codeant-ai-for-open-source[bot] commented on code in PR #39922:
URL: https://github.com/apache/superset/pull/39922#discussion_r3482251111


##########
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:

Review Comment:
   ✅ **Customized review instruction saved!**
   
   **Instruction:**
   > Do not require per-method docstrings for plugin implementation methods 
when the method contract is already documented in the shared Protocol and the 
class-level docstring identifies the chart type; avoid flagging missing method 
docstrings across chart plugin implementation files unless there is a 
project-wide policy change.
   
   **Applied to:**
     - `superset/mcp_service/chart/plugins/**`
   
   ---
   💡 *To manage or update this instruction, visit: [CodeAnt AI 
Settings](https://app.codeant.ai/org/settings/learnings)*



##########
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]:

Review Comment:
   ✅ **Customized review instruction saved!**
   
   **Instruction:**
   > Do not require per-method docstrings on chart plugin implementation 
methods when the corresponding Protocol already documents the method contract; 
class-level docstrings and the shared Protocol are sufficient.
   
   **Applied to:**
     - `superset/mcp_service/chart/plugins/**`
   
   ---
   💡 *To manage or update this instruction, visit: [CodeAnt AI 
Settings](https://app.codeant.ai/org/settings/learnings)*



##########
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]:

Review Comment:
   ✅ **Customized review instruction saved!**
   
   **Instruction:**
   > Do not require per-method prose docstrings for implementation methods in 
chart plugin files; the class-level docstring and the Protocol in plugin.py are 
sufficient to document the contract.
   
   **Applied to:**
     - `superset/mcp_service/chart/plugins/**`
   
   ---
   💡 *To manage or update this instruction, visit: [CodeAnt AI 
Settings](https://app.codeant.ai/org/settings/learnings)*



##########
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:
   ✅ **Customized review instruction saved!**
   
   **Instruction:**
   > Do not require per-method prose docstrings for implementation methods in 
chart plugin classes when the corresponding Protocol already documents the 
method contract; rely on the class-level docstring and Protocol documentation 
instead.
   
   **Applied to:**
     - `superset/mcp_service/chart/plugins/**`
   
   ---
   💡 *To manage or update this instruction, visit: [CodeAnt AI 
Settings](https://app.codeant.ai/org/settings/learnings)*



##########
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:
+        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("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:

Review Comment:
   ✅ **Customized review instruction saved!**
   
   **Instruction:**
   > Do not require per-method docstrings on chart plugin implementation 
methods; rely on the class-level docstring and the Protocol declaration for 
method contracts and invariants.
   
   **Applied to:**
     - `superset/mcp_service/chart/plugins/**`
   
   ---
   💡 *To manage or update this instruction, visit: [CodeAnt AI 
Settings](https://app.codeant.ai/org/settings/learnings)*



##########
superset/mcp_service/chart/registry.py:
##########
@@ -0,0 +1,279 @@
+# 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.
+
+"""
+ChartTypeRegistry — central registry mapping chart_type strings to plugins.
+
+Replaces the four previously-scattered dispatch locations:
+  - schema_validator.py: chart_type_validators dict
+  - dataset_validator.py: isinstance branches in _extract_column_references()
+  - chart_utils.py: if/elif chain in map_config_to_form_data()
+  - dataset_validator.py: isinstance branches in normalize_column_names()
+
+Usage::
+
+    from superset.mcp_service.chart.registry import get_registry
+
+    plugin = get_registry().get("xy")
+    if plugin is None:
+        raise ValueError("Unknown chart type: xy")
+    form_data = plugin.to_form_data(config, dataset_id)
+"""
+
+from __future__ import annotations
+
+import logging
+import sys
+import threading
+from collections.abc import Callable, Iterable
+from dataclasses import dataclass, field
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from superset.mcp_service.chart.plugin import ChartTypePlugin
+
+logger = logging.getLogger(__name__)
+
+_REGISTRY: dict[str, "ChartTypePlugin"] = {}
+_plugins_loaded = False
+_plugins_load_failed = False
+_plugins_lock = threading.RLock()
+
+# ---------------------------------------------------------------------------
+# Plugin filter — replaced atomically by configure() at app startup.
+# Default: all registered plugins visible (no disabled set, no callable).
+# ---------------------------------------------------------------------------
+
+PluginEnabledFunc = Callable[[str], bool]
+
+
+@dataclass(frozen=True)
+class _PluginFilterConfig:
+    disabled_plugins: frozenset[str] = field(default_factory=frozenset)
+    enabled_func: PluginEnabledFunc | None = None

Review Comment:
   ✅ **Customized review instruction saved!**
   
   **Instruction:**
   > Do not require per-method prose docstrings for plugin implementation 
classes when the corresponding Protocol already documents the method contracts; 
a class-level docstring is sufficient in this code area.
   
   **Applied to:**
     - `superset/mcp_service/chart/**`
   
   ---
   💡 *To manage or update this instruction, visit: [CodeAnt AI 
Settings](https://app.codeant.ai/org/settings/learnings)*



##########
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:

Review Comment:
   ✅ **Customized review instruction saved!**
   
   **Instruction:**
   > Do not require per-method docstrings for implementation methods in chart 
plugin files when the class-level docstring and the Protocol declaration 
already document the contract; avoid flagging this as a missing-docstring issue 
in implementation code.
   
   **Applied to:**
     - `superset/mcp_service/chart/plugins/**`
   
   ---
   💡 *To manage or update this instruction, visit: [CodeAnt AI 
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