@optimize Operator in TuskLang - Go Guide

⚡ Optimization Power: @optimize Operator Unleashed

TuskLang's @optimize operator is your performance rebellion. We don't bow to any king—especially not to slow, inefficient systems. Here's how to use @optimize in Go projects to automatically tune and optimize your application performance.

📋 Table of Contents

- What is @optimize? - Basic Usage - Optimization Targets - Performance Monitoring - Go Integration - Best Practices

🚀 What is @optimize?

The @optimize operator automatically optimizes configuration values based on performance metrics and system behavior. No more manual tuning—just pure, automated optimization.

🛠️ Basic Usage

[optimization]
connection_pool: @optimize("db_connections", 10, "response_time")
cache_size: @optimize("memory_cache", 1000, "hit_rate")
timeout: @optimize("api_timeout", 5000, "success_rate")

🎯 Optimization Targets

Database Optimization

[database]
pool_size: @optimize("connection_pool", 10, "query_time")
batch_size: @optimize("batch_processing", 100, "throughput")
timeout: @optimize("query_timeout", 30, "error_rate")

Memory Optimization

[memory]
cache_size: @optimize("cache_memory", 512, "cache_hit_rate")
buffer_size: @optimize("io_buffer", 4096, "io_throughput")
heap_size: @optimize("heap_memory", 1024, "gc_frequency")

Network Optimization

[network]
timeout: @optimize("request_timeout", 5000, "response_time")
retries: @optimize("retry_attempts", 3, "success_rate")
keepalive: @optimize("keepalive_time", 60, "connection_reuse")

📊 Performance Monitoring

[metrics]
response_time: @metrics("api_response_time_ms", 45)
throughput: @metrics("requests_per_second", 1000)
error_rate: @metrics("error_percentage", 0.1)
resource_usage: @metrics("cpu_usage_percent", 75)

🔗 Go Integration

// Access optimized values
poolSize := config.GetInt("pool_size")
cacheSize := config.GetInt("cache_size")
timeout := config.GetInt("timeout")
// Monitor performance
config.RecordMetric("response_time", 45)
config.RecordMetric("throughput", 1000)
config.RecordMetric("error_rate", 0.1)

Custom Optimization Logic

type Optimizer struct {
    target string
    metric string
    currentValue int
}
func (o *Optimizer) Optimize(metrics map[string]float64) int {
    // Implement your optimization algorithm
    if metrics[o.metric] > threshold {
        return o.currentValue * 2
    }
    return o.currentValue / 2
}
func (o *Optimizer) ApplyOptimization(newValue int) error {
    // Apply the optimized value
    o.currentValue = newValue
    return nil
}

🥇 Best Practices

- Start with conservative optimization ranges - Monitor optimization impact carefully - Implement rollback mechanisms - Document optimization objectives - Test optimizations in staging first

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TuskLang: Automated optimization with @optimize.