aminghadersohi commented on code in PR #39922:
URL: https://github.com/apache/superset/pull/39922#discussion_r3493567495
##########
superset/mcp_service/chart/validation/dataset_validator.py:
##########
@@ -269,59 +265,31 @@ def _get_dataset_context(dataset_id: int | str) ->
DatasetContext | None:
return None
@staticmethod
- def _extract_column_references(config: Any) -> List[ColumnRef]: # noqa:
C901
- """Extract all column references from a chart configuration.
-
- Covers every supported ``ChartConfig`` variant so fast-path tools
- (``generate_explore_link``, ``update_chart_preview``) that only run
- Tier-1 validation still catch bad column refs in pie / pivot table /
- mixed timeseries / handlebars / big number charts — not just XY and
- table.
+ def _extract_column_references(
+ config: ChartConfig,
+ ) -> List[ColumnRef]:
+ """Extract all column references from configuration via the plugin
registry.
+
+ Previously only handled TableChartConfig and XYChartConfig, causing
+ 5 of 7 chart types to silently skip column validation. Now delegates
+ to the plugin for each chart type so all types are covered.
"""
- refs: List[ColumnRef] = []
-
- if isinstance(config, TableChartConfig):
- refs.extend(config.columns)
- elif isinstance(config, XYChartConfig):
- if config.x is not None:
- refs.append(config.x)
- refs.extend(config.y)
- if config.group_by:
- refs.extend(config.group_by)
- elif isinstance(config, PieChartConfig):
- refs.append(config.dimension)
- refs.append(config.metric)
- elif isinstance(config, PivotTableChartConfig):
- refs.extend(config.rows)
- if config.columns:
- refs.extend(config.columns)
- refs.extend(config.metrics)
- elif isinstance(config, MixedTimeseriesChartConfig):
- refs.append(config.x)
- refs.extend(config.y)
- if config.group_by:
- refs.extend(config.group_by)
- refs.extend(config.y_secondary)
- if config.group_by_secondary:
- refs.extend(config.group_by_secondary)
- elif isinstance(config, HandlebarsChartConfig):
- if config.columns:
- refs.extend(config.columns)
- if config.groupby:
- refs.extend(config.groupby)
- if config.metrics:
- refs.extend(config.metrics)
- elif isinstance(config, BigNumberChartConfig):
- refs.append(config.metric)
- if config.temporal_column:
- refs.append(ColumnRef(name=config.temporal_column))
-
- # Filter columns (shared by every config type that defines
``filters``).
- if filters := getattr(config, "filters", None):
- for filter_config in filters:
- refs.append(ColumnRef(name=filter_config.column))
-
- return refs
+ # Local import: plugins call DatasetValidator helpers from
+ # normalize_column_refs().
+ # A top-level import of registry in dataset_validator would make
loading this
+ # module implicitly trigger plugin registration, creating a circular
dependency.
+ from superset.mcp_service.chart.registry import get_registry
+
+ chart_type = getattr(config, "chart_type", None)
+ if chart_type is None:
+ return []
+
+ plugin = get_registry().get(chart_type)
+ if plugin is None:
+ logger.warning("No plugin registered for chart_type=%r",
chart_type)
+ return []
+
Review Comment:
Returning `[]` here is the correct defensive behavior.
`_pre_validate_chart_type` (in `schema_validator.py`) already rejects unknown
`chart_type` values before the pipeline reaches column extraction — so
`get_registry().get(chart_type)` returning `None` is only reachable if
something calls `extract_column_refs` while bypassing the schema validator
(e.g., a test calling the method directly). Returning `[]` in that case lets
the rest of the pipeline continue; raising here would turn a bypass of the
schema check into an unhandled 500-style error. The warning log already
surfaces the gap.
##########
superset/mcp_service/chart/plugins/handlebars.py:
##########
@@ -0,0 +1,194 @@
+# 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.
+
+"""Handlebars 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 (
+ _handlebars_chart_what,
+ _summarize_filters,
+ map_handlebars_config,
+)
+from superset.mcp_service.chart.plugin import BaseChartPlugin
+from superset.mcp_service.chart.schemas import ColumnRef, HandlebarsChartConfig
+from superset.mcp_service.chart.validation.dataset_validator import
DatasetValidator
+from superset.mcp_service.common.error_schemas import ChartGenerationError
+
+
+class HandlebarsChartPlugin(BaseChartPlugin):
+ """Plugin for handlebars chart type (custom HTML template charts)."""
+
+ chart_type = "handlebars"
+ display_name = "Handlebars (Custom Template)"
+ native_viz_types: ClassVar[Mapping[str, str]] = {
+ "handlebars": "Custom Template Chart",
+ }
+
+ def pre_validate(
+ self,
+ config: dict[str, Any],
+ ) -> ChartGenerationError | None:
+ if "handlebars_template" not in config:
+ return ChartGenerationError(
+ error_type="missing_handlebars_template",
+ message="Handlebars chart missing required field:
handlebars_template",
+ details=(
+ "Handlebars charts require a 'handlebars_template' string "
+ "containing Handlebars HTML template markup"
+ ),
+ suggestions=[
+ "Add 'handlebars_template' with a Handlebars HTML
template",
+ "Data is available as {{data}} array in the template",
+ "Example: '<ul>{{#each data}}<li>{{this.name}}: "
+ "{{this.value}}</li>{{/each}}</ul>'",
+ ],
+ error_code="MISSING_HANDLEBARS_TEMPLATE",
+ )
+
+ template = config.get("handlebars_template")
+ if not isinstance(template, str) or not template.strip():
+ return ChartGenerationError(
+ error_type="invalid_handlebars_template",
+ message="Handlebars template must be a non-empty string",
+ details=(
+ "The 'handlebars_template' field must be a non-empty
string "
+ "containing valid Handlebars HTML template markup"
+ ),
+ suggestions=[
+ "Ensure handlebars_template is a non-empty string",
+ "Example: '<ul>{{#each
data}}<li>{{this.name}}</li>{{/each}}</ul>'",
+ ],
+ error_code="INVALID_HANDLEBARS_TEMPLATE",
+ )
+
+ query_mode = config.get("query_mode", "aggregate")
+ if query_mode not in ("aggregate", "raw"):
+ return ChartGenerationError(
+ error_type="invalid_query_mode",
+ message="Invalid query_mode for handlebars chart",
+ details="query_mode must be either 'aggregate' or 'raw'",
+ suggestions=[
+ "Use 'aggregate' for aggregated data (default)",
+ "Use 'raw' for individual rows",
+ ],
+ error_code="INVALID_QUERY_MODE",
+ )
+
+ if query_mode == "raw" and not config.get("columns"):
+ return ChartGenerationError(
+ error_type="missing_raw_columns",
+ message="Handlebars chart in 'raw' mode requires 'columns'",
+ details=(
+ "When query_mode is 'raw', you must specify which columns "
+ "to include in the query results"
+ ),
+ suggestions=[
+ "Add 'columns': [{'name': 'column_name'}] for raw mode",
+ "Or use query_mode='aggregate' with 'metrics' and optional
'groupby'", # noqa: E501
+ ],
+ error_code="MISSING_RAW_COLUMNS",
+ )
+
+ if query_mode == "aggregate" and not config.get("metrics"):
+ return ChartGenerationError(
+ error_type="missing_aggregate_metrics",
+ message="Handlebars chart in 'aggregate' mode requires
'metrics'",
+ details=(
+ "When query_mode is 'aggregate' (default), you must
specify "
+ "at least one metric with an aggregate function"
+ ),
+ suggestions=[
+ "Add 'metrics': [{'name': 'column', 'aggregate': 'SUM'}]",
+ "Or use query_mode='raw' with 'columns' for individual
rows",
+ ],
+ error_code="MISSING_AGGREGATE_METRICS",
+ )
+
+ return None
+
+ def extract_column_refs(self, config: Any) -> list[ColumnRef]:
+ if not isinstance(config, HandlebarsChartConfig):
+ return []
+ refs: list[ColumnRef] = []
+ if config.columns:
+ refs.extend(config.columns)
+ if config.metrics:
+ refs.extend(config.metrics)
+ if config.groupby:
+ refs.extend(config.groupby)
+ 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_handlebars_config(config)
+
+ def generate_name(self, config: Any, dataset_name: str | None = None) ->
str:
+ what = _handlebars_chart_what(config)
+ context = _summarize_filters(getattr(config, "filters", None))
+ return self._with_context(what, context)
+
+ def resolve_viz_type(self, config: Any) -> str:
+ return "handlebars"
+
+ def normalize_column_refs(self, config: Any, dataset_context: Any) -> Any:
+ config_dict = config.model_dump()
+
+ def _norm_list(key: str) -> None:
+ if config_dict.get(key):
+ for col in config_dict[key]:
+ if col.get("saved_metric"):
+ col["name"] =
DatasetValidator.get_canonical_metric_name(
+ col["name"], dataset_context
+ )
+ elif not col.get("sql_expression"):
+ col["name"] =
DatasetValidator.get_canonical_column_name(
+ col["name"], dataset_context
+ )
+
+ _norm_list("columns")
+ _norm_list("metrics")
+ _norm_list("groupby")
Review Comment:
Valid concern. The correct fix is schema-level rejection analogous to what
`validate_no_sql_expression_on_dimensions` already does for `sql_expression` on
`columns`/`groupby`: add a similar `@model_validator` on
`HandlebarsChartConfig` that rejects `saved_metric=True` on `groupby` entries.
Changing the normalizer to use column lookup for `groupby` unconditionally
would be wrong — if the schema allowed it, column lookup would fail for a
legitimate metric name. Once the schema rejects it, the `saved_metric` branch
in `_norm_list("groupby")` becomes dead code and can be removed as cleanup.
Flagging as a follow-up to the schema validators rather than in this
registry-architecture PR.
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