Fix Pylint

Fix Pylint Issues Skill

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:

• Getting the GitHub issue URL from the user
• Reading and analyzing the issue details
• Setting up or using existing virtual environment
• Installing required dependencies
• Running pylint on the specific files/areas mentioned in the issue
• Analyzing the pylint output to identify warnings
• Searching codebase for existing patterns to follow
• Applying fixes only with 100% confidence
• Re-running pylint to verify fixes

10. Providing a summary of what was fixed

Running Pylint

Command:

cd sdk/ml/azure-ai-ml
azpysdk pylint .

> Note: azpysdk runs at the package level only. To focus on specific files, run the full check and filter the output by file path.

Reference Documentation

• Azure SDK Python Pylint Guidelines
• Official Pylint Documentation
• Azure SDK Python Pylint Guide
• Tool Usage Guide

Fixing Strategy

Step 0: Get GitHub Issue Details

Check if user provided in their request:

• GitHub issue URL (look for https://github.com/Azure/azure-sdk-for-python/issues/... in user's message)
• Virtual environment path (look for phrases like "using venv", "use env", "virtual environment at", or just the venv name)

If GitHub issue URL is missing:

Ask: "Please provide the GitHub issue URL for the pylint problems you want to fix."

If virtual environment is missing:

Ask: "Do you have an existing virtual environment path, or should I create 'env'?"

Once you have the issue URL:

Read the issue to understand which files/modules and specific warnings to fix.

Step 1: CRITICAL - Activate Virtual Environment FIRST

IMMEDIATELY activate the virtual environment before ANY other command:

# Activate the provided virtual environment (e.g., envml, env, venv)
.\<venv-name>\Scripts\Activate.ps1

# If creating new virtual environment:
python -m venv env
.\env\Scripts\Activate.ps1

⚠️ IMPORTANT: ALL subsequent commands MUST run within the activated virtual environment. Never run commands outside the venv.

Step 2: Install Dependencies (within activated venv)

# Navigate to azure-ai-ml directory (within activated venv)
cd sdk/ml/azure-ai-ml

# Install dev dependencies from dev_requirements.txt (within activated venv)
pip install -r dev_requirements.txt

# Install the package in editable mode (within activated venv)
pip install -e .

Step 3: Identify Target Files (within activated venv)

Based on the GitHub issue details, determine which files to check:

Option A - Run pylint on the package and filter output:

# Ensure you're in azure-ai-ml directory (within activated venv)
cd sdk/ml/azure-ai-ml

# Run pylint on the full package, then filter output for files from the issue
azpysdk pylint .
# Review output for warnings in the specific files/modules mentioned in the issue

Option B - Check modified files (if no specific target):

git diff --name-only HEAD | Select-String "sdk/ml/azure-ai-ml"
git diff --cached --name-only | Select-String "sdk/ml/azure-ai-ml"

Step 4: Run Pylint (within activated venv)

⚠️ Ensure virtual environment is still activated before running:

# Navigate to azure-ai-ml directory
cd sdk/ml/azure-ai-ml

# Run pylint on the package (within activated venv)
azpysdk pylint .
# Filter output for the specific files/modules from the issue

Step 5: Analyze Warnings

Parse the pylint output to identify:

• Warning type and code (e.g., C0103, W0212, R0913)
• File path and line number
• Specific issue description
• Cross-reference with the GitHub issue to ensure you're fixing the right problems

Step 6: Search for Existing Patterns

Before fixing, search the codebase for how similar issues are handled:

# Example: Search for similar function patterns
grep -r "pattern" sdk/ml/azure-ai-ml/

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

Follow Azure SDK Python guidelines

Make minimal, targeted changes

FORBIDDEN ACTIONS:

Fix warnings without complete confidence

Create new files for solutions

Import non-existent modules

Add new dependencies or imports

Make unnecessary large changes

Change code style without clear reason

Delete code without clear justification

Step 8: Verify Fixes

Re-run pylint to ensure:

• The warning is resolved
• No new warnings were introduced
• The code still functions correctly

Step 9: Summary

Provide a summary:

• GitHub issue being addressed
• Number of warnings fixed
• Number of warnings remaining
• Types of fixes applied
• Any warnings that need manual review

Common Pylint Issues and Fixes

Missing Docstrings

Warning: C0111: Missing module/function/class docstring

Fix: Add proper docstring following Azure SDK style:

def function_name(param: str) -> None:
    """Brief description of function.
    
    :param param: Description of parameter
    :type param: str
    :return: None
    """

Too Many Arguments

Warning: R0913: Too many arguments

Fix: Consider grouping related parameters into a configuration object or using keyword-only arguments.

Line Too Long

Warning: C0301: Line too long

Fix: Break line at logical points following PEP 8 style.

Unused Import

Warning: W0611: Unused import

Fix: Remove the unused import statement.

Invalid Name

Warning: C0103: Invalid name

Fix: Rename to follow snake_case for functions/variables, PascalCase for classes.

Example Workflow

# 0. Get issue details
# User provides: https://github.com/Azure/azure-sdk-for-python/issues/12345
# Issue mentions: pylint warnings in azure/ai/ml/operations/job_operations.py

# 1. CRITICAL - Activate virtual environment FIRST
.\<venv-name>\Scripts\Activate.ps1  # Use the venv name provided by user
cd sdk/ml/azure-ai-ml
pip install -r dev_requirements.txt
pip install -e .

# 2. Identify target from issue
$targetFile = "azure/ai/ml/operations/job_operations.py"

# 3. Run pylint on the package and check output for target file
azpysdk pylint .
# Filter output for warnings in $targetFile

# 4. Analyze output and identify fixable issues
# Cross-reference with GitHub issue #12345

# 5. Search for existing patterns in codebase
Get-ChildItem -Recurse azure/ai/ml/ | Select-String "similar_pattern"

# 6. Apply fixes to identified files

# 7. Re-run pylint to verify
azpysdk pylint .

# 8. Report results

Notes

• Always read the existing code to understand patterns before making changes
• Prefer following existing patterns over strict rule compliance
• 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