codeant-ai-for-open-source[bot] commented on code in PR #41611: URL: https://github.com/apache/superset/pull/41611#discussion_r3531328463
########## tests/unit_tests/mcp_service/semantic_layer/tool/test_get_compatible_dimensions.py: ########## @@ -0,0 +1,231 @@ +# 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. + +"""Unit tests for the get_compatible_dimensions MCP tool.""" + +from __future__ import annotations + +import importlib +from collections.abc import Generator +from unittest.mock import MagicMock, Mock, patch + +import pytest +from fastmcp import Client, FastMCP + +from superset.errors import ErrorLevel, SupersetError, SupersetErrorType +from superset.exceptions import SupersetSecurityException +from superset.mcp_service.app import mcp +from superset.utils import json + +get_compatible_dimensions_module = importlib.import_module( + "superset.mcp_service.semantic_layer.tool.get_compatible_dimensions" +) Review Comment: **Suggestion:** Add an explicit type annotation for this module-level variable (for example a module type) to satisfy the required type-hint coverage for relevant variables. [custom_rule] **Severity Level:** Minor ⚠️ <details> <summary><b>Why it matters? 🤔 </b></summary> This new module-level variable is assigned the imported module object without any type annotation, and it is clearly annotatable (for example as a module type or `ModuleType`), so it violates the required Python type-hint coverage rule. </details> [](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=dd7c8021b345428e9b739f4f143c8de8&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset) [](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=dd7c8021b345428e9b739f4f143c8de8&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:** tests/unit_tests/mcp_service/semantic_layer/tool/test_get_compatible_dimensions.py **Line:** 34:36 **Comment:** *Custom Rule: Add an explicit type annotation for this module-level variable (for example a module type) to satisfy the required type-hint coverage for relevant variables. 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%2F41611&comment_hash=60989f630f838433456558f78d9bf96e951f9ba5089a7cd58cbca6423761af6f&reaction=like'>👍</a> | <a href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F41611&comment_hash=60989f630f838433456558f78d9bf96e951f9ba5089a7cd58cbca6423761af6f&reaction=dislike'>👎</a> ########## superset/mcp_service/semantic_layer/tool/list_metrics.py: ########## @@ -0,0 +1,294 @@ +# 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. + +"""MCP tool: list_metrics + +Unified metric discovery across built-in datasets and external semantic views. +""" + +import logging +from typing import Any + +from fastmcp import Context +from superset_core.mcp.decorators import tool, ToolAnnotations + +from superset.daos.dataset import DatasetDAO +from superset.daos.semantic_layer import SemanticViewDAO +from superset.extensions import db, event_logger +from superset.mcp_service.privacy import ( + DATA_MODEL_METADATA_ERROR_TYPE, + requires_data_model_metadata_access, + user_can_view_data_model_metadata, +) +from superset.mcp_service.semantic_layer.schemas import ( + DimensionInfo, + ListMetricsRequest, + MetricInfo, + MetricList, + SemanticLayerError, +) + +logger = logging.getLogger(__name__) + + +def _matches_search(text: str | None, search: str) -> bool: + if not text: + return False + return search.lower() in text.lower() + + +def _builtin_compatible_dims(dataset: Any) -> list[DimensionInfo]: + """Return groupby-enabled columns as compatible dimensions for a built-in metric.""" + return [ + DimensionInfo( + name=col.column_name, + verbose_name=col.verbose_name or None, + description=col.description or None, + type=col.type or None, + is_dttm=bool(col.is_dttm), + groupby=bool(col.groupby), + filterable=bool(col.filterable), + source="builtin", + ) + for col in dataset.columns + if col.groupby + ] + + +def _collect_builtin_metrics(request: ListMetricsRequest) -> list[MetricInfo]: + """Collect metrics from built-in SqlaTable datasets.""" + from sqlalchemy.orm import subqueryload + + from superset.connectors.sqla.models import SqlaTable + + with event_logger.log_context(action="mcp.list_metrics.builtin_query"): + if request.dataset_id is not None: + from sqlalchemy.orm import subqueryload + + from superset.connectors.sqla.models import SqlaTable + + dataset = DatasetDAO.find_by_id( + request.dataset_id, + query_options=[ + subqueryload(SqlaTable.columns), + subqueryload(SqlaTable.metrics), + ], + ) Review Comment: **Suggestion:** Add an explicit type annotation for this DAO result variable to comply with the required type-hint coverage for relevant variables. [custom_rule] **Severity Level:** Minor ⚠️ <details> <summary><b>Why it matters? 🤔 </b></summary> The new code assigns the result of a DAO lookup to `dataset` without any explicit type annotation. This is a new relevant variable that can be annotated, so it violates the type-hint requirement. </details> [](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=abbd344a2d384dd583dde128cf327c73&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset) [](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=abbd344a2d384dd583dde128cf327c73&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/semantic_layer/tool/list_metrics.py **Line:** 84:90 **Comment:** *Custom Rule: Add an explicit type annotation for this DAO result variable to comply with the required type-hint coverage for relevant variables. 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%2F41611&comment_hash=14a1b3d7c150309f3511c92fa856632ae656b166887cb8dbb50170b2d86ec565&reaction=like'>👍</a> | <a href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F41611&comment_hash=14a1b3d7c150309f3511c92fa856632ae656b166887cb8dbb50170b2d86ec565&reaction=dislike'>👎</a> ########## superset/mcp_service/semantic_layer/tool/list_metrics.py: ########## @@ -0,0 +1,294 @@ +# 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. + +"""MCP tool: list_metrics + +Unified metric discovery across built-in datasets and external semantic views. +""" + +import logging +from typing import Any + +from fastmcp import Context +from superset_core.mcp.decorators import tool, ToolAnnotations + +from superset.daos.dataset import DatasetDAO +from superset.daos.semantic_layer import SemanticViewDAO +from superset.extensions import db, event_logger +from superset.mcp_service.privacy import ( + DATA_MODEL_METADATA_ERROR_TYPE, + requires_data_model_metadata_access, + user_can_view_data_model_metadata, +) +from superset.mcp_service.semantic_layer.schemas import ( + DimensionInfo, + ListMetricsRequest, + MetricInfo, + MetricList, + SemanticLayerError, +) + +logger = logging.getLogger(__name__) + + +def _matches_search(text: str | None, search: str) -> bool: + if not text: + return False + return search.lower() in text.lower() + + +def _builtin_compatible_dims(dataset: Any) -> list[DimensionInfo]: + """Return groupby-enabled columns as compatible dimensions for a built-in metric.""" + return [ + DimensionInfo( + name=col.column_name, + verbose_name=col.verbose_name or None, + description=col.description or None, + type=col.type or None, + is_dttm=bool(col.is_dttm), + groupby=bool(col.groupby), + filterable=bool(col.filterable), + source="builtin", + ) + for col in dataset.columns + if col.groupby + ] + + +def _collect_builtin_metrics(request: ListMetricsRequest) -> list[MetricInfo]: + """Collect metrics from built-in SqlaTable datasets.""" + from sqlalchemy.orm import subqueryload + + from superset.connectors.sqla.models import SqlaTable + + with event_logger.log_context(action="mcp.list_metrics.builtin_query"): + if request.dataset_id is not None: + from sqlalchemy.orm import subqueryload + + from superset.connectors.sqla.models import SqlaTable + + dataset = DatasetDAO.find_by_id( + request.dataset_id, + query_options=[ + subqueryload(SqlaTable.columns), + subqueryload(SqlaTable.metrics), + ], + ) + datasets = [dataset] if dataset else [] + else: + from sqlalchemy.orm import subqueryload + + from superset.connectors.sqla.models import SqlaTable + + # Use _apply_base_filter with explicit eager loading to avoid + # N+1 queries when iterating dataset.metrics / dataset.columns. + query = db.session.query(SqlaTable).options( + subqueryload(SqlaTable.columns), + subqueryload(SqlaTable.metrics), + ) + datasets = DatasetDAO._apply_base_filter(query).all() + + results: list[MetricInfo] = [] + for dataset in datasets: + compat_dims = ( + _builtin_compatible_dims(dataset) + if request.include_compatible_dimensions + else [] + ) + for metric in dataset.metrics: + name = metric.metric_name or "" + desc = metric.description or "" + if request.search and not ( + _matches_search(name, request.search) + or _matches_search(desc, request.search) + ): + continue + results.append( + MetricInfo( + name=name, + verbose_name=metric.verbose_name or None, + description=desc or None, + expression=metric.expression or None, + d3format=metric.d3format or None, + warning_text=metric.warning_text or None, + source="builtin", + dataset_id=dataset.id, + dataset_name=dataset.table_name, + compatible_dimensions=compat_dims, + ) + ) + return results + + +async def _collect_external_metrics( + request: ListMetricsRequest, + ctx: Context, +) -> list[MetricInfo]: + """Collect metrics from external SemanticView models.""" + with event_logger.log_context(action="mcp.list_metrics.external_query"): + if request.view_id is not None: + view = SemanticViewDAO.find_by_id(request.view_id) + views = [view] if view else [] Review Comment: **Suggestion:** Add an explicit type annotation for this semantic view lookup variable so the new code does not omit type hints on relevant variables. [custom_rule] **Severity Level:** Minor ⚠️ <details> <summary><b>Why it matters? 🤔 </b></summary> The new code introduces `view` as a DAO result variable without an explicit type annotation. Since the rule requires type hints for relevant variables that can be annotated, this is a real violation. </details> [](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=1a5ed1baee3449ff98d5f2ea3c4ea597&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset) [](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=1a5ed1baee3449ff98d5f2ea3c4ea597&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/semantic_layer/tool/list_metrics.py **Line:** 144:145 **Comment:** *Custom Rule: Add an explicit type annotation for this semantic view lookup variable so the new code does not omit type hints on relevant variables. 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%2F41611&comment_hash=24b97d95c9d195c8e10ca89395a0556e5fc4e8641cd960a53be9a6b25bb7dce6&reaction=like'>👍</a> | <a href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F41611&comment_hash=24b97d95c9d195c8e10ca89395a0556e5fc4e8641cd960a53be9a6b25bb7dce6&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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