codeant-ai-for-open-source[bot] commented on code in PR #36805:
URL: https://github.com/apache/superset/pull/36805#discussion_r2693166969
##########
superset/db_engine_specs/couchbase.py:
##########
@@ -86,6 +87,34 @@ class CouchbaseEngineSpec(BasicParametersMixin,
BaseEngineSpec):
)
parameters_schema = CouchbaseParametersSchema()
+ metadata = {
+ "description": (
+ "Couchbase is a distributed NoSQL document database with SQL++
support."
+ ),
+ "logo": "couchbase.png",
+ "homepage_url": "https://www.couchbase.com/";,
+ "category": DatabaseCategory.SEARCH_NOSQL,
+ "pypi_packages": ["couchbase-sqlalchemy"],
+ "connection_string":
"couchbase://{username}:{password}@{host}:{port}?ssl=true",
+ "default_port": 8091,
+ "parameters": {
+ "username": "Couchbase username",
+ "password": "Couchbase password",
+ "host": "Couchbase host or connection string for cloud",
+ "port": "Couchbase port (default 8091)",
+ },
Review Comment:
**Suggestion:** The Couchbase metadata `parameters` list omits the required
`database` field even though `validate_parameters` requires `"database"` to be
present, so the generated documentation will not mention a mandatory parameter
and can mislead users into configuring incomplete connection details. [logic
error]
<details>
<summary><b>Severity Level:</b> Critical 🚨</summary>
```mdx
- ❌ Users misled by docs, causing connection validation errors.
- ⚠️ Generated docs out-of-sync with runtime validation.
```
</details>
```suggestion
"database": "Couchbase bucket or database name",
```
<details>
<summary><b>Steps of Reproduction ✅ </b></summary>
```mdx
1. Open superset/db_engine_specs/couchbase.py and locate the metadata
"parameters" mapping
(PR hunk shows it starting at line 100). The mapping currently lists
username, password,
host, port — it omits "database".
2. Inspect CouchbaseEngineSpec.validate_parameters (present in the same
file) which builds
required = {"host", "username", "password", "database"} and checks for
missing required
parameters. This function is defined in this file and will flag "database"
as required at
runtime when validating connection properties.
3. Run the docs generator (docs/scripts/generate-database-docs.mjs) which
uses
metadata["parameters"] to document required/optional connection fields.
Because "database"
is omitted in metadata (lines 100-105), the generated docs won't indicate
that "database"
is required.
4. Create a connection guided by the generated docs (e.g., follow the MDX
page for
Couchbase). The docs will not instruct the user to provide "database",
leading them to
configure a connection missing the database/bucket name. When Superset later
attempts to
validate connection properties (which calls
CouchbaseEngineSpec.validate_parameters in
this file), the validation will produce a missing-parameter warning/error
referencing
"database", causing confusion and a mismatch between docs and runtime
validation.
Note: This reproduction traces the exact code paths: metadata used by the
docs generator
(superset/db_engine_specs/couchbase.py:100-105) and runtime validation in
CouchbaseEngineSpec.validate_parameters within the same module.
```
</details>
<details>
<summary><b>Prompt for AI Agent 🤖 </b></summary>
```mdx
This is a comment left during a code review.
**Path:** superset/db_engine_specs/couchbase.py
**Line:** 105:105
**Comment:**
*Logic Error: The Couchbase metadata `parameters` list omits the
required `database` field even though `validate_parameters` requires
`"database"` to be present, so the generated documentation will not mention a
mandatory parameter and can mislead users into configuring incomplete
connection details.
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.
```
</details>
##########
superset/db_engine_specs/gsheets.py:
##########
@@ -103,6 +104,23 @@ class GSheetsEngineSpec(ShillelaghEngineSpec):
default_driver = "apsw"
sqlalchemy_uri_placeholder = "gsheets://"
+ metadata = {
+ "description": (
+ "Google Sheets allows querying spreadsheets as SQL tables "
+ "via shillelagh."
+ ),
+ "logo": "gsheets.png",
+ "homepage_url": "https://www.google.com/sheets/about/";,
+ "category": DatabaseCategory.CLOUD_GOOGLE,
Review Comment:
**Suggestion:** The `category` field in the `metadata` dict uses
`DatabaseCategory.CLOUD_GOOGLE`, but `DatabaseCategory` only defines
`CLOUD_GCP`, so this will raise an `AttributeError` when the module is imported
and prevent Superset from starting. [logic error]
<details>
<summary><b>Severity Level:</b> Critical 🚨</summary>
```mdx
- ❌ Superset process fails during startup/import.
- ❌ Webserver/worker cannot load DB engine specs.
- ❌ CLI commands importing engine specs error.
- ⚠️ Docs generation that imports engine specs may fail.
```
</details>
```suggestion
"category": DatabaseCategory.CLOUD_GCP,
```
<details>
<summary><b>Steps of Reproduction ✅ </b></summary>
```mdx
1. Ensure the repository is checked out with the PR changes applied (the
final file state
includes `superset/db_engine_specs/gsheets.py`).
2. Start a Python REPL or import the package that loads DB engine specs,
e.g. run: `python
-c "import superset.db_engine_specs.gsheets"` from the repository root. This
attempts to
import `gsheets.py` which references DatabaseCategory.
3. During import, `gsheets.py` executes the module-level assignment of
`metadata` which
contains the line at `superset/db_engine_specs/gsheets.py:114` ("category":
DatabaseCategory.CLOUD_GOOGLE,).
4. Python resolves `DatabaseCategory` from
`superset/db_engine_specs/base.py`. The class
`DatabaseCategory` in `superset/db_engine_specs/base.py` (see lines 190-199)
defines
`CLOUD_GCP` but does not define `CLOUD_GOOGLE`. A read of
`superset/db_engine_specs/base.py:196-199` shows `CLOUD_GCP = "Cloud -
Google"`.
5. Because `CLOUD_GOOGLE` is not an attribute on `DatabaseCategory`,
attempting to access
`DatabaseCategory.CLOUD_GOOGLE` raises AttributeError at import time, e.g.
"AttributeError: type object 'DatabaseCategory' has no attribute
'CLOUD_GOOGLE'".
6. Observed outcome: import fails immediately and the process that attempted
the import
(webserver, CLI, or docs generation that imports engine specs) crashes
before completing
initialization.
Note: This reproduction uses concrete file locations and line numbers
discovered via code
inspection: `gsheets.py:114` (the problematic metadata line) and
`base.py:190-199`
(DatabaseCategory definition).
```
</details>
<details>
<summary><b>Prompt for AI Agent 🤖 </b></summary>
```mdx
This is a comment left during a code review.
**Path:** superset/db_engine_specs/gsheets.py
**Line:** 114:114
**Comment:**
*Logic Error: The `category` field in the `metadata` dict uses
`DatabaseCategory.CLOUD_GOOGLE`, but `DatabaseCategory` only defines
`CLOUD_GCP`, so this will raise an `AttributeError` when the module is imported
and prevent Superset from starting.
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.
```
</details>
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