration.
+"""
+
+from typing import Any
+
+import pytest
+from pydantic import TypeAdapter, ValidationError
+
+from superset.common.form_data_query_context import columns_from_form_data
+from superset.mcp_service.chart.chart_helpers import resolve_groupby
+from superset.mcp_service.chart.chart_utils import map_sankey_config
+from superset.mcp_service.chart.schemas import ChartConfig, SankeyChartConfig
+
+
+class TestSankeyChartConfigSchema:
+ """SankeyChartConfig schema validation."""
+
+ def test_basic_sankey_config(self) -> None:
+ config = SankeyChartConfig(
+ chart_type="sankey_v2",
+ source={"name": "from_stage"},
+ target={"name": "to_stage"},
+ metric={"name": "users", "aggregate": "SUM"},
+ )
+ assert config.source.name == "from_stage"
+ assert config.target.name == "to_stage"
+ assert config.sort_by_metric is True # shared control default
+
+ @pytest.mark.parametrize("missing", ["source", "target", "metric"])
+ def test_sankey_missing_required(self, missing: str) -> None:
+ cfg = {
+ "chart_type": "sankey_v2",
+ "source": {"name": "from_stage"},
+ "target": {"name": "to_stage"},
+ "metric": {"name": "users", "aggregate": "SUM"},
+ }
+ del cfg[missing]
+ with pytest.raises(ValidationError):
+ SankeyChartConfig(**cfg)
+
+ def test_sankey_rejects_extra_fields(self) -> None:
+ with pytest.raises(ValidationError):
+ SankeyChartConfig(
+ chart_type="sankey_v2",
+ source={"name": "from_stage"},
+ target={"name": "to_stage"},
+ metric={"name": "users", "aggregate": "SUM"},
+ bogus=1,
+ )
+
+ def test_sankey_source_rejects_saved_metric(self) -> None:
+ with pytest.raises(ValidationError):
+ SankeyChartConfig(
+ chart_type="sankey_v2",
+ source={"name": "count", "saved_metric": True},
+ target={"name": "to_stage"},
+ metric={"name": "users", "aggregate": "SUM"},
+ )
+
+ def test_sankey_target_rejects_saved_metric(self) -> None:
+ with pytest.raises(ValidationError):
+ SankeyChartConfig(
+ chart_type="sankey_v2",
+ source={"name": "from_stage"},
+ target={"name": "count", "saved_metric": True},
+ metric={"name": "users", "aggregate": "SUM"},
+ )
+
+ def test_sankey_source_rejects_aggregate(self) -> None:
+ """An aggregate makes source metric-like; source is a node
dimension."""
+ with pytest.raises(ValidationError):
+ SankeyChartConfig(
+ chart_type="sankey_v2",
+ source={"name": "amount", "aggregate": "SUM"},
+ target={"name": "to_stage"},
+ metric={"name": "users", "aggregate": "SUM"},
+ )
+
+ def test_sankey_target_rejects_aggregate(self) -> None:
+ with pytest.raises(ValidationError):
+ SankeyChartConfig(
+ chart_type="sankey_v2",
+ source={"name": "from_stage"},
+ target={"name": "amount", "aggregate": "SUM"},
+ metric={"name": "users", "aggregate": "SUM"},
+ )
+
+ def test_chart_config_union_dispatches_sankey(self) -> None:
+ config = TypeAdapter(ChartConfig).validate_python(
+ {
+ "chart_type": "sankey_v2",
+ "source": {"name": "from_stage"},
+ "target": {"name": "to_stage"},
+ "metric": {"name": "users", "aggregate": "SUM"},
+ }
+ )
+ assert isinstance(config, SankeyChartConfig)
+
+
+class TestMapSankeyConfig:
+ """form_data mapping must match the frontend Sankey buildQuery."""
+
+ def test_basic_sankey_form_data(self) -> None:
+ config = SankeyChartConfig(
+ chart_type="sankey_v2",
+ source={"name": "from_stage"},
+ target={"name": "to_stage"},
+ metric={"name": "users", "aggregate": "SUM"},
+ )
+ form_data = map_sankey_config(config)
+ assert form_data["viz_type"] == "sankey_v2"
+ assert form_data["source"] == "from_stage"
+ assert form_data["target"] == "to_stage"
+ assert form_data["groupby"] == ["from_stage", "to_stage"]
+ assert form_data["metric"]["label"] == "SUM(users)"
+ assert form_data["sort_by_metric"] is True
+ # orderby is applied by the query-dict builder, not stashed in
form_data
+ # (a top-level form_data['orderby'] is a no-op on the MCP path)
+ assert "orderby" not in form_data
+
+ def test_sankey_form_data_with_filters_and_no_sort(self) -> None:
+ config = SankeyChartConfig(
+ chart_type="sankey_v2",
+ source={"name": "from_stage"},
+ target={"name": "to_stage"},
+ metric={"name": "users", "aggregate": "SUM"},
+ sort_by_metric=False,
+ filters=[{"column": "year", "op": "=", "value": 2026}],
+ )
+ form_data = map_sankey_config(config)
+ assert form_data["sort_by_metric"] is False
+ assert "orderby" not in form_data # no metric ordering when unset
+ assert form_data["adhoc_filters"], "filters must map to adhoc_filters"
Review Comment:
This test covers that `orderby` is not stored in `form_data` when
`sort_by_metric=False`, but it doesn't assert the more important behavior
introduced in `_build_single_query_dict`: that the built query dict also omits
`orderby` in this case. Adding that assertion would prevent regressions where
`sort_by_metric=False` still orders results.
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