"""
Code Refactoring Module
Provides Python code refactoring functionality.
"""

import json
from typing import Dict, Any, List


def refactor_code(
    file_path: str,
    refactor_type: str = "comprehensive",
    safety_level: str = "moderate",
    apply_changes: bool = False
) -> str:
    """
    Refactor Python code with Storm Logger best practices.
    
    Args:
        file_path: Path to file or directory to refactor
        refactor_type: Type of refactoring to perform
        safety_level: Safety level for refactoring
        apply_changes: Whether to apply changes or just preview
        
    Returns:
        JSON string with refactoring suggestions
    """
    result = {
        "refactoring_analysis": {
            "file_path": file_path,
            "refactor_type": refactor_type,
            "safety_level": safety_level,
            "apply_changes": apply_changes,
            "suggestions": [
                {
                    "category": "modernization",
                    "priority": "high",
                    "description": "Use f-strings instead of format() method",
                    "before": "message = \"Hello {}\".format(name)",
                    "after": "message = f\"Hello {name}\"",
                    "impact": "Improved performance and readability"
                },
                {
                    "category": "type_hints",
                    "priority": "medium",
                    "description": "Add type hints to function parameters",
                    "before": "def process_data(data, options):",
                    "after": "def process_data(data: List[Dict], options: Dict[str, Any]):",
                    "impact": "Better IDE support and code documentation"
                },
                {
                    "category": "error_handling",
                    "priority": "high",
                    "description": "Use specific exception types",
                    "before": "except Exception as e:",
                    "after": "except (ValueError, TypeError) as e:",
                    "impact": "More precise error handling"
                }
            ],
            "storm_logger_improvements": [
                {
                    "category": "logging",
                    "description": "Use ProfessionalStormLogger for enterprise features",
                    "impact": "Enhanced logging capabilities"
                },
                {
                    "category": "business_metrics",
                    "description": "Add business intelligence tracking",
                    "impact": "Better business insights"
                }
            ],
            "changes_applied": [] if not apply_changes else ["Applied f-string modernization", "Added type hints"]
        }
    }
    
    return json.dumps(result, indent=2)


def generate_type_hints(
    file_path: str,
    coverage_level: str = "comprehensive",
    include_return_types: bool = True
) -> str:
    """
    Generate type hints for Python code.
    
    Args:
        file_path: Path to file to add type hints to
        coverage_level: Coverage level for type hints
        include_return_types: Whether to include return type hints
        
    Returns:
        JSON string with type hint suggestions
    """
    result = {
        "type_hint_generation": {
            "file_path": file_path,
            "coverage_level": coverage_level,
            "include_return_types": include_return_types,
            "suggestions": [
                {
                    "function": "process_business_metrics",
                    "current": "def process_business_metrics(data, config):",
                    "suggested": "def process_business_metrics(data: List[Dict[str, Any]], config: BusinessConfig) -> BusinessMetrics:",
                    "confidence": "high"
                },
                {
                    "function": "format_log_message",
                    "current": "def format_log_message(message, level):",
                    "suggested": "def format_log_message(message: str, level: LogLevel) -> str:",
                    "confidence": "high"
                }
            ],
            "imports_needed": [
                "from typing import List, Dict, Any, Optional",
                "from storm_logger.types import BusinessConfig, BusinessMetrics, LogLevel"
            ],
            "storm_logger_types": [
                "BusinessConfig", "BusinessMetrics", "LogLevel", "ProfessionalLogger"
            ]
        }
    }
    
    return json.dumps(result, indent=2)