"""
T226: Performance Renderer (Experimental)
Renderizador de video/GIF de performance
"""

import json
import os
from datetime import datetime
from typing import Dict, List, Any, Optional, Tuple


class PerformanceRenderer:
    """
    Renderizador experimental de performance.
    
    T226: Crea visualizaciones de la performance del sistema.
    NOTA: Requiere dependencias adicionales (PIL, matplotlib, opcionalmente opencv)
    """
    
    def __init__(self, output_dir: str = None):
        self.output_dir = output_dir or os.path.join(
            os.path.dirname(os.path.dirname(__file__)),
            'cloud', 'renders'
        )
        os.makedirs(self.output_dir, exist_ok=True)
        
    def render_performance_gif(self, duration_seconds: int = 30,
                               fps: int = 10,
                               width: int = 640,
                               height: int = 360) -> Dict[str, Any]:
        """
        Renderiza GIF de performance.
        
        Args:
            duration_seconds: Duración del GIF
            fps: Frames por segundo
            width: Ancho en píxeles
            height: Alto en píxeles
            
        Returns:
            Ruta al GIF generado o estado experimental
        """
        timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
        output_path = os.path.join(self.output_dir, f'performance_{timestamp}.gif')
        
        # NOTA: Implementación real requeriría PIL/Pillow
        # Esta es una versión de placeholder que documenta la estructura
        
        try:
            # Simulación de renderizado
            frames = self._generate_simulation_frames(duration_seconds, fps, width, height)
            
            return {
                'status': 'experimental',
                'output_path': output_path,
                'frames_generated': len(frames),
                'duration_seconds': duration_seconds,
                'fps': fps,
                'resolution': f'{width}x{height}',
                'message': 'GIF rendering requires PIL/Pillow and imageio packages',
                'implementation_note': 'Full implementation would use PIL.Image, imageio, and matplotlib'
            }
        except Exception as e:
            return {
                'status': 'error',
                'error': str(e),
                'message': 'GIF rendering not available - install PIL/Pillow and imageio'
            }
    
    def render_performance_video(self, duration_seconds: int = 60,
                                  fps: int = 30,
                                  width: int = 1920,
                                  height: int = 1080,
                                  codec: str = 'h264') -> Dict[str, Any]:
        """
        Renderiza video de performance.
        
        Args:
            duration_seconds: Duración del video
            fps: Frames por segundo
            width: Ancho en píxeles
            height: Alto en píxeles
            codec: Códec de video
            
        Returns:
            Ruta al video generado o estado experimental
        """
        timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
        output_path = os.path.join(self.output_dir, f'performance_{timestamp}.mp4')
        
        try:
            # Simulación de renderizado
            return {
                'status': 'experimental',
                'output_path': output_path,
                'duration_seconds': duration_seconds,
                'fps': fps,
                'resolution': f'{width}x{height}',
                'codec': codec,
                'message': 'Video rendering requires opencv-python (cv2) package',
                'implementation_note': 'Full implementation would use cv2.VideoWriter'
            }
        except Exception as e:
            return {
                'status': 'error',
                'error': str(e),
                'message': 'Video rendering not available - install opencv-python'
            }
    
    def generate_performance_html(self, session_id: str = None) -> Dict[str, Any]:
        """Genera visualización HTML animada de la performance."""
        timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
        output_path = os.path.join(self.output_dir, f'performance_{timestamp}.html')
        
        html_content = self._generate_performance_html_content(session_id)
        
        with open(output_path, 'w', encoding='utf-8') as f:
            f.write(html_content)
        
        return {
            'status': 'success',
            'output_path': output_path,
            'format': 'html',
            'interactive': True,
            'size_bytes': os.path.getsize(output_path)
        }
    
    def _generate_simulation_frames(self, duration: int, fps: int, 
                                     width: int, height: int) -> List[Dict]:
        """Genera frames simulados para el renderizado."""
        total_frames = duration * fps
        frames = []
        
        for i in range(total_frames):
            frame = {
                'index': i,
                'timestamp': i / fps,
                'simulated': True,
                'content': {
                    'bars': self._get_current_bar(i, fps),
                    'bpm': 128,
                    'active_tracks': ['drums', 'bass', 'music'],
                    'cpu_usage': 45 + (i % 20),  # Simulación
                    'memory_mb': 512 + (i % 100)
                }
            }
            frames.append(frame)
        
        return frames
    
    def _get_current_bar(self, frame_index: int, fps: int) -> int:
        """Calcula bar actual basado en frame."""
        # Asumiendo 128 BPM, 4 beats por bar
        bpm = 128
        seconds_per_beat = 60.0 / bpm
        seconds_per_bar = seconds_per_beat * 4
        
        current_time = frame_index / fps
        return int(current_time / seconds_per_bar) + 1
    
    def _generate_performance_html_content(self, session_id: str = None) -> str:
        """Genera contenido HTML para visualización."""
        return '''<!DOCTYPE html>
<html>
<head>
    <meta charset="UTF-8">
    <title>AbletonMCP-AI Performance Visualization</title>
    <style>
        body {
            margin: 0;
            background: #0a0a0a;
            color: #fff;
            font-family: 'Courier New', monospace;
            overflow: hidden;
        }
        .container {
            display: flex;
            flex-direction: column;
            height: 100vh;
        }
        .header {
            background: #1a1a2e;
            padding: 20px;
            border-bottom: 2px solid #4CAF50;
        }
        .header h1 {
            margin: 0;
            font-size: 18px;
            color: #4CAF50;
        }
        .visualizer {
            flex: 1;
            display: flex;
            align-items: center;
            justify-content: center;
            background: linear-gradient(135deg, #0a0a0a 0%, #1a1a2e 100%);
        }
        .bars {
            display: flex;
            align-items: flex-end;
            gap: 4px;
            height: 200px;
        }
        .bar {
            width: 20px;
            background: linear-gradient(to top, #4CAF50, #8BC34A);
            border-radius: 2px;
            animation: bounce 0.5s ease-in-out infinite;
        }
        @keyframes bounce {
            0%, 100% { height: 50px; }
            50% { height: 150px; }
        }
        .info {
            position: absolute;
            bottom: 20px;
            left: 20px;
            font-size: 12px;
            color: #888;
        }
        .metrics {
            position: absolute;
            top: 100px;
            right: 20px;
            background: rgba(0,0,0,0.5);
            padding: 15px;
            border-radius: 8px;
            font-size: 12px;
        }
        .metric {
            margin: 5px 0;
        }
        .metric-label {
            color: #888;
        }
        .metric-value {
            color: #4CAF50;
            margin-left: 10px;
        }
    </style>
</head>
<body>
    <div class="container">
        <div class="header">
            <h1>🎵 AbletonMCP-AI Performance Visualizer</h1>
        </div>
        <div class="visualizer">
            <div class="bars">
                <div class="bar" style="animation-delay: 0s"></div>
                <div class="bar" style="animation-delay: 0.1s"></div>
                <div class="bar" style="animation-delay: 0.2s"></div>
                <div class="bar" style="animation-delay: 0.3s"></div>
                <div class="bar" style="animation-delay: 0.4s"></div>
                <div class="bar" style="animation-delay: 0.5s"></div>
                <div class="bar" style="animation-delay: 0.6s"></div>
                <div class="bar" style="animation-delay: 0.7s"></div>
            </div>
            <div class="metrics">
                <div class="metric">
                    <span class="metric-label">BPM:</span>
                    <span class="metric-value" id="bpm">128</span>
                </div>
                <div class="metric">
                    <span class="metric-label">Bar:</span>
                    <span class="metric-value" id="bar">1</span>
                </div>
                <div class="metric">
                    <span class="metric-label">CPU:</span>
                    <span class="metric-value" id="cpu">45%</span>
                </div>
                <div class="metric">
                    <span class="metric-label">Memory:</span>
                    <span class="metric-value" id="memory">512MB</span>
                </div>
            </div>
        </div>
        <div class="info">
            T226: Experimental Performance Visualization<br>
            Rendering: HTML/CSS Animation
        </div>
    </div>
    <script>
        // Simulación de actualización de métricas
        let bar = 1;
        setInterval(() => {
            bar++;
            document.getElementById('bar').textContent = bar;
            document.getElementById('cpu').textContent = (40 + Math.random() * 20).toFixed(1) + '%';
            document.getElementById('memory').textContent = (500 + Math.random() * 100).toFixed(0) + 'MB';
        }, 1875); // 128 BPM = 1.875s por bar
    </script>
</body>
</html>'''


def render_performance_video(duration_seconds: int = 30, 
                              resolution: str = '720p') -> Dict[str, Any]:
    """
    T226: Renderiza video/GIF de performance (Experimental).
    
    Args:
        duration_seconds: Duración del video
        resolution: '480p', '720p', '1080p'
        
    Returns:
        Estado del renderizado
    """
    resolutions = {
        '480p': (854, 480),
        '720p': (1280, 720),
        '1080p': (1920, 1080)
    }
    
    width, height = resolutions.get(resolution, (1280, 720))
    
    renderer = PerformanceRenderer()
    
    # Por defecto, generar HTML (siempre disponible)
    html_result = renderer.generate_performance_html()
    
    # Intentar GIF (requiere dependencias)
    gif_result = renderer.render_performance_gif(
        duration_seconds=duration_seconds,
        width=width // 2,
        height=height // 2
    )
    
    return {
        'status': 'experimental',
        'html_output': html_result,
        'gif_output': gif_result,
        'message': 'T226 is experimental - HTML visualization always available'
    }


if __name__ == '__main__':
    # Test del renderizador
    result = render_performance_video(duration_seconds=10, resolution='720p')
    print(json.dumps(result, indent=2))
