436-code-generation-patterns

Code Generation Patterns

Purpose: Ensure professional-grade AI-generated code without common formatting errors.

Critical Patterns

Formatting Rules

# ✅ CORRECT Structure
def process():
    """Process data."""
    return data

# ❌ AVOID: Same-line docstrings
def bad(): """Wrong""" return None

Import Organization

# Standard → Third-party → Local
import os
import json

import numpy as np
import pandas as pd

from .utils import helper
from .models import DataModel

Error Handling

# Always include proper error handling
try:
    result = risky_operation()
except SpecificError as e:
    logger.error(f"Operation failed: {e}")
    raise ProcessingError(f"Cannot process: {e}") from e

Type Safety

from typing import List, Dict, Optional

def process_items(items: List[Dict[str, Any]]) -> Optional[pd.DataFrame]:
    """Process with full type hints."""
    if not items:
        return None
    return pd.DataFrame(items)

Common Pitfalls

1. Missing newlines after docstrings/comments
2. Incomplete imports - always specify full paths
3. Bare exceptions - catch specific errors
4. No type hints - add for public APIs
5. Magic numbers - use named constants

Validation Checklist

• Proper indentation (4 spaces)
• Docstrings for public functions
• Error handling for I/O operations
• Type hints for parameters/returns
• No trailing whitespace
• Consistent quote style

Quick Fixes

# Auto-format Python
black --line-length 88 *.py

# Type checking
mypy --strict *.py

# Linting
ruff check --fix *.py