codeant-ai-for-open-source[bot] commented on code in PR #39922: URL: https://github.com/apache/superset/pull/39922#discussion_r3501363118
########## superset/mcp_service/chart/plugins/pie.py: ########## @@ -0,0 +1,139 @@ +# 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. + +"""Pie chart type plugin.""" + +from __future__ import annotations + +from typing import Any + +from superset.mcp_service.chart.chart_utils import ( + _pie_chart_what, + _summarize_filters, + map_pie_config, +) +from superset.mcp_service.chart.plugin import BaseChartPlugin +from superset.mcp_service.chart.schemas import ColumnRef, PieChartConfig +from superset.mcp_service.chart.validation.dataset_validator import DatasetValidator +from superset.mcp_service.common.error_schemas import ChartGenerationError + + +class PieChartPlugin(BaseChartPlugin): + """Plugin for pie chart type.""" + + chart_type = "pie" + display_name = "Pie / Donut Chart" + native_viz_types = { + "pie": "Pie Chart", + } + + def pre_validate( + self, + config: dict[str, Any], + ) -> ChartGenerationError | None: + missing_fields = [] + + if "dimension" not in config and "groupby" not in config: + missing_fields.append("'dimension' (category column for slices)") + if "metric" not in config: + missing_fields.append("'metric' (value metric for slice sizes)") + + if missing_fields: + return ChartGenerationError( + error_type="missing_pie_fields", + message=( + f"Pie chart missing required fields: {', '.join(missing_fields)}" + ), + details=( + "Pie charts require a dimension (categories) and a metric (values)" + ), + suggestions=[ + "Add 'dimension' field: {'name': 'category_column'}", + "Add 'metric' field: {'name': 'value_column', 'aggregate': 'SUM'}", + "Example: {'chart_type': 'pie', 'dimension': {'name': 'product'}, " + "'metric': {'name': 'revenue', 'aggregate': 'SUM'}}", + ], + error_code="MISSING_PIE_FIELDS", + ) + + return None + + def extract_column_refs(self, config: Any) -> list[ColumnRef]: + if not isinstance(config, PieChartConfig): + return [] + refs: list[ColumnRef] = [config.dimension, 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_pie_config(config) + + def generate_name(self, config: Any, dataset_name: str | None = None) -> str: + what = _pie_chart_what(config) + context = _summarize_filters(config.filters) + return self._with_context(what, context) + + def resolve_viz_type(self, config: Any) -> str: + return "pie" + + def normalize_column_refs(self, config: Any, dataset_context: Any) -> Any: + config_dict = config.model_dump() + + if config_dict.get("dimension"): + config_dict["dimension"]["name"] = ( + DatasetValidator._get_canonical_column_name( + config_dict["dimension"]["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 PieChartConfig.model_validate(config_dict) + + def schema_error_hint(self) -> ChartGenerationError | None: + return ChartGenerationError( Review Comment: ✅ **Customized review instruction saved!** **Instruction:** > Do not require docstrings for small Python methods when their purpose and contract are already obvious from the method name or Protocol/interface definition; only flag missing docstrings when the behavior or return structure is non-obvious. **Applied to:** - `**/*.py` --- 💡 *To manage or update this instruction, visit: [CodeAnt AI Settings](https://app.codeant.ai/org/settings/learnings)* ########## superset/mcp_service/chart/plugins/pivot_table.py: ########## @@ -0,0 +1,163 @@ +# 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. + +"""Pivot table chart type plugin.""" + +from __future__ import annotations + +from typing import Any + +from superset.mcp_service.chart.chart_utils import ( + _pivot_table_what, + _summarize_filters, + map_pivot_table_config, +) +from superset.mcp_service.chart.plugin import BaseChartPlugin +from superset.mcp_service.chart.schemas import ColumnRef, PivotTableChartConfig +from superset.mcp_service.chart.validation.dataset_validator import DatasetValidator +from superset.mcp_service.common.error_schemas import ChartGenerationError + + +class PivotTableChartPlugin(BaseChartPlugin): + """Plugin for pivot_table chart type.""" + + chart_type = "pivot_table" + display_name = "Pivot Table" + native_viz_types = { + "pivot_table_v2": "Pivot Table", + } + + def pre_validate( + self, + config: dict[str, Any], + ) -> ChartGenerationError | None: + missing_fields = [] + + if not (config.get("rows") or config.get("groupby") or config.get("dimension")): + missing_fields.append("'rows' (row grouping columns)") + if not config.get("metrics"): + missing_fields.append("'metrics' (aggregation metrics)") + + if missing_fields: + return ChartGenerationError( + error_type="missing_pivot_fields", + message=( + f"Pivot table missing required fields: {', '.join(missing_fields)}" + ), + details="Pivot tables require row groupings and metrics", + suggestions=[ + "Add 'rows' field: [{'name': 'category'}]", + "Add 'metrics' field: [{'name': 'sales', 'aggregate': 'SUM'}]", + "Optional 'columns' for cross-tabulation: [{'name': 'region'}]", + ], + error_code="MISSING_PIVOT_FIELDS", + ) + + rows_val = ( + config.get("rows") or config.get("groupby") or config.get("dimension") or [] + ) + if not isinstance(rows_val, list): + return ChartGenerationError( + error_type="invalid_rows_format", + message="Rows must be a list of columns", + details="The 'rows' field must be an array of column specifications", + suggestions=[ + "Wrap row columns in array: 'rows': [{'name': 'category'}]", + ], + error_code="INVALID_ROWS_FORMAT", + ) + + if not isinstance(config.get("metrics", []), list): + return ChartGenerationError( + error_type="invalid_metrics_format", + message="Metrics must be a list", + details="The 'metrics' field must be an array of metric specifications", + suggestions=[ + "Wrap metrics in array: 'metrics': [{'name': 'sales', " + "'aggregate': 'SUM'}]", + ], + error_code="INVALID_METRICS_FORMAT", + ) + + return None + + def extract_column_refs(self, config: Any) -> list[ColumnRef]: + if not isinstance(config, PivotTableChartConfig): + return [] + refs: list[ColumnRef] = list(config.rows) + refs.extend(config.metrics) + if config.columns: + refs.extend(config.columns) + 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_pivot_table_config(config) + + def generate_name(self, config: Any, dataset_name: str | None = None) -> str: + what = _pivot_table_what(config) + context = _summarize_filters(config.filters) + return self._with_context(what, context) Review Comment: ✅ **Customized review instruction saved!** **Instruction:** > Do not require docstrings for newly added Python methods when the method contract and purpose are already self-evident; only flag missing docstrings when the rationale or behavior is non-obvious. **Applied to:** - `**/*.py` --- 💡 *To manage or update this instruction, visit: [CodeAnt AI Settings](https://app.codeant.ai/org/settings/learnings)* ########## 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 = [] Review Comment: ✅ **Customized review instruction saved!** **Instruction:** > Avoid flagging missing local variable annotations when the type is already unambiguous from inference and the code passes existing mypy/pre-commit checks. **Applied to:** - `**/*.py` --- 💡 *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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