code-review

# Python Code Review

Follow these guidelines when reviewing Python code.

## Review Checklist

### Identifying Problems

Look for these issues in code changes:

- **Runtime errors**: Potential exceptions, None/null issues, index out of bounds
- **Performance**: Unbounded O(n²) operations, N+1 queries, unnecessary allocations
- **Side effects**: Unintended behavioral changes affecting other components
- **Backwards compatibility**: Breaking API changes without migration path
- **ORM queries**: Complex Django/SQLAlchemy ORM with unexpected query performance
- **Security vulnerabilities**: Injection, XSS, access control gaps, secrets exposure

### Design Assessment

- Do component interactions make logical sense?
- Does the change align with existing project architecture?
- Are there conflicts with current requirements or goals?

### Test Coverage

Every PR should have appropriate test coverage:

- Unit tests for business logic
- Integration tests for component interactions
- End-to-end tests for critical user paths

Verify tests cover actual requirements and edge cases. Avoid excessive branching or looping in test code.

### Long-Term Impact

Flag for senior engineer review when changes involve:

- Database schema modifications
- API contract changes
- New framework or library adoption
- Performance-critical code paths
- Security-sensitive functionality

## Feedback Guidelines

### Tone

- Be polite and empathetic
- Provide actionable suggestions, not vague criticism
- Phrase as questions when uncertain: "Have you considered...?"

### Approval

- Approve when only minor issues remain
- Don't block PRs for stylistic preferences
- Remember: the goal is risk reduction, not perfect code

## Common Patterns to Flag

### N+1 Queries (Django)

```python
# Bad: N+1 query
for user in users:
    print(user.profile.name)  # Separate query per user

# Good: Prefetch related
users = User.objects.prefetch_related('profile')
```

### N+1 Queries (SQLAlchemy)

```python
# Bad: N+1 q