codeant-ai-for-open-source[bot] commented on code in PR #39922:
URL: https://github.com/apache/superset/pull/39922#discussion_r3398598396


##########
superset/mcp_service/chart/plugins/mixed_timeseries.py:
##########
@@ -0,0 +1,170 @@
+# 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 typing import Any
+
+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 = {
+        "mixed_timeseries": "Mixed Timeseries Chart",
+    }
+
+    def pre_validate(
+        self,
+        config: dict[str, Any],
+    ) -> ChartGenerationError | None:
+        missing_fields = []
+
+        if "x" not in config and "x_axis" not in config:
+            missing_fields.append("'x' (X-axis temporal column)")
+        if not config.get("y") and not config.get("metrics"):
+            missing_fields.append("'y' (primary Y-axis metrics)")
+        if not config.get("y_secondary") and not config.get("metrics_b"):
+            missing_fields.append("'y_secondary' (secondary Y-axis metrics)")
+
+        if missing_fields:
+            return ChartGenerationError(
+                error_type="missing_mixed_timeseries_fields",
+                message=(
+                    f"Mixed timeseries chart missing required fields: "
+                    f"{', '.join(missing_fields)}"
+                ),
+                details=(
+                    "Mixed timeseries charts require an x-axis, primary 
metrics, "
+                    "and secondary metrics"
+                ),
+                suggestions=[
+                    "Add 'x' field: {'name': 'date_column'}",
+                    "Add 'y' field: [{'name': 'revenue', 'aggregate': 'SUM'}]",
+                    "Add 'y_secondary': [{'name': 'orders', 'aggregate': 
'COUNT'}]",
+                    "Optional: 'primary_kind' and 'secondary_kind' for chart 
types",
+                ],
+                error_code="MISSING_MIXED_TIMESERIES_FIELDS",
+            )
+
+        for field_name in ["y", "y_secondary"]:
+            if not isinstance(config.get(field_name, []), list):
+                return ChartGenerationError(
+                    error_type=f"invalid_{field_name}_format",
+                    message=f"'{field_name}' must be a list of metrics",
+                    details=(
+                        f"The '{field_name}' field must be an array of metric "
+                        "specifications"
+                    ),
+                    suggestions=[
+                        f"Wrap in array: '{field_name}': "
+                        "[{'name': 'col', 'aggregate': 'SUM'}]",
+                    ],
+                    error_code=f"INVALID_{field_name.upper()}_FORMAT",
+                )
+
+        return None
+
+    def extract_column_refs(self, config: Any) -> list[ColumnRef]:

Review Comment:
   **Suggestion:** Add a method docstring that explains what column references 
are extracted and when an empty list is returned. [custom_rule]
   
   **Severity Level:** Minor ⚠️
   <details>
   <summary><b>Why it matters? 🤔 </b></summary>
   
   This newly added method has no docstring, which violates the rule requiring 
new Python functions to be documented inline.
   </details>
   
   [Fix in 
Cursor](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=06cf7df5af554d9a8ae5ae77d02eddb4&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=06cf7df5af554d9a8ae5ae77d02eddb4&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/mixed_timeseries.py
   **Line:** 95:95
   **Comment:**
        *Custom Rule: Add a method docstring that explains what column 
references are extracted and when an empty list 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=c8d7ba6700da951d94bdd5d18745532f5c53f61213c576e62b86fb06aa40a6c3&reaction=like'>👍</a>
 | <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=c8d7ba6700da951d94bdd5d18745532f5c53f61213c576e62b86fb06aa40a6c3&reaction=dislike'>👎</a>



##########
superset/mcp_service/chart/plugins/mixed_timeseries.py:
##########
@@ -0,0 +1,170 @@
+# 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 typing import Any
+
+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 = {
+        "mixed_timeseries": "Mixed Timeseries Chart",
+    }
+
+    def pre_validate(
+        self,
+        config: dict[str, Any],
+    ) -> ChartGenerationError | None:
+        missing_fields = []
+
+        if "x" not in config and "x_axis" not in config:
+            missing_fields.append("'x' (X-axis temporal column)")
+        if not config.get("y") and not config.get("metrics"):
+            missing_fields.append("'y' (primary Y-axis metrics)")
+        if not config.get("y_secondary") and not config.get("metrics_b"):
+            missing_fields.append("'y_secondary' (secondary Y-axis metrics)")
+
+        if missing_fields:
+            return ChartGenerationError(
+                error_type="missing_mixed_timeseries_fields",
+                message=(
+                    f"Mixed timeseries chart missing required fields: "
+                    f"{', '.join(missing_fields)}"
+                ),
+                details=(
+                    "Mixed timeseries charts require an x-axis, primary 
metrics, "
+                    "and secondary metrics"
+                ),
+                suggestions=[
+                    "Add 'x' field: {'name': 'date_column'}",
+                    "Add 'y' field: [{'name': 'revenue', 'aggregate': 'SUM'}]",
+                    "Add 'y_secondary': [{'name': 'orders', 'aggregate': 
'COUNT'}]",
+                    "Optional: 'primary_kind' and 'secondary_kind' for chart 
types",
+                ],
+                error_code="MISSING_MIXED_TIMESERIES_FIELDS",
+            )
+
+        for field_name in ["y", "y_secondary"]:
+            if not isinstance(config.get(field_name, []), list):
+                return ChartGenerationError(
+                    error_type=f"invalid_{field_name}_format",
+                    message=f"'{field_name}' must be a list of metrics",
+                    details=(
+                        f"The '{field_name}' field must be an array of metric "
+                        "specifications"
+                    ),
+                    suggestions=[
+                        f"Wrap in array: '{field_name}': "
+                        "[{'name': 'col', 'aggregate': 'SUM'}]",
+                    ],
+                    error_code=f"INVALID_{field_name.upper()}_FORMAT",
+                )
+
+        return None
+
+    def extract_column_refs(self, config: Any) -> list[ColumnRef]:
+        if not isinstance(config, MixedTimeseriesChartConfig):
+            return []
+        refs: list[ColumnRef] = [config.x]
+        refs.extend(config.y)
+        refs.extend(config.y_secondary)
+        if config.group_by:
+            refs.extend(config.group_by)
+        if config.group_by_secondary:
+            refs.extend(config.group_by_secondary)
+        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_mixed_timeseries_config(config, dataset_id=dataset_id)
+
+    def generate_name(self, config: Any, dataset_name: str | None = None) -> 
str:
+        what = _mixed_timeseries_what(config)
+        context = _summarize_filters(config.filters)
+        return self._with_context(what, context)
+
+    def resolve_viz_type(self, config: Any) -> str:
+        return "mixed_timeseries"
+
+    def normalize_column_refs(self, config: Any, dataset_context: Any) -> Any:

Review Comment:
   **Suggestion:** Add a docstring explaining how this method normalizes column 
and metric references before schema validation. [custom_rule]
   
   **Severity Level:** Minor ⚠️
   <details>
   <summary><b>Why it matters? 🤔 </b></summary>
   
   This newly introduced method does not include a docstring. The custom rule 
requires new functions and classes to be documented inline, so the suggestion 
is valid.
   </details>
   
   [Fix in 
Cursor](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=1e83d1090206415a949c736f754ae251&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=1e83d1090206415a949c736f754ae251&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/mixed_timeseries.py
   **Line:** 123:123
   **Comment:**
        *Custom Rule: Add a docstring explaining how this method normalizes 
column and metric references before schema validation.
   
   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=ef4dd05c0118759d31b7fa564f0a7837effe268d0c52f891b90d28a961bdd536&reaction=like'>👍</a>
 | <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=ef4dd05c0118759d31b7fa564f0a7837effe268d0c52f891b90d28a961bdd536&reaction=dislike'>👎</a>



##########
superset/mcp_service/chart/plugins/pie.py:
##########
@@ -0,0 +1,137 @@
+# 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:
+            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]:

Review Comment:
   **Suggestion:** Add a concise docstring that explains this method's 
conversion responsibility and how `dataset_id` is treated. [custom_rule]
   
   **Severity Level:** Minor ⚠️
   <details>
   <summary><b>Why it matters? 🤔 </b></summary>
   
   This newly added method has no docstring in the final file. Since the rule 
requires newly added Python functions to include docstrings, the suggestion is 
correctly identifying a violation.
   </details>
   
   [Fix in 
Cursor](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=020f0b8877d444a78fb1d209bfb8ff74&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=020f0b8877d444a78fb1d209bfb8ff74&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/pie.py
   **Line:** 84:86
   **Comment:**
        *Custom Rule: Add a concise docstring that explains this method's 
conversion responsibility and how `dataset_id` is treated.
   
   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=a6d09b691b4917dc620d42d2ecb617ca4c95c3c3e16c7cdfaec37fec926e80eb&reaction=like'>👍</a>
 | <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=a6d09b691b4917dc620d42d2ecb617ca4c95c3c3e16c7cdfaec37fec926e80eb&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.

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]

Reply via email to