Python Code Review

Conduct thorough code reviews for Python projects.

Quick Start

When reviewing Python code:

1. •Read the code to understand its purpose
2. •Check against the review checklist
3. •Provide categorized feedback
4. •Suggest specific improvements

Review Checklist

Code Quality

• • Functions are focused and appropriately sized (< 50 lines ideal)
• • Variable names are descriptive and follow snake_case
• • No magic numbers (use named constants)
• • DRY principle followed (no code duplication)
• • Appropriate use of list comprehensions vs loops

Type Safety

• • Type hints on function signatures
• • Complex types use typing module appropriately
• • Optional values handled with Optional[T] or T | None

Error Handling

• • Exceptions are specific (not bare except:)
• • Errors are logged appropriately
• • Resources cleaned up (use context managers)
• • Graceful degradation where appropriate

Security

• • No hardcoded secrets or credentials
• • Input validation present
• • SQL queries use parameterized statements
• • File paths are sanitized

Performance

• • No N+1 query patterns
• • Large data sets use generators
• • Caching used where beneficial
• • No unnecessary database calls in loops

Testing

• • Unit tests exist for new functions
• • Edge cases are tested
• • Mocking used appropriately for external dependencies

Feedback Format

Categorize feedback by priority:

• •🔴 Critical: Must fix before merge (bugs, security issues)
• •🟡 Suggestion: Recommended improvements
• •🟢 Nit: Minor style or preference items

Example Feedback

🔴 **Critical**: Line 45 - SQL injection vulnerability
The query uses string formatting. Use parameterized queries instead:
cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))

🟡 **Suggestion**: Line 23 - Consider using a context manager
Replace explicit file.close() with a `with` statement for automatic cleanup.

🟢 **Nit**: Line 12 - Variable naming
Consider renaming `x` to `user_count` for clarity.

Common Python Anti-Patterns

Watch for these issues:

1. •Mutable default arguments: def foo(items=[])
2. •Bare except clauses: except: catches everything
3. •Using is for value comparison: Use == for values
4. •Not using f-strings: Prefer f-strings over .format() or %
5. •Importing *: Pollutes namespace, use explicit imports