sadpandajoe commented on code in PR #43771:
URL: https://github.com/apache/superset/pull/43771#discussion_r3971738907
##########
superset/mcp_service/chart/chart_helpers.py:
##########
@@ -446,12 +564,200 @@ def _resolve_deck_gl_metrics(
if value:
metrics.append(value)
elif isinstance(prf, str) and _is_metric_ref(prf):
- # Legacy deck_scatter: point_radius_fixed as a bare non-numeric metric
key
- logger.debug("Legacy point_radius_fixed string metric encountered:
%s", prf)
metrics.append(prf)
return metrics
+def _deck_query_adapter( # noqa: C901
+ form_data: dict[str, Any], query: dict[str, Any], viz_type: str
+) -> dict[str, Any]:
+ """Apply the native frontend builder for a single Deck.gl layer."""
+ base_columns = list(query.get("columns") or [])
+ base_metrics = list(query.get("metrics") or [])
+ filters = list(query.get("filters") or [])
+ tooltips = _deck_tooltip_columns(form_data.get("tooltip_contents"))
+
+ def add_null(column: str, *, value: Any = ...) -> None:
+ clause: dict[str, Any] = {"col": column, "op": "IS NOT NULL"}
+ if value is not ...:
+ clause["val"] = value
+ filters.append(clause)
+
+ if viz_type == "deck_geojson":
+ geometry = form_data.get("geojson")
+ if not isinstance(geometry, str) or not geometry:
+ raise ValueError("GeoJSON column is required for GeoJSON charts")
+ columns = _add_deck_columns(base_columns, [geometry] if geometry else
[])
+ cross_filter = form_data.get("cross_filter_column")
+ if cross_filter:
+ columns = _add_deck_columns(columns, [cross_filter])
+ columns = _add_deck_columns(columns, tooltips)
+ if form_data.get("filter_nulls", True) and isinstance(geometry, str):
+ add_null(geometry)
+ query.update(
+ columns=columns,
+ metrics=[],
+ groupby=[],
+ filters=filters,
+ is_timeseries=False,
+ )
+ return query
+
+ if viz_type == "deck_polygon":
+ line_column = form_data.get("line_column")
+ if not isinstance(line_column, str) or not line_column:
+ raise ValueError("Polygon column is required for Polygon charts")
+ columns = _add_deck_columns(base_columns, [line_column] if line_column
else [])
+ cross_filter = form_data.get("cross_filter_column")
+ if cross_filter:
+ columns = _add_deck_columns(columns, [cross_filter])
+ columns = _add_deck_columns(columns, tooltips)
+ metrics: list[Any] = []
+ if metric := form_data.get("metric"):
+ metrics.append(metric)
+ radius = form_data.get("point_radius_fixed")
+ if (
+ isinstance(radius, dict)
+ and radius.get("type") == "metric"
+ and radius.get("value") is not None
+ ):
+ metrics.append(radius["value"])
+ if form_data.get("filter_nulls", True) and isinstance(line_column,
str):
+ add_null(line_column)
+ if metric:
+ add_null(_deck_metric_label(metric))
+ query.update(
+ columns=columns,
+ metrics=metrics,
+ filters=filters,
+ is_timeseries=False,
+ )
+ return query
+
+ if viz_type == "deck_path":
+ line_column = form_data.get("line_column")
+ if not isinstance(line_column, str) or not line_column:
+ raise ValueError("Line column is required for Path charts")
+ columns = list(base_columns)
+ metrics = list(base_metrics)
Review Comment:
For `deck_path`, `base_metrics` includes the aliased `size` value verbatim,
so a saved chart with fixed `size="100"` emits a metric literally named `100`
and changes a raw query into an aggregate. Can this filter scalar size values
here as the scatter path does and keep the regression test aligned?
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