Telegram-Audio-Downloader

🚀 Performance Guide - Telegram Audio Downloader

Version: 1.0.0
Updated: 2024-01-20
Target Audience: Power Users, System Administrators

📋 Table of Contents

Performance Overview
System Requirements
Configuration Optimization
Network Optimization
Storage Optimization
Memory Management
Monitoring & Metrics
Benchmarking

📊 Performance Overview

Key Performance Metrics

Metric	Default	Optimized	Enterprise
Concurrent Downloads	3	8	16
Rate Limit (calls/sec)	1.0	2.0	5.0
Memory Usage (MB)	150	300	1000
Download Speed (MB/s)	2-5	10-20	50+
Success Rate	95%	98%	99.5%

💻 System Requirements

Recommended Configuration

Hardware:
  CPU: 4+ cores, 3.0+ GHz
  RAM: 8+ GB
  Storage: 100+ GB SSD
  Network: 100+ Mbps fiber

Software:
  OS: Linux (Ubuntu 20.04+)
  Python: 3.11+
  SSD storage for downloads

High-Performance Setup

Hardware:
  CPU: 8+ cores, 3.5+ GHz
  RAM: 16+ GB DDR4
  Storage: 1+ TB NVMe SSD
  Network: 1+ Gbps dedicated

Software:
  OS: Linux with performance kernel
  Python: 3.12 with optimizations
  RAID 0 for download storage

⚙️ Configuration Optimization

High-Performance Configuration

Create performance_config.ini:

[downloader]
max_concurrent_downloads = 8
rate_limit_delay = 0.5
connection_timeout = 60
retry_attempts = 5

[storage]
download_dir = /mnt/fast_ssd/downloads
use_memory_cache = true
cache_size_mb = 512

[network]
chunk_size = 1048576  # 1MB chunks
max_connections = 10
keepalive = true

[performance]
verify_downloads = false
extract_metadata = false
log_level = WARNING

Memory-Optimized Configuration

[memory]
max_memory_mb = 1024
cleanup_frequency = 50
garbage_collect_frequency = 100

[downloader]
max_concurrent_downloads = 4
buffer_size = 65536  # 64KB
stream_downloads = true

🌐 Network Optimization

TCP Tuning (Linux)

# Optimize TCP settings for high throughput
echo 'net.core.rmem_max = 67108864' >> /etc/sysctl.conf
echo 'net.core.wmem_max = 67108864' >> /etc/sysctl.conf
echo 'net.ipv4.tcp_congestion_control = bbr' >> /etc/sysctl.conf

# Apply settings
sysctl -p

High-Performance Download Script

#!/usr/bin/env python3
"""
High-performance downloader with optimizations.
"""
import asyncio
from telegram_audio_downloader.downloader import AudioDownloader

class HighPerformanceDownloader(AudioDownloader):
    def __init__(self, **kwargs):
        super().__init__(
            max_concurrent_downloads=16,
            rate_limit_delay=0.3,
            **kwargs
        )
    
    async def optimized_download(self, group, **kwargs):
        """Optimized download with connection pooling."""
        await self.initialize_client()
        
        try:
            result = await self.download_audio_files(
                group_identifier=group,
                **kwargs
            )
            return result
        finally:
            pass  # Keep connections warm

async def main():
    downloader = HighPerformanceDownloader()
    result = await downloader.optimized_download("@music_group", limit=100)
    print(f"Downloaded {result['completed']} files")

if __name__ == "__main__":
    asyncio.run(main())

Bandwidth Management

# Command-line optimization
telegram-audio-downloader download @group \
    --max-concurrent 8 \
    --rate-limit 0.5 \
    --skip-existing \
    --no-verify \
    --chunk-size 1MB

💾 Storage Optimization

SSD Configuration

# Format for optimal performance
mkfs.ext4 -O ^has_journal /dev/nvme0n1p1

# Mount with performance options
mount -o noatime,nodiratime,nobarrier /dev/nvme0n1p1 /mnt/downloads

Directory Structure

# optimal_storage.py
from pathlib import Path

class StorageManager:
    def __init__(self, base_path="/mnt/downloads"):
        self.base_path = Path(base_path)
        self.setup_directories()
    
    def setup_directories(self):
        """Create optimal directory structure."""
        directories = [
            "incoming",      # New downloads
            "completed",     # Finished downloads
            "cache",         # Temporary files
        ]
        
        for directory in directories:
            (self.base_path / directory).mkdir(parents=True, exist_ok=True)
    
    def get_optimal_path(self, file_info):
        """Get optimal path based on file characteristics."""
        if file_info.get('size', 0) > 50 * 1024 * 1024:  # 50MB
            return self.base_path / "completed" / "large"
        
        date_dir = file_info.get('date', '').split('T')[0]
        return self.base_path / "completed" / date_dir

🧠 Memory Management

Memory Monitor

# memory_manager.py
import gc
import psutil

class MemoryManager:
    def __init__(self, max_memory_mb=1024):
        self.max_memory_bytes = max_memory_mb * 1024 * 1024
    
    def get_memory_usage(self):
        """Get current memory usage."""
        process = psutil.Process()
        return {
            'rss_mb': process.memory_info().rss / 1024 / 1024,
            'percent': process.memory_percent()
        }
    
    def is_memory_limit_exceeded(self):
        """Check if memory limit is exceeded."""
        usage = self.get_memory_usage()
        return usage['rss_mb'] > self.max_memory_bytes / 1024 / 1024 * 0.8
    
    def emergency_cleanup(self):
        """Perform emergency memory cleanup."""
        return gc.collect()

# Usage in downloads
memory_manager = MemoryManager()

if memory_manager.is_memory_limit_exceeded():
    memory_manager.emergency_cleanup()

📈 Monitoring & Metrics

Real-Time Performance Monitor

# monitor.py
import time
import psutil
from dataclasses import dataclass

@dataclass
class PerformanceMetrics:
    downloads_completed: int = 0
    downloads_failed: int = 0
    average_speed_mbps: float = 0.0
    cpu_usage: float = 0.0
    memory_usage_mb: float = 0.0
    success_rate: float = 0.0

class PerformanceMonitor:
    def __init__(self):
        self.start_time = time.time()
        self.downloads_completed = 0
        self.downloads_failed = 0
        self.total_bytes = 0
    
    def get_current_metrics(self):
        """Get current performance metrics."""
        cpu_percent = psutil.cpu_percent()
        memory = psutil.virtual_memory()
        
        return PerformanceMetrics(
            downloads_completed=self.downloads_completed,
            downloads_failed=self.downloads_failed,
            average_speed_mbps=self._calculate_speed(),
            cpu_usage=cpu_percent,
            memory_usage_mb=memory.used / (1024 * 1024),
            success_rate=self._calculate_success_rate()
        )
    
    def _calculate_speed(self):
        """Calculate average download speed."""
        duration = time.time() - self.start_time
        if duration > 0:
            return (self.total_bytes / duration) / (1024 * 1024)
        return 0.0
    
    def _calculate_success_rate(self):
        """Calculate download success rate."""
        total = self.downloads_completed + self.downloads_failed
        if total > 0:
            return self.downloads_completed / total
        return 0.0
    
    def on_download_complete(self, file_size):
        """Record successful download."""
        self.downloads_completed += 1
        self.total_bytes += file_size
    
    def on_download_failed(self):
        """Record failed download."""
        self.downloads_failed += 1

# Global monitor instance
monitor = PerformanceMonitor()

Performance Dashboard

# Monitor downloads in real-time
telegram-audio-downloader download @group --monitor --verbose

# Generate performance report
telegram-audio-downloader stats --performance --export-json

🎯 Benchmarking

Performance Benchmarks

#!/usr/bin/env python3
"""
Benchmark script for performance testing.
"""
import asyncio
import time
from telegram_audio_downloader.downloader import AudioDownloader

async def benchmark_download_speeds():
    """Benchmark different configuration settings."""
    
    configs = [
        {"max_concurrent": 1, "rate_limit": 2.0},   # Conservative
        {"max_concurrent": 4, "rate_limit": 1.0},   # Balanced
        {"max_concurrent": 8, "rate_limit": 0.5},   # Aggressive
    ]
    
    for config in configs:
        print(f"Testing config: {config}")
        
        downloader = AudioDownloader(**config)
        await downloader.initialize_client()
        
        start_time = time.time()
        try:
            result = await downloader.download_audio_files(
                "@test_group", 
                limit=10
            )
            
            duration = time.time() - start_time
            speed = result.get('total_size', 0) / duration / (1024 * 1024)
            
            print(f"  Duration: {duration:.1f}s")
            print(f"  Speed: {speed:.1f} MB/s")
            print(f"  Success: {result['completed']}/{result['completed'] + result['failed']}")
            
        finally:
            await downloader.close()
        
        print()

if __name__ == "__main__":
    asyncio.run(benchmark_download_speeds())

Quick Performance Test

# Test current performance
telegram-audio-downloader download @test_group \
    --limit 10 \
    --benchmark \
    --verbose

# Compare configurations
for concurrent in 1 4 8; do
    echo "Testing $concurrent concurrent downloads"
    time telegram-audio-downloader download @test_group \
        --limit 20 \
        --max-concurrent $concurrent \
        --skip-existing
done

🔧 Optimization Commands

Quick Optimization

# High-speed download
telegram-audio-downloader download @group \
    --max-concurrent 8 \
    --rate-limit 0.5 \
    --no-verify \
    --skip-existing

# Memory-efficient download
telegram-audio-downloader download @group \
    --max-concurrent 2 \
    --memory-limit 512MB \
    --cleanup-frequency 10

# Network-optimized download
telegram-audio-downloader download @group \
    --chunk-size 2MB \
    --timeout 60 \
    --max-retries 5

System Monitoring

# Monitor system resources during download
# Terminal 1: Start download
telegram-audio-downloader download @large_group --monitor

# Terminal 2: Monitor system
watch -n 1 'free -h && echo && df -h && echo && ps aux | grep telegram'

📚 Performance Best Practices

Do’s

✅ Use SSD storage for downloads
✅ Optimize network settings for your connection
✅ Monitor memory usage during large downloads
✅ Use appropriate concurrency levels
✅ Enable skip-existing for resumable downloads

Don’ts

❌ Don’t use maximum concurrency on limited hardware
❌ Don’t disable rate limiting completely
❌ Don’t ignore memory warnings
❌ Don’t run on network storage for temp files
❌ Don’t forget to clean up old downloads

For additional optimization help, visit our GitHub repository or performance discussions.

Last updated: 2024-01-20
Version: 1.0.0

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