"""
debug_wrapper.py - Debug Monitoring Module
Injects debugging capabilities without modifying core modules
"""

import os
import time
import json
import numpy as np
import cv2
from collections import deque, Counter
from pathlib import Path
from typing import Any, Dict, List, Optional
import traceback

# Disable Gradio analytics (avoids pandas OptionError bug)
try:
    import gradio as gr
    gr.analytics_enabled = False
except Exception:
    pass

# Create debug directory
DEBUG_DIR = Path("debug_samples")
DEBUG_DIR.mkdir(exist_ok=True)

class DebugMonitor:
    """Centralized debug monitoring and logging"""
    
    def __init__(self, keep_last_logs: int = 200):
        self.keep_last_logs = keep_last_logs
        self.reset()
        
    def reset(self):
        """Reset all debug state"""
        self.start_time = time.time()
        self.frame_count = 0
        self.counters = Counter()
        self.similarities = deque(maxlen=2000)
        self.recent_logs = deque(maxlen=self.keep_last_logs)
        self.bad_samples = []
        self.match_records = []
        self.live_stats = {}  # Live statistics for display
        
    def log(self, msg: str, level: str = "INFO"):
        """Add log entry with timestamp"""
        ts = time.strftime("%H:%M:%S")
        entry = f"[{ts}] [{level}] {msg}"
        print(entry, flush=True)
        self.recent_logs.append(entry)
        
    def save_bad_sample(self, img_bgr: np.ndarray, similarity: float, dog_id: int, track_id: int) -> Optional[str]:
        """Save problematic detection sample"""
        try:
            idx = len(self.bad_samples) + 1
            fname = DEBUG_DIR / f"bad_sample_{idx:04d}_sim{similarity:.2f}_dog{dog_id}.jpg"
            cv2.imwrite(str(fname), img_bgr)
            
            self.bad_samples.append({
                'file': str(fname),
                'similarity': similarity,
                'dog_id': dog_id,
                'track_id': track_id,
                'timestamp': time.time()
            })
            
            self.log(f"Saved bad sample #{idx}: sim={similarity:.3f}, dog_id={dog_id}, track={track_id}", "WARNING")
            return str(fname)
        except Exception as e:
            self.log(f"Error saving bad sample: {e}", "ERROR")
            return None
    
    def update_live_stats(self):
        """Update live statistics for display"""
        total_matches = self.counters['reid_matches']
        total_attempts = self.counters['reid_attempts'] or 1
        
        self.live_stats = {
            'frame': self.frame_count,
            'dogs_detected': len(set(r['dog_id'] for r in self.match_records if r['dog_id'] > 0)),
            'active_tracks': self.counters['active_tracks'],
            'match_rate': total_matches / total_attempts,
            'avg_similarity': np.mean(self.similarities) if self.similarities else 0.0,
            'fps': self.frame_count / (time.time() - self.start_time + 1)
        }
    
    def get_debug_output(self, lines: int = 10) -> str:
        """Get recent log lines for UI display"""
        return "\n".join(list(self.recent_logs)[-lines:])
    
    def get_debug_summary(self) -> str:
        """Get comprehensive debug summary"""
        c = self.counters
        total_matches = c['reid_matches']
        total_attempts = c['reid_attempts'] or 1
        match_rate = total_matches / total_attempts
        avg_sim = np.mean(self.similarities) if self.similarities else 0.0
        elapsed = time.time() - self.start_time
        
        # Get unique dogs
        unique_dogs = len(set(r['dog_id'] for r in self.match_records if r['dog_id'] > 0))
        
        summary = f"""📊 Debug Summary
━━━━━━━━━━━━━━━━━━━━━━
Frames: {self.frame_count} | Time: {elapsed:.1f}s | FPS: {self.frame_count/(elapsed+1):.1f}
Detections: {c['detections']} | Tracks: {c['tracks_created']} | Confirmed: {c['tracks_confirmed']}
Unique Dogs: {unique_dogs} | Active Tracks: {c['active_tracks']}
ReID Attempts: {total_attempts} | Matches: {total_matches} ({match_rate:.1%})
Avg Similarity: {avg_sim:.3f} | Feature Fails: {c['feature_fail']}
Bad Samples Saved: {len(self.bad_samples)}"""
        
        return summary
    
    def save_debug_report(self, filepath: str = "debug_report.json"):
        """Save comprehensive debug report"""
        try:
            report = {
                'timestamp': time.strftime("%Y-%m-%d %H:%M:%S"),
                'frames_processed': self.frame_count,
                'elapsed_time': time.time() - self.start_time,
                'counters': dict(self.counters),
                'avg_similarity': float(np.mean(self.similarities)) if self.similarities else 0.0,
                'similarity_distribution': {
                    'min': float(min(self.similarities)) if self.similarities else 0,
                    'max': float(max(self.similarities)) if self.similarities else 0,
                    'percentiles': {
                        '25%': float(np.percentile(list(self.similarities), 25)) if self.similarities else 0,
                        '50%': float(np.percentile(list(self.similarities), 50)) if self.similarities else 0,
                        '75%': float(np.percentile(list(self.similarities), 75)) if self.similarities else 0,
                        '90%': float(np.percentile(list(self.similarities), 90)) if self.similarities else 0
                    }
                },
                'bad_samples': self.bad_samples[:20],
                'match_records_last': self.match_records[-50:]
            }
            
            with open(filepath, "w") as f:
                json.dump(report, f, indent=2, default=str)
            
            self.log(f"Saved debug report to {filepath}", "INFO")
        except Exception as e:
            self.log(f"Failed to save debug report: {e}", "ERROR")

def add_debugging(app: Any) -> Any:
    """
    Inject debug monitoring into DogMonitoringApp
    
    Args:
        app: DogMonitoringApp instance
        
    Returns:
        Modified app with debug capabilities
    """
    # Create debug monitor
    app.debug_monitor = DebugMonitor()
    
    # ============== Wrap detector.detect ==============
    if hasattr(app, "detector") and hasattr(app.detector, "detect"):
        original_detect = app.detector.detect
        
        def wrapped_detect(frame, *args, **kwargs):
            try:
                detections = original_detect(frame, *args, **kwargs)
                n = len(detections) if detections else 0
                app.debug_monitor.counters['detections'] += n
                if n > 0:
                    app.debug_monitor.log(f"Detected {n} dogs in frame {app.debug_monitor.frame_count}", "DEBUG")
                return detections
            except Exception as e:
                app.debug_monitor.log(f"Detection error: {e}", "ERROR")
                return []
        
        app.detector.detect = wrapped_detect
        app.debug_monitor.log("Injected debug wrapper for detector.detect()")
    
    # ============== Wrap tracker.update ==============
    if hasattr(app, "tracker") and hasattr(app.tracker, "update"):
        original_tracker_update = app.tracker.update
        
        def wrapped_tracker_update(detections, *args, **kwargs):
            try:
                before_ids = set([t.track_id for t in getattr(app.tracker, "tracks", [])])
                tracks = original_tracker_update(detections, *args, **kwargs)
                after_ids = set([t.track_id for t in getattr(app.tracker, "tracks", [])])
                
                new_ids = after_ids - before_ids
                app.debug_monitor.counters['tracks_created'] += len(new_ids)
                app.debug_monitor.counters['tracks_confirmed'] += len(tracks)
                app.debug_monitor.counters['active_tracks'] = len(tracks)
                
                if new_ids:
                    app.debug_monitor.log(f"Created {len(new_ids)} new tracks", "DEBUG")
                
                return tracks
            except Exception as e:
                app.debug_monitor.log(f"Tracker error: {e}", "ERROR")
                return []
        
        app.tracker.update = wrapped_tracker_update
        app.debug_monitor.log("Injected debug wrapper for tracker.update()")
    
    # ============== Wrap reid.match_or_register ==============
    if hasattr(app, "reid") and hasattr(app.reid, "match_or_register"):
        original_match = app.reid.match_or_register
        
        def wrapped_match(track, *args, **kwargs):
            app.debug_monitor.counters['reid_attempts'] += 1
            try:
                dog_id, confidence = original_match(track, *args, **kwargs)
                dog_id = int(dog_id)
                sim = float(confidence)
                
                # Record similarity
                app.debug_monitor.similarities.append(sim)
                app.debug_monitor.match_records.append({
                    'sim': sim,
                    'dog_id': dog_id,
                    'track_id': getattr(track, 'track_id', None),
                    'frame': app.debug_monitor.frame_count
                })
                
                # Check for problematic matches
                threshold = getattr(app.reid, 'similarity_threshold', getattr(app, 'reid_threshold', 0.7))
                
                # Save bad samples (very low similarity)
                if sim < (threshold - 0.2) and track.detections:
                    latest_crop = None
                    for det in reversed(track.detections):
                        if det.image_crop is not None:
                            latest_crop = det.image_crop
                            break
                    
                    if latest_crop is not None:
                        app.debug_monitor.save_bad_sample(
                            latest_crop, sim, dog_id, 
                            getattr(track, 'track_id', 0)
                        )
                
                # Count match/miss
                if sim >= threshold:
                    app.debug_monitor.counters['reid_matches'] += 1
                else:
                    app.debug_monitor.counters['reid_misses'] += 1
                
                return dog_id, sim
                
            except Exception as e:
                app.debug_monitor.log(f"ReID error: {traceback.format_exc()}", "ERROR")
                app.debug_monitor.counters['feature_fail'] += 1
                return 0, 0.0
        
        app.reid.match_or_register = wrapped_match
        app.debug_monitor.log("Injected debug wrapper for reid.match_or_register()")
    
    # ============== Wrap main process_video ==============
    if hasattr(app, "process_video"):
        original_process_video = app.process_video
        
        def wrapped_process_video(video_path: str, progress=None):
            # Reset debug state
            app.debug_monitor.reset()
            app.debug_monitor.log(f"Starting video processing: {video_path}")
            
            # Wrap progress callback to count frames
            if progress:
                original_progress = progress
                def wrapped_progress(val, desc=None):
                    app.debug_monitor.frame_count = int(val * 100)  # Approximate frame count
                    app.debug_monitor.update_live_stats()
                    return original_progress(val, desc)
                progress = wrapped_progress
            
            try:
                result = original_process_video(video_path, progress)
                
                # Save debug report
                app.debug_monitor.save_debug_report()
                app.debug_monitor.log("Video processing completed successfully")
                
                return result
                
            except Exception as e:
                app.debug_monitor.log(f"Process video error: {traceback.format_exc()}", "ERROR")
                raise
        
        app.process_video = wrapped_process_video
        app.debug_monitor.log("Injected debug wrapper for process_video()")
    
    # ============== Add convenience methods ==============
    app.get_debug_output = lambda lines=10: app.debug_monitor.get_debug_output(lines)
    app.get_debug_summary = lambda: app.debug_monitor.get_debug_summary()
    app.get_live_stats = lambda: app.debug_monitor.live_stats
    
    app.debug_monitor.log("✓ Debug monitoring system initialized")
    return app