Pylint 3.3.6 updates [azure-ai-ml]

[PratibhaShrivastav18]

Description

Compatible with pylint 3.3.6

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All SDK Contribution checklist:

• The pull request does not introduce [breaking changes]
• CHANGELOG is updated for new features, bug fixes or other significant changes.
• I have read the contribution guidelines.

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• Title of the pull request is clear and informative.
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Testing Guidelines

• Pull request includes test coverage for the included changes.

[Copilot]

Pull Request Overview

This PR updates logging in several modules to improve clarity and consistency when handling exceptions with pylint 3.3.6.

• Standardizes exception logging by separating concise user‐facing messages and detailed debug logs.
• Removes exception interpolation from warning/error logs in favor of dedicated debug logging.

Reviewed Changes

Copilot reviewed 6 out of 6 changed files in this pull request and generated 6 comments.

Show a summary per file

File	Description
sdk/ml/azure-ai-ml/azure/ai/ml/operations/_workspace_operations_base.py	Updates logging for duration errors by splitting warning and debug logs.
sdk/ml/azure-ai-ml/azure/ai/ml/operations/_component_operations.py	Splits exception log messages into info/error and debug logs for more consistent logging.
sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/job.py	Changes exception logging level from info to debug and adds an info log for failure.
sdk/ml/azure-ai-ml/azure/ai/ml/_utils/_artifact_utils.py	Updates artifact tool path logging to separate warning and debug details.
sdk/ml/azure-ai-ml/azure/ai/ml/_azure_environments.py	Refines logging messages by removing exception details from warnings and adding debug logs.
sdk/ml/azure-ai-ml/azure/ai/ml/_arm_deployments/arm_deployment_executor.py	Updates polling exception logging to display exception type only in the debug log.

Comments suppressed due to low confidence (2)

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/job.py:337

• [nitpick] Check if lowering the logging level for exceptions might obscure error context during parsing issues; ensure that the operational logging configuration captures sufficient details.

module_logger.debug("Exception: %s.\n%s\nUnable to parse the job resource: %s.\n",

sdk/ml/azure-ai-ml/azure/ai/ml/_azure_environments.py:301

• [nitpick] Verify that removing the exception details from the warning log does not hinder troubleshooting connectivity or configuration issues in certain environments.

module_logger.warning("Error: Azure ML was unable to load cloud metadata from the metadata url.")