Replication/cross_platform.py

#!/usr/bin/env python3
"""
Réplication Cross-Platform
Déploiement sur multiples plateformes cloud et edge
"""

import asyncio
import random
from typing import Dict, List, Any
import logging

class CrossPlatform:
    """
    Gestionnaire de déploiement cross-platform
    Support pour multiples environnements cloud et edge
    """
    
    def __init__(self):
        self.logger = logging.getLogger("cross_platform")
        self.supported_platforms = []
        self.deployment_configs = {}
        self.platform_health = {}
        
    async def initialize(self):
        """Initialise le système cross-platform"""
        self.logger.info("🌐 Initialisation du système cross-platform...")
        
        try:
            await self._load_platform_support()
            await self._setup_deployment_configs()
            await self._monitor_platform_health()
            
            self.logger.info("✅ Système cross-platform initialisé")
            return True
            
        except Exception as e:
            self.logger.error(f"❌ Erreur d'initialisation cross-platform: {e}")
            return False
    
    async def deploy_to_platform(self, platform: str, deployment_package: Dict) -> Dict[str, Any]:
        """Déploie sur une plateforme spécifique"""
        if platform not in self.supported_platforms:
            return {"error": "Plateforme non supportée"}
        
        deployment_id = f"DEPLOY_{len(self.deployment_configs) + 1:06d}"
        
        deployment_result = await self._execute_deployment(platform, deployment_package)
        
        self.deployment_configs[deployment_id] = {
            "platform": platform,
            "package": deployment_package,
            "status": "deployed",
            "deployment_time": deployment_result.get("duration", 0),
            "endpoint": deployment_result.get("endpoint", "")
        }
        
        return {
            "deployment_id": deployment_id,
            "platform": platform,
            "status": "success",
            "endpoint": deployment_result.get("endpoint", ""),
            "deployment_time": deployment_result.get("duration", 0)
        }
    
    async def multi_platform_deploy(self, deployment_package: Dict, platforms: List[str] = None) -> Dict[str, Any]:
        """Déploie sur multiples plateformes simultanément"""
        if platforms is None:
            platforms = self.supported_platforms[:3]  # 3 premières plateformes par défaut
        
        deployment_tasks = []
        for platform in platforms:
            task = self.deploy_to_platform(platform, deployment_package)
            deployment_tasks.append(task)
        
        results = await asyncio.gather(*deployment_tasks, return_exceptions=True)
        
        successful_deploys = [r for r in results if isinstance(r, dict) and "deployment_id" in r]
        failed_deploys = [r for r in results if isinstance(r, Exception)]
        
        return {
            "total_platforms": len(platforms),
            "successful_deploys": len(successful_deploys),
            "failed_deploys": len(failed_deploys),
            "deployment_ids": [d["deployment_id"] for d in successful_deploys],
            "failed_platforms": [str(e) for e in failed_deploys]
        }
    
    async def get_platform_status(self, platform: str = None) -> Dict[str, Any]:
        """Retourne le statut des plateformes"""
        if platform:
            return self.platform_health.get(platform, {"error": "Plateforme non surveillée"})
        
        return {
            "monitored_platforms": len(self.platform_health),
            "platform_status": self.platform_health,
            "overall_health": await self._calculate_overall_health()
        }
    
    async def _load_platform_support(self):
        """Charge le support des plateformes"""
        self.supported_platforms = [
            "huggingface_spaces",
            "streamlit_cloud",
            "heroku",
            "vercel",
            "netlify",
            "aws_amplify",
            "google_cloud_run",
            "azure_static_web_apps",
            "digitalocean_apps",
            "railway"
        ]
        
        self.logger.info(f"🖥️ {len(self.supported_platforms)} plateformes supportées")
    
    async def _setup_deployment_configs(self):
        """Configure les paramètres de déploiement"""
        for platform in self.supported_platforms:
            self.deployment_configs[platform] = {
                "runtime": "python_3_10",
                "requirements": ["gradio", "aiohttp", "numpy"],
                "environment_variables": {
                    "BAROUIA_ENV": "production",
                    "QUANTUM_MODE": "enabled"
                }
            }
    
    async def _monitor_platform_health(self):
        """Surveille la santé des plateformes"""
        for platform in self.supported_platforms:
            self.platform_health[platform] = {
                "status": "healthy",
                "latency": random.uniform(10, 200),
                "uptime": random.uniform(0.95, 0.999),
                "last_check": __import__('time').time()
            }
        
        # Surveillance continue
        asyncio.create_task(self._continuous_health_monitoring())
    
    async def _execute_deployment(self, platform: str, package: Dict) -> Dict[str, Any]:
        """Exécute le déploiement sur une plateforme"""
        # Simulation du déploiement
        deployment_time = random.uniform(5.0, 30.0)
        
        return {
            "success": True,
            "platform": platform,
            "duration": deployment_time,
            "endpoint": f"https://{platform}.barouia-cortex.ai",
            "resources_allocated": {
                "cpu": package.get("resources", {}).get("cpu", 1),
                "memory": package.get("resources", {}).get("memory", 512)
            }
        }
    
    async def _calculate_overall_health(self) -> str:
        """Calcule la santé globale des plateformes"""
        healthy_count = sum(1 for status in self.platform_health.values() 
                          if status["status"] == "healthy")
        
        health_ratio = healthy_count / len(self.platform_health)
        
        if health_ratio >= 0.9:
            return "excellent"
        elif health_ratio >= 0.7:
            return "good"
        elif health_ratio >= 0.5:
            return "degraded"
        else:
            return "poor"
    
    async def _continuous_health_monitoring(self):
        """Surveillance continue de la santé"""
        while True:
            await asyncio.sleep(60)  # Toutes les minutes
            
            for platform in self.supported_platforms:
                # Simulation de fluctuations de santé
                status_change = random.random()
                if status_change < 0.05:  # 5% de chance de changement
                    new_status = "degraded" if self.platform_health[platform]["status"] == "healthy" else "healthy"
                    self.platform_health[platform]["status"] = new_status
                    self.platform_health[platform]["latency"] = random.uniform(10, 200)
                    self.platform_health[platform]["last_check"] = __import__('time').time()
            
            self.logger.debug("📊 Santé des plateformes mise à jour")