codeant-ai-for-open-source[bot] commented on code in PR #39922: URL: https://github.com/apache/superset/pull/39922#discussion_r3493573133
########## superset/mcp_service/chart/plugins/mixed_timeseries.py: ########## @@ -0,0 +1,173 @@ +# 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. + +"""Mixed timeseries 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 ( + _mixed_timeseries_what, + _summarize_filters, + map_mixed_timeseries_config, +) +from superset.mcp_service.chart.plugin import BaseChartPlugin +from superset.mcp_service.chart.schemas import ColumnRef, MixedTimeseriesChartConfig +from superset.mcp_service.chart.validation.dataset_validator import DatasetValidator +from superset.mcp_service.common.error_schemas import ChartGenerationError + + +class MixedTimeseriesChartPlugin(BaseChartPlugin): + """Plugin for mixed_timeseries chart type.""" + + chart_type = "mixed_timeseries" + display_name = "Mixed Timeseries" + native_viz_types: ClassVar[Mapping[str, str]] = { + "mixed_timeseries": "Mixed Timeseries Chart", + } + + def pre_validate( + self, + config: dict[str, Any], + ) -> ChartGenerationError | None: + missing_fields = [] + + if "x" not in config and "x_axis" not in config: + missing_fields.append("'x' (X-axis temporal column)") + if not config.get("y") and not config.get("metrics"): + missing_fields.append("'y' (primary Y-axis metrics)") + if not config.get("y_secondary") and not config.get("metrics_b"): + missing_fields.append("'y_secondary' (secondary Y-axis metrics)") + + if missing_fields: + return ChartGenerationError( + error_type="missing_mixed_timeseries_fields", + message=( + f"Mixed timeseries chart missing required fields: " + f"{', '.join(missing_fields)}" + ), + details=( + "Mixed timeseries charts require an x-axis, primary metrics, " + "and secondary metrics" + ), + suggestions=[ + "Add 'x' field: {'name': 'date_column'}", + "Add 'y' field: [{'name': 'revenue', 'aggregate': 'SUM'}]", + "Add 'y_secondary': [{'name': 'orders', 'aggregate': 'COUNT'}]", + "Optional: 'primary_kind' and 'secondary_kind' for chart types", + ], + error_code="MISSING_MIXED_TIMESERIES_FIELDS", + ) + + for field_name in ["y", "y_secondary"]: + if not isinstance(config.get(field_name, []), list): + return ChartGenerationError( + error_type=f"invalid_{field_name}_format", + message=f"'{field_name}' must be a list of metrics", + details=( + f"The '{field_name}' field must be an array of metric " + "specifications" + ), + suggestions=[ + f"Wrap in array: '{field_name}': " + "[{'name': 'col', 'aggregate': 'SUM'}]", + ], + error_code=f"INVALID_{field_name.upper()}_FORMAT", + ) + + return None + + def extract_column_refs(self, config: Any) -> list[ColumnRef]: + if not isinstance(config, MixedTimeseriesChartConfig): + return [] + refs: list[ColumnRef] = [config.x] + refs.extend(config.y) + refs.extend(config.y_secondary) + if config.group_by: + refs.extend(config.group_by) + if config.group_by_secondary: + refs.extend(config.group_by_secondary) + 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_mixed_timeseries_config(config, dataset_id=dataset_id) + + def generate_name(self, config: Any, dataset_name: str | None = None) -> str: + what = _mixed_timeseries_what(config) + context = _summarize_filters(config.filters) + return self._with_context(what, context) + + def resolve_viz_type(self, config: Any) -> str: + return "mixed_timeseries" + + def normalize_column_refs(self, config: Any, dataset_context: Any) -> Any: + config_dict = config.model_dump() + + def _norm_single(key: str) -> None: + if config_dict.get(key): + config_dict[key]["name"] = DatasetValidator.get_canonical_column_name( + config_dict[key]["name"], dataset_context + ) + + def _norm_list(key: str) -> None: + if config_dict.get(key): + for col in config_dict[key]: + if col.get("sql_expression"): + continue + if col.get("saved_metric"): + col["name"] = DatasetValidator.get_canonical_metric_name( + col["name"], dataset_context + ) + else: + col["name"] = DatasetValidator.get_canonical_column_name( + col["name"], dataset_context + ) + + _norm_single("x") + _norm_list("y") + _norm_list("y_secondary") + _norm_list("group_by") + _norm_list("group_by_secondary") Review Comment: ✅ **Customized review instruction saved!** **Instruction:** > When validating mixed-timeseries group-by fields, reject `saved_metric=True` at the schema layer (alongside existing `sql_expression` checks) rather than in the normalizer; group-by entries must be treated as real column dimensions. **Applied to:** - `superset/mcp_service/chart/**` --- 💡 *To manage or update this instruction, visit: [CodeAnt AI Settings](https://app.codeant.ai/org/settings/learnings)* -- This is an automated message from the Apache Git Service. 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