"""
Disaster Recovery & Business Continuity System
Enterprise-grade disaster recovery and business continuity planning for Project Starlight
"""

import json
import math
import base64
import hashlib
import datetime
import re
import string
import itertools
import collections
import dataclasses
from typing import Dict, List, Optional, Any, Union, Tuple
from dataclasses import dataclass
from enum import Enum


class DisasterType(Enum):
    NATURAL_DISASTER = "natural_disaster"
    CYBER_ATTACK = "cyber_attack"
    HARDWARE_FAILURE = "hardware_failure"
    DATA_CORRUPTION = "data_corruption"
    NETWORK_OUTAGE = "network_outage"
    POWER_FAILURE = "power_failure"
    HUMAN_ERROR = "human_error"


class RecoveryTier(Enum):
    TIER_1 = "tier_1"  # RPO < 1 hour, RTO < 4 hours
    TIER_2 = "tier_2"  # RPO < 4 hours, RTO < 24 hours
    TIER_3 = "tier_3"  # RPO < 24 hours, RTO < 72 hours
    TIER_4 = "tier_4"  # RPO < 7 days, RTO < 30 days


class AlertLevel(Enum):
    INFO = "info"
    WARNING = "warning"
    CRITICAL = "critical"
    EMERGENCY = "emergency"


@dataclass
class RecoveryObjective:
    rpo_hours: float  # Recovery Point Objective
    rto_hours: float  # Recovery Time Objective
    tier: RecoveryTier


@dataclass
class BackupPolicy:
    backup_frequency_hours: int
    retention_days: int
    storage_locations: List[str]
    encryption_enabled: bool
    verification_frequency_days: int


@dataclass
class DisasterScenario:
    name: str
    disaster_type: DisasterType
    probability_score: float  # 0.0 to 1.0
    impact_score: float      # 0.0 to 1.0
    risk_score: float        # probability * impact
    recovery_objective: RecoveryObjective


@dataclass
class RecoveryProcedure:
    scenario_name: str
    steps: List[str]
    estimated_duration_hours: float
    required_resources: List[str]
    success_criteria: List[str]
    rollback_procedure: List[str]


@dataclass
class BusinessContinuityPlan:
    plan_id: str
    scenarios: List[DisasterScenario]
    backup_policies: List[BackupPolicy]
    recovery_procedures: List[RecoveryProcedure]
    contact_matrix: Dict[str, List[str]]
    last_updated: datetime.datetime
    version: str


class DisasterRecoverySystem:
    """Enterprise disaster recovery and business continuity system"""
    
    def __init__(self):
        self.bc_plan: Optional[BusinessContinuityPlan] = None
        self.disaster_history: List[Dict[str, Any]] = []
        self.backup_logs: List[Dict[str, Any]] = []
        
    def create_enterprise_scenarios(self) -> List[DisasterScenario]:
        """Create comprehensive disaster scenarios for steganography detection system"""
        scenarios = [
            # Critical scenarios for AI/ML systems
            DisasterScenario(
                name="ml_model_corruption",
                disaster_type=DisasterType.DATA_CORRUPTION,
                probability_score=0.15,
                impact_score=0.95,
                risk_score=0.1425,
                recovery_objective=RecoveryObjective(1.0, 2.0, RecoveryTier.TIER_1)
            ),
            DisasterScenario(
                name="training_data_loss",
                disaster_type=DisasterType.DATA_CORRUPTION,
                probability_score=0.10,
                impact_score=0.90,
                risk_score=0.09,
                recovery_objective=RecoveryObjective(4.0, 8.0, RecoveryTier.TIER_2)
            ),
            
            # Infrastructure scenarios
            DisasterScenario(
                name="primary_datacenter_outage",
                disaster_type=DisasterType.NATURAL_DISASTER,
                probability_score=0.05,
                impact_score=0.85,
                risk_score=0.0425,
                recovery_objective=RecoveryObjective(1.0, 4.0, RecoveryTier.TIER_1)
            ),
            DisasterScenario(
                name="ransomware_attack",
                disaster_type=DisasterType.CYBER_ATTACK,
                probability_score=0.20,
                impact_score=0.95,
                risk_score=0.19,
                recovery_objective=RecoveryObjective(0.5, 6.0, RecoveryTier.TIER_1)
            ),
            DisasterScenario(
                name="database_failure",
                disaster_type=DisasterType.HARDWARE_FAILURE,
                probability_score=0.25,
                impact_score=0.80,
                risk_score=0.20,
                recovery_objective=RecoveryObjective(2.0, 4.0, RecoveryTier.TIER_1)
            ),
            
            # Network scenarios
            DisasterScenario(
                name="internet_outage",
                disaster_type=DisasterType.NETWORK_OUTAGE,
                probability_score=0.30,
                impact_score=0.60,
                risk_score=0.18,
                recovery_objective=RecoveryObjective(0.0, 1.0, RecoveryTier.TIER_1)
            ),
            DisasterScenario(
                name="internal_network_failure",
                disaster_type=DisasterType.NETWORK_OUTAGE,
                probability_score=0.15,
                impact_score=0.70,
                risk_score=0.105,
                recovery_objective=RecoveryObjective(1.0, 2.0, RecoveryTier.TIER_1)
            ),
            
            # Human error scenarios
            DisasterScenario(
                name="accidental_deletion",
                disaster_type=DisasterType.HUMAN_ERROR,
                probability_score=0.40,
                impact_score=0.50,
                risk_score=0.20,
                recovery_objective=RecoveryObjective(1.0, 1.0, RecoveryTier.TIER_1)
            ),
            DisasterScenario(
                name="misconfiguration",
                disaster_type=DisasterType.HUMAN_ERROR,
                probability_score=0.35,
                impact_score=0.60,
                risk_score=0.21,
                recovery_objective=RecoveryObjective(0.5, 2.0, RecoveryTier.TIER_1)
            )
        ]
        
        return scenarios
    
    def create_backup_policies(self) -> List[BackupPolicy]:
        """Create enterprise backup policies"""
        policies = [
            # Critical AI model backups
            BackupPolicy(
                backup_frequency_hours=6,
                retention_days=90,
                storage_locations=["primary_cloud", "secondary_cloud", "on_prem_tape"],
                encryption_enabled=True,
                verification_frequency_days=7
            ),
            
            # Training data backups
            BackupPolicy(
                backup_frequency_hours=12,
                retention_days=365,
                storage_locations=["primary_cloud", "cold_storage"],
                encryption_enabled=True,
                verification_frequency_days=30
            ),
            
            # Configuration and code backups
            BackupPolicy(
                backup_frequency_hours=1,
                retention_days=30,
                storage_locations=["primary_cloud", "git_repositories"],
                encryption_enabled=True,
                verification_frequency_days=1
            ),
            
            # Database backups
            BackupPolicy(
                backup_frequency_hours=4,
                retention_days=180,
                storage_locations=["primary_cloud", "secondary_cloud", "on_prem_storage"],
                encryption_enabled=True,
                verification_frequency_days=7
            ),
            
            # System state backups
            BackupPolicy(
                backup_frequency_hours=24,
                retention_days=30,
                storage_locations=["on_prem_storage", "secondary_cloud"],
                encryption_enabled=True,
                verification_frequency_days=7
            )
        ]
        
        return policies
    
    def create_recovery_procedures(self) -> List[RecoveryProcedure]:
        """Create detailed recovery procedures"""
        procedures = [
            # ML model corruption recovery
            RecoveryProcedure(
                scenario_name="ml_model_corruption",
                steps=[
                    "Verify model corruption using validation dataset",
                    "Isolate corrupted model from production",
                    "Restore latest verified model from backup",
                    "Run model validation tests",
                    "Gradual traffic rollout to restored model",
                    "Monitor performance metrics for 2 hours",
                    "Full production deployment after validation"
                ],
                estimated_duration_hours=2.0,
                required_resources=["ML_engineers", "model_backups", "validation_dataset"],
                success_criteria=[
                    "Model accuracy >= baseline - 2%",
                    "Response time < 500ms",
                    "No prediction failures in validation set"
                ],
                rollback_procedure=[
                    "Stop traffic to restored model",
                    "Switch to previous known-good model",
                    "Investigate restoration failure",
                    "Document lessons learned"
                ]
            ),
            
            # Ransomware attack recovery
            RecoveryProcedure(
                scenario_name="ransomware_attack",
                steps=[
                    "Immediate isolation of affected systems",
                    "Activate incident response team",
                    "Assess scope of encryption",
                    "Restore from clean backups",
                    "Verify systems are malware-free",
                    "Apply security patches",
                    "Gradual system restoration",
                    "Post-incident security assessment"
                ],
                estimated_duration_hours=6.0,
                required_resources=["security_team", "it_infrastructure", "clean_backups", "forensic_tools"],
                success_criteria=[
                    "All systems restored from clean backups",
                    "Security scan shows no malware",
                    "Business operations fully functional"
                ],
                rollback_procedure=[
                    "Extended isolation if reinfection detected",
                    "Alternative recovery path activation",
                    "Communication to stakeholders"
                ]
            ),
            
            # Database failure recovery
            RecoveryProcedure(
                scenario_name="database_failure",
                steps=[
                    "Verify database failure type",
                    "Initiate failover to standby database",
                    "Verify data integrity",
                    "Update application connections",
                    "Monitor performance",
                    "Repair primary database",
                    "Test failback procedure"
                ],
                estimated_duration_hours=4.0,
                required_resources=["database_admins", "standby_database", "connection_configs"],
                success_criteria=[
                    "Database connectivity 100%",
                    "Data consistency verified",
                    "Application performance within SLA"
                ],
                rollback_procedure=[
                    "Revert to original database if stable",
                    "Document failure root cause",
                    "Update monitoring thresholds"
                ]
            )
        ]
        
        return procedures
    
    def create_contact_matrix(self) -> Dict[str, List[str]]:
        """Create emergency contact matrix"""
        return {
            "emergency_response_team": [
                "incident_commander",
                "technical_lead",
                "communications_lead",
                "security_officer"
            ],
            "technical_teams": [
                "infrastructure_engineers",
                "database_administrators",
                "ml_engineers",
                "security_engineers",
                "network_engineers"
            ],
            "management": [
                "cto",
                "vp_engineering",
                "director_operations",
                "product_manager"
            ],
            "external_contacts": [
                "cloud_provider_support",
                "security_consultants",
                "legal_counsel",
                "pr_team"
            ],
            "stakeholders": [
                "business_leaders",
                "key_customers",
                "regulatory_contacts",
                "board_members"
            ]
        }
    
    def generate_business_continuity_plan(self) -> BusinessContinuityPlan:
        """Generate comprehensive business continuity plan"""
        plan_id = f"BCP_{datetime.datetime.now().strftime('%Y%m%d')}_v1.0"
        
        plan = BusinessContinuityPlan(
            plan_id=plan_id,
            scenarios=self.create_enterprise_scenarios(),
            backup_policies=self.create_backup_policies(),
            recovery_procedures=self.create_recovery_procedures(),
            contact_matrix=self.create_contact_matrix(),
            last_updated=datetime.datetime.now(),
            version="1.0"
        )
        
        self.bc_plan = plan
        return plan
    
    def simulate_disaster_recovery(self, scenario_name: str) -> Dict[str, Any]:
        """Simulate disaster recovery execution"""
        if not self.bc_plan:
            return {"error": "Business continuity plan not generated"}
        
        # Find scenario and procedure
        scenario = next((s for s in self.bc_plan.scenarios if s.name == scenario_name), None)
        procedure = next((p for p in self.bc_plan.recovery_procedures if p.scenario_name == scenario_name), None)
        
        if not scenario or not procedure:
            return {"error": f"Scenario {scenario_name} not found"}
        
        print(f"🚨 SIMULATION: {scenario_name}")
        print(f"Disaster Type: {scenario.disaster_type.value}")
        print(f"Risk Score: {scenario.risk_score:.3f}")
        print(f"Target RPO: {scenario.recovery_objective.rpo_hours}h")
        print(f"Target RTO: {scenario.recovery_objective.rto_hours}h")
        
        simulation_start = datetime.datetime.now()
        step_results = []
        
        # Simulate each recovery step
        for i, step in enumerate(procedure.steps, 1):
            step_start = datetime.datetime.now()
            
            # Simulate step execution time (varies by complexity)
            step_duration = 0.1 + (len(step.split()) * 0.05) + (hash(step) % 100) / 500
            
            # Simulate step success/failure (90% success rate)
            step_success = (hash(step) % 100) < 90
            
            step_end = step_start + datetime.timedelta(seconds=step_duration)
            
            step_result = {
                "step_number": i,
                "description": step,
                "start_time": step_start.isoformat(),
                "end_time": step_end.isoformat(),
                "duration_seconds": step_duration,
                "status": "success" if step_success else "failed",
                "notes": None if step_success else "Step requires manual intervention"
            }
            
            step_results.append(step_result)
            
            status_icon = "✅" if step_success else "❌"
            print(f"{status_icon} Step {i}: {step[:50]}{'...' if len(step) > 50 else ''}")
        
        simulation_end = datetime.datetime.now()
        total_duration = (simulation_end - simulation_start).total_seconds()
        
        # Calculate simulation metrics
        successful_steps = sum(1 for r in step_results if r["status"] == "success")
        recovery_success = successful_steps == len(procedure.steps)
        
        # Convert to hours for comparison with RTO
        actual_rto = total_duration / 3600
        rto_met = actual_rto <= scenario.recovery_objective.rto_hours
        
        simulation_result = {
            "scenario_name": scenario_name,
            "simulation_id": f"SIM_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}",
            "start_time": simulation_start.isoformat(),
            "end_time": simulation_end.isoformat(),
            "total_duration_seconds": total_duration,
            "actual_rto_hours": actual_rto,
            "target_rto_hours": scenario.recovery_objective.rto_hours,
            "rto_met": rto_met,
            "recovery_successful": recovery_success,
            "steps_executed": len(step_results),
            "steps_successful": successful_steps,
            "steps_failed": len(step_results) - successful_steps,
            "step_results": step_results
        }
        
        # Record in disaster history
        self.disaster_history.append(simulation_result)
        
        print(f"\n📊 Simulation Results:")
        print(f"Recovery Success: {'✅' if recovery_success else '❌'}")
        print(f"RTO Met: {'✅' if rto_met else '❌'}")
        print(f"Actual RTO: {actual_rto:.3f}h")
        print(f"Target RTO: {scenario.recovery_objective.rto_hours}h")
        
        return simulation_result
    
    def generate_recovery_report(self) -> Dict[str, Any]:
        """Generate comprehensive disaster recovery report"""
        if not self.bc_plan:
            return {"error": "Business continuity plan not generated"}
        
        report = {
            "plan_summary": {
                "plan_id": self.bc_plan.plan_id,
                "version": self.bc_plan.version,
                "last_updated": self.bc_plan.last_updated.isoformat(),
                "total_scenarios": len(self.bc_plan.scenarios),
                "total_backup_policies": len(self.bc_plan.backup_policies),
                "total_recovery_procedures": len(self.bc_plan.recovery_procedures)
            },
            "risk_assessment": [],
            "backup_strategy": [],
            "recovery_capabilities": [],
            "simulation_history": self.disaster_history,
            "compliance_status": {
                "rpo_compliance": True,
                "rto_compliance": True,
                "backup_verification": True,
                "last_drill_date": None
            }
        }
        
        # Process risk assessment
        for scenario in self.bc_plan.scenarios:
            risk_assessment = {
                "scenario": scenario.name,
                "disaster_type": scenario.disaster_type.value,
                "probability": scenario.probability_score,
                "impact": scenario.impact_score,
                "risk_score": scenario.risk_score,
                "recovery_tier": scenario.recovery_objective.tier.value,
                "rpo_hours": scenario.recovery_objective.rpo_hours,
                "rto_hours": scenario.recovery_objective.rto_hours,
                "risk_level": self._calculate_risk_level(scenario.risk_score)
            }
            report["risk_assessment"].append(risk_assessment)
        
        # Process backup strategy
        for i, policy in enumerate(self.bc_plan.backup_policies, 1):
            backup_info = {
                "policy_id": f"BACKUP_POLICY_{i}",
                "backup_frequency_hours": policy.backup_frequency_hours,
                "retention_days": policy.retention_days,
                "storage_locations": policy.storage_locations,
                "encryption_enabled": policy.encryption_enabled,
                "verification_frequency_days": policy.verification_frequency_days
            }
            report["backup_strategy"].append(backup_info)
        
        # Process recovery capabilities
        for procedure in self.bc_plan.recovery_procedures:
            capability = {
                "scenario": procedure.scenario_name,
                "steps_count": len(procedure.steps),
                "estimated_duration_hours": procedure.estimated_duration_hours,
                "required_resources": procedure.required_resources,
                "success_criteria_count": len(procedure.success_criteria),
                "has_rollback": len(procedure.rollback_procedure) > 0
            }
            report["recovery_capabilities"].append(capability)
        
        # Update compliance status
        if self.disaster_history:
            latest_simulation = max(self.disaster_history, key=lambda x: x['start_time'])
            report["compliance_status"]["last_drill_date"] = latest_simulation['start_time']
            
            # Check compliance based on simulations
            successful_simulations = sum(1 for sim in self.disaster_history if sim['recovery_successful'])
            report["compliance_status"]["drill_success_rate"] = (successful_simulations / len(self.disaster_history)) * 100
        
        return report
    
    def _calculate_risk_level(self, risk_score: float) -> str:
        """Calculate risk level based on risk score"""
        if risk_score >= 0.8:
            return "critical"
        elif risk_score >= 0.6:
            return "high"
        elif risk_score >= 0.4:
            return "medium"
        elif risk_score >= 0.2:
            return "low"
        else:
            return "minimal"


def main():
    """Main disaster recovery system runner"""
    dr_system = DisasterRecoverySystem()
    
    # Generate business continuity plan
    print("📋 Generating Business Continuity Plan...")
    bc_plan = dr_system.generate_business_continuity_plan()
    print(f"✅ Plan Generated: {bc_plan.plan_id}")
    
    # Run simulations for critical scenarios
    critical_scenarios = ["ml_model_corruption", "ransomware_attack", "database_failure"]
    
    print(f"\n🚨 Running Disaster Recovery Simulations...")
    for scenario in critical_scenarios:
        print(f"\n{'='*60}")
        result = dr_system.simulate_disaster_recovery(scenario)
    
    # Generate comprehensive report
    print(f"\n📊 Generating Recovery Report...")
    report = dr_system.generate_recovery_report()
    
    # Summary statistics
    print(f"\n📈 Disaster Recovery Summary:")
    print(f"Total Scenarios: {report['plan_summary']['total_scenarios']}")
    print(f"Backup Policies: {report['plan_summary']['total_backup_policies']}")
    print(f"Recovery Procedures: {report['plan_summary']['total_recovery_procedures']}")
    print(f"Simulations Run: {len(report['simulation_history'])}")
    
    if report['compliance_status']['last_drill_date']:
        print(f"Drill Success Rate: {report['compliance_status'].get('drill_success_rate', 0):.1f}%")
    
    return report


if __name__ == "__main__":
    main()