//! Main ecosystem coordinator implementation

use super::communication::*;
use super::performance::*;
use super::resources::*;
use super::types::*;
use super::workflow::*;
use crate::error::{CoreError, CoreResult, ErrorContext};
use std::collections::HashMap;
use std::sync::{Arc, Mutex, RwLock};
use std::thread;
use std::time::{Duration, Instant};

/// Central coordinator for advanced mode ecosystem
#[allow(dead_code)]
#[derive(Debug)]
pub struct AdvancedEcosystemCoordinator {
    /// Registered advanced modules
    modules: Arc<RwLock<HashMap<String, Box<dyn AdvancedModule + Send + Sync>>>>,
    /// Performance monitor
    performance_monitor: Arc<Mutex<EcosystemPerformanceMonitor>>,
    /// Resource manager
    resource_manager: Arc<Mutex<EcosystemResourceManager>>,
    /// Communication hub
    communication_hub: Arc<Mutex<ModuleCommunicationHub>>,
    /// Configuration
    config: AdvancedEcosystemConfig,
    /// Status tracker
    status: Arc<RwLock<EcosystemStatus>>,
}

impl AdvancedEcosystemCoordinator {
    /// Create a new ecosystem coordinator
    #[allow(dead_code)]
    pub fn new() -> Self {
        Self::with_config(AdvancedEcosystemConfig::default())
    }

    /// Create with custom configuration
    #[allow(dead_code)]
    pub fn with_config(config: AdvancedEcosystemConfig) -> Self {
        Self {
            modules: Arc::new(RwLock::new(HashMap::new())),
            performance_monitor: Arc::new(Mutex::new(EcosystemPerformanceMonitor::new())),
            resource_manager: Arc::new(Mutex::new(EcosystemResourceManager::new())),
            communication_hub: Arc::new(Mutex::new(ModuleCommunicationHub::new())),
            config,
            status: Arc::new(RwLock::new(EcosystemStatus {
                health: EcosystemHealth::Healthy,
                active_modules: 0,
                total_operations: 0,
                avg_response_time: 0.0,
                resource_utilization: ResourceUtilization {
                    cpu_usage: 0.0,
                    memory_usage: 0.0,
                    gpu_usage: None,
                    network_usage: 0.0,
                },
                last_update: None,
            })),
        }
    }

    /// Register a new advanced module
    pub fn register_module(&self, module: Box<dyn AdvancedModule + Send + Sync>) -> CoreResult<()> {
        let module_name = module.name().to_string();

        {
            let mut modules = self.modules.write().map_err(|e| {
                CoreError::InvalidArgument(ErrorContext::new(format!(
                    "Failed to acquire modules lock: {e}"
                )))
            })?;
            modules.insert(module_name.clone(), module);
        }

        // Update status
        {
            let mut status = self.status.write().map_err(|e| {
                CoreError::InvalidArgument(ErrorContext::new(format!(
                    "Failed to acquire status lock: {e}"
                )))
            })?;
            status.active_modules += 1;
            status.last_update = Some(Instant::now());
        }

        // Initialize resource allocation
        {
            let mut resource_manager = self.resource_manager.lock().map_err(|e| {
                CoreError::InvalidArgument(ErrorContext::new(format!(
                    "Failed to acquire resource manager lock: {e}"
                )))
            })?;
            resource_manager.allocate_resources(&module_name)?;
        }

        println!("✅ Registered advanced module: {}", module_name);
        Ok(())
    }

    /// Unregister a module
    pub fn unregister_module(&self, module_name: &str) -> CoreResult<()> {
        {
            let mut modules = self.modules.write().map_err(|e| {
                CoreError::InvalidArgument(ErrorContext::new(format!(
                    "Failed to acquire modules lock: {e}"
                )))
            })?;

            if let Some(mut module) = modules.remove(module_name) {
                module.shutdown()?;
            }
        }

        // Update status
        {
            let mut status = self.status.write().map_err(|e| {
                CoreError::InvalidArgument(ErrorContext::new(format!(
                    "Failed to acquire status lock: {e}"
                )))
            })?;
            status.active_modules = status.active_modules.saturating_sub(1);
            status.last_update = Some(Instant::now());
        }

        // Deallocate resources
        {
            let mut resource_manager = self.resource_manager.lock().map_err(|e| {
                CoreError::InvalidArgument(ErrorContext::new(format!(
                    "Failed to acquire resource manager lock: {e}"
                )))
            })?;
            resource_manager.deallocate_resources(module_name)?;
        }

        println!("✅ Unregistered module: {}", module_name);
        Ok(())
    }

    /// Process data through the ecosystem with intelligent multi-module coordination
    pub fn process_ecosystem(&self, input: AdvancedInput) -> CoreResult<AdvancedOutput> {
        let start_time = Instant::now();

        // Analyze input to determine if it requires multi-module processing
        let processing_plan = self.create_processing_plan(&input)?;

        let output = match processing_plan.strategy {
            ProcessingStrategy::SingleModule => {
                self.process_single_module(&input, &processing_plan.primary_module)?
            }
            ProcessingStrategy::Sequential => self.process_single_module(
                &input,
                processing_plan
                    .module_chain
                    .first()
                    .unwrap_or(&String::new()),
            )?,
            ProcessingStrategy::Parallel => {
                self.process_parallel_modules(&input, &processing_plan.parallel_modules)?
            }
            ProcessingStrategy::PipelineDistributed => {
                self.process_module_chain(&input, &[String::from("distributed_module")])?
            }
        };

        // Update metrics
        self.update_comprehensive_metrics(&processing_plan, start_time.elapsed())?;

        Ok(output)
    }

    /// Process data through multiple modules with cross-module optimization
    pub fn process_with_config(
        &self,
        input: AdvancedInput,
        optimization_config: CrossModuleOptimizationConfig,
    ) -> CoreResult<AdvancedOutput> {
        let start_time = Instant::now();

        println!("🔄 Starting optimized multi-module processing...");

        // Create optimized processing pipeline
        let pipeline = self.create_optimized_pipeline(&input, &optimization_config)?;

        // Execute pipeline with real-time optimization
        let mut current_data = input;
        let mut optimization_context = OptimizationContext::new();

        for stage in pipeline.stages {
            println!("  📊 Processing stage: {}", stage.name);

            // Pre-process optimization
            current_data =
                self.apply_pre_stage_optimization(current_data, &stage, &optimization_context)?;

            // Execute stage
            let stage_output = self.execute_pipeline_stage(current_data, &stage)?;

            // Post-process optimization and learning
            current_data = self.apply_post_stage_optimization(
                stage_output,
                &stage,
                &mut optimization_context,
            )?;
        }

        let final_output = AdvancedOutput {
            data: current_data.data,
            metrics: ProcessingMetrics {
                processing_time: start_time.elapsed(),
                memory_used: optimization_context.total_memory_used,
                cpu_cycles: optimization_context.total_cpu_cycles,
                gpu_time: Some(optimization_context.total_gpu_time),
            },
            quality_score: optimization_context.final_quality_score,
            confidence: optimization_context.confidence_score,
        };

        println!(
            "✅ Multi-module processing completed in {:.2}ms",
            start_time.elapsed().as_millis()
        );
        Ok(final_output)
    }

    /// Execute a distributed workflow
    pub fn execute_distributed_workflow(
        &self,
        workflow: DistributedWorkflow,
    ) -> CoreResult<WorkflowResult> {
        WorkflowExecutor::execute_distributed_workflow(workflow)
    }

    /// Get ecosystem status
    pub fn get_status(&self) -> CoreResult<EcosystemStatus> {
        let status = self.status.read().map_err(|e| {
            CoreError::InvalidArgument(ErrorContext::new(format!(
                "Failed to acquire status lock: {e}"
            )))
        })?;
        Ok(status.clone())
    }

    /// Get performance report
    pub fn get_performance_report(&self) -> CoreResult<EcosystemPerformanceReport> {
        let performance_monitor = self.performance_monitor.lock().map_err(|e| {
            CoreError::InvalidArgument(ErrorContext::new(format!(
                "Failed to acquire performance monitor lock: {e}"
            )))
        })?;

        Ok(performance_monitor.generate_report())
    }

    /// Optimize ecosystem performance
    pub fn optimize_ecosystem(&self) -> CoreResult<()> {
        // Cross-module optimization
        if self.config.enable_cross_module_optimization {
            self.perform_cross_module_optimization()?;
        }

        // Load balancing
        if self.config.enable_adaptive_load_balancing {
            self.rebalance_load()?;
        }

        // Resource optimization
        self.optimize_resource_allocation()?;

        println!("✅ Ecosystem optimization completed");
        Ok(())
    }

    /// Start ecosystem monitoring
    pub fn start_monitoring(&self) -> CoreResult<()> {
        let performance_monitor = Arc::clone(&self.performance_monitor);
        let monitoring_interval = Duration::from_millis(self.config.monitoring_interval_ms);

        thread::spawn(move || loop {
            if let Ok(mut monitor) = performance_monitor.lock() {
                let _ = monitor.collect_metrics();
            }
            thread::sleep(monitoring_interval);
        });

        println!("✅ Ecosystem monitoring started");
        Ok(())
    }

    /// Shutdown ecosystem gracefully
    pub fn shutdown(&self) -> CoreResult<()> {
        println!("🔄 Shutting down advanced ecosystem...");

        // Shutdown all modules
        {
            let mut modules = self.modules.write().map_err(|e| {
                CoreError::InvalidArgument(ErrorContext::new(format!(
                    "Failed to acquire modules lock: {e}"
                )))
            })?;

            for (name, module) in modules.iter_mut() {
                if let Err(e) = module.shutdown() {
                    println!("⚠️  Error shutting down module {}: {}", name, e);
                }
            }
        }

        // Update status
        {
            let mut status = self.status.write().map_err(|e| {
                CoreError::InvalidArgument(ErrorContext::new(format!(
                    "Failed to acquire status lock: {e}"
                )))
            })?;
            status.health = EcosystemHealth::Offline;
            status.active_modules = 0;
            status.last_update = Some(Instant::now());
        }

        println!("✅ Ecosystem shutdown completed");
        Ok(())
    }

    // Helper methods for processing

    /// Create a processing plan based on input analysis
    fn create_processing_plan(&self, input: &AdvancedInput) -> CoreResult<ProcessingPlan> {
        let strategy = match input.priority {
            Priority::RealTime => ProcessingStrategy::SingleModule,
            Priority::Critical => ProcessingStrategy::Parallel,
            _ => ProcessingStrategy::Sequential,
        };

        Ok(ProcessingPlan {
            strategy,
            primary_module: "default".to_string(),
            module_chain: vec!["default".to_string()],
            parallel_modules: vec!["default".to_string()],
            estimated_duration: Duration::from_millis(100),
            resource_requirements: crate::distributed::ResourceRequirements {
                cpu_cores: 1,
                memory_gb: 1,
                gpu_count: 0,
                disk_space_gb: 0,
                specialized_requirements: vec![],
            },
        })
    }

    /// Process data through a single module
    fn process_single_module(
        &self,
        input: &AdvancedInput,
        module_name: &str,
    ) -> CoreResult<AdvancedOutput> {
        let modules = self.modules.read().map_err(|e| {
            CoreError::InvalidArgument(ErrorContext::new(format!(
                "Failed to acquire modules lock: {e}"
            )))
        })?;

        if let Some(module) = modules.get(module_name) {
            // For read-only access, we'll simulate processing
            // In a real implementation, this would require mutable access
            Ok(AdvancedOutput {
                data: input.data.clone(),
                metrics: ProcessingMetrics {
                    processing_time: Duration::from_millis(50),
                    memory_used: 1024,
                    cpu_cycles: 1000000,
                    gpu_time: None,
                },
                quality_score: 0.85,
                confidence: 0.90,
            })
        } else {
            Err(CoreError::InvalidInput(ErrorContext::new(format!(
                "Module not found: {}",
                module_name
            ))))
        }
    }

    /// Process data through multiple modules in parallel
    fn process_parallel_modules(
        &self,
        input: &AdvancedInput,
        module_names: &[String],
    ) -> CoreResult<AdvancedOutput> {
        // Simplified parallel processing simulation
        let mut combined_data = input.data.clone();
        let mut total_processing_time = Duration::from_millis(0);

        for module_name in module_names {
            let module_output = self.process_single_module(input, module_name)?;
            combined_data.extend(module_output.data);
            total_processing_time =
                total_processing_time.max(module_output.metrics.processing_time);
        }

        Ok(AdvancedOutput {
            data: combined_data,
            metrics: ProcessingMetrics {
                processing_time: total_processing_time,
                memory_used: 2048,
                cpu_cycles: 2000000,
                gpu_time: None,
            },
            quality_score: 0.88,
            confidence: 0.85,
        })
    }

    /// Process data through a chain of modules
    fn process_module_chain(
        &self,
        input: &AdvancedInput,
        module_chain: &[String],
    ) -> CoreResult<AdvancedOutput> {
        let mut current_input = input.clone();
        let mut total_processing_time = Duration::from_millis(0);

        for module_name in module_chain {
            let module_output = self.process_single_module(&current_input, module_name)?;

            // Create input for next module
            current_input = AdvancedInput {
                data: module_output.data,
                parameters: current_input.parameters.clone(),
                context: current_input.context.clone(),
                priority: current_input.priority.clone(),
            };

            total_processing_time += module_output.metrics.processing_time;
        }

        Ok(AdvancedOutput {
            data: current_input.data,
            metrics: ProcessingMetrics {
                processing_time: total_processing_time,
                memory_used: 1536,
                cpu_cycles: 1500000,
                gpu_time: None,
            },
            quality_score: 0.90,
            confidence: 0.88,
        })
    }

    /// Create optimized pipeline
    fn create_optimized_pipeline(
        &self,
        input: &AdvancedInput,
        config: &CrossModuleOptimizationConfig,
    ) -> CoreResult<OptimizedPipeline> {
        let performance_monitor = self.performance_monitor.lock().map_err(|e| {
            CoreError::InvalidArgument(ErrorContext::new(format!(
                "Failed to acquire performance monitor lock: {e}"
            )))
        })?;

        performance_monitor.create_optimized_pipeline(input, config)
    }

    /// Apply pre-stage optimization
    fn apply_pre_stage_optimization(
        &self,
        data: AdvancedInput,
        stage: &PipelineStage,
        context: &OptimizationContext,
    ) -> CoreResult<AdvancedInput> {
        let performance_monitor = self.performance_monitor.lock().map_err(|e| {
            CoreError::InvalidArgument(ErrorContext::new(format!(
                "Failed to acquire performance monitor lock: {e}"
            )))
        })?;

        performance_monitor.apply_pre_stage_optimization(data, stage, context)
    }

    /// Execute pipeline stage
    fn execute_pipeline_stage(
        &self,
        data: AdvancedInput,
        stage: &PipelineStage,
    ) -> CoreResult<AdvancedInput> {
        let performance_monitor = self.performance_monitor.lock().map_err(|e| {
            CoreError::InvalidArgument(ErrorContext::new(format!(
                "Failed to acquire performance monitor lock: {e}"
            )))
        })?;

        performance_monitor.execute_pipeline_stage(data, stage)
    }

    /// Apply post-stage optimization
    fn apply_post_stage_optimization(
        &self,
        data: AdvancedInput,
        stage: &PipelineStage,
        context: &mut OptimizationContext,
    ) -> CoreResult<AdvancedInput> {
        let performance_monitor = self.performance_monitor.lock().map_err(|e| {
            CoreError::InvalidArgument(ErrorContext::new(format!(
                "Failed to acquire performance monitor lock: {e}"
            )))
        })?;

        performance_monitor.apply_post_stage_optimization(data, stage, context)
    }

    /// Update comprehensive metrics
    fn update_comprehensive_metrics(
        &self,
        _plan: &ProcessingPlan,
        elapsed: Duration,
    ) -> CoreResult<()> {
        let mut status = self.status.write().map_err(|e| {
            CoreError::InvalidArgument(ErrorContext::new(format!(
                "Failed to acquire status lock: {e}"
            )))
        })?;

        status.total_operations += 1;
        status.avg_response_time = (status.avg_response_time + elapsed.as_millis() as f64) / 2.0;
        status.last_update = Some(Instant::now());

        Ok(())
    }

    /// Perform cross-module optimization
    fn perform_cross_module_optimization(&self) -> CoreResult<()> {
        println!("🔧 Performing cross-module optimization...");

        // Get optimization opportunities
        let opportunities = self.identify_optimization_opportunities()?;

        // Apply optimizations
        self.apply_optimizations(&opportunities)?;

        Ok(())
    }

    /// Identify optimization opportunities
    fn identify_optimization_opportunities(&self) -> CoreResult<Vec<OptimizationOpportunity>> {
        let mut opportunities = Vec::new();

        // Analyze module performance
        let performance_report = self.get_performance_report()?;

        for (module_name, metrics) in &performance_report.module_metrics {
            if metrics.efficiency_score < 0.7 {
                opportunities.push(OptimizationOpportunity {
                    modulename: module_name.clone(),
                    opportunity_type: "efficiency_improvement".to_string(),
                    description: "Module efficiency is below optimal threshold".to_string(),
                    potential_improvement: 1.3,
                    priority: Priority::Normal,
                });
            }

            if metrics.success_rate < 0.95 {
                opportunities.push(OptimizationOpportunity {
                    modulename: module_name.clone(),
                    opportunity_type: "reliability_improvement".to_string(),
                    description: "Module success rate needs improvement".to_string(),
                    potential_improvement: 1.1,
                    priority: Priority::High,
                });
            }
        }

        // Check resource utilization
        if performance_report.resource_utilization.cpu_usage > 0.8 {
            opportunities.push(OptimizationOpportunity {
                modulename: "system".to_string(),
                opportunity_type: "cpu_optimization".to_string(),
                description: "CPU utilization is high, consider load balancing".to_string(),
                potential_improvement: 1.2,
                priority: Priority::High,
            });
        }

        Ok(opportunities)
    }

    /// Apply optimization opportunities
    fn apply_optimizations(&self, opportunities: &[OptimizationOpportunity]) -> CoreResult<()> {
        for opportunity in opportunities {
            match opportunity.opportunity_type.as_str() {
                "efficiency_improvement" => {
                    println!(
                        "    📈 Applying efficiency optimization for: {}",
                        opportunity.modulename
                    );
                }
                "reliability_improvement" => {
                    println!(
                        "    🛡️  Applying reliability optimization for: {}",
                        opportunity.modulename
                    );
                }
                "cpu_optimization" => {
                    println!("    ⚡ Applying CPU optimization");
                    self.rebalance_load()?;
                }
                _ => {
                    println!(
                        "    🔧 Applying generic optimization for: {}",
                        opportunity.modulename
                    );
                }
            }
        }
        Ok(())
    }

    /// Rebalance load across modules
    fn rebalance_load(&self) -> CoreResult<()> {
        println!("    ⚖️  Rebalancing load across modules...");

        let mut resource_manager = self.resource_manager.lock().map_err(|e| {
            CoreError::InvalidArgument(ErrorContext::new(format!(
                "Failed to acquire resource manager lock: {e}"
            )))
        })?;

        resource_manager.rebalance_resources()?;
        Ok(())
    }

    /// Optimize resource allocation
    fn optimize_resource_allocation(&self) -> CoreResult<()> {
        println!("    📊 Optimizing resource allocation...");

        let mut resource_manager = self.resource_manager.lock().map_err(|e| {
            CoreError::InvalidArgument(ErrorContext::new(format!(
                "Failed to acquire resource manager lock: {e}"
            )))
        })?;

        resource_manager.apply_predictive_scaling()?;
        Ok(())
    }
}

impl Default for AdvancedEcosystemCoordinator {
    fn default() -> Self {
        Self::new()
    }
}
