Files
mev-beta/pkg/arbitrum/enhanced_example.go
Krypto Kajun 3f69aeafcf fix: resolve all compilation issues across transport and lifecycle packages
- Fixed duplicate type declarations in transport package
- Removed unused variables in lifecycle and dependency injection
- Fixed big.Int arithmetic operations in uniswap contracts
- Added missing methods to MetricsCollector (IncrementCounter, RecordLatency, etc.)
- Fixed jitter calculation in TCP transport retry logic
- Updated ComponentHealth field access to use transport type
- Ensured all core packages build successfully

All major compilation errors resolved:
 Transport package builds clean
 Lifecycle package builds clean
 Main MEV bot application builds clean
 Fixed method signature mismatches
 Resolved type conflicts and duplications

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-09-19 17:23:14 -05:00

600 lines
17 KiB
Go

package arbitrum
import (
"fmt"
"log"
"time"
"github.com/fraktal/mev-beta/internal/logger"
"github.com/fraktal/mev-beta/pkg/oracle"
)
// ExampleUsage demonstrates how to use the enhanced DEX parser
func ExampleUsage() {
// Initialize logger
logger := logger.New("enhanced-parser", "info", "json")
// Initialize price oracle (placeholder)
priceOracle := &oracle.PriceOracle{} // This would be properly initialized
// Create enhanced parser configuration
config := &EnhancedParserConfig{
RPCEndpoint: "wss://arbitrum-mainnet.core.chainstack.com/your-api-key",
RPCTimeout: 30 * time.Second,
MaxRetries: 3,
EnabledProtocols: []Protocol{
ProtocolUniswapV2, ProtocolUniswapV3,
ProtocolSushiSwapV2, ProtocolSushiSwapV3,
ProtocolCamelotV2, ProtocolCamelotV3,
ProtocolTraderJoeV1, ProtocolTraderJoeV2, ProtocolTraderJoeLB,
ProtocolCurve, ProtocolBalancerV2,
ProtocolKyberClassic, ProtocolKyberElastic,
ProtocolGMX, ProtocolRamses, ProtocolChronos,
},
MinLiquidityUSD: 1000.0,
MaxSlippageBps: 1000, // 10%
EnablePoolDiscovery: true,
EnableEventEnrichment: true,
MaxWorkers: 10,
CacheSize: 10000,
CacheTTL: 1 * time.Hour,
BatchSize: 100,
EnableMetrics: true,
MetricsInterval: 1 * time.Minute,
EnableHealthCheck: true,
}
// Create enhanced parser
parser, err := NewEnhancedDEXParser(config, logger, priceOracle)
if err != nil {
log.Fatalf("Failed to create enhanced parser: %v", err)
}
defer parser.Close()
// Example 1: Parse a specific transaction
exampleParseTransaction(parser)
// Example 2: Parse a block
exampleParseBlock(parser)
// Example 3: Monitor real-time events
exampleRealTimeMonitoring(parser)
// Example 4: Analyze parser metrics
exampleAnalyzeMetrics(parser)
}
// exampleParseTransaction demonstrates parsing a specific transaction
func exampleParseTransaction(parser *EnhancedDEXParser) {
fmt.Println("=== Example: Parse Specific Transaction ===")
// This would be a real transaction hash from Arbitrum
// txHash := common.HexToHash("0x1234567890abcdef...")
// For demonstration, we'll show the expected workflow:
/*
// Get transaction
tx, receipt, err := getTransactionAndReceipt(txHash)
if err != nil {
log.Printf("Failed to get transaction: %v", err)
return
}
// Parse transaction
result, err := parser.ParseTransaction(tx, receipt)
if err != nil {
log.Printf("Failed to parse transaction: %v", err)
return
}
// Display results
fmt.Printf("Found %d DEX events:\n", len(result.Events))
for i, event := range result.Events {
fmt.Printf("Event %d:\n", i+1)
fmt.Printf(" Protocol: %s\n", event.Protocol)
fmt.Printf(" Type: %s\n", event.EventType)
fmt.Printf(" Contract: %s\n", event.ContractAddress.Hex())
if event.AmountIn != nil {
fmt.Printf(" Amount In: %s\n", event.AmountIn.String())
}
if event.AmountOut != nil {
fmt.Printf(" Amount Out: %s\n", event.AmountOut.String())
}
fmt.Printf(" Token In: %s\n", event.TokenInSymbol)
fmt.Printf(" Token Out: %s\n", event.TokenOutSymbol)
if event.AmountInUSD > 0 {
fmt.Printf(" Value USD: $%.2f\n", event.AmountInUSD)
}
fmt.Printf(" Is MEV: %t\n", event.IsMEV)
if event.IsMEV {
fmt.Printf(" MEV Type: %s\n", event.MEVType)
fmt.Printf(" Profit: $%.2f\n", event.ProfitUSD)
}
fmt.Println()
}
fmt.Printf("Discovered %d new pools\n", len(result.NewPools))
fmt.Printf("Processing time: %dms\n", result.ProcessingTimeMs)
*/
fmt.Println("Transaction parsing example completed (placeholder)")
}
// exampleParseBlock demonstrates parsing an entire block
func exampleParseBlock(parser *EnhancedDEXParser) {
fmt.Println("=== Example: Parse Block ===")
// Parse a recent block (this would be a real block number)
_ = uint64(200000000) // Example block number placeholder
// Parse block
/*
result, err := parser.ParseBlock(blockNumber)
if err != nil {
log.Printf("Failed to parse block: %v", err)
return
}
// Analyze results
protocolCounts := make(map[Protocol]int)
eventTypeCounts := make(map[EventType]int)
totalVolumeUSD := 0.0
mevCount := 0
for _, event := range result.Events {
protocolCounts[event.Protocol]++
eventTypeCounts[event.EventType]++
totalVolumeUSD += event.AmountInUSD
if event.IsMEV {
mevCount++
}
}
fmt.Printf("Block %d Analysis:\n", blockNumber)
fmt.Printf(" Total Events: %d\n", len(result.Events))
fmt.Printf(" Total Volume: $%.2f\n", totalVolumeUSD)
fmt.Printf(" MEV Events: %d\n", mevCount)
fmt.Printf(" New Pools: %d\n", len(result.NewPools))
fmt.Printf(" Errors: %d\n", len(result.Errors))
fmt.Println(" Protocol Breakdown:")
for protocol, count := range protocolCounts {
fmt.Printf(" %s: %d events\n", protocol, count)
}
fmt.Println(" Event Type Breakdown:")
for eventType, count := range eventTypeCounts {
fmt.Printf(" %s: %d events\n", eventType, count)
}
*/
fmt.Println("Block parsing example completed (placeholder)")
}
// exampleRealTimeMonitoring demonstrates real-time event monitoring
func exampleRealTimeMonitoring(parser *EnhancedDEXParser) {
fmt.Println("=== Example: Real-Time Monitoring ===")
// This would set up real-time monitoring
/*
ctx, cancel := context.WithTimeout(context.Background(), 5*time.Minute)
defer cancel()
// Subscribe to new blocks
blockChan := make(chan uint64, 100)
go subscribeToNewBlocks(ctx, blockChan) // This would be implemented
// Process blocks as they arrive
for {
select {
case blockNumber := <-blockChan:
go func(bn uint64) {
result, err := parser.ParseBlock(bn)
if err != nil {
log.Printf("Failed to parse block %d: %v", bn, err)
return
}
// Filter for high-value or MEV events
for _, event := range result.Events {
if event.AmountInUSD > 10000 || event.IsMEV {
log.Printf("High-value event detected: %s %s $%.2f",
event.Protocol, event.EventType, event.AmountInUSD)
if event.IsMEV {
log.Printf("MEV opportunity: %s profit $%.2f",
event.MEVType, event.ProfitUSD)
}
}
}
}(blockNumber)
case <-ctx.Done():
return
}
}
*/
fmt.Println("Real-time monitoring example completed (placeholder)")
}
// exampleAnalyzeMetrics demonstrates how to analyze parser performance
func exampleAnalyzeMetrics(parser *EnhancedDEXParser) {
fmt.Println("=== Example: Parser Metrics Analysis ===")
// Get current metrics
metrics := parser.GetMetrics()
fmt.Printf("Parser Performance Metrics:\n")
fmt.Printf(" Uptime: %v\n", time.Since(metrics.StartTime))
fmt.Printf(" Total Transactions Parsed: %d\n", metrics.TotalTransactionsParsed)
fmt.Printf(" Total Events Parsed: %d\n", metrics.TotalEventsParsed)
fmt.Printf(" Total Pools Discovered: %d\n", metrics.TotalPoolsDiscovered)
fmt.Printf(" Parse Error Count: %d\n", metrics.ParseErrorCount)
fmt.Printf(" Average Processing Time: %.2fms\n", metrics.AvgProcessingTimeMs)
fmt.Printf(" Last Processed Block: %d\n", metrics.LastProcessedBlock)
fmt.Println(" Protocol Breakdown:")
for protocol, count := range metrics.ProtocolBreakdown {
fmt.Printf(" %s: %d events\n", protocol, count)
}
fmt.Println(" Event Type Breakdown:")
for eventType, count := range metrics.EventTypeBreakdown {
fmt.Printf(" %s: %d events\n", eventType, count)
}
// Calculate error rate
if metrics.TotalTransactionsParsed > 0 {
errorRate := float64(metrics.ParseErrorCount) / float64(metrics.TotalTransactionsParsed) * 100
fmt.Printf(" Error Rate: %.2f%%\n", errorRate)
}
// Performance assessment
if metrics.AvgProcessingTimeMs < 100 {
fmt.Println(" Performance: Excellent")
} else if metrics.AvgProcessingTimeMs < 500 {
fmt.Println(" Performance: Good")
} else {
fmt.Println(" Performance: Needs optimization")
}
}
// IntegrationExample shows how to integrate with existing MEV bot architecture
func IntegrationExample() {
fmt.Println("=== Integration with Existing MEV Bot ===")
// This shows how the enhanced parser would integrate with the existing
// MEV bot architecture described in the codebase
/*
// 1. Initialize enhanced parser
config := DefaultEnhancedParserConfig()
config.RPCEndpoint = "wss://arbitrum-mainnet.core.chainstack.com/your-api-key"
logger := logger.New(logger.Config{Level: "info"})
oracle := &oracle.PriceOracle{} // Initialize with actual oracle
parser, err := NewEnhancedDEXParser(config, logger, oracle)
if err != nil {
log.Fatalf("Failed to create parser: %v", err)
}
defer parser.Close()
// 2. Integrate with existing arbitrage detection
// Replace the existing simple parser with enhanced parser in:
// - pkg/market/pipeline.go
// - pkg/monitor/concurrent.go
// - pkg/scanner/concurrent.go
// 3. Example integration point in market pipeline
func (p *MarketPipeline) ProcessTransaction(tx *types.Transaction, receipt *types.Receipt) error {
// Use enhanced parser instead of simple parser
result, err := p.enhancedParser.ParseTransaction(tx, receipt)
if err != nil {
return fmt.Errorf("enhanced parsing failed: %w", err)
}
// Process each detected DEX event
for _, event := range result.Events {
// Convert to existing arbitrage opportunity format
opportunity := &ArbitrageOpportunity{
Protocol: string(event.Protocol),
TokenIn: event.TokenIn,
TokenOut: event.TokenOut,
AmountIn: event.AmountIn,
AmountOut: event.AmountOut,
ExpectedProfit: event.ProfitUSD,
PoolAddress: event.PoolAddress,
Timestamp: event.Timestamp,
}
// Apply existing arbitrage detection logic
if p.isArbitrageOpportunity(opportunity) {
p.opportunityChannel <- opportunity
}
}
return nil
}
// 4. Enhanced MEV detection
func (p *MarketPipeline) detectMEVOpportunities(events []*EnhancedDEXEvent) {
for _, event := range events {
if event.IsMEV {
switch event.MEVType {
case "arbitrage":
p.handleArbitrageOpportunity(event)
case "sandwich":
p.handleSandwichOpportunity(event)
case "liquidation":
p.handleLiquidationOpportunity(event)
}
}
}
}
// 5. Pool discovery integration
func (p *PoolDiscovery) discoverNewPools() {
// Use enhanced parser's pool discovery
pools, err := p.enhancedParser.DiscoverPools(latestBlock-1000, latestBlock)
if err != nil {
p.logger.Error("Pool discovery failed", "error", err)
return
}
for _, pool := range pools {
// Add to existing pool registry
p.addPool(pool)
// Update pool cache
p.poolCache.AddPool(pool)
}
}
*/
fmt.Println("Integration example completed (placeholder)")
}
// BenchmarkExample demonstrates performance testing
func BenchmarkExample() {
fmt.Println("=== Performance Benchmark ===")
/*
// This would run performance benchmarks
config := DefaultEnhancedParserConfig()
config.MaxWorkers = 20
config.EnableMetrics = true
parser, _ := NewEnhancedDEXParser(config, logger, oracle)
defer parser.Close()
// Benchmark block parsing
startTime := time.Now()
blockCount := 1000
for i := 0; i < blockCount; i++ {
blockNumber := uint64(200000000 + i)
_, err := parser.ParseBlock(blockNumber)
if err != nil {
log.Printf("Failed to parse block %d: %v", blockNumber, err)
}
}
duration := time.Since(startTime)
blocksPerSecond := float64(blockCount) / duration.Seconds()
fmt.Printf("Benchmark Results:\n")
fmt.Printf(" Blocks parsed: %d\n", blockCount)
fmt.Printf(" Duration: %v\n", duration)
fmt.Printf(" Blocks per second: %.2f\n", blocksPerSecond)
metrics := parser.GetMetrics()
fmt.Printf(" Average processing time: %.2fms\n", metrics.AvgProcessingTimeMs)
fmt.Printf(" Total events found: %d\n", metrics.TotalEventsParsed)
*/
fmt.Println("Benchmark example completed (placeholder)")
}
// MonitoringDashboardExample shows how to create a monitoring dashboard
func MonitoringDashboardExample() {
fmt.Println("=== Monitoring Dashboard ===")
/*
// This would create a real-time monitoring dashboard
type DashboardMetrics struct {
CurrentBlock uint64
EventsPerSecond float64
PoolsDiscovered uint64
MEVOpportunities uint64
TotalVolumeUSD float64
TopProtocols map[Protocol]uint64
ErrorRate float64
ProcessingLatency time.Duration
}
func createDashboard(parser *EnhancedDEXParser) *DashboardMetrics {
metrics := parser.GetMetrics()
// Calculate events per second
uptime := time.Since(metrics.StartTime).Seconds()
eventsPerSecond := float64(metrics.TotalEventsParsed) / uptime
// Calculate error rate
errorRate := 0.0
if metrics.TotalTransactionsParsed > 0 {
errorRate = float64(metrics.ParseErrorCount) / float64(metrics.TotalTransactionsParsed) * 100
}
return &DashboardMetrics{
CurrentBlock: metrics.LastProcessedBlock,
EventsPerSecond: eventsPerSecond,
PoolsDiscovered: metrics.TotalPoolsDiscovered,
TotalVolumeUSD: calculateTotalVolume(metrics),
TopProtocols: metrics.ProtocolBreakdown,
ErrorRate: errorRate,
ProcessingLatency: time.Duration(metrics.AvgProcessingTimeMs) * time.Millisecond,
}
}
// Display dashboard
ticker := time.NewTicker(10 * time.Second)
defer ticker.Stop()
for range ticker.C {
dashboard := createDashboard(parser)
fmt.Printf("\n=== DEX Parser Dashboard ===\n")
fmt.Printf("Current Block: %d\n", dashboard.CurrentBlock)
fmt.Printf("Events/sec: %.2f\n", dashboard.EventsPerSecond)
fmt.Printf("Pools Discovered: %d\n", dashboard.PoolsDiscovered)
fmt.Printf("Total Volume: $%.2f\n", dashboard.TotalVolumeUSD)
fmt.Printf("Error Rate: %.2f%%\n", dashboard.ErrorRate)
fmt.Printf("Latency: %v\n", dashboard.ProcessingLatency)
fmt.Println("Top Protocols:")
for protocol, count := range dashboard.TopProtocols {
if count > 0 {
fmt.Printf(" %s: %d\n", protocol, count)
}
}
}
*/
fmt.Println("Monitoring dashboard example completed (placeholder)")
}
// ProductionDeploymentExample shows production deployment considerations
func ProductionDeploymentExample() {
fmt.Println("=== Production Deployment Guide ===")
fmt.Println(`
Production Deployment Checklist:
1. Infrastructure Setup:
- Use redundant RPC endpoints
- Configure load balancing
- Set up monitoring and alerting
- Implement log aggregation
- Configure auto-scaling
2. Configuration:
- Set appropriate cache sizes based on memory
- Configure worker pools based on CPU cores
- Set reasonable timeouts and retries
- Enable metrics and health checks
- Configure database persistence
3. Security:
- Secure RPC endpoints with authentication
- Use environment variables for secrets
- Implement rate limiting
- Set up network security
- Enable audit logging
4. Performance Optimization:
- Profile memory usage
- Monitor CPU utilization
- Optimize database queries
- Implement connection pooling
- Use efficient data structures
5. Monitoring:
- Set up Prometheus metrics
- Configure Grafana dashboards
- Implement alerting rules
- Monitor error rates
- Track performance metrics
6. Disaster Recovery:
- Implement backup strategies
- Set up failover mechanisms
- Test recovery procedures
- Document emergency procedures
- Plan for data corruption scenarios
Example production configuration:
config := &EnhancedParserConfig{
RPCEndpoint: os.Getenv("ARBITRUM_RPC_ENDPOINT"),
RPCTimeout: 45 * time.Second,
MaxRetries: 5,
EnabledProtocols: allProtocols,
MinLiquidityUSD: 500.0,
MaxSlippageBps: 2000,
EnablePoolDiscovery: true,
EnableEventEnrichment: true,
MaxWorkers: runtime.NumCPU() * 2,
CacheSize: 50000,
CacheTTL: 2 * time.Hour,
BatchSize: 200,
EnableMetrics: true,
MetricsInterval: 30 * time.Second,
EnableHealthCheck: true,
EnablePersistence: true,
DatabaseURL: os.Getenv("DATABASE_URL"),
RedisURL: os.Getenv("REDIS_URL"),
}
`)
}
// AdvancedFeaturesExample demonstrates advanced features
func AdvancedFeaturesExample() {
fmt.Println("=== Advanced Features ===")
fmt.Println(`
Advanced Features Available:
1. Multi-Protocol Arbitrage Detection:
- Cross-DEX arbitrage opportunities
- Flash loan integration
- Gas cost optimization
- Profit threshold filtering
2. MEV Protection:
- Sandwich attack detection
- Front-running identification
- Private mempool integration
- MEV protection strategies
3. Liquidity Analysis:
- Pool depth analysis
- Impermanent loss calculation
- Yield farming opportunities
- Liquidity mining rewards
4. Risk Management:
- Smart slippage protection
- Position sizing algorithms
- Market impact analysis
- Volatility assessment
5. Machine Learning Integration:
- Pattern recognition
- Predictive analytics
- Anomaly detection
- Strategy optimization
6. Advanced Caching:
- Distributed caching
- Cache warming strategies
- Intelligent prefetching
- Memory optimization
7. Real-Time Analytics:
- Stream processing
- Complex event processing
- Real-time aggregations
- Alert systems
8. Custom Protocol Support:
- Plugin architecture
- Custom parser development
- Protocol-specific optimizations
- Extension mechanisms
`)
}