#!/usr/bin/env python3
"""Analyze clippy warnings from output file."""

import re
from collections import defaultdict
from pathlib import Path

def analyze_clippy_output(filepath):
    """Analyze clippy output and categorize warnings."""
    
    warning_types = defaultdict(list)
    warning_counts = defaultdict(int)
    file_warnings = defaultdict(list)
    
    with open(filepath, 'r', encoding='utf-8') as f:
        lines = f.readlines()
    
    current_warning = None
    current_file = None
    
    for i, line in enumerate(lines):
        # Extract warning type and location
        if line.strip().startswith('warning:') and '-->' in (lines[i+1] if i+1 < len(lines) else ''):
            warning_text = line.strip()
            location = lines[i+1].strip()
            
            # Extract file path
            match = re.search(r'--> (.+):(\d+):(\d+)', location)
            if match:
                file_path = match.group(1)
                line_num = match.group(2)
                
                # Extract warning type from help text or note
                warning_type = "unknown"
                for j in range(i+1, min(i+10, len(lines))):
                    if 'clippy::' in lines[j]:
                        clippy_match = re.search(r'clippy::(\w+)', lines[j])
                        if clippy_match:
                            warning_type = clippy_match.group(1)
                            break
                
                warning_counts[warning_type] += 1
                file_warnings[file_path].append({
                    'type': warning_type,
                    'line': line_num,
                    'text': warning_text.replace('warning: ', '')
                })
    
    return warning_counts, file_warnings

def categorize_severity(warning_type):
    """Categorize warning by severity."""
    
    critical = {
        'correctness', 'suspicious', 'panic', 'unwrap_used', 
        'expect_used', 'indexing_slicing', 'panic_in_result_fn'
    }
    
    high = {
        'perf', 'performance', 'nursery', 'cargo', 
        'missing_errors_doc', 'missing_panics_doc', 'must_use_candidate'
    }
    
    medium = {
        'complexity', 'style', 'pedantic', 'redundant_clone',
        'needless_pass_by_value', 'unnecessary_wraps'
    }
    
    low = {
        'restriction', 'needless_raw_string_hashes', 'doc_markdown',
        'missing_const_for_fn', 'default_numeric_fallback'
    }
    
    if warning_type in critical:
        return 'CRITICAL'
    elif warning_type in high:
        return 'HIGH'
    elif warning_type in medium:
        return 'MEDIUM'
    elif warning_type in low:
        return 'LOW'
    else:
        return 'UNKNOWN'

def main():
    filepath = Path('/home/jgrusewski/Work/foxhunt/clippy_full_output.txt')
    
    warning_counts, file_warnings = analyze_clippy_output(filepath)
    
    # Categorize by severity
    severity_counts = defaultdict(int)
    severity_types = defaultdict(list)
    
    for warning_type, count in warning_counts.items():
        severity = categorize_severity(warning_type)
        severity_counts[severity] += count
        severity_types[severity].append((warning_type, count))
    
    print("=" * 80)
    print("CLIPPY WARNING ANALYSIS")
    print("=" * 80)
    print()
    
    # Summary by severity
    print("SEVERITY SUMMARY:")
    print("-" * 80)
    for severity in ['CRITICAL', 'HIGH', 'MEDIUM', 'LOW', 'UNKNOWN']:
        if severity in severity_counts:
            print(f"{severity:10s}: {severity_counts[severity]:5d} warnings")
    print()
    
    # Top warnings by type
    print("TOP WARNING TYPES:")
    print("-" * 80)
    sorted_warnings = sorted(warning_counts.items(), key=lambda x: x[1], reverse=True)
    for warning_type, count in sorted_warnings[:20]:
        severity = categorize_severity(warning_type)
        print(f"  [{severity:8s}] {warning_type:40s}: {count:5d}")
    print()
    
    # Files with most warnings
    print("FILES WITH MOST WARNINGS:")
    print("-" * 80)
    sorted_files = sorted(file_warnings.items(), key=lambda x: len(x[1]), reverse=True)
    for filepath, warnings in sorted_files[:15]:
        print(f"  {filepath:60s}: {len(warnings):5d} warnings")
    print()
    
    # Critical warnings detail
    print("CRITICAL WARNINGS DETAIL:")
    print("-" * 80)
    for warning_type, count in sorted_warnings:
        if categorize_severity(warning_type) == 'CRITICAL':
            print(f"\n{warning_type.upper()} ({count} occurrences):")
            # Find examples
            examples = []
            for filepath, warnings in file_warnings.items():
                for w in warnings:
                    if w['type'] == warning_type and len(examples) < 3:
                        examples.append(f"  - {filepath}:{w['line']} - {w['text']}")
            for ex in examples:
                print(ex)

if __name__ == '__main__':
    main()