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code_language: Python, coding_standards: PEP 8 and team style guide, review_focus: security and performance ```python def get_user_data(user_id): query = f"SELECT * FROM users WHERE id = {user_id}" cursor.execute(query) result = cursor.fetchall() user_list = [] for row in result: user_dict = {} user_dict['id'] = row[0] user_dict['name'] = row[1] user_dict['email'] = row[2] user_list.append(user_dict) return user_list ```

### 🔍 EXECUTIVE SUMMARY - Overall code quality score: 3/10 - Primary concerns: SQL injection vulnerability, inefficient data processing, poor error handling - Estimated time to address: 2-3 hours ### ⚠️ CRITICAL ISSUES **SQL Injection Vulnerability (HIGH RISK)** - Location: Line 2 - Issue: Direct string interpolation in SQL query allows injection attacks - Fix: Use parameterized queries: `cursor.execute("SELECT * FROM users WHERE id = %s", (user_id,))` **No Error Handling (MEDIUM RISK)** - Location: Function-wide - Issue: Database errors will crash the application - Fix: Add try-catch blocks and proper error responses ### 💡 IMPROVEMENT OPPORTUNITIES **Inefficient Data Conversion** - Current: Manual dictionary construction in loop - Suggested: Use `cursor.description` with `zip()` for dynamic column mapping - Benefit: More maintainable and handles schema changes automatically **Missing Type Hints and Validation** - Add function signature: `def get_user_data(user_id: int) -> List[Dict[str, Any]]:` - Validate user_id is positive integer before query ### ✅ POSITIVE HIGHLIGHTS - Clear, descriptive function name - Logical flow that's easy to follow ### 📋 CHECKLIST FOR DEVELOPER - [ ] Replace string interpolation with parameterized query - [ ] Add comprehensive error handling - [ ] Implement input validation - [ ] Add type hints and docstring - [ ] Consider using ORM or query builder for better maintainability