codeant-ai-for-open-source[bot] commented on code in PR #39922: URL: https://github.com/apache/superset/pull/39922#discussion_r3398599091
########## superset/mcp_service/chart/plugin.py: ########## @@ -0,0 +1,263 @@ +# 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. + +""" +ChartTypePlugin protocol and BaseChartPlugin base class. + +Each chart type owns its pre-validation, column extraction, form_data mapping, +and post-map validation in a single plugin class. This eliminates the previous +pattern of 4 separate dispatch points (schema_validator.py, dataset_validator.py, +chart_utils.py, pipeline.py) that had to be updated in sync whenever a new chart +type was added. +""" + +from __future__ import annotations + +from typing import Any, Protocol, runtime_checkable + +from superset.mcp_service.chart.schemas import ColumnRef +from superset.mcp_service.common.error_schemas import ChartGenerationError + + +@runtime_checkable +class ChartTypePlugin(Protocol): + """ + Protocol that every chart-type plugin must satisfy. + + Implementing all eight methods in a single class guarantees that adding a + new chart type requires only one new file — the plugin — rather than edits + across multiple separate files. + """ + + #: Discriminator value matching ChartConfig's chart_type field. + chart_type: str + + #: Human-readable name shown to users (e.g. "Line / Bar / Area / Scatter"). + display_name: str + + #: Maps every Superset-internal viz_type this plugin can produce to a + #: user-facing display name, e.g. {"echarts_timeseries_line": "Line Chart"}. + #: Used by the registry to resolve display names for existing charts without + #: needing a separate JSON mapping file. + native_viz_types: dict[str, str] + + def pre_validate( + self, + config: dict[str, Any], + ) -> ChartGenerationError | None: + """ + Early validation of the raw config dict before Pydantic parsing. + + Called by SchemaValidator before attempting to parse the request. + Should check that required top-level keys are present and well-typed. + + Returns None if valid, ChartGenerationError if invalid. + """ + ... + + def extract_column_refs( + self, + config: Any, + ) -> list[ColumnRef]: + """ + Extract all column references from a parsed chart config. + + Called by DatasetValidator to validate that all referenced columns exist + in the dataset. Must cover every field that holds a column name, + including filters. + + Returns a list of ColumnRef objects (may be empty). + """ + ... + + def to_form_data( + self, + config: Any, + dataset_id: int | str | None = None, + ) -> dict[str, Any]: + """ + Map a parsed chart config to Superset's internal form_data dict. + + Replaces the if/elif chain in chart_utils.map_config_to_form_data(). + + Returns a Superset form_data dict ready for caching and rendering. + """ + ... + + def post_map_validate( + self, + config: Any, + form_data: dict[str, Any], + dataset_id: int | str | None = None, + ) -> ChartGenerationError | None: + """ + Validate the mapped form_data after to_form_data() runs. + + Use this for cross-field constraints that can only be checked once + form_data is assembled (e.g. BigNumber trendline requires a temporal + column whose type must be verified against the dataset). + + Returns None if valid, ChartGenerationError if invalid. + """ + ... + + def normalize_column_refs( + self, + config: Any, + dataset_context: Any, + ) -> Any: + """ + Return a new config with column names normalized to canonical dataset casing. + + Called by DatasetValidator.normalize_column_names(). The default + implementation (in BaseChartPlugin) returns the config unchanged; plugins + with column fields override this to fix case sensitivity mismatches. + + Returns a new config object (or the original if no normalization needed). + """ + ... + + def get_runtime_warnings( + self, + config: Any, + dataset_id: int | str, + ) -> list[str]: + """ + Return chart-type-specific runtime warnings (performance, compatibility). + + Called by RuntimeValidator to collect per-type warnings. Warnings are + informational only — they never block chart generation. The default + implementation returns an empty list; plugins override this to emit + chart-type-specific warnings (e.g. XY cardinality checks). + + Returns a list of warning message strings (may be empty). + """ + ... + + def generate_name( + self, + config: Any, + dataset_name: str | None = None, + ) -> str: + """ + Return a descriptive chart name for the given config. + + Called by chart_utils.generate_chart_name(). The name should follow + the standard format conventions documented in that function. Plugins + that do not override this return the generic fallback "Chart". + """ + ... + + def resolve_viz_type(self, config: Any) -> str: + """ + Return the Superset-internal viz_type string for this config. + + Called by chart_utils._resolve_viz_type(). The returned string must + match a registered Superset viz plugin (e.g. "echarts_timeseries_line"). + Plugins that do not override this return "unknown". + """ + ... + + def schema_error_hint(self) -> ChartGenerationError | None: + """ + Return a user-friendly error for Pydantic discriminated-union parse failures. + + Called by SchemaValidator when Pydantic cannot parse the config union and + the chart_type is known. Returning None falls back to the generic error. + """ + ... + + +class BaseChartPlugin: + """ + Base class providing sensible defaults for all ChartTypePlugin methods. + + Concrete plugins extend this and override only what they need. Default + implementations: ``pre_validate`` → None (valid), ``extract_column_refs`` → [], + ``post_map_validate`` → None, ``normalize_column_refs`` → config unchanged, + ``get_runtime_warnings`` → [], ``generate_name`` → "Chart", + ``resolve_viz_type`` → "unknown", ``schema_error_hint`` → None. + ``to_form_data`` raises ``NotImplementedError`` and must be overridden. + """ + + chart_type: str = "" + display_name: str = "" + # Class-level dict shared across all subclasses that don't override it. + # Subclasses MUST override this as a class attribute (not mutate in place) + # to avoid corrupting the shared empty-dict default for other plugins. + native_viz_types: dict[str, str] = {} + + def pre_validate( + self, + config: dict[str, Any], + ) -> ChartGenerationError | None: + return None Review Comment: **Suggestion:** Add a concise docstring to this newly added method describing its default validation behavior and return contract. [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 new functions and classes to be documented inline, so this is a real violation. </details> [Fix in Cursor](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=24ff8e4875f9414abee47e54f0cd53f6&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=24ff8e4875f9414abee47e54f0cd53f6&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/plugin.py **Line:** 204:208 **Comment:** *Custom Rule: Add a concise docstring to this newly added method describing its default validation behavior and return contract. 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=d757c4d5e6f9fc68f3c7955e83f3b8e582b4f7cf2290e2ad59745c7809e4a8b9&reaction=like'>👍</a> | <a href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=d757c4d5e6f9fc68f3c7955e83f3b8e582b4f7cf2290e2ad59745c7809e4a8b9&reaction=dislike'>👎</a> ########## 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: Review Comment: **Suggestion:** Add a docstring to `normalize_column_refs` describing normalization steps and the expected output schema object. [custom_rule] **Severity Level:** Minor ⚠️ <details> <summary><b>Why it matters? 🤔 </b></summary> The method is newly added and does not include a docstring. This violates the stated rule for new Python functions/classes needing inline documentation. </details> [Fix in Cursor](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=839139503f44473b8eec91375297f84a&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=839139503f44473b8eec91375297f84a&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:** 154:154 **Comment:** *Custom Rule: Add a docstring to `normalize_column_refs` describing normalization steps and the expected output schema object. 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=a30fae1ca263065c7a8c96ed1d653c0345f77df36ef175ff18c7525ba2bab828&reaction=like'>👍</a> | <a href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=a30fae1ca263065c7a8c96ed1d653c0345f77df36ef175ff18c7525ba2bab828&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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