"""
Enterprise Quality Assurance Orchestrator
Main entry point for Project Starlight enterprise-grade quality assurance system
"""

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 QASystemStatus(Enum):
    HEALTHY = "healthy"
    DEGRADED = "degraded"
    FAILED = "failed"
    INITIALIZING = "initializing"


@dataclass
class QAExecutionSummary:
    execution_id: str
    start_time: datetime.datetime
    end_time: Optional[datetime.datetime]
    duration_seconds: float
    total_tests_run: int
    tests_passed: int
    tests_failed: int
    load_tests_run: int
    ci_pipeline_runs: int
    disaster_recovery_simulations: int
    monitoring_cycles: int
    overall_status: QASystemStatus
    recommendations: List[str]


class EnterpriseQAOrchestrator:
    """Enterprise Quality Assurance Orchestrator for Project Starlight"""
    
    def __init__(self):
        self.status = QASystemStatus.INITIALIZING
        self.execution_history: List[QAExecutionSummary] = []
        
    def run_complete_qa_cycle(self) -> QAExecutionSummary:
        """Run complete enterprise QA cycle"""
        execution_id = f"QA_CYCLE_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}"
        start_time = datetime.datetime.now()
        
        print("🚀 Starting Enterprise QA Cycle for Project Starlight")
        print("=" * 80)
        
        try:
            # Step 1: Testing Framework
            print("\n[1/5] 🧪 Running Comprehensive Test Suite...")
            from testing_framework import StarlightTestFramework
            
            test_framework = StarlightTestFramework()
            test_report = test_framework.run_all_tests()
            
            total_tests = test_report['summary']['total_tests']
            tests_passed = test_report['summary']['total_passed']
            tests_failed = test_report['summary']['total_failed']
            
            print(f"✅ Tests: {tests_passed}/{total_tests} passed")
            
            # Step 2: CI/CD Pipeline
            print("\n[2/5] ⚙️ Executing CI/CD Pipeline...")
            from ci_cd_pipeline import CICDPipeline
            
            ci_pipeline = CICDPipeline()
            ci_execution = ci_pipeline.execute_pipeline(
                branch="enterprise-qa",
                commit_hash=hashlib.sha256(execution_id.encode()).hexdigest()[:10]
            )
            
            ci_pipeline_runs = 1
            ci_success = ci_execution.status.value == "success"
            print(f"{'✅' if ci_success else '❌'} CI/CD: {ci_execution.status.value}")
            
            # Step 3: Load Testing
            print("\n[3/5] 🚀 Running Load Tests...")
            from load_testing import LoadTestEngine
            
            load_engine = LoadTestEngine()
            # Run a subset of load tests for demo
            scenarios = load_engine.create_enterprise_scenarios()[:3]  # Run first 3 scenarios
            load_results = []
            
            for scenario in scenarios:
                result = load_engine.execute_load_test(scenario)
                load_results.append(result)
            
            load_tests_run = len(scenarios)
            avg_throughput = sum(r.throughput for r in load_results) / len(load_results) if load_results else 0
            print(f"✅ Load Tests: {load_tests_run} scenarios, Avg Throughput: {avg_throughput:.2f} RPS")
            
            # Step 4: Disaster Recovery
            print("\n[4/5] 🚨 Testing Disaster Recovery...")
            from disaster_recovery import DisasterRecoverySystem
            
            dr_system = DisasterRecoverySystem()
            dr_system.generate_business_continuity_plan()
            
            # Run critical disaster recovery simulations
            critical_scenarios = ["ml_model_corruption", "ransomware_attack"]
            dr_simulations = 0
            
            for scenario in critical_scenarios:
                try:
                    dr_result = dr_system.simulate_disaster_recovery(scenario)
                    if dr_result.get('recovery_successful', False):
                        dr_simulations += 1
                except Exception as e:
                    print(f"⚠️ DR Simulation {scenario} failed: {str(e)}")
            
            print(f"✅ Disaster Recovery: {dr_simulations}/{len(critical_scenarios)} simulations successful")
            
            # Step 5: Monitoring System
            print("\n[5/5] 📊 Testing Monitoring System...")
            from monitoring_system import MonitoringSystem
            
            monitoring = MonitoringSystem()
            monitoring.setup_monitoring()
            
            # Run brief monitoring simulation
            monitoring_report = monitoring.simulate_monitoring_cycle(duration_minutes=1)
            monitoring_cycles = monitoring_report['monitoring_summary']['simulation_cycles']
            
            system_health = monitoring_report['system_health']['overall_status']
            print(f"✅ Monitoring: {monitoring_cycles} cycles, System Health: {system_health}")
            
            # Calculate execution summary
            end_time = datetime.datetime.now()
            duration_seconds = (end_time - start_time).total_seconds()
            
            # Determine overall status
            success_rate = (tests_passed / total_tests * 100) if total_tests > 0 else 0
            ci_ok = ci_success
            load_ok = avg_throughput > 0
            dr_ok = dr_simulations >= len(critical_scenarios) * 0.8  # 80% success rate
            monitoring_ok = system_health != "unhealthy"
            
            if success_rate >= 95 and ci_ok and load_ok and dr_ok and monitoring_ok:
                overall_status = QASystemStatus.HEALTHY
            elif success_rate >= 80 and ci_ok and (load_ok or dr_ok or monitoring_ok):
                overall_status = QASystemStatus.DEGRADED
            else:
                overall_status = QASystemStatus.FAILED
            
            # Generate recommendations
            recommendations = self._generate_recommendations(
                success_rate, ci_ok, load_ok, dr_ok, monitoring_ok
            )
            
            summary = QAExecutionSummary(
                execution_id=execution_id,
                start_time=start_time,
                end_time=end_time,
                duration_seconds=duration_seconds,
                total_tests_run=total_tests,
                tests_passed=tests_passed,
                tests_failed=tests_failed,
                load_tests_run=load_tests_run,
                ci_pipeline_runs=ci_pipeline_runs,
                disaster_recovery_simulations=dr_simulations,
                monitoring_cycles=monitoring_cycles,
                overall_status=overall_status,
                recommendations=recommendations
            )
            
            self.execution_history.append(summary)
            self.status = overall_status
            
            # Print final summary
            print("\n" + "=" * 80)
            print("📊 ENTERPRISE QA CYCLE COMPLETE")
            print("=" * 80)
            print(f"Execution ID: {execution_id}")
            print(f"Duration: {duration_seconds:.2f} seconds")
            print(f"Overall Status: {overall_status.value.upper()}")
            print(f"Test Success Rate: {success_rate:.1f}%")
            print(f"CI/CD Pipeline: {'✅' if ci_ok else '❌'}")
            print(f"Load Testing: {'✅' if load_ok else '❌'}")
            print(f"Disaster Recovery: {'✅' if dr_ok else '❌'}")
            print(f"Monitoring: {'✅' if monitoring_ok else '❌'}")
            
            if recommendations:
                print(f"\n💡 Recommendations:")
                for i, rec in enumerate(recommendations, 1):
                    print(f"{i}. {rec}")
            
            return summary
            
        except Exception as e:
            end_time = datetime.datetime.now()
            duration_seconds = (end_time - start_time).total_seconds()
            
            error_summary = QAExecutionSummary(
                execution_id=execution_id,
                start_time=start_time,
                end_time=end_time,
                duration_seconds=duration_seconds,
                total_tests_run=0,
                tests_passed=0,
                tests_failed=0,
                load_tests_run=0,
                ci_pipeline_runs=0,
                disaster_recovery_simulations=0,
                monitoring_cycles=0,
                overall_status=QASystemStatus.FAILED,
                recommendations=[f"Critical error during QA execution: {str(e)}"]
            )
            
            self.execution_history.append(error_summary)
            self.status = QASystemStatus.FAILED
            
            print(f"\n❌ QA Cycle Failed: {str(e)}")
            return error_summary
    
    def _generate_recommendations(self, test_rate: float, ci_ok: bool, load_ok: bool, 
                                 dr_ok: bool, monitoring_ok: bool) -> List[str]:
        """Generate improvement recommendations"""
        recommendations = []
        
        if test_rate < 95:
            recommendations.append("Investigate failing tests and improve code coverage")
        
        if not ci_ok:
            recommendations.append("Fix CI/CD pipeline failures before production deployment")
        
        if not load_ok:
            recommendations.append("Optimize system performance for high-traffic scenarios")
        
        if not dr_ok:
            recommendations.append("Strengthen disaster recovery procedures and backup strategies")
        
        if not monitoring_ok:
            recommendations.append("Improve system monitoring and alerting configurations")
        
        # Enterprise-grade recommendations
        if test_rate >= 95 and ci_ok and load_ok and dr_ok and monitoring_ok:
            recommendations.append("System meets enterprise standards - proceed with production deployment")
            recommendations.append("Schedule regular QA cycles to maintain quality standards")
            recommendations.append("Consider expanding test coverage for new features")
        
        return recommendations
    
    def generate_enterprise_report(self) -> Dict[str, Any]:
        """Generate comprehensive enterprise QA report"""
        if not self.execution_history:
            return {"message": "No QA executions available"}
        
        latest_execution = self.execution_history[-1]
        total_executions = len(self.execution_history)
        
        # Calculate historical metrics
        successful_executions = sum(1 for exec in self.execution_history 
                                 if exec.overall_status == QASystemStatus.HEALTHY)
        degraded_executions = sum(1 for exec in self.execution_history 
                                if exec.overall_status == QASystemStatus.DEGRADED)
        failed_executions = sum(1 for exec in self.execution_history 
                             if exec.overall_status == QASystemStatus.FAILED)
        
        avg_duration = sum(exec.duration_seconds for exec in self.execution_history) / total_executions
        
        report = {
            "executive_summary": {
                "current_status": self.status.value,
                "total_qa_cycles": total_executions,
                "success_rate": (successful_executions / total_executions) * 100,
                "latest_execution": latest_execution.execution_id,
                "average_duration_minutes": avg_duration / 60,
                "report_generated_at": datetime.datetime.now().isoformat()
            },
            "quality_metrics": {
                "total_tests_run": sum(exec.total_tests_run for exec in self.execution_history),
                "overall_test_success_rate": 0,
                "ci_pipeline_success_rate": 0,
                "load_test_success_rate": 0,
                "disaster_recovery_success_rate": 0
            },
            "system_capabilities": {
                "testing_framework": "✅ Enterprise-grade comprehensive testing",
                "ci_cd_pipeline": "✅ Automated pipeline with security scans",
                "load_testing": "✅ High-traffic scenario testing",
                "disaster_recovery": "✅ Business continuity planning",
                "monitoring": "✅ Real-time production monitoring"
            },
            "latest_execution": {
                "execution_id": latest_execution.execution_id,
                "status": latest_execution.overall_status.value,
                "duration_minutes": latest_execution.duration_seconds / 60,
                "test_results": {
                    "total_tests": latest_execution.total_tests_run,
                    "passed": latest_execution.tests_passed,
                    "failed": latest_execution.tests_failed,
                    "success_rate": (latest_execution.tests_passed / latest_execution.total_tests_run * 100) if latest_execution.total_tests_run > 0 else 0
                },
                "component_results": {
                    "ci_pipeline_runs": latest_execution.ci_pipeline_runs,
                    "load_tests_run": latest_execution.load_tests_run,
                    "disaster_recovery_simulations": latest_execution.disaster_recovery_simulations,
                    "monitoring_cycles": latest_execution.monitoring_cycles
                },
                "recommendations": latest_execution.recommendations
            },
            "compliance_status": {
                "enterprise_standards_met": latest_execution.overall_status == QASystemStatus.HEALTHY,
                "quality_assurance": "✅ Comprehensive testing framework",
                "continuous_integration": "✅ Automated CI/CD pipeline",
                "performance_testing": "✅ Load and stress testing",
                "business_continuity": "✅ Disaster recovery planning",
                "production_monitoring": "✅ Real-time monitoring and alerting"
            }
        }
        
        # Calculate quality metrics
        total_tests = sum(exec.total_tests_run for exec in self.execution_history)
        total_passed = sum(exec.tests_passed for exec in self.execution_history)
        
        if total_tests > 0:
            report["quality_metrics"]["overall_test_success_rate"] = (total_passed / total_tests) * 100
        
        return report


def main():
    """Main enterprise QA orchestrator"""
    orchestrator = EnterpriseQAOrchestrator()
    
    # Run complete QA cycle
    summary = orchestrator.run_complete_qa_cycle()
    
    # Generate enterprise report
    report = orchestrator.generate_enterprise_report()
    
    return {
        "qa_summary": summary,
        "enterprise_report": report
    }


if __name__ == "__main__":
    main()