import { DataRelationManager } from '../../core/utils/data-relations'
import { UserGenerator } from '../../core/generators/users'
import { AudioGenerator } from '../../core/generators/audio'
import { ConversationGenerator } from '../../core/generators/conversations'
import { StreamServerFixtures } from '../../services/stream-server'
import { vezaFaker } from '../../core/utils/faker-config'
import { globalConfig } from '../../core/config'
import type { User, Audio, Message, Conversation } from '../../core/schemas/database'

/**
 * High Load Performance Scenario
 * 
 * Simulates high traffic conditions to test system performance and scalability
 */
export interface HighLoadScenarioContext {
  loadProfile: LoadProfile
  concurrentUsers: ConcurrentUser[]
  streamingSessions: StreamingSession[]
  messageFlood: MessageFlood[]
  systemMetrics: SystemMetrics
  testParameters: LoadTestParameters
}

export interface LoadProfile {
  name: string
  description: string
  duration: number // seconds
  rampUpTime: number // seconds
  peakUsers: number
  averageSessionDuration: number // seconds
  actionsPerUser: number
  expectedThroughput: number // requests per second
}

export interface ConcurrentUser {
  id: string
  user: User
  sessionStart: Date
  sessionEnd: Date
  actions: UserLoadAction[]
  currentActivity: 'streaming' | 'browsing' | 'chatting' | 'idle'
  connectionQuality: 'excellent' | 'good' | 'poor'
  deviceType: 'desktop' | 'mobile' | 'tablet'
}

export interface StreamingSession {
  id: string
  userId: string
  trackId: string
  startTime: Date
  duration: number // seconds
  quality: 'low' | 'medium' | 'high' | 'lossless'
  bitrate: number
  bufferEvents: BufferEvent[]
  networkConditions: NetworkCondition
}

export interface MessageFlood {
  conversationId: string
  participantIds: string[]
  messagesPerSecond: number
  duration: number // seconds
  totalMessages: number
  messageTypes: ('text' | 'image' | 'audio' | 'file')[]
}

export interface BufferEvent {
  timestamp: Date
  type: 'buffer_start' | 'buffer_end' | 'quality_change' | 'connection_drop'
  duration?: number // milliseconds
  metadata?: any
}

export interface NetworkCondition {
  bandwidth: number // Mbps
  latency: number // ms
  packetLoss: number // percentage
  stability: 'stable' | 'unstable' | 'intermittent'
}

export interface SystemMetrics {
  expectedLoad: {
    cpuUsage: number // percentage
    memoryUsage: number // percentage
    diskIO: number // MB/s
    networkIO: number // MB/s
    databaseConnections: number
    redisConnections: number
  }
  performanceTargets: {
    averageResponseTime: number // ms
    p95ResponseTime: number // ms
    errorRate: number // percentage
    throughput: number // requests per second
    concurrentStreams: number
  }
}

export interface LoadTestParameters {
  scenario: string
  environment: 'testing' | 'staging' | 'production'
  testType: 'stress' | 'load' | 'spike' | 'endurance'
  dataSize: 'small' | 'medium' | 'large' | 'xlarge'
  monitoring: {
    metricsInterval: number // seconds
    alertThresholds: AlertThreshold[]
    reportingEnabled: boolean
  }
}

export interface AlertThreshold {
  metric: string
  operator: '>' | '<' | '>=' | '<=' | '=='
  value: number
  severity: 'warning' | 'critical'
}

export interface UserLoadAction {
  type: 'login' | 'stream_track' | 'send_message' | 'create_playlist' | 'search' | 'browse'
  timestamp: Date
  duration: number // ms
  success: boolean
  responseTime: number // ms
  errorCode?: string
  metadata?: any
}

/**
 * High Load Scenario Generator
 */
export class HighLoadScenario {
  /**
   * Generate high load test scenario
   */
  static async setup(loadProfile?: Partial<LoadProfile>): Promise<HighLoadScenarioContext> {
    console.log('🚀 Setting up high load performance scenario...')
    
    const profile = this.createLoadProfile(loadProfile)
    console.log(`📊 Load profile: ${profile.name} - ${profile.peakUsers} concurrent users`)
    
    // Generate concurrent users
    console.log('👥 Generating concurrent users...')
    const concurrentUsers = await this.generateConcurrentUsers(profile.peakUsers)
    
    // Generate streaming sessions
    console.log('🎵 Setting up streaming sessions...')
    const streamingSessions = this.generateStreamingSessions(concurrentUsers, profile)
    
    // Generate message flood scenarios
    console.log('💬 Creating message flood scenarios...')
    const messageFlood = this.generateMessageFlood(concurrentUsers, profile)
    
    // Calculate system metrics
    const systemMetrics = this.calculateSystemMetrics(profile, concurrentUsers.length)
    
    // Setup test parameters
    const testParameters = this.createTestParameters(profile)
    
    const context: HighLoadScenarioContext = {
      loadProfile: profile,
      concurrentUsers,
      streamingSessions,
      messageFlood,
      systemMetrics,
      testParameters
    }
    
    console.log('✅ High load scenario setup complete')
    console.log(`📈 Expected throughput: ${profile.expectedThroughput} req/s`)
    console.log(`⏱️  Test duration: ${profile.duration}s`)
    
    return context
  }
  
  /**
   * Generate multiple load scenarios
   */
  static async setupMultipleScenarios(): Promise<HighLoadScenarioContext[]> {
    const scenarios: HighLoadScenarioContext[] = []
    
    // Light load scenario
    scenarios.push(await this.setup({
      name: 'Light Load',
      peakUsers: 100,
      duration: 300, // 5 minutes
      expectedThroughput: 50
    }))
    
    // Medium load scenario
    scenarios.push(await this.setup({
      name: 'Medium Load',
      peakUsers: 500,
      duration: 600, // 10 minutes
      expectedThroughput: 200
    }))
    
    // Heavy load scenario
    scenarios.push(await this.setup({
      name: 'Heavy Load',
      peakUsers: 1000,
      duration: 900, // 15 minutes
      expectedThroughput: 500
    }))
    
    // Spike test scenario
    scenarios.push(await this.setup({
      name: 'Spike Test',
      peakUsers: 2000,
      duration: 300, // 5 minutes
      rampUpTime: 30, // Quick ramp up
      expectedThroughput: 1000
    }))
    
    return scenarios
  }
  
  /**
   * Simulate load test execution
   */
  static simulateLoadTest(context: HighLoadScenarioContext): {
    executionPlan: LoadTestExecution[]
    expectedResults: LoadTestResults
    monitoringPlan: MonitoringPlan
  } {
    console.log(`🎯 Simulating load test: ${context.loadProfile.name}`)
    
    const executionPlan = this.createExecutionPlan(context)
    const expectedResults = this.calculateExpectedResults(context)
    const monitoringPlan = this.createMonitoringPlan(context)
    
    console.log('✅ Load test simulation complete')
    
    return {
      executionPlan,
      expectedResults,
      monitoringPlan
    }
  }
  
  /**
   * Generate stress test data
   */
  static generateStressTestData(maxUsers: number = 5000): {
    users: User[]
    tracks: Audio[]
    concurrentSessions: number
    expectedBottlenecks: string[]
  } {
    console.log(`💥 Generating stress test data for ${maxUsers} users...`)
    
    // Generate users for stress test
    const users = UserGenerator.generateBatch(maxUsers, {
      status: 'active',
      withStats: false // Minimal data for performance
    })
    
    // Generate tracks for streaming
    const tracks = AudioGenerator.generateBatch(1000, {
      isPopular: true, // Popular tracks will be requested more
      withWaveform: false // Skip waveform for performance
    })
    
    // Calculate concurrent sessions (70% of users streaming)
    const concurrentSessions = Math.floor(maxUsers * 0.7)
    
    // Identify expected bottlenecks
    const expectedBottlenecks = [
      'Database connection pool exhaustion',
      'Redis memory usage spike',
      'Network bandwidth saturation',
      'CPU usage from audio processing',
      'WebSocket connection limits',
      'File system I/O for audio streaming'
    ]
    
    console.log(`✅ Stress test data generated: ${users.length} users, ${tracks.length} tracks`)
    
    return {
      users,
      tracks,
      concurrentSessions,
      expectedBottlenecks
    }
  }
  
  /**
   * Private helper methods
   */
  private static createLoadProfile(partial?: Partial<LoadProfile>): LoadProfile {
    const defaultProfile: LoadProfile = {
      name: 'Standard Load Test',
      description: 'Standard load testing scenario for Veza Platform',
      duration: 600, // 10 minutes
      rampUpTime: 120, // 2 minutes
      peakUsers: globalConfig.generation.performance.concurrentUsers,
      averageSessionDuration: 300, // 5 minutes
      actionsPerUser: 20,
      expectedThroughput: 100 // requests per second
    }
    
    return { ...defaultProfile, ...partial }
  }
  
  private static async generateConcurrentUsers(count: number): Promise<ConcurrentUser[]> {
    const users: ConcurrentUser[] = []
    const startTime = new Date()
    
    for (let i = 0; i < count; i++) {
      const user = UserGenerator.generate({
        status: 'active',
        withStats: false
      })
      
      const sessionDuration = vezaFaker.number.int({ min: 180, max: 1800 }) // 3-30 minutes
      const sessionStart = new Date(startTime.getTime() + vezaFaker.number.int({ min: 0, max: 120000 })) // Stagger logins
      
      const concurrentUser: ConcurrentUser = {
        id: user.id,
        user,
        sessionStart,
        sessionEnd: new Date(sessionStart.getTime() + sessionDuration * 1000),
        actions: this.generateUserActions(sessionDuration),
        currentActivity: vezaFaker.helpers.arrayElement(['streaming', 'browsing', 'chatting', 'idle']),
        connectionQuality: vezaFaker.utils.weightedChoice([
          { item: 'excellent', weight: 0.3 },
          { item: 'good', weight: 0.5 },
          { item: 'poor', weight: 0.2 }
        ]),
        deviceType: vezaFaker.helpers.arrayElement(['desktop', 'mobile', 'tablet'])
      }
      
      users.push(concurrentUser)
    }
    
    return users
  }
  
  private static generateStreamingSessions(
    users: ConcurrentUser[], 
    profile: LoadProfile
  ): StreamingSession[] {
    const sessions: StreamingSession[] = []
    
    // 70% of users will be streaming
    const streamingUsers = users.filter(() => vezaFaker.datatype.boolean({ probability: 0.7 }))
    
    streamingUsers.forEach(concurrentUser => {
      const sessionCount = vezaFaker.number.int({ min: 1, max: 3 })
      
      for (let i = 0; i < sessionCount; i++) {
        const session = StreamServerFixtures.generateStreamingSession(
          concurrentUser.user.id,
          vezaFaker.string.uuid() // Random track ID
        )
        
        // Add load-specific data
        const streamingSession: StreamingSession = {
          ...session,
          bufferEvents: this.generateBufferEvents(session.duration),
          networkConditions: this.generateNetworkConditions(concurrentUser.connectionQuality)
        }
        
        sessions.push(streamingSession)
      }
    })
    
    return sessions
  }
  
  private static generateMessageFlood(
    users: ConcurrentUser[], 
    profile: LoadProfile
  ): MessageFlood[] {
    const floods: MessageFlood[] = []
    
    // Create high-traffic conversations
    const highTrafficConversations = Math.floor(profile.peakUsers / 50) // One per 50 users
    
    for (let i = 0; i < highTrafficConversations; i++) {
      const participantCount = vezaFaker.number.int({ min: 20, max: 100 })
      const participants = vezaFaker.helpers.arrayElements(users, participantCount)
      
      const flood: MessageFlood = {
        conversationId: vezaFaker.string.uuid(),
        participantIds: participants.map(p => p.id),
        messagesPerSecond: vezaFaker.number.int({ min: 5, max: 50 }),
        duration: profile.duration * 0.8, // 80% of test duration
        totalMessages: 0, // Will be calculated
        messageTypes: ['text', 'image', 'audio']
      }
      
      flood.totalMessages = Math.floor(flood.messagesPerSecond * flood.duration)
      floods.push(flood)
    }
    
    return floods
  }
  
  private static generateUserActions(sessionDuration: number): UserLoadAction[] {
    const actions: UserLoadAction[] = []
    const actionCount = Math.floor(sessionDuration / 15) // One action every 15 seconds on average
    
    const actionTypes = ['stream_track', 'send_message', 'search', 'browse', 'create_playlist']
    const weights = [0.4, 0.25, 0.15, 0.15, 0.05] // Stream track is most common
    
    for (let i = 0; i < actionCount; i++) {
      const actionType = vezaFaker.utils.weightedChoice(
        actionTypes.map((type, index) => ({ item: type, weight: weights[index] || 0.1 }))
      ) as any
      
      const timestamp = new Date(Date.now() + i * 15000 + vezaFaker.number.int({ min: 0, max: 10000 }))
      const success = vezaFaker.datatype.boolean({ probability: 0.95 }) // 95% success rate
      
      actions.push({
        type: actionType,
        timestamp,
        duration: this.getActionDuration(actionType),
        success,
        responseTime: success ? 
          vezaFaker.number.int({ min: 50, max: 500 }) : 
          vezaFaker.number.int({ min: 1000, max: 5000 }),
        errorCode: success ? '' : this.getErrorCode(actionType),
        metadata: this.getActionMetadata(actionType)
      })
    }
    
    return actions
  }
  
  private static generateBufferEvents(duration: number): BufferEvent[] {
    const events: BufferEvent[] = []
    const eventCount = Math.floor(duration / 60) // One event per minute on average
    
    for (let i = 0; i < eventCount; i++) {
      const eventType = vezaFaker.helpers.arrayElement([
        'buffer_start', 'buffer_end', 'quality_change', 'connection_drop'
      ]) as any
      
      events.push({
        timestamp: new Date(Date.now() + i * 60000 + vezaFaker.number.int({ min: 0, max: 30000 })),
        type: eventType,
        duration: eventType.includes('buffer') ? vezaFaker.number.int({ min: 100, max: 3000 }) : undefined,
        metadata: {
          reason: this.getBufferEventReason(eventType),
          severity: vezaFaker.helpers.arrayElement(['low', 'medium', 'high'])
        }
      })
    }
    
    return events
  }
  
  private static generateNetworkConditions(quality: string): NetworkCondition {
    const conditions = {
      excellent: {
        bandwidth: vezaFaker.number.int({ min: 50, max: 100 }),
        latency: vezaFaker.number.int({ min: 10, max: 30 }),
        packetLoss: vezaFaker.number.float({ min: 0, max: 0.1 }),
        stability: 'stable' as const
      },
      good: {
        bandwidth: vezaFaker.number.int({ min: 20, max: 50 }),
        latency: vezaFaker.number.int({ min: 30, max: 100 }),
        packetLoss: vezaFaker.number.float({ min: 0.1, max: 1 }),
        stability: vezaFaker.helpers.arrayElement(['stable', 'unstable']) as any
      },
      poor: {
        bandwidth: vezaFaker.number.int({ min: 5, max: 20 }),
        latency: vezaFaker.number.int({ min: 100, max: 500 }),
        packetLoss: vezaFaker.number.float({ min: 1, max: 5 }),
        stability: vezaFaker.helpers.arrayElement(['unstable', 'intermittent']) as any
      }
    }
    
    return conditions[quality as keyof typeof conditions] || conditions.good
  }
  
  private static calculateSystemMetrics(profile: LoadProfile, userCount: number): SystemMetrics {
    // Estimate system resource usage based on load
    const baseLoad = userCount / 1000 // Base calculation per 1000 users
    
    return {
      expectedLoad: {
        cpuUsage: Math.min(90, 20 + baseLoad * 30), // 20-90%
        memoryUsage: Math.min(85, 30 + baseLoad * 25), // 30-85%
        diskIO: Math.min(100, 10 + baseLoad * 40), // MB/s
        networkIO: Math.min(500, 50 + baseLoad * 200), // MB/s
        databaseConnections: Math.min(100, 10 + Math.floor(baseLoad * 50)),
        redisConnections: Math.min(200, 20 + Math.floor(baseLoad * 80))
      },
      performanceTargets: {
        averageResponseTime: 200, // ms
        p95ResponseTime: 500, // ms
        errorRate: 1, // 1% error rate acceptable
        throughput: profile.expectedThroughput,
        concurrentStreams: Math.floor(userCount * 0.7)
      }
    }
  }
  
  private static createTestParameters(profile: LoadProfile): LoadTestParameters {
    return {
      scenario: profile.name,
      environment: 'testing',
      testType: 'load',
      dataSize: profile.peakUsers > 1000 ? 'large' : 'medium',
      monitoring: {
        metricsInterval: 10, // seconds
        alertThresholds: [
          { metric: 'response_time_p95', operator: '>', value: 1000, severity: 'warning' },
          { metric: 'error_rate', operator: '>', value: 5, severity: 'critical' },
          { metric: 'cpu_usage', operator: '>', value: 90, severity: 'warning' },
          { metric: 'memory_usage', operator: '>', value: 90, severity: 'critical' }
        ],
        reportingEnabled: true
      }
    }
  }
  
  private static createExecutionPlan(context: HighLoadScenarioContext): LoadTestExecution[] {
    const plan: LoadTestExecution[] = []
    const { loadProfile } = context
    
    // Ramp up phase
    plan.push({
      phase: 'ramp_up',
      duration: loadProfile.rampUpTime,
      startUsers: 0,
      endUsers: loadProfile.peakUsers,
      description: 'Gradually increase user load'
    })
    
    // Steady state phase
    plan.push({
      phase: 'steady_state',
      duration: loadProfile.duration - loadProfile.rampUpTime - 60,
      startUsers: loadProfile.peakUsers,
      endUsers: loadProfile.peakUsers,
      description: 'Maintain peak load'
    })
    
    // Ramp down phase
    plan.push({
      phase: 'ramp_down',
      duration: 60,
      startUsers: loadProfile.peakUsers,
      endUsers: 0,
      description: 'Gradually decrease user load'
    })
    
    return plan
  }
  
  private static calculateExpectedResults(context: HighLoadScenarioContext): LoadTestResults {
    const { loadProfile, systemMetrics } = context
    
    return {
      throughput: {
        expected: loadProfile.expectedThroughput,
        minimum: loadProfile.expectedThroughput * 0.8,
        maximum: loadProfile.expectedThroughput * 1.2
      },
      responseTime: {
        average: systemMetrics.performanceTargets.averageResponseTime,
        p95: systemMetrics.performanceTargets.p95ResponseTime,
        p99: systemMetrics.performanceTargets.p95ResponseTime * 1.5
      },
      errorRate: {
        expected: systemMetrics.performanceTargets.errorRate,
        maximum: 5 // 5% maximum acceptable error rate
      },
      resourceUsage: systemMetrics.expectedLoad,
      bottlenecks: [
        'Database connection pool under high concurrent access',
        'Redis memory usage during peak streaming',
        'Network bandwidth for concurrent audio streams',
        'WebSocket connection management'
      ]
    }
  }
  
  private static createMonitoringPlan(context: HighLoadScenarioContext): MonitoringPlan {
    return {
      metrics: [
        'response_time_avg',
        'response_time_p95',
        'response_time_p99',
        'throughput_rps',
        'error_rate_percent',
        'cpu_usage_percent',
        'memory_usage_percent',
        'disk_io_mbps',
        'network_io_mbps',
        'active_connections',
        'streaming_sessions_count',
        'message_queue_size'
      ],
      alerts: context.testParameters.monitoring.alertThresholds,
      reports: [
        'Real-time dashboard',
        'Performance summary report',
        'Error analysis report',
        'Resource utilization report',
        'Bottleneck identification report'
      ],
      frequency: context.testParameters.monitoring.metricsInterval
    }
  }
  
  private static getActionDuration(actionType: string): number {
    const durations = {
      login: vezaFaker.number.int({ min: 1000, max: 3000 }),
      stream_track: vezaFaker.number.int({ min: 30000, max: 300000 }), // 30s to 5min
      send_message: vezaFaker.number.int({ min: 500, max: 2000 }),
      create_playlist: vezaFaker.number.int({ min: 5000, max: 15000 }),
      search: vezaFaker.number.int({ min: 200, max: 1000 }),
      browse: vezaFaker.number.int({ min: 2000, max: 10000 })
    }
    
    return durations[actionType as keyof typeof durations] || 1000
  }
  
  private static getErrorCode(actionType: string): string {
    const errorCodes = {
      login: vezaFaker.helpers.arrayElement(['AUTH_FAILED', 'RATE_LIMITED', 'SERVER_ERROR']),
      stream_track: vezaFaker.helpers.arrayElement(['TRACK_NOT_FOUND', 'STREAMING_ERROR', 'BANDWIDTH_LIMIT']),
      send_message: vezaFaker.helpers.arrayElement(['MESSAGE_TOO_LONG', 'RATE_LIMITED', 'CONVERSATION_NOT_FOUND']),
      create_playlist: vezaFaker.helpers.arrayElement(['INVALID_DATA', 'QUOTA_EXCEEDED', 'SERVER_ERROR']),
      search: vezaFaker.helpers.arrayElement(['INVALID_QUERY', 'SEARCH_TIMEOUT', 'SERVER_ERROR']),
      browse: vezaFaker.helpers.arrayElement(['PAGE_NOT_FOUND', 'SERVER_ERROR', 'TIMEOUT'])
    }
    
    return errorCodes[actionType as keyof typeof errorCodes] || 'UNKNOWN_ERROR'
  }
  
  private static getActionMetadata(actionType: string): any {
    switch (actionType) {
      case 'stream_track':
        return {
          quality: vezaFaker.helpers.arrayElement(['low', 'medium', 'high']),
          duration: vezaFaker.number.int({ min: 30, max: 300 })
        }
      case 'search':
        return {
          query: vezaFaker.music.songTitle(),
          filters: vezaFaker.helpers.arrayElements(['genre', 'artist', 'year'], 2)
        }
      case 'send_message':
        return {
          messageLength: vezaFaker.number.int({ min: 10, max: 500 }),
          hasAttachment: vezaFaker.datatype.boolean({ probability: 0.1 })
        }
      default:
        return {}
    }
  }
  
  private static getBufferEventReason(eventType: string): string {
    const reasons = {
      buffer_start: vezaFaker.helpers.arrayElement(['slow_connection', 'server_load', 'network_congestion']),
      buffer_end: 'buffer_filled',
      quality_change: vezaFaker.helpers.arrayElement(['bandwidth_adaptation', 'user_preference', 'automatic_adjustment']),
      connection_drop: vezaFaker.helpers.arrayElement(['network_timeout', 'server_restart', 'client_disconnect'])
    }
    
    return reasons[eventType as keyof typeof reasons] || 'unknown'
  }
}

// Additional interfaces for the load test execution
interface LoadTestExecution {
  phase: string
  duration: number
  startUsers: number
  endUsers: number
  description: string
}

interface LoadTestResults {
  throughput: {
    expected: number
    minimum: number
    maximum: number
  }
  responseTime: {
    average: number
    p95: number
    p99: number
  }
  errorRate: {
    expected: number
    maximum: number
  }
  resourceUsage: any
  bottlenecks: string[]
}

interface MonitoringPlan {
  metrics: string[]
  alerts: AlertThreshold[]
  reports: string[]
  frequency: number
}

/**
 * Export scenario configuration
 */
export const HIGH_LOAD_SCENARIO = {
  name: 'High Load Performance Test',
  description: 'Comprehensive load testing scenario for system performance validation',
  duration: 'Variable (5-15 minutes)',
  complexity: 'high',
  userTypes: ['concurrent_users'],
  expectedOutcomes: [
    'System handles peak load without degradation',
    'Response times remain within acceptable limits',
    'Error rates stay below threshold',
    'Resource usage is optimized',
    'Bottlenecks are identified and documented'
  ],
  testCoverage: [
    'concurrent_user_handling',
    'streaming_performance',
    'database_scalability',
    'redis_cache_performance',
    'websocket_connections',
    'api_response_times',
    'error_handling_under_load'
  ]
}