codeant-ai-for-open-source[bot] commented on code in PR #39898:
URL: https://github.com/apache/superset/pull/39898#discussion_r3192150614
##########
superset/mcp_service/dataset/schemas.py:
##########
@@ -93,6 +93,29 @@ class TableColumnInfo(BaseModel):
filterable: bool | None = Field(None, description="Is filterable")
description: str | None = Field(None, description="Column description")
+ @model_serializer(mode="wrap")
+ def _filter_column_fields_by_context(
+ self, serializer: Any, info: Any
+ ) -> Dict[str, Any]:
+ """Filter column fields based on serialization context.
+
+ If context contains 'column_fields', only include those fields.
+ Otherwise, include all fields. This trims wide datasets so a
+ 50-column dataset doesn't ship 50 long descriptions when the
+ caller only needs column_name + type.
+ """
+ data = serializer(self)
+
+ if info.context and isinstance(info.context, dict):
+ column_fields = info.context.get("column_fields")
+ if column_fields:
+ requested = set(column_fields)
+ # Always preserve column_name as the only required field
+ requested.add("column_name")
+ return {k: v for k, v in data.items() if k in requested}
Review Comment:
**Suggestion:** The column filtering check treats an explicitly provided
empty list as "no filter" and returns all column fields. This is a logic bug
because callers can pass `column_fields=[]` (or values that parse to an empty
list) and unexpectedly get verbose fields like `description` for every column,
which defeats the payload-size reduction and can reintroduce oversized
responses/timeouts. Handle empty lists as a valid filter input (e.g., still
enforce the minimal required field set) instead of falling back to full
serialization. [logic error]
<details>
<summary><b>Severity Level:</b> Critical 🚨</summary>
```mdx
- ❌ MCP `get_dataset_info` cannot honor explicit empty column_fields.
- ⚠️ Wide datasets may still return verbose per-column descriptions.
```
</details>
<details>
<summary><b>Steps of Reproduction ✅ </b></summary>
```mdx
1. In
`superset/tests/unit_tests/mcp_service/dataset/tool/test_dataset_tools.py:18-31`,
copy the pattern of `test_get_dataset_info_respects_column_fields` but
change the request
payload to use an empty list for `column_fields`:
`{"request": {"identifier": 3, "select_columns": ["id", "columns"],
"column_fields":
[]}}`.
2. This request is validated into `GetDatasetInfoRequest` in
`superset/mcp_service/dataset/schemas.py:172-221`; the
`@field_validator("column_fields")`
calls `parse_json_or_list` (see `schema_utils.py:111-151`), which returns
`[]` unchanged
for a Python list, so `request.column_fields` is an empty list, not `None`.
3. The MCP tool handler `get_dataset_info` in
`superset/mcp_service/dataset/tool/get_dataset_info.py:21-27` fetches a
`DatasetInfo`
instance, then at lines 119-126 calls `result.model_dump(...,
context={"select_columns":
request.select_columns, "column_fields": request.column_fields})`, so
`info.context["column_fields"]` is `[]` for this call.
4. During serialization, each `TableColumnInfo` is processed by
`_filter_column_fields_by_context` in
`superset/mcp_service/dataset/schemas.py:27-48`;
`info.context` is a dict and `column_fields` is `[]`, so the `if
column_fields:` check at
lines 40-42 evaluates false and the method returns `data` unfiltered at line
48, including
verbose fields like `description`, `groupby`, `filterable`, etc. This
contradicts the
request's explicit `column_fields=[]` and re-expands column payloads,
undermining the PR's
goal of trimming oversized responses.
```
</details>
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ation.%0A%0AValidate%20the%20correctness%20of%20the%20flagged%20issue.%20If%20correct%2C%20How%20can%20I%20resolve%20this%3F%20If%20you%20propose%20a%20fix%2C%20implement%20it%20and%20please%20make%20it%20concise.%0AOnce%20fix%20is%20implemented%2C%20also%20check%20other%20comments%20on%20the%20same%20PR%2C%20and%20ask%20user%20if%20the%20user%20wants%20to%20fix%20the%20rest%20of%20the%20comments%20as%20well.%20if%20said%20yes%2C%20then%20fetch%20all%20the%20comments%20validate%20the%20correctness%20and%20implement%20a%20minimal%20fix%0A)
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lds.%20This%20is%20a%20logic%20bug%20because%20callers%20can%20pass%20%60column_fields%3D%5B%5D%60%20%28or%20values%20that%20parse%20to%20an%20empty%20list%29%20and%20unexpectedly%20get%20verbose%20fields%20like%20%60description%60%20for%20every%20column%2C%20which%20defeats%20the%20payload-size%20reduction%20and%20can%20reintroduce%20oversized%20responses%2Ftimeouts.%20Handle%20empty%20lists%20as%20a%20valid%20filter%20input%20%28e.g.%2C%20still%20enforce%20the%20minimal%20required%20field%20set%29%20instead%20of%20falling%20back%20to%20full%20serialization.%0A%0AValidate%20the%20correctness%20of%20the%20flagged%20issue.%20If%20correct%2C%20How%20can%20I%20resolve%20this%3F%20If%20you%20propose%20a%20fix%2C%20implement%20it%20and%20please%20make%20it%20concise.%0AOnce%20fix%20is%20implemented%2C%20also%20check%20other%20comments%20on%20the%20same%20PR%2C%20and%20ask%20user%20if%20the%20user%20wants%20to%20fix%20the%20rest%20of%20the%20comments%20as%20well.%20if%20said%20yes%2C%20th
en%20fetch%20all%20the%20comments%20validate%20the%20correctness%20and%20implement%20a%20minimal%20fix%0A)
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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/dataset/schemas.py
**Line:** 109:115
**Comment:**
*Logic Error: The column filtering check treats an explicitly provided
empty list as "no filter" and returns all column fields. This is a logic bug
because callers can pass `column_fields=[]` (or values that parse to an empty
list) and unexpectedly get verbose fields like `description` for every column,
which defeats the payload-size reduction and can reintroduce oversized
responses/timeouts. Handle empty lists as a valid filter input (e.g., still
enforce the minimal required field set) instead of falling back to full
serialization.
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>
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