aminghadersohi commented on code in PR #39922: URL: https://github.com/apache/superset/pull/39922#discussion_r3501356022
########## superset/mcp_service/chart/plugins/handlebars.py: ########## @@ -0,0 +1,193 @@ +# 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 typing import Any + +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 = { + "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: Review Comment: Declining — docstring is a Minor ⚠️ suggestion from automated bot review. Per project standards, short comments/docstrings are added only when the `why` is non-obvious; method contracts here are self-evident from the Protocol definition and method names. ########## 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 [] Review Comment: Declining — docstring is a Minor ⚠️ suggestion from automated bot review. Per project standards, short comments/docstrings are added only when the `why` is non-obvious; method contracts here are self-evident from the Protocol definition and method names. ########## 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) Review Comment: Declining — docstring is a Minor ⚠️ suggestion from automated bot review. Per project standards, short comments/docstrings are added only when the `why` is non-obvious; method contracts here are self-evident from the Protocol definition and method names. ########## 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) + + def resolve_viz_type(self, config: Any) -> str: + return "pivot_table_v2" + + def normalize_column_refs(self, config: Any, dataset_context: Any) -> Any: + config_dict = config.model_dump() Review Comment: Declining — docstring is a Minor ⚠️ suggestion from automated bot review. Per project standards, short comments/docstrings are added only when the `why` is non-obvious; method contracts here are self-evident from the Protocol definition and method names. ########## 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) + + def resolve_viz_type(self, config: Any) -> str: + return "pivot_table_v2" + + def normalize_column_refs(self, config: Any, dataset_context: Any) -> Any: + config_dict = config.model_dump() + + def _norm_col_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_col_list("rows") + _norm_col_list("metrics") + _norm_col_list("columns") + DatasetValidator._normalize_filters(config_dict, dataset_context) + return PivotTableChartConfig.model_validate(config_dict) + + def schema_error_hint(self) -> ChartGenerationError | None: + return ChartGenerationError( Review Comment: Declining — docstring is a Minor ⚠️ suggestion from automated bot review. Per project standards, short comments/docstrings are added only when the `why` is non-obvious; method contracts here are self-evident from the Protocol definition and method names. ########## superset/mcp_service/chart/plugins/table.py: ########## @@ -0,0 +1,135 @@ +# 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. + +"""Table chart type plugin.""" + +from __future__ import annotations + +from typing import Any + +from superset.mcp_service.chart.chart_utils import ( + _summarize_filters, + _table_chart_what, + map_table_config, +) +from superset.mcp_service.chart.plugin import BaseChartPlugin +from superset.mcp_service.chart.schemas import ColumnRef, TableChartConfig +from superset.mcp_service.chart.validation.dataset_validator import DatasetValidator +from superset.mcp_service.common.error_schemas import ChartGenerationError + + +class TableChartPlugin(BaseChartPlugin): + """Plugin for table chart type.""" + + chart_type = "table" + display_name = "Table" + native_viz_types = { + "table": "Table", + "ag-grid-table": "Interactive Table", + } + + def pre_validate( + self, + config: dict[str, Any], + ) -> ChartGenerationError | None: + columns = ( + config.get("columns") or config.get("all_columns") or config.get("groupby") + ) + if not columns: + return ChartGenerationError( + error_type="missing_columns", + message="Table chart missing required field: columns", + details=( + "Table charts require a 'columns' array to specify which " + "columns to display" + ), + suggestions=[ + "Add 'columns' field with array of column specifications", + "Example: 'columns': [{'name': 'product'}, {'name': 'sales', " + "'aggregate': 'SUM'}]", + "Each column can have optional 'aggregate' for metrics", + ], + error_code="MISSING_COLUMNS", + ) + + if not isinstance(columns, list): + return ChartGenerationError( + error_type="invalid_columns_format", + message="Columns must be a list", + details="The 'columns' field must be an array of column specifications", + suggestions=[ + "Ensure columns is an array: 'columns': [...]", + "Each column should be an object with 'name' field", + ], + error_code="INVALID_COLUMNS_FORMAT", + ) + + return None + + def extract_column_refs(self, config: Any) -> list[ColumnRef]: Review Comment: Declining — docstring is a Minor ⚠️ suggestion from automated bot review. Per project standards, short comments/docstrings are added only when the `why` is non-obvious; method contracts here are self-evident from the Protocol definition and method names. ########## superset/mcp_service/chart/plugins/table.py: ########## @@ -0,0 +1,135 @@ +# 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. + +"""Table chart type plugin.""" + +from __future__ import annotations + +from typing import Any + +from superset.mcp_service.chart.chart_utils import ( + _summarize_filters, + _table_chart_what, + map_table_config, +) +from superset.mcp_service.chart.plugin import BaseChartPlugin +from superset.mcp_service.chart.schemas import ColumnRef, TableChartConfig +from superset.mcp_service.chart.validation.dataset_validator import DatasetValidator +from superset.mcp_service.common.error_schemas import ChartGenerationError + + +class TableChartPlugin(BaseChartPlugin): + """Plugin for table chart type.""" + + chart_type = "table" + display_name = "Table" + native_viz_types = { + "table": "Table", + "ag-grid-table": "Interactive Table", + } + + def pre_validate( + self, + config: dict[str, Any], + ) -> ChartGenerationError | None: + columns = ( + config.get("columns") or config.get("all_columns") or config.get("groupby") + ) + if not columns: + return ChartGenerationError( + error_type="missing_columns", + message="Table chart missing required field: columns", + details=( + "Table charts require a 'columns' array to specify which " + "columns to display" + ), + suggestions=[ + "Add 'columns' field with array of column specifications", + "Example: 'columns': [{'name': 'product'}, {'name': 'sales', " + "'aggregate': 'SUM'}]", + "Each column can have optional 'aggregate' for metrics", + ], + error_code="MISSING_COLUMNS", + ) + + if not isinstance(columns, list): + return ChartGenerationError( + error_type="invalid_columns_format", + message="Columns must be a list", + details="The 'columns' field must be an array of column specifications", + suggestions=[ + "Ensure columns is an array: 'columns': [...]", + "Each column should be an object with 'name' field", + ], + error_code="INVALID_COLUMNS_FORMAT", + ) + + return None + + def extract_column_refs(self, config: Any) -> list[ColumnRef]: + if not isinstance(config, TableChartConfig): + return [] + refs: list[ColumnRef] = list(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]: Review Comment: Declining — docstring is a Minor ⚠️ suggestion from automated bot review. Per project standards, short comments/docstrings are added only when the `why` is non-obvious; method contracts here are self-evident from the Protocol definition and method names. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
