"""
Structure analysis utilities for detecting fields in JSON data.
"""

from typing import Dict, Any, List


def detect_summary_fields(data: Dict[str, Any]) -> List[str]:
    """
    Detect summary/aggregate fields in the data structure.
    Looks for fields in 'summary' sections or aggregate fields.
    """
    summary_fields = []
    
    # Check for 'summary' in results
    if 'results' in data and isinstance(data['results'], dict):
        if 'summary' in data['results']:
            summary_data = data['results']['summary']
            if isinstance(summary_data, dict):
                summary_fields.extend([f"summary.{key}" for key in summary_data.keys()])
    
    # Check for top-level 'summary'
    if 'summary' in data and isinstance(data['summary'], dict):
        summary_fields.extend([f"summary.{key}" for key in data['summary'].keys()])
    
    # Look for aggregate patterns in field names
    def find_aggregate_fields(obj, path=""):
        if isinstance(obj, dict):
            for key, value in obj.items():
                current_path = f"{path}.{key}" if path else key
                
                # Check for aggregate patterns
                if any(pattern in key.lower() for pattern in ['total', 'count', 'sum', 'average', 'avg', 'percent', 'percentage']):
                    if isinstance(value, (int, float)):
                        summary_fields.append(current_path)
                
                # Recurse
                find_aggregate_fields(value, current_path)
        elif isinstance(obj, list) and len(obj) > 0:
            find_aggregate_fields(obj[0], path)
    
    find_aggregate_fields(data)
    
    # Remove duplicates and return
    return list(set(summary_fields))


def classify_data_structure(data: Dict[str, Any]) -> Dict[str, Any]:
    """
    Classify the data structure and return categorization.
    """
    config_fields = []
    object_arrays = []
    
    def classify_recursive(obj, path=""):
        if isinstance(obj, dict):
            for key, value in obj.items():
                current_path = f"{path}.{key}" if path else key
                
                # Check for config/compliance fields
                if any(pattern in key.lower() for pattern in ['config', 'compliance', 'enabled', 'enforced', 'policy']):
                    config_fields.append(current_path)
                
                # Check for object arrays
                if isinstance(value, list) and len(value) > 0 and isinstance(value[0], dict):
                    object_arrays.append(current_path)
                
                # Recurse
                classify_recursive(value, current_path)
        elif isinstance(obj, list) and len(obj) > 0:
            classify_recursive(obj[0], path)
    
    classify_recursive(data)
    
    return {
        'config_fields': config_fields,
        'object_arrays': object_arrays
    }


def get_hierarchy_summary(data: Dict[str, Any]) -> Dict[str, Any]:
    """
    Get a summary of the data hierarchy.
    """
    has_summary = False
    
    # Check for summary sections
    if 'results' in data and isinstance(data['results'], dict):
        if 'summary' in data['results']:
            has_summary = True
    
    if 'summary' in data:
        has_summary = True
    
    return {
        'has_summary': has_summary,
        'levels': 2 if has_summary else 1
    }