codeant-ai-for-open-source[bot] commented on code in PR #39922: URL: https://github.com/apache/superset/pull/39922#discussion_r3398599163
########## 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: Review Comment: **Suggestion:** Add a docstring to `pre_validate` that explains what configuration checks are performed and when a validation error is returned. [custom_rule] **Severity Level:** Minor ⚠️ <details> <summary><b>Why it matters? 🤔 </b></summary> This is a newly added Python method in a new file, and it has no docstring. The custom rule requires newly added Python functions and classes to include docstrings, so this is a real violation. </details> [Fix in Cursor](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=9d55b31efe1848929d13edba06959411&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset) | [Fix in VSCode Claude](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=9d55b31efe1848929d13edba06959411&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset) *(Use Cmd/Ctrl + Click for best experience)* <details> <summary><b>Prompt for AI Agent 🤖 </b></summary> ```mdx This is a comment left during a code review. **Path:** superset/mcp_service/chart/plugins/handlebars.py **Line:** 44:47 **Comment:** *Custom Rule: Add a docstring to `pre_validate` that explains what configuration checks are performed and when a validation error is returned. Validate the correctness of the flagged issue. If correct, How can I resolve this? If you propose a fix, implement it and please make it concise. Once fix is implemented, also check other comments on the same PR, and ask user if the user wants to fix the rest of the comments as well. if said yes, then fetch all the comments validate the correctness and implement a minimal fix ``` </details> <a href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=165e68f45810c6ccff95a876c79ee096a4ed97c162432c36b39a2eacb53dacb0&reaction=like'>👍</a> | <a href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=165e68f45810c6ccff95a876c79ee096a4ed97c162432c36b39a2eacb53dacb0&reaction=dislike'>👎</a> ########## superset/mcp_service/chart/plugins/pivot_table.py: ########## @@ -0,0 +1,158 @@ +# 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"): + 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", + ) + + if not isinstance(config.get("rows", []), 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: Review Comment: **Suggestion:** Add an inline docstring to this method describing the normalization process and expected output type after canonicalization. [custom_rule] **Severity Level:** Minor ⚠️ <details> <summary><b>Why it matters? 🤔 </b></summary> This is a newly added method and there is no docstring above it. That is a direct match for the custom rule about documenting new functions and methods. </details> [Fix in Cursor](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=3fc1806e34e7433c82aaa46028968c02&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset) | [Fix in VSCode Claude](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=3fc1806e34e7433c82aaa46028968c02&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset) *(Use Cmd/Ctrl + Click for best experience)* <details> <summary><b>Prompt for AI Agent 🤖 </b></summary> ```mdx This is a comment left during a code review. **Path:** superset/mcp_service/chart/plugins/pivot_table.py **Line:** 120:120 **Comment:** *Custom Rule: Add an inline docstring to this method describing the normalization process and expected output type after canonicalization. Validate the correctness of the flagged issue. If correct, How can I resolve this? If you propose a fix, implement it and please make it concise. Once fix is implemented, also check other comments on the same PR, and ask user if the user wants to fix the rest of the comments as well. if said yes, then fetch all the comments validate the correctness and implement a minimal fix ``` </details> <a href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=f9e7339627600252248cc93e54eb17590ec6d0fdb743e7d6afba81f5b0d19689&reaction=like'>👍</a> | <a href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=f9e7339627600252248cc93e54eb17590ec6d0fdb743e7d6afba81f5b0d19689&reaction=dislike'>👎</a> ########## superset/mcp_service/chart/plugins/big_number.py: ########## @@ -0,0 +1,247 @@ +# 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. + +"""Big number chart type plugin.""" + +from __future__ import annotations + +from typing import Any + +from superset.mcp_service.chart.chart_utils import ( + _big_number_chart_what, + _summarize_filters, + is_column_truly_temporal, + map_big_number_config, +) +from superset.mcp_service.chart.plugin import BaseChartPlugin +from superset.mcp_service.chart.schemas import BigNumberChartConfig, ColumnRef +from superset.mcp_service.chart.validation.dataset_validator import DatasetValidator +from superset.mcp_service.common.error_schemas import ChartGenerationError + + +class BigNumberChartPlugin(BaseChartPlugin): + """Plugin for big_number chart type.""" + + chart_type = "big_number" + display_name = "Big Number" + native_viz_types = { + "big_number": "Big Number with Trendline", + "big_number_total": "Big Number", + } + + def pre_validate( + self, + config: dict[str, Any], + ) -> ChartGenerationError | None: + if "metric" not in config: + return ChartGenerationError( + error_type="missing_metric", + message="Big Number chart missing required field: metric", + details=( + "Big Number charts require a 'metric' field " + "specifying the value to display" + ), + suggestions=[ + "Add 'metric' with name and aggregate: " + "{'name': 'revenue', 'aggregate': 'SUM'}", + "The aggregate function is required (SUM, COUNT, AVG, MIN, MAX)", + "Example: {'chart_type': 'big_number', " + "'metric': {'name': 'sales', 'aggregate': 'SUM'}}", + ], + error_code="MISSING_BIG_NUMBER_METRIC", + ) + + metric = config.get("metric", {}) + if not isinstance(metric, dict): + return ChartGenerationError( + error_type="invalid_metric_type", + message="Big Number metric must be a dict with 'name' and 'aggregate'", + details=( + f"The 'metric' field must be an object, got {type(metric).__name__}" + ), + suggestions=[ + "Use a dict: {'name': 'col', 'aggregate': 'SUM'}", + "Valid aggregates: SUM, COUNT, AVG, MIN, MAX", + ], + error_code="INVALID_BIG_NUMBER_METRIC_TYPE", + ) + if metric.get("sql_expression"): + label = metric.get("label") + if not isinstance(label, str) or not label.strip(): + return ChartGenerationError( + error_type="missing_sql_metric_label", + message="SQL expression metrics require a non-empty 'label'", + details=( + "When using a custom SQL expression as the Big Number metric, " + "a human-readable 'label' string is required so Superset can " + "display the metric name." + ), + suggestions=[ + "Add 'label': e.g. {'sql_expression': 'SUM(a)/SUM(b)', " + "'label': 'Conversion Rate'}", + "The label must be a non-empty string", + ], + error_code="MISSING_SQL_METRIC_LABEL", + ) + elif not metric.get("aggregate") and not metric.get("saved_metric"): + return ChartGenerationError( + error_type="missing_metric_aggregate", + message=( + "Big Number metric must include an aggregate function " + "or reference a saved metric" + ), + details=( + "The metric must have an 'aggregate' field or 'saved_metric': true" + ), + suggestions=[ + "Add 'aggregate': {'name': 'col', 'aggregate': 'SUM'}", + "Or use a saved metric: {'name': 'metric', 'saved_metric': true}", + "Valid aggregates: SUM, COUNT, AVG, MIN, MAX", + ], + error_code="MISSING_BIG_NUMBER_AGGREGATE", + ) + + show_trendline = config.get("show_trendline", False) + temporal_column = config.get("temporal_column") + if show_trendline and not temporal_column: + return ChartGenerationError( + error_type="missing_temporal_column", + message="Trendline requires a temporal column", + details=( + "When 'show_trendline' is True, " + "a 'temporal_column' must be specified" + ), + suggestions=[ + "Add 'temporal_column': 'date_column_name'", + "Or set 'show_trendline': false for number only", + "Use get_dataset_info to find temporal columns", + ], + error_code="MISSING_TEMPORAL_COLUMN", + ) + + return None + + def extract_column_refs(self, config: Any) -> list[ColumnRef]: + if not isinstance(config, BigNumberChartConfig): + return [] + refs: list[ColumnRef] = [config.metric] + # temporal_column is a str field, not a ColumnRef — validate it exists + if config.temporal_column: + refs.append(ColumnRef(name=config.temporal_column)) + 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_big_number_config(config) + + def post_map_validate( + self, + config: Any, + form_data: dict[str, Any], + dataset_id: int | str | None = None, + ) -> ChartGenerationError | None: + """Verify the trendline temporal column is a real temporal SQL type. + + This check was previously baked into map_config_to_form_data() in + chart_utils.py as a special case. Moving it here keeps the dispatcher + clean and makes the constraint explicit and discoverable. + """ + if not isinstance(config, BigNumberChartConfig): + return None + if not (config.show_trendline and config.temporal_column): + return None + + if not is_column_truly_temporal(config.temporal_column, dataset_id): + return ChartGenerationError( + error_type="non_temporal_trendline_column", + message=( + f"Big Number trendline requires a temporal SQL column; " + f"'{config.temporal_column}' is not temporal." + ), + details=( + f"Column '{config.temporal_column}' does not have a temporal " + f"SQL type (DATE, DATETIME, TIMESTAMP). The trendline requires " + f"a true temporal column for DATE_TRUNC to work." + ), + suggestions=[ + "Use get_dataset_info to find columns with temporal SQL types", + "Set 'show_trendline': false to use any column as the metric", + "If the column contains dates stored as integers, " + "consider casting it in a virtual dataset", + ], + error_code="NON_TEMPORAL_TRENDLINE_COLUMN", + ) + + return None + + def generate_name(self, config: Any, dataset_name: str | None = None) -> str: + what = _big_number_chart_what(config) + context = _summarize_filters(getattr(config, "filters", None)) + return self._with_context(what, context) + + def resolve_viz_type(self, config: Any) -> str: + show_trendline = getattr(config, "show_trendline", False) + temporal_column = getattr(config, "temporal_column", None) + if show_trendline and temporal_column: + return "big_number" + return "big_number_total" + + def normalize_column_refs(self, config: Any, dataset_context: Any) -> Any: Review Comment: **Suggestion:** Add a docstring that explains this normalization step, expected input model shape, and what normalized object is returned. [custom_rule] **Severity Level:** Minor ⚠️ <details> <summary><b>Why it matters? 🤔 </b></summary> This is a new method in the added plugin class and it does not have a docstring. The suggestion correctly identifies a real rule violation. </details> [Fix in Cursor](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=39252514ae4c4e5d860faaa918d38c40&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset) | [Fix in VSCode Claude](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=39252514ae4c4e5d860faaa918d38c40&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset) *(Use Cmd/Ctrl + Click for best experience)* <details> <summary><b>Prompt for AI Agent 🤖 </b></summary> ```mdx This is a comment left during a code review. **Path:** superset/mcp_service/chart/plugins/big_number.py **Line:** 207:207 **Comment:** *Custom Rule: Add a docstring that explains this normalization step, expected input model shape, and what normalized object is returned. Validate the correctness of the flagged issue. If correct, How can I resolve this? If you propose a fix, implement it and please make it concise. Once fix is implemented, also check other comments on the same PR, and ask user if the user wants to fix the rest of the comments as well. if said yes, then fetch all the comments validate the correctness and implement a minimal fix ``` </details> <a href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=e15a10d724b1fa5abe1ef591cb41ed5ce3ca3361588a68958b82f429cb3f405c&reaction=like'>👍</a> | <a href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=e15a10d724b1fa5abe1ef591cb41ed5ce3ca3361588a68958b82f429cb3f405c&reaction=dislike'>👎</a> -- 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. 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