codeant-ai-for-open-source[bot] commented on code in PR #40961:
URL: https://github.com/apache/superset/pull/40961#discussion_r3482126982
##########
superset/mcp_service/dashboard/schemas.py:
##########
@@ -1512,3 +1523,225 @@ def dashboard_layout_serializer(dashboard: "Dashboard")
-> DashboardLayout:
has_layout=bool(position_json_str),
)
)
+
+
+# Per-dataset caps keep responses small enough for LLM context: wide
+# datasets can have hundreds of columns, which would dwarf the fields an
+# agent actually needs to configure native filters.
+MAX_DASHBOARD_DATASET_COLUMNS = 100
+MAX_DASHBOARD_DATASET_METRICS = 50
+
+
+class DashboardDatasetColumn(BaseModel):
+ """Lean column representation for dashboard dataset context."""
+
+ column_name: str = Field(..., description="Column name")
+ verbose_name: str | None = Field(None, description="Verbose (display)
name")
+ type: str | None = Field(None, description="Column data type")
+ is_dttm: bool | None = Field(None, description="Is datetime column")
+
+
+class DashboardDatasetMetric(BaseModel):
+ """Lean metric representation for dashboard dataset context."""
+
+ metric_name: str = Field(..., description="Saved metric name")
+ verbose_name: str | None = Field(None, description="Verbose (display)
name")
+ expression: str | None = Field(None, description="SQL expression")
+
+
+class DashboardDatasetDatabaseInfo(BaseModel):
+ """Database connection summary for a dashboard dataset."""
+
+ id: int | None = Field(None, description="Database ID")
+ name: str | None = Field(None, description="Database name")
+ backend: str | None = Field(None, description="Database backend (engine)")
+
+
+class DashboardDatasetSummary(BaseModel):
+ """A dataset used by a dashboard's charts, with columns and metrics."""
+
+ id: int | None = Field(None, description="Dataset ID")
+ uuid: str | None = Field(None, description="Dataset UUID")
+ table_name: str | None = Field(None, description="Table name")
+ schema_name: str | None = Field(None, description="Schema name")
+ database: DashboardDatasetDatabaseInfo | None = Field(
+ None, description="Database the dataset belongs to"
+ )
+ chart_count: int = Field(
+ 0, description="Number of charts on the dashboard using this dataset"
+ )
+ columns: List[DashboardDatasetColumn] = Field(
+ default_factory=list, description="Dataset columns"
+ )
+ metrics: List[DashboardDatasetMetric] = Field(
+ default_factory=list, description="Dataset metrics"
+ )
+ total_column_count: int = Field(
+ 0, description="Total number of columns on the dataset"
+ )
+ total_metric_count: int = Field(
+ 0, description="Total number of metrics on the dataset"
+ )
+ columns_truncated: bool = Field(
+ False,
+ description=(
+ "True when the columns list was truncated to keep the response
small"
+ ),
+ )
+ metrics_truncated: bool = Field(
+ False,
+ description=(
+ "True when the metrics list was truncated to keep the response
small"
+ ),
+ )
+
+ @model_serializer(mode="wrap")
+ def _rename_schema_field(self, serializer: Any, info: Any) -> Dict[str,
Any]:
+ """Serialize 'schema_name' as 'schema' to match API conventions."""
+ data = serializer(self)
+ if "schema_name" in data:
+ data["schema"] = data.pop("schema_name")
+ return data
+
+
+class DashboardDatasets(BaseModel):
+ """Response schema for get_dashboard_datasets."""
+
+ id: int | None = Field(None, description="Dashboard ID")
+ dashboard_title: str | None = Field(None, description="Dashboard title")
+ uuid: str | None = Field(None, description="Dashboard UUID")
Review Comment:
**Suggestion:** Drop the integer dashboard identifier from the new dashboard
datasets response and keep UUID as the externally exposed identifier.
[custom_rule]
**Severity Level:** Minor ⚠️
<details>
<summary><b>Why it matters? 🤔 </b></summary>
The newly introduced response schema exposes a dashboard integer ID even
though a UUID field is also present. This is a real instance of the rule
against exposing internal integer IDs in newly added public API identifiers.
</details>
[](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=6ba963bbc4f247bab249cdebe333e92e&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
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<details>
<summary><b>Prompt for AI Agent 🤖 </b></summary>
```mdx
This is a comment left during a code review.
**Path:** superset/mcp_service/dashboard/schemas.py
**Line:** 1610:1612
**Comment:**
*Custom Rule: Drop the integer dashboard identifier from the new
dashboard datasets response and keep UUID as the externally exposed identifier.
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%2F40961&comment_hash=8eb6546c7f1f56b38d033cb01d7f8dd2da2bbc9180c103aa9bf6c938d52c8f0c&reaction=like'>👍</a>
| <a
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F40961&comment_hash=8eb6546c7f1f56b38d033cb01d7f8dd2da2bbc9180c103aa9bf6c938d52c8f0c&reaction=dislike'>👎</a>
##########
superset/mcp_service/dashboard/schemas.py:
##########
@@ -1512,3 +1523,225 @@ def dashboard_layout_serializer(dashboard: "Dashboard")
-> DashboardLayout:
has_layout=bool(position_json_str),
)
)
+
+
+# Per-dataset caps keep responses small enough for LLM context: wide
+# datasets can have hundreds of columns, which would dwarf the fields an
+# agent actually needs to configure native filters.
+MAX_DASHBOARD_DATASET_COLUMNS = 100
+MAX_DASHBOARD_DATASET_METRICS = 50
+
+
+class DashboardDatasetColumn(BaseModel):
+ """Lean column representation for dashboard dataset context."""
+
+ column_name: str = Field(..., description="Column name")
+ verbose_name: str | None = Field(None, description="Verbose (display)
name")
+ type: str | None = Field(None, description="Column data type")
+ is_dttm: bool | None = Field(None, description="Is datetime column")
+
+
+class DashboardDatasetMetric(BaseModel):
+ """Lean metric representation for dashboard dataset context."""
+
+ metric_name: str = Field(..., description="Saved metric name")
+ verbose_name: str | None = Field(None, description="Verbose (display)
name")
+ expression: str | None = Field(None, description="SQL expression")
+
+
+class DashboardDatasetDatabaseInfo(BaseModel):
+ """Database connection summary for a dashboard dataset."""
+
+ id: int | None = Field(None, description="Database ID")
+ name: str | None = Field(None, description="Database name")
+ backend: str | None = Field(None, description="Database backend (engine)")
+
+
+class DashboardDatasetSummary(BaseModel):
+ """A dataset used by a dashboard's charts, with columns and metrics."""
+
+ id: int | None = Field(None, description="Dataset ID")
+ uuid: str | None = Field(None, description="Dataset UUID")
Review Comment:
**Suggestion:** Remove the exposed integer dataset identifier from the new
dataset summary response and rely on the UUID field as the public identifier.
[custom_rule]
**Severity Level:** Minor ⚠️
<details>
<summary><b>Why it matters? 🤔 </b></summary>
The new public response model exposes an internal integer dataset ID
alongside a UUID field. That matches the custom rule's concern about newly
added public API identifiers exposing internal integer IDs when a UUID public
identifier is being added.
</details>
[](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=d77fa0b8e5c644bf9c7594b11ce2c453&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
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<details>
<summary><b>Prompt for AI Agent 🤖 </b></summary>
```mdx
This is a comment left during a code review.
**Path:** superset/mcp_service/dashboard/schemas.py
**Line:** 1563:1564
**Comment:**
*Custom Rule: Remove the exposed integer dataset identifier from the
new dataset summary response and rely on the UUID field as the public
identifier.
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%2F40961&comment_hash=b33aac168b812ccb100b10f4784a468841c6777268a90815be0cf24b08509d59&reaction=like'>👍</a>
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href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F40961&comment_hash=b33aac168b812ccb100b10f4784a468841c6777268a90815be0cf24b08509d59&reaction=dislike'>👎</a>
##########
tests/unit_tests/mcp_service/dashboard/tool/test_get_dashboard_datasets.py:
##########
@@ -0,0 +1,355 @@
+# 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 MCP get_dashboard_datasets tool."""
+
+from unittest.mock import Mock, patch
+
+import pytest
+from fastmcp import Client
+
+from superset.mcp_service.app import mcp
+from superset.mcp_service.utils.sanitization import (
+ LLM_CONTEXT_CLOSE_DELIMITER,
+ LLM_CONTEXT_OPEN_DELIMITER,
+)
+from superset.utils import json
+
+
+def _wrapped(value: str) -> str:
+ return
f"{LLM_CONTEXT_OPEN_DELIMITER}\n{value}\n{LLM_CONTEXT_CLOSE_DELIMITER}"
+
+
+def _build_column_mock(
+ name: str,
+ *,
+ verbose_name: str | None = None,
+ type_: str | None = "VARCHAR",
+ is_dttm: bool = False,
+) -> Mock:
+ column = Mock()
+ column.column_name = name
+ column.verbose_name = verbose_name
+ column.type = type_
+ column.is_dttm = is_dttm
+ return column
+
+
+def _build_metric_mock(
+ name: str,
+ *,
+ verbose_name: str | None = None,
+ expression: str | None = None,
+) -> Mock:
+ metric = Mock()
+ metric.metric_name = name
+ metric.verbose_name = verbose_name
+ metric.expression = expression
+ return metric
+
+
+def _build_database_mock(
+ *, database_id: int = 7, name: str = "examples", backend: str =
"postgresql"
+) -> Mock:
+ database = Mock()
+ database.id = database_id
+ database.database_name = name
+ database.backend = backend
+ return database
+
+
+def _build_datasource_mock(
+ *,
+ dataset_id: int,
+ uuid: str | None = None,
+ table_name: str = "my_table",
+ schema: str | None = "public",
+ database: Mock | None = None,
+ columns: list[Mock] | None = None,
+ metrics: list[Mock] | None = None,
+) -> Mock:
+ datasource = Mock()
+ datasource.id = dataset_id
+ datasource.uuid = uuid
+ datasource.table_name = table_name
+ datasource.schema = schema
+ datasource.database = database
+ datasource.columns = columns or []
+ datasource.metrics = metrics or []
+ return datasource
+
+
+def _build_slice_mock(datasource: Mock) -> Mock:
+ slc = Mock()
+ slc.datasource_id = datasource.id
+ slc.datasource = datasource
+ return slc
Review Comment:
**Suggestion:** Add an inline docstring describing what this helper builds
and returns, since newly added functions should be documented. [custom_rule]
**Severity Level:** Minor ⚠️
<details>
<summary><b>Why it matters? 🤔 </b></summary>
This newly added helper function does not include a docstring. The custom
rule explicitly requires new Python functions and classes to be documented
inline, so the suggestion is valid.
</details>
[](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=c09131053f704981aab04fa92a31342e&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
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*(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/dashboard/tool/test_get_dashboard_datasets.py
**Line:** 96:100
**Comment:**
*Custom Rule: Add an inline docstring describing what this helper
builds and returns, since newly added functions should be documented.
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%2F40961&comment_hash=6fc094bc1cf3f91f4321a80517ea06e25ab2db4643ebae2d417e92ad5593881e&reaction=like'>👍</a>
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##########
tests/unit_tests/mcp_service/dashboard/tool/test_get_dashboard_datasets.py:
##########
@@ -0,0 +1,355 @@
+# 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 MCP get_dashboard_datasets tool."""
+
+from unittest.mock import Mock, patch
+
+import pytest
+from fastmcp import Client
+
+from superset.mcp_service.app import mcp
+from superset.mcp_service.utils.sanitization import (
+ LLM_CONTEXT_CLOSE_DELIMITER,
+ LLM_CONTEXT_OPEN_DELIMITER,
+)
+from superset.utils import json
+
+
+def _wrapped(value: str) -> str:
+ return
f"{LLM_CONTEXT_OPEN_DELIMITER}\n{value}\n{LLM_CONTEXT_CLOSE_DELIMITER}"
+
+
+def _build_column_mock(
+ name: str,
+ *,
+ verbose_name: str | None = None,
+ type_: str | None = "VARCHAR",
+ is_dttm: bool = False,
+) -> Mock:
+ column = Mock()
+ column.column_name = name
+ column.verbose_name = verbose_name
+ column.type = type_
+ column.is_dttm = is_dttm
+ return column
+
+
+def _build_metric_mock(
+ name: str,
+ *,
+ verbose_name: str | None = None,
+ expression: str | None = None,
+) -> Mock:
+ metric = Mock()
+ metric.metric_name = name
+ metric.verbose_name = verbose_name
+ metric.expression = expression
+ return metric
+
+
+def _build_database_mock(
+ *, database_id: int = 7, name: str = "examples", backend: str =
"postgresql"
+) -> Mock:
+ database = Mock()
+ database.id = database_id
+ database.database_name = name
+ database.backend = backend
+ return database
+
+
+def _build_datasource_mock(
+ *,
+ dataset_id: int,
+ uuid: str | None = None,
+ table_name: str = "my_table",
+ schema: str | None = "public",
+ database: Mock | None = None,
+ columns: list[Mock] | None = None,
+ metrics: list[Mock] | None = None,
+) -> Mock:
+ datasource = Mock()
+ datasource.id = dataset_id
+ datasource.uuid = uuid
+ datasource.table_name = table_name
+ datasource.schema = schema
+ datasource.database = database
+ datasource.columns = columns or []
+ datasource.metrics = metrics or []
+ return datasource
+
+
+def _build_slice_mock(datasource: Mock) -> Mock:
+ slc = Mock()
+ slc.datasource_id = datasource.id
+ slc.datasource = datasource
+ return slc
+
+
+def _build_dashboard_mock(
+ *,
+ dashboard_id: int = 1,
+ title: str = "Test Dashboard",
+ uuid: str | None = "dashboard-uuid-1",
+ slices: list[Mock] | None = None,
+) -> Mock:
+ dashboard = Mock()
+ dashboard.id = dashboard_id
+ dashboard.dashboard_title = title
+ dashboard.uuid = uuid
+ dashboard.slices = slices or []
+ return dashboard
+
+
[email protected]
+def mcp_server():
+ return mcp
+
+
[email protected](autouse=True)
Review Comment:
**Suggestion:** Add a return type annotation for this fixture (for example a
generator/yielding mock type) to satisfy full typing requirements for new
functions. [custom_rule]
**Severity Level:** Minor ⚠️
<details>
<summary><b>Why it matters? 🤔 </b></summary>
This newly added fixture function has no parameter or return type
annotations. Even though it yields a mock, the code still violates the rule
requiring new Python functions to be fully typed.
</details>
[](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=33cd18b8815f4d70a7370e1d23f348a5&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
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*(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/dashboard/tool/test_get_dashboard_datasets.py
**Line:** 123:123
**Comment:**
*Custom Rule: Add a return type annotation for this fixture (for
example a generator/yielding mock type) to satisfy full typing requirements for
new functions.
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%2F40961&comment_hash=184b6102ed61f99a8182108c149194f6d2920e9bd2ff336bbf54415ee5fb660c&reaction=like'>👍</a>
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##########
tests/unit_tests/mcp_service/dashboard/tool/test_get_dashboard_datasets.py:
##########
@@ -0,0 +1,355 @@
+# 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 MCP get_dashboard_datasets tool."""
+
+from unittest.mock import Mock, patch
+
+import pytest
+from fastmcp import Client
+
+from superset.mcp_service.app import mcp
+from superset.mcp_service.utils.sanitization import (
+ LLM_CONTEXT_CLOSE_DELIMITER,
+ LLM_CONTEXT_OPEN_DELIMITER,
+)
+from superset.utils import json
+
+
+def _wrapped(value: str) -> str:
+ return
f"{LLM_CONTEXT_OPEN_DELIMITER}\n{value}\n{LLM_CONTEXT_CLOSE_DELIMITER}"
+
+
+def _build_column_mock(
+ name: str,
+ *,
+ verbose_name: str | None = None,
+ type_: str | None = "VARCHAR",
+ is_dttm: bool = False,
+) -> Mock:
+ column = Mock()
+ column.column_name = name
+ column.verbose_name = verbose_name
+ column.type = type_
+ column.is_dttm = is_dttm
+ return column
+
+
+def _build_metric_mock(
+ name: str,
+ *,
+ verbose_name: str | None = None,
+ expression: str | None = None,
+) -> Mock:
+ metric = Mock()
+ metric.metric_name = name
+ metric.verbose_name = verbose_name
+ metric.expression = expression
+ return metric
+
+
+def _build_database_mock(
+ *, database_id: int = 7, name: str = "examples", backend: str =
"postgresql"
+) -> Mock:
+ database = Mock()
+ database.id = database_id
+ database.database_name = name
+ database.backend = backend
+ return database
+
+
+def _build_datasource_mock(
+ *,
+ dataset_id: int,
+ uuid: str | None = None,
+ table_name: str = "my_table",
+ schema: str | None = "public",
+ database: Mock | None = None,
+ columns: list[Mock] | None = None,
+ metrics: list[Mock] | None = None,
+) -> Mock:
+ datasource = Mock()
+ datasource.id = dataset_id
+ datasource.uuid = uuid
+ datasource.table_name = table_name
+ datasource.schema = schema
+ datasource.database = database
+ datasource.columns = columns or []
+ datasource.metrics = metrics or []
+ return datasource
+
+
+def _build_slice_mock(datasource: Mock) -> Mock:
+ slc = Mock()
+ slc.datasource_id = datasource.id
+ slc.datasource = datasource
+ return slc
+
+
+def _build_dashboard_mock(
+ *,
+ dashboard_id: int = 1,
+ title: str = "Test Dashboard",
+ uuid: str | None = "dashboard-uuid-1",
+ slices: list[Mock] | None = None,
+) -> Mock:
+ dashboard = Mock()
+ dashboard.id = dashboard_id
+ dashboard.dashboard_title = title
+ dashboard.uuid = uuid
+ dashboard.slices = slices or []
+ return dashboard
+
+
[email protected]
Review Comment:
**Suggestion:** Add an explicit return type annotation to this fixture so
the new function is fully typed. [custom_rule]
**Severity Level:** Minor ⚠️
<details>
<summary><b>Why it matters? 🤔 </b></summary>
This is a newly added Python function with no return type annotation. The
custom rule requires new Python code to be fully typed, so the suggestion
correctly identifies a real violation.
</details>
[](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=b1c7d96756d34224937a03152150bbd9&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=b1c7d96756d34224937a03152150bbd9&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/dashboard/tool/test_get_dashboard_datasets.py
**Line:** 118:118
**Comment:**
*Custom Rule: Add an explicit return type annotation to this fixture so
the new function is fully typed.
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%2F40961&comment_hash=79e425c9f499292233c7866f154a3a276853d7297ae38570a539fd7feec3dff1&reaction=like'>👍</a>
| <a
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F40961&comment_hash=79e425c9f499292233c7866f154a3a276853d7297ae38570a539fd7feec3dff1&reaction=dislike'>👎</a>
##########
tests/unit_tests/mcp_service/dashboard/tool/test_get_dashboard_datasets.py:
##########
@@ -0,0 +1,355 @@
+# 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 MCP get_dashboard_datasets tool."""
+
+from unittest.mock import Mock, patch
+
+import pytest
+from fastmcp import Client
+
+from superset.mcp_service.app import mcp
+from superset.mcp_service.utils.sanitization import (
+ LLM_CONTEXT_CLOSE_DELIMITER,
+ LLM_CONTEXT_OPEN_DELIMITER,
+)
+from superset.utils import json
+
+
+def _wrapped(value: str) -> str:
+ return
f"{LLM_CONTEXT_OPEN_DELIMITER}\n{value}\n{LLM_CONTEXT_CLOSE_DELIMITER}"
+
+
+def _build_column_mock(
+ name: str,
+ *,
+ verbose_name: str | None = None,
+ type_: str | None = "VARCHAR",
+ is_dttm: bool = False,
+) -> Mock:
+ column = Mock()
+ column.column_name = name
+ column.verbose_name = verbose_name
+ column.type = type_
+ column.is_dttm = is_dttm
+ return column
+
+
+def _build_metric_mock(
+ name: str,
+ *,
+ verbose_name: str | None = None,
+ expression: str | None = None,
+) -> Mock:
+ metric = Mock()
+ metric.metric_name = name
+ metric.verbose_name = verbose_name
+ metric.expression = expression
+ return metric
+
+
+def _build_database_mock(
+ *, database_id: int = 7, name: str = "examples", backend: str =
"postgresql"
+) -> Mock:
+ database = Mock()
+ database.id = database_id
+ database.database_name = name
+ database.backend = backend
+ return database
+
+
+def _build_datasource_mock(
+ *,
+ dataset_id: int,
+ uuid: str | None = None,
+ table_name: str = "my_table",
+ schema: str | None = "public",
+ database: Mock | None = None,
+ columns: list[Mock] | None = None,
+ metrics: list[Mock] | None = None,
+) -> Mock:
+ datasource = Mock()
+ datasource.id = dataset_id
+ datasource.uuid = uuid
+ datasource.table_name = table_name
+ datasource.schema = schema
+ datasource.database = database
+ datasource.columns = columns or []
+ datasource.metrics = metrics or []
+ return datasource
+
+
+def _build_slice_mock(datasource: Mock) -> Mock:
+ slc = Mock()
+ slc.datasource_id = datasource.id
+ slc.datasource = datasource
+ return slc
+
+
+def _build_dashboard_mock(
+ *,
+ dashboard_id: int = 1,
+ title: str = "Test Dashboard",
+ uuid: str | None = "dashboard-uuid-1",
+ slices: list[Mock] | None = None,
+) -> Mock:
+ dashboard = Mock()
+ dashboard.id = dashboard_id
+ dashboard.dashboard_title = title
+ dashboard.uuid = uuid
+ dashboard.slices = slices or []
+ return dashboard
+
+
[email protected]
+def mcp_server():
+ return mcp
+
+
[email protected](autouse=True)
+def mock_auth():
+ with patch("superset.mcp_service.auth.get_user_from_request") as
mock_get_user:
+ mock_user = Mock()
+ mock_user.id = 1
+ mock_user.username = "admin"
+ mock_get_user.return_value = mock_user
+ yield mock_get_user
+
+
[email protected](autouse=True)
+def mock_dataset_access():
+ with patch(
+ "superset.mcp_service.auth.has_dataset_access", return_value=True
+ ) as mock_access:
+ yield mock_access
+
+
+@patch("superset.daos.dashboard.DashboardDAO.find_by_id")
[email protected]
+async def test_get_dashboard_datasets_multiple_datasets(mock_find, mcp_server):
+ sales = _build_datasource_mock(
+ dataset_id=10,
+ uuid="dataset-uuid-10",
+ table_name="sales",
+ schema="public",
+ database=_build_database_mock(),
+ columns=[
+ _build_column_mock("region", verbose_name="Region"),
+ _build_column_mock("order_date", type_="TIMESTAMP", is_dttm=True),
+ ],
+ metrics=[
+ _build_metric_mock(
+ "total_revenue",
+ verbose_name="Total Revenue",
+ expression="SUM(revenue)",
+ )
+ ],
+ )
+ customers = _build_datasource_mock(
+ dataset_id=20,
+ uuid="dataset-uuid-20",
+ table_name="customers",
+ schema="crm",
+ database=_build_database_mock(database_id=8, name="crm_db",
backend="mysql"),
+ columns=[_build_column_mock("customer_name")],
+ metrics=[],
+ )
+ mock_find.return_value = _build_dashboard_mock(
+ slices=[
+ _build_slice_mock(sales),
+ _build_slice_mock(sales),
+ _build_slice_mock(customers),
+ ]
+ )
+
+ async with Client(mcp_server) as client:
+ result = await client.call_tool(
+ "get_dashboard_datasets", {"request": {"identifier": 1}}
+ )
+ data = json.loads(result.content[0].text)
+
+ assert data["id"] == 1
+ assert data["dashboard_title"] == _wrapped("Test Dashboard")
+ assert data["uuid"] == "dashboard-uuid-1"
+ assert data["dataset_count"] == 2
+ assert data["inaccessible_dataset_count"] == 0
+ assert len(data["datasets"]) == 2
+
+ datasets_by_id = {d["id"]: d for d in data["datasets"]}
+ sales_data = datasets_by_id[10]
+ assert sales_data["uuid"] == "dataset-uuid-10"
+ assert sales_data["table_name"] == "sales"
+ assert sales_data["schema"] == "public"
+ assert sales_data["database"] == {
+ "id": 7,
+ "name": "examples",
+ "backend": "postgresql",
+ }
+ assert sales_data["chart_count"] == 2
+ assert sales_data["columns"] == [
+ {
+ "column_name": "region",
+ "verbose_name": _wrapped("Region"),
+ "type": "VARCHAR",
+ "is_dttm": False,
+ },
+ {
+ "column_name": "order_date",
+ "verbose_name": None,
+ "type": "TIMESTAMP",
+ "is_dttm": True,
+ },
+ ]
+ assert sales_data["metrics"] == [
+ {
+ "metric_name": "total_revenue",
+ "verbose_name": _wrapped("Total Revenue"),
+ "expression": _wrapped("SUM(revenue)"),
+ }
+ ]
+ assert sales_data["total_column_count"] == 2
+ assert sales_data["total_metric_count"] == 1
+ assert sales_data["columns_truncated"] is False
+ assert sales_data["metrics_truncated"] is False
+
+ customers_data = datasets_by_id[20]
+ assert customers_data["table_name"] == "customers"
+ assert customers_data["schema"] == "crm"
+ assert customers_data["chart_count"] == 1
+ assert customers_data["metrics"] == []
+
+
+@patch("superset.daos.dashboard.DashboardDAO.find_by_id")
[email protected]
+async def test_get_dashboard_datasets_by_slug(mock_find, mcp_server):
+ datasource = _build_datasource_mock(
+ dataset_id=10,
+ table_name="sales",
+ database=_build_database_mock(),
+ columns=[_build_column_mock("region")],
+ )
+ dashboard = _build_dashboard_mock(slices=[_build_slice_mock(datasource)])
+
+ def find_by_id(identifier, id_column=None, query_options=None):
Review Comment:
**Suggestion:** Add parameter and return type annotations to this newly
introduced inner function to keep all new callable definitions fully typed.
[custom_rule]
**Severity Level:** Minor ⚠️
<details>
<summary><b>Why it matters? 🤔 </b></summary>
This is a newly introduced inner function with untyped parameters and no
return type annotation. That is a direct match for the custom typing rule.
</details>
[](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=d6645bcbdacd4611b8906502aa628e3b&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=d6645bcbdacd4611b8906502aa628e3b&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/dashboard/tool/test_get_dashboard_datasets.py
**Line:** 247:247
**Comment:**
*Custom Rule: Add parameter and return type annotations to this newly
introduced inner function to keep all new callable definitions fully typed.
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%2F40961&comment_hash=510b91d062b5b29c300ea9ffec386ad492b65a85d571df8aa59000125322bf83&reaction=like'>👍</a>
| <a
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F40961&comment_hash=510b91d062b5b29c300ea9ffec386ad492b65a85d571df8aa59000125322bf83&reaction=dislike'>👎</a>
##########
tests/unit_tests/mcp_service/dashboard/tool/test_get_dashboard_datasets.py:
##########
@@ -0,0 +1,355 @@
+# 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 MCP get_dashboard_datasets tool."""
+
+from unittest.mock import Mock, patch
+
+import pytest
+from fastmcp import Client
+
+from superset.mcp_service.app import mcp
+from superset.mcp_service.utils.sanitization import (
+ LLM_CONTEXT_CLOSE_DELIMITER,
+ LLM_CONTEXT_OPEN_DELIMITER,
+)
+from superset.utils import json
+
+
+def _wrapped(value: str) -> str:
+ return
f"{LLM_CONTEXT_OPEN_DELIMITER}\n{value}\n{LLM_CONTEXT_CLOSE_DELIMITER}"
+
+
+def _build_column_mock(
+ name: str,
+ *,
+ verbose_name: str | None = None,
+ type_: str | None = "VARCHAR",
+ is_dttm: bool = False,
+) -> Mock:
+ column = Mock()
+ column.column_name = name
+ column.verbose_name = verbose_name
+ column.type = type_
+ column.is_dttm = is_dttm
+ return column
+
+
+def _build_metric_mock(
+ name: str,
+ *,
+ verbose_name: str | None = None,
+ expression: str | None = None,
+) -> Mock:
+ metric = Mock()
+ metric.metric_name = name
+ metric.verbose_name = verbose_name
+ metric.expression = expression
+ return metric
+
+
+def _build_database_mock(
+ *, database_id: int = 7, name: str = "examples", backend: str =
"postgresql"
+) -> Mock:
+ database = Mock()
+ database.id = database_id
+ database.database_name = name
+ database.backend = backend
+ return database
+
+
+def _build_datasource_mock(
+ *,
+ dataset_id: int,
+ uuid: str | None = None,
+ table_name: str = "my_table",
+ schema: str | None = "public",
+ database: Mock | None = None,
+ columns: list[Mock] | None = None,
+ metrics: list[Mock] | None = None,
+) -> Mock:
+ datasource = Mock()
+ datasource.id = dataset_id
+ datasource.uuid = uuid
+ datasource.table_name = table_name
+ datasource.schema = schema
+ datasource.database = database
+ datasource.columns = columns or []
+ datasource.metrics = metrics or []
+ return datasource
+
+
+def _build_slice_mock(datasource: Mock) -> Mock:
+ slc = Mock()
+ slc.datasource_id = datasource.id
+ slc.datasource = datasource
+ return slc
+
+
+def _build_dashboard_mock(
+ *,
+ dashboard_id: int = 1,
+ title: str = "Test Dashboard",
+ uuid: str | None = "dashboard-uuid-1",
+ slices: list[Mock] | None = None,
+) -> Mock:
+ dashboard = Mock()
+ dashboard.id = dashboard_id
+ dashboard.dashboard_title = title
+ dashboard.uuid = uuid
+ dashboard.slices = slices or []
+ return dashboard
+
+
[email protected]
+def mcp_server():
+ return mcp
+
+
[email protected](autouse=True)
+def mock_auth():
+ with patch("superset.mcp_service.auth.get_user_from_request") as
mock_get_user:
+ mock_user = Mock()
+ mock_user.id = 1
+ mock_user.username = "admin"
+ mock_get_user.return_value = mock_user
+ yield mock_get_user
+
+
[email protected](autouse=True)
+def mock_dataset_access():
+ with patch(
+ "superset.mcp_service.auth.has_dataset_access", return_value=True
+ ) as mock_access:
+ yield mock_access
+
+
+@patch("superset.daos.dashboard.DashboardDAO.find_by_id")
[email protected]
+async def test_get_dashboard_datasets_multiple_datasets(mock_find, mcp_server):
Review Comment:
**Suggestion:** Add type annotations for the test function parameters and an
explicit `-> None` return annotation so the new function is fully typed.
[custom_rule]
**Severity Level:** Minor ⚠️
<details>
<summary><b>Why it matters? 🤔 </b></summary>
This new async test function has unannotated parameters and no explicit
return type. The rule requires newly added Python functions to be fully typed,
so this is a real violation.
</details>
[](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=958aa147cce649a897a4b52e284ece47&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=958aa147cce649a897a4b52e284ece47&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/dashboard/tool/test_get_dashboard_datasets.py
**Line:** 143:143
**Comment:**
*Custom Rule: Add type annotations for the test function parameters and
an explicit `-> None` return annotation so the new function is fully typed.
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%2F40961&comment_hash=92546a3951115947cc5ee89f5aa46f9543c15b79e84bc4873faecc66a629e0a4&reaction=like'>👍</a>
| <a
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F40961&comment_hash=92546a3951115947cc5ee89f5aa46f9543c15b79e84bc4873faecc66a629e0a4&reaction=dislike'>👎</a>
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