Resolving next-pylint 4.0.5 issues for azure-ai-ml sdk and updating s…

.github/skills/ml/fix-pylint/SKILL.md

@@ -7,6 +7,8 @@ description: Automatically fix pylint issues in azure-ai-ml package following Az
 
 This skill automatically fixes pylint warnings in the azure-ai-ml package by analyzing existing code patterns and applying fixes with 100% confidence based on GitHub issues.
 
+> **Scope:** Fix **only mandatory/blocking issues** — warnings that will cause CI to fail. Leave optional/informational warnings as-is.
+
 ## Overview
 
 Intelligently fixes pylint issues by:
@@ -19,12 +21,11 @@ Intelligently fixes pylint issues by:
 7. Searching codebase for existing patterns to follow
 8. Applying fixes only with 100% confidence
 9. Re-running pylint to verify fixes
-10. Creating a pull request that references the GitHub issue
-11. Providing a summary of what was fixed
+10. Providing a summary of what was fixed
 
 ## Running Pylint
 
-**Command for entire package:**
+**Command for entire package (tox):**
 ```powershell
 cd sdk/ml/azure-ai-ml
 tox -e pylint --c ../../../eng/tox/tox.ini --root .
@@ -146,6 +147,8 @@ Use the existing code patterns to ensure consistency.
 
 ### Step 7: Apply Fixes (ONLY if 100% confident)
 
+> **Fix only mandatory/blocking issues.** Skip optional or informational warnings that do not cause CI failure.
+
 **ALLOWED ACTIONS:**
  Fix warnings with 100% confidence
  Use existing file patterns as reference
@@ -161,14 +164,14 @@ Use the existing code patterns to ensure consistency.
  Change code style without clear reason
  Delete code without clear justification
 
-### Step 7: Verify Fixes
+### Step 8: Verify Fixes
 
 Re-run pylint to ensure:
 - The warning is resolved
 - No new warnings were introduced
 - The code still functions correctly
 
-### Step 8: Summary
+### Step 9: Summary
 
 Provide a summary:
 - GitHub issue being addressed
@@ -177,67 +180,6 @@ Provide a summary:
 - Types of fixes applied
 - Any warnings that need manual review
 
-### Step 9: Create Pull Request
-
-After successfully fixing pylint issues, create a pull request:
-
-**Stage and commit the changes:**
-```powershell
-# Stage all modified files
-git add .
-
-# Create a descriptive commit message referencing the issue
-git commit -m "fix(azure-ai-ml): resolve pylint warnings (#<issue-number>)
-
-- Fixed <list specific types of warnings>
-- Updated <files/modules affected>
-- All pylint checks now pass
-
-Closes #<issue-number>"
-```
-
-**Create pull request using GitHub CLI or MCP server:**
-
-Option 1 - Using GitHub CLI (if available):
-```powershell
-# Create a new branch
-$branchName = "fix/azure-ai-ml-pylint-<issue-number>"
-git checkout -b $branchName
-
-# Push the branch
-git push origin $branchName
-
-# Create PR using gh CLI
-gh pr create `
-  --title "fix(azure-ai-ml): Resolve pylint warnings (#<issue-number>)" `
-  --body "## Description
-This PR fixes pylint warnings in the azure-ai-ml package as reported in #<issue-number>.
-
-## Changes
-- Fixed pylint warnings following Azure SDK Python guidelines
-- Ensured consistency with existing code patterns
-- Targeted fixes for: <specific files/modules from issue>
-- All pylint checks now pass for the affected areas
-
-## Testing
-- [x] Ran pylint on affected files and verified all warnings are resolved
-- [x] No new warnings introduced
-- [x] Verified fixes follow existing code patterns
-
-## Related Issues
-Fixes #<issue-number>" `
-  --base main `
-  --repo Azure/azure-sdk-for-python
-```
-
-Option 2 - Manual PR creation (if GitHub CLI not available):
-1. Push branch: `git push origin <branch-name>`
-2. Navigate to: https://github.com/Azure/azure-sdk-for-python/compare/main...<branch-name>
-3. Create the pull request manually with the description above
-
-Option 3 - Using GitHub MCP server (if available):
-Use the GitHub MCP tools to create a pull request programmatically against the Azure/azure-sdk-for-python repository, main branch.
-
 ## Common Pylint Issues and Fixes
 
 ### Missing Docstrings
@@ -302,28 +244,14 @@ tox -e pylint --c ../../../eng/tox/tox.ini --root . -- $targetFile
 # Cross-reference with GitHub issue #12345
 
 # 5. Search for existing patterns in codebase
-grep -r "similar_pattern" azure/ai/ml/
+Get-ChildItem -Recurse azure/ai/ml/ | Select-String "similar_pattern"
 
 # 6. Apply fixes to identified files
 
 # 7. Re-run pylint to verify
 tox -e pylint --c ../../../eng/tox/tox.ini --root . -- $targetFile
 
 # 8. Report results
-
-# 9. Create PR referencing the issue
-$branchName = "fix/azure-ai-ml-pylint-12345"
-git checkout -b $branchName
-git add .
-git commit -m "fix(azure-ai-ml): resolve pylint warnings (#12345)
-
-Closes #12345"
-git push origin $branchName
-gh pr create `
-  --title "fix(azure-ai-ml): Resolve pylint warnings (#12345)" `
-  --body "Fixes #12345" `
-  --base main `
-  --repo Azure/azure-sdk-for-python
 ```
 
 ## Notes
@@ -333,4 +261,3 @@ gh pr create `
 - If unsure about a fix, mark it for manual review
 - Some warnings may require architectural changes - don't force fixes
 - Test the code after fixing to ensure functionality is preserved
-- Always reference the GitHub issue in commits and PRs

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_autogen_entities/_model_base.py

@@ -683,9 +683,13 @@ def _get_deserialize_callable_from_annotation(  # pylint: disable=R0911
 
     # is it optional?
     try:
-        if any(a for a in annotation.__args__ if a == type(None)):  # pyright: ignore
+        if any(
+            a for a in annotation.__args__ if a == type(None)
+        ):  # pyright: ignore  # pylint: disable=unidiomatic-typecheck
             if_obj_deserializer = _get_deserialize_callable_from_annotation(
-                next(a for a in annotation.__args__ if a != type(None)), module, rf  # pyright: ignore
+                next(a for a in annotation.__args__ if a != type(None)),
+                module,
+                rf,  # pyright: ignore  # pylint: disable=unidiomatic-typecheck
             )
 
             return functools.partial(_deserialize_with_optional, if_obj_deserializer)

sdk/ml/azure-ai-ml/azure/ai/ml/operations/_deployment_template_operations.py

@@ -91,7 +91,7 @@ def _get_registry_endpoint(self) -> str:
                     return f"https://{region}.api.azureml.ms"
 
         except Exception as e:
-            module_logger.warning("Could not determine registry region dynamically: %s. Using default.", e)
+            module_logger.debug("Could not determine registry region dynamically: %s. Using default.", e)
 
         # Fallback to default region if unable to determine dynamically
         return f"https://int.experiments.azureml-test.net"
@@ -337,7 +337,7 @@ def get(self, name: str, version: Optional[str] = None, **kwargs: Any) -> Deploy
             )
             return DeploymentTemplate._from_rest_object(result)
         except Exception as e:
-            module_logger.warning("DeploymentTemplate get operation failed: %s", e)
+            module_logger.debug("DeploymentTemplate get operation failed: %s", e)
             raise ResourceNotFoundError(f"DeploymentTemplate {name}:{version} not found") from e
 
     @distributed_trace
@@ -351,31 +351,27 @@ def create_or_update(self, deployment_template: DeploymentTemplate, **kwargs: An
         :return: DeploymentTemplate object representing the created or updated resource.
         :rtype: ~azure.ai.ml.entities.DeploymentTemplate
         """
-        try:
-            # Ensure we have a DeploymentTemplate object
-            if not isinstance(deployment_template, DeploymentTemplate):
-                raise ValueError("deployment_template must be a DeploymentTemplate object")
+        # Ensure we have a DeploymentTemplate object
+        if not isinstance(deployment_template, DeploymentTemplate):
+            raise ValueError("deployment_template must be a DeploymentTemplate object")
 
-            if hasattr(self._service_client, "deployment_templates"):
-                endpoint = self._get_registry_endpoint()
+        if hasattr(self._service_client, "deployment_templates"):
+            endpoint = self._get_registry_endpoint()
 
-                rest_object = deployment_template._to_rest_object()
-                self._service_client.deployment_templates.begin_create(
-                    endpoint=endpoint,
-                    subscription_id=self._operation_scope.subscription_id,
-                    resource_group_name=self._operation_scope.resource_group_name,
-                    registry_name=self._operation_scope.registry_name,
-                    name=deployment_template.name,
-                    version=deployment_template.version,
-                    body=rest_object,
-                    **kwargs,
-                )
-                return deployment_template
-            else:
-                raise RuntimeError("DeploymentTemplate service not available")
-        except Exception as e:
-            module_logger.error("DeploymentTemplate create_or_update operation failed: %s", e)
-            raise
+            rest_object = deployment_template._to_rest_object()
+            self._service_client.deployment_templates.begin_create(
+                endpoint=endpoint,
+                subscription_id=self._operation_scope.subscription_id,
+                resource_group_name=self._operation_scope.resource_group_name,
+                registry_name=self._operation_scope.registry_name,
+                name=deployment_template.name,
+                version=deployment_template.version,
+                body=rest_object,
+                **kwargs,
+            )
+            return deployment_template
+        else:
+            raise RuntimeError("DeploymentTemplate service not available")
 
     @distributed_trace
     @monitor_with_telemetry_mixin(ops_logger, "DeploymentTemplate.Delete", ActivityType.PUBLICAPI)
@@ -407,7 +403,7 @@ def delete(self, name: str, version: Optional[str] = None, **kwargs: Any) -> Non
         except ResourceNotFoundError:
             raise
         except Exception as e:
-            module_logger.error("DeploymentTemplate delete operation failed: %s", e)
+            module_logger.debug("DeploymentTemplate delete operation failed: %s", e)
             raise
 
     @distributed_trace
@@ -423,18 +419,14 @@ def archive(self, name: str, version: Optional[str] = None, **kwargs: Any) -> De
         :rtype: ~azure.ai.ml.entities.DeploymentTemplate
         :raises: ~azure.core.exceptions.ResourceNotFoundError if deployment template not found.
         """
-        try:
-            # Get the existing template
-            template = self.get(name=name, version=version, **kwargs)
+        # Get the existing template
+        template = self.get(name=name, version=version, **kwargs)
 
-            # Set stage to Archived
-            template.stage = "Archived"
+        # Set stage to Archived
+        template.stage = "Archived"
 
-            # Update the template using create_or_update
-            return self.create_or_update(template, **kwargs)
-        except Exception as e:
-            module_logger.error("DeploymentTemplate archive operation failed: %s", e)
-            raise
+        # Update the template using create_or_update
+        return self.create_or_update(template, **kwargs)
 
     @distributed_trace
     @monitor_with_telemetry_mixin(ops_logger, "DeploymentTemplate.Restore", ActivityType.PUBLICAPI)
@@ -449,15 +441,11 @@ def restore(self, name: str, version: Optional[str] = None, **kwargs: Any) -> De
         :rtype: ~azure.ai.ml.entities.DeploymentTemplate
         :raises: ~azure.core.exceptions.ResourceNotFoundError if deployment template not found.
         """
-        try:
-            # Get the existing template
-            template = self.get(name=name, version=version, **kwargs)
+        # Get the existing template
+        template = self.get(name=name, version=version, **kwargs)
 
-            # Set stage to Development
-            template.stage = "Development"
+        # Set stage to Development
+        template.stage = "Development"
 
-            # Update the template using create_or_update
-            return self.create_or_update(template, **kwargs)
-        except Exception as e:
-            module_logger.error("DeploymentTemplate restore operation failed: %s", e)
-            raise
+        # Update the template using create_or_update
+        return self.create_or_update(template, **kwargs)

sdk/ml/azure-ai-ml/tests/batch_services/e2etests/test_batch_endpoint.py

@@ -34,7 +34,7 @@ def test_batch_endpoint_create(self, client: MLClient, rand_batch_name: Callable
         try:
             client.batch_endpoints.get(name=name)
         except Exception as e:
-            assert type(e) is ResourceNotFoundError
+            assert isinstance(e, ResourceNotFoundError)
             return
 
         raise Exception(f"Batch endpoint {name} is supposed to be deleted.")
@@ -62,7 +62,7 @@ def test_mlflow_batch_endpoint_create_and_update(
         try:
             client.batch_endpoints.get(name=name)
         except Exception as e:
-            assert type(e) is ResourceNotFoundError
+            assert isinstance(e, ResourceNotFoundError)
             return
 
         raise Exception(f"Batch endpoint {name} is supposed to be deleted.")

sdk/ml/azure-ai-ml/tests/connection/e2etests/test_connections.py

@@ -256,7 +256,7 @@ def test_workspace_connections_create_update_and_delete_ai_search(
         wps_connection = client.connections.create_or_update(workspace_connection=wps_connection)
         client.connections.delete(name=wps_connection_name)
 
-        assert type(wps_connection) == AzureAISearchConnection
+        assert isinstance(wps_connection, AzureAISearchConnection)
         assert wps_connection.name == wps_connection_name
         assert wps_connection.credentials.type == camel_to_snake(ConnectionAuthType.API_KEY)
         # assert wps_connection.api_key == "3333" # TODO add api key retrieval everywhere