Initial commit: Set up MEV bot project structure

This commit is contained in:
Krypto Kajun
2025-09-12 01:16:30 -05:00
commit ba80b273e4
22 changed files with 1035 additions and 0 deletions

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# Binaries
bin/
# Configuration files that might contain sensitive information
config/local.yaml
config/secrets.yaml
# Go workspace
go.work
# Test coverage files
coverage.txt
coverage.html
# IDE files
.vscode/
.idea/
*.swp
*.swo
# OS generated files
.DS_Store
.DS_Store?
._*
.Spotlight-V100
.Trashes
ehthumbs.db
Thumbs.db
# Log files
*.log
# Database files
*.db

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# MEV Bot Development Prompts
This directory contains prompts that can be used with AI coding assistants to help with the development of the MEV bot.
## Purpose
These prompts are designed to help developers:
1. Understand complex Uniswap V3 pricing mathematics
2. Implement efficient market scanning algorithms
3. Optimize arbitrage detection logic
4. Handle Ethereum transaction monitoring
5. Implement gas optimization strategies
## Usage
When working on specific parts of the MEV bot, you can use these prompts with your AI coding assistant to get targeted help and suggestions.

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You are an expert in Ethereum and Arbitrum blockchain development. I'm building an MEV bot in Go that needs to monitor the Arbitrum sequencer for potential swap transactions.
I need help with:
1. Setting up a connection to an Arbitrum node (both RPC and WebSocket)
2. Efficiently monitoring new blocks as they are added to the chain
3. Monitoring the mempool for pending transactions
4. Identifying transactions that interact with Uniswap-like contracts
5. Decoding transaction data to extract swap parameters
6. Handling network errors and reconnections gracefully
Please provide production-ready Go code that:
- Uses the go-ethereum library
- Implements efficient polling or event-driven monitoring
- Handles errors gracefully
- Follows Go best practices
- Is optimized for performance
- Includes comprehensive comments
The code should:
- Connect to the Arbitrum mainnet RPC endpoint (https://arb1.arbitrum.io/rpc)
- Monitor for transactions to common DEX contract addresses
- Extract function signatures and parameters from transaction data
- Decode swap function calls to get token addresses and amounts

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You are an expert in Go error handling and logging best practices. I'm building an MEV bot in Go that needs robust error handling and comprehensive logging for production deployment.
I need help with:
1. Implementing structured logging throughout the application
2. Creating meaningful error messages for debugging
3. Implementing retry mechanisms for transient failures
4. Handling fatal errors gracefully
5. Implementing circuit breakers for external services
6. Creating health checks and metrics
Please provide production-ready Go code that:
- Uses a structured logging library (like zap or logrus)
- Implements comprehensive error wrapping and context
- Includes retry mechanisms with exponential backoff
- Handles fatal errors gracefully with proper cleanup
- Follows Go best practices for error handling
- Is optimized for performance
- Includes comprehensive comments
The code should:
- Log at appropriate levels (debug, info, warn, error)
- Include contextual information in log messages
- Implement circuit breakers for RPC connections
- Handle timeouts appropriately
- Provide health check endpoints
- Export metrics for monitoring

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You are an expert in Ethereum gas optimization and MEV strategies. I'm building an MEV bot in Go that needs to optimize transaction submission for maximum profitability.
I need help with:
1. Estimating optimal gas prices for arbitrage transactions
2. Implementing transaction bundling strategies
3. Working with flashbots or similar MEV protection services
4. Optimizing transaction ordering within bundles
5. Handling frontrunning and backrunning strategies
6. Managing gas refunds and stipends
Please provide production-ready Go code that:
- Integrates with flashbots or similar MEV protection services
- Calculates optimal gas prices based on network conditions
- Implements transaction bundling for atomic execution
- Handles errors and edge cases properly
- Follows Go best practices
- Is optimized for performance
- Includes comprehensive comments
The code should:
- Connect to flashbots relay or similar service
- Calculate optimal gas prices based on base fee and priority fees
- Bundle transactions for atomic execution
- Handle failed transactions gracefully
- Implement retry logic with exponential backoff

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You are an expert in MEV (Maximal Extractable Value) and DeFi arbitrage strategies. I'm building an MEV bot in Go that needs to scan markets for arbitrage opportunities.
I need help with:
1. Implementing efficient market scanning algorithms
2. Calculating price impact of large swaps
3. Detecting triangular arbitrage opportunities
4. Estimating gas costs for arbitrage transactions
5. Determining profitability after gas costs
6. Implementing risk management strategies
Please provide production-ready Go code that:
- Implements efficient data structures for market data
- Calculates arbitrage opportunities across multiple pools
- Estimates gas costs accurately
- Handles edge cases properly
- Follows Go best practices
- Is optimized for performance
- Includes comprehensive comments
The code should:
- Work with Uniswap V3 pool data
- Calculate price impact using liquidity and swap amounts
- Identify profitable arbitrage paths
- Estimate transaction costs
- Filter opportunities based on minimum profit thresholds

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You are an expert in Go testing and test-driven development. I'm building an MEV bot in Go that needs comprehensive test coverage to ensure reliability.
I need help with:
1. Creating unit tests for Uniswap V3 pricing calculations
2. Implementing integration tests for Arbitrum monitoring
3. Creating mock contracts and transactions for testing
4. Testing market scanning algorithms with real-world data
5. Implementing property-based testing for mathematical functions
6. Creating benchmarks for performance-critical code
Please provide production-ready Go test code that:
- Uses the standard testing package and testify for assertions
- Implements table-driven tests for pricing functions
- Creates realistic mock data for testing
- Includes benchmarks for performance-critical functions
- Follows Go testing best practices
- Provides comprehensive coverage
- Includes comprehensive comments
The test code should:
- Test edge cases and boundary conditions
- Validate mathematical accuracy of pricing functions
- Simulate network errors and timeouts
- Test various swap scenarios
- Benchmark performance of critical algorithms
- Provide meaningful test output

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You are an expert in Uniswap V3 mathematics and smart contract development. I'm building an MEV bot in Go that needs to calculate price movements using Uniswap V3 pricing functions.
I need help with implementing these specific functions:
1. sqrtPriceX96 to tick conversion
2. tick to sqrtPriceX96 conversion
3. price to tick conversion
4. tick to price conversion
5. Calculating price impact of a swap given liquidity and amount
Please provide production-ready Go code that:
- Uses the math/big package for precision
- Handles edge cases properly
- Is optimized for performance
- Follows Go best practices
- Includes comprehensive comments explaining the mathematics
The code should work with:
- sqrtPriceX96 values (uint160 in Solidity, but we'll use big.Int in Go)
- tick values (int24 in Solidity, but we'll use int in Go)
- liquidity values (uint128 in Solidity, but we'll use big.Int in Go)
Please also explain the mathematical relationships between these values according to the Uniswap V3 whitepaper.

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# MEV Bot Project - Qwen Code Context
This file contains context information for Qwen Code about the MEV Bot project.
## Project Overview
This is an MEV (Maximal Extractable Value) bot written in Go 1.24+ that monitors the Arbitrum sequencer for potential swap opportunities. When a potential swap is detected, the bot scans the market to determine if the swap is large enough to move the price using off-chain methods.
## Project Structure
- `cmd/` - Main applications
- `internal/` - Private application and library code
- `pkg/` - Library code that can be used by external projects
- `config/` - Configuration files
- `@prompts/` - AI prompts for development assistance
- `docs/` - Documentation
- `scripts/` - Scripts for building, testing, and deployment
## Technologies
- Go 1.24+
- Arbitrum sequencer monitoring
- Uniswap V3 pricing functions (price to tick, sqrtPriceX96 to tick, etc.)
## Development Notes
- Focus on off-chain price movement calculations
- Refer to official Uniswap V3 documentation for pricing functions
- Implement market scanning functionality for potential arbitrage opportunities

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# MEV Bot
An MEV (Maximal Extractable Value) bot written in Go that monitors the Arbitrum sequencer for potential swap opportunities and identifies profitable arbitrage opportunities.
## Overview
This bot monitors the Arbitrum sequencer for attempted swaps and analyzes them to determine if they are large enough to create price movements that can be exploited for arbitrage. It uses off-chain methods to calculate price movements using Uniswap V3 pricing functions.
## Features
- Real-time monitoring of Arbitrum sequencer
- Detection of potential swap transactions
- Market scanning for price movement analysis
- Uniswap V3 pricing calculations (price to tick, sqrtPriceX96 to tick, etc.)
- Arbitrage opportunity identification
## Prerequisites
- Go 1.24 or higher
- Access to Arbitrum node
## Installation
```bash
go mod tidy
```
## Usage
```bash
go run cmd/mev-bot/main.go
```
## Configuration
Configuration files can be found in the `config/` directory.
## Project Structure
```
.
├── cmd/ # Main applications
├── config/ # Configuration files
├── internal/ # Private application and library code
├── pkg/ # Library code that can be used by external projects
├── @prompts/ # AI prompts for development assistance
├── docs/ # Documentation
├── scripts/ # Scripts for building, testing, and deployment
├── go.mod # Go module definition
├── go.sum # Go module checksums
├── README.md # This file
└── QWEN.md # Qwen Code context file
```
## Development
### Prompts Directory
The `@prompts/` directory contains prompts that can be used with AI coding assistants for various development tasks.
### Contributing
1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request
## License
MIT

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package main
import (
"fmt"
"log"
"os"
"github.com/urfave/cli/v2"
)
func main() {
app := &cli.App{
Name: "mev-bot",
Usage: "An MEV bot that monitors Arbitrum sequencer for swap opportunities",
Commands: []*cli.Command{
{
Name: "start",
Usage: "Start the MEV bot",
Action: func(c *cli.Context) error {
fmt.Println("Starting MEV bot...")
// TODO: Implement bot start logic
return nil
},
},
{
Name: "scan",
Usage: "Scan for potential arbitrage opportunities",
Action: func(c *cli.Context) error {
fmt.Println("Scanning for arbitrage opportunities...")
// TODO: Implement scanning logic
return nil
},
},
},
}
if err := app.Run(os.Args); err != nil {
log.Fatal(err)
}
}

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# MEV Bot Configuration
# Arbitrum node configuration
arbitrum:
# RPC endpoint for Arbitrum node
rpc_endpoint: "https://arb1.arbitrum.io/rpc"
# WebSocket endpoint for Arbitrum node (optional)
ws_endpoint: ""
# Chain ID for Arbitrum (42161 for mainnet)
chain_id: 42161
# Bot configuration
bot:
# Enable or disable the bot
enabled: true
# Polling interval in seconds
polling_interval: 1
# Minimum profit threshold in USD
min_profit_threshold: 10.0
# Gas price multiplier (for faster transactions)
gas_price_multiplier: 1.2
# Uniswap configuration
uniswap:
# Factory contract address
factory_address: "0x1F98431c8aD98523631AE4a59f267346ea31F984"
# Position manager contract address
position_manager_address: "0xC36442b4a4522E871399CD717aBDD847Ab11FE88"
# Supported fee tiers
fee_tiers:
- 500 # 0.05%
- 3000 # 0.3%
- 10000 # 1%
# Logging configuration
log:
# Log level (debug, info, warn, error)
level: "info"
# Log format (json, text)
format: "text"
# Log file path (empty for stdout)
file: ""
# Database configuration
database:
# Database file path
file: "mev-bot.db"

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# MEV Bot Architecture
This document describes the high-level architecture of the MEV bot.
## Components
### 1. Arbitrum Monitor
Responsible for monitoring the Arbitrum sequencer for new blocks and transactions.
Key responsibilities:
- Connect to Arbitrum RPC endpoint
- Monitor new blocks as they are added
- Identify potential swap transactions
- Extract transaction details
### 2. Market Scanner
Analyzes potential swap transactions to determine if they create arbitrage opportunities.
Key responsibilities:
- Calculate price impact of swaps
- Scan for arbitrage opportunities across pools
- Estimate profitability after gas costs
- Filter opportunities based on configured thresholds
### 3. Uniswap Pricing
Handles all Uniswap V3 pricing calculations.
Key responsibilities:
- Convert between sqrtPriceX96 and ticks
- Calculate price impact of swaps
- Work with liquidity values
- Implement Uniswap V3 mathematical formulas
### 4. Transaction Executor
Responsible for executing profitable arbitrage transactions.
Key responsibilities:
- Construct arbitrage transactions
- Optimize gas usage
- Submit transactions to flashbots or similar services
- Handle transaction confirmation and errors
## Data Flow
1. Arbitrum Monitor detects new blocks and transactions
2. Potential swap transactions are sent to Market Scanner
3. Market Scanner analyzes swaps and identifies opportunities
4. Profitable opportunities are sent to Transaction Executor
5. Transaction Executor constructs and submits arbitrage transactions
## Configuration
The bot is configured through config/config.yaml which allows customization of:
- Arbitrum RPC endpoints
- Polling intervals
- Profit thresholds
- Gas price multipliers
- Logging settings

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# Monitoring System Documentation
This document explains how the MEV bot monitors the Arbitrum sequencer for potential swap transactions.
## Overview
The monitoring system connects to an Arbitrum RPC endpoint and continuously monitors for new blocks and transactions. It identifies potential swap transactions and forwards them to the market scanner for analysis.
## Components
### ArbitrumMonitor
The main monitoring component that handles:
- Connecting to the Arbitrum RPC endpoint
- Polling for new blocks
- Processing transactions in new blocks
- Identifying potential swap transactions
### Transaction Processing
Each transaction is analyzed to determine if it's a potential swap:
1. Check if the transaction is calling a known DEX contract
2. Decode the transaction data to extract swap parameters
3. Extract token addresses and amounts
4. Calculate potential price impact
## Configuration
The monitoring system is configured through config/config.yaml:
- `arbitrum.rpc_endpoint`: The RPC endpoint to connect to
- `bot.polling_interval`: How often to check for new blocks
- `arbitrum.chain_id`: The chain ID to ensure we're on the correct network
## Implementation Details
The monitor uses the go-ethereum library to interact with the Arbitrum network. It implements efficient polling to minimize RPC calls while ensuring timely detection of new blocks.
Key features:
- Graceful error handling and reconnection
- Configurable polling intervals
- Transaction sender identification
- Support for both RPC and WebSocket endpoints

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# Uniswap V3 Pricing Documentation
This document explains the Uniswap V3 pricing model and how it's implemented in the MEV bot.
## Core Concepts
### Ticks
In Uniswap V3, prices are represented as ticks. A tick is defined as:
```
tick = log√1.0001(√P)
```
Where P is the price of token1 in terms of token0.
Ticks are integers that range from -887272 to 887272.
### sqrtPriceX96
Prices are stored internally as sqrtPriceX96, which is:
```
sqrtPriceX96 = √P * 2^96
```
This allows for precise fixed-point arithmetic without floating-point operations.
### Liquidity
Liquidity in a pool is represented as a uint128 value that determines the depth of the pool at a given price.
## Mathematical Relationships
### Converting between representations
1. Tick to sqrtPriceX96:
```
sqrtPriceX96 = 1.0001^(tick/2) * 2^96
```
2. sqrtPriceX96 to Tick:
```
tick = log_1.0001(sqrtPriceX96 / 2^96)^2
```
3. Price to Tick:
```
tick = log_1.0001(price)
```
## Implementation Details
Our Go implementation uses the math/big package for precision and handles the fixed-point arithmetic required for Uniswap V3 calculations.
Key functions:
- `SqrtPriceX96ToPrice`: Converts sqrtPriceX96 to a floating-point price
- `PriceToSqrtPriceX96`: Converts a floating-point price to sqrtPriceX96
- `TickToSqrtPriceX96`: Converts a tick to sqrtPriceX96
- `SqrtPriceX96ToTick`: Converts sqrtPriceX96 to a tick

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module github.com/your-username/mev-beta
go 1.24
require (
github.com/ethereum/go-ethereum v1.14.12
github.com/urfave/cli/v2 v2.27.4
)
require (
github.com/cpuguy83/go-md2man/v2 v2.0.4 // indirect
github.com/gballet/go-libpcsclite v0.0.0-20200512141541-2758323733fd // indirect
github.com/gorilla/websocket v1.5.3 // indirect
github.com/hashicorp/go-bexpr v0.1.11 // indirect
github.com/holiman/uint256 v1.2.4 // indirect
github.com/klauspost/compress v1.17.9 // indirect
github.com/kr/text v0.2.0 // indirect
github.com/mitchellh/mapstructure v1.5.0 // indirect
github.com/niemeyer/pretty v0.0.0-20200227124842-a10e7caefd8e // indirect
github.com/pkg/errors v0.9.1 // indirect
github.com/russross/blackfriday/v2 v2.1.0 // indirect
github.com/shopspring/decimal v1.4.0 // indirect
github.com/xeipuuv/gojsonpointer v0.0.0-20190905194746-02993c407bfb // indirect
github.com/xeipuuv/gojsonreference v0.0.0-20180127040603-bd5ef7bd5415 // indirect
github.com/xeipuuv/gojsonschema v1.2.0 // indirect
github.com/xrash/smetrics v0.0.0-20201216005158-039620a65673 // indirect
golang.org/x/crypto v0.26.0 // indirect
golang.org/x/exp v0.0.0-20240719175910-8a7402abbf56 // indirect
golang.org/x/mod v0.19.0 // indirect
golang.org/x/sys v0.24.0 // indirect
golang.org/x/term v0.23.0 // indirect
golang.org/x/text v0.17.0 // indirect
golang.org/x/tools v0.25.0 // indirect
gopkg.in/check.v1 v1.0.0-20200227125254-8fa46927fb4f // indirect
gopkg.in/yaml.v3 v3.0.1 // indirect
)
// Replace with your actual fork or repository when available
replace github.com/your-username/mev-beta => ./

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package monitor
import (
"context"
"fmt"
"log"
"math/big"
"time"
"github.com/ethereum/go-ethereum"
"github.com/ethereum/go-ethereum/common"
"github.com/ethereum/go-ethereum/core/types"
"github.com/ethereum/go-ethereum/ethclient"
)
// ArbitrumMonitor monitors the Arbitrum sequencer for transactions
type ArbitrumMonitor struct {
client *ethclient.Client
rpcEndpoint string
pollInterval time.Duration
running bool
}
// NewArbitrumMonitor creates a new Arbitrum monitor
func NewArbitrumMonitor(rpcEndpoint string, pollInterval time.Duration) (*ArbitrumMonitor, error) {
client, err := ethclient.Dial(rpcEndpoint)
if err != nil {
return nil, fmt.Errorf("failed to connect to Arbitrum node: %v", err)
}
return &ArbitrumMonitor{
client: client,
rpcEndpoint: rpcEndpoint,
pollInterval: pollInterval,
running: false,
}, nil
}
// Start begins monitoring the Arbitrum sequencer
func (m *ArbitrumMonitor) Start(ctx context.Context) error {
log.Println("Starting Arbitrum sequencer monitoring...")
m.running = true
// Get the latest block to start from
header, err := m.client.HeaderByNumber(ctx, nil)
if err != nil {
return fmt.Errorf("failed to get latest block header: %v", err)
}
lastBlock := header.Number.Uint64()
log.Printf("Starting from block: %d", lastBlock)
for m.running {
select {
case <-ctx.Done():
m.running = false
return nil
case <-time.After(m.pollInterval):
// Get the latest block
header, err := m.client.HeaderByNumber(ctx, nil)
if err != nil {
log.Printf("Failed to get latest block header: %v", err)
continue
}
currentBlock := header.Number.Uint64()
// Process blocks from lastBlock+1 to currentBlock
for blockNum := lastBlock + 1; blockNum <= currentBlock; blockNum++ {
if err := m.processBlock(ctx, blockNum); err != nil {
log.Printf("Failed to process block %d: %v", blockNum, err)
}
}
lastBlock = currentBlock
}
}
return nil
}
// Stop stops the monitor
func (m *ArbitrumMonitor) Stop() {
m.running = false
}
// processBlock processes a single block for potential swap transactions
func (m *ArbitrumMonitor) processBlock(ctx context.Context, blockNumber uint64) error {
log.Printf("Processing block %d", blockNumber)
// Get block by number
block, err := m.client.BlockByNumber(ctx, big.NewInt(int64(blockNumber)))
if err != nil {
return fmt.Errorf("failed to get block %d: %v", blockNumber, err)
}
// Process each transaction in the block
for _, tx := range block.Transactions() {
if err := m.processTransaction(ctx, tx); err != nil {
log.Printf("Failed to process transaction %s: %v", tx.Hash().Hex(), err)
}
}
return nil
}
// processTransaction analyzes a transaction for potential swap opportunities
func (m *ArbitrumMonitor) processTransaction(ctx context.Context, tx *types.Transaction) error {
// Check if this is a potential swap transaction
// This is a simplified check - in practice, you would check for
// specific function signatures of Uniswap-like contracts
// For now, we'll just log all transactions
from, err := m.client.TransactionSender(ctx, tx, common.Hash{}, 0)
if err != nil {
// This can happen for pending transactions
from = common.HexToAddress("0x0")
}
log.Printf("Transaction: %s, From: %s, To: %s, Value: %s ETH",
tx.Hash().Hex(),
from.Hex(),
func() string {
if tx.To() != nil {
return tx.To().Hex()
}
return "contract creation"
}(),
new(big.Float).Quo(new(big.Float).SetInt(tx.Value()), big.NewFloat(1e18)).String(),
)
// TODO: Add logic to detect swap transactions and analyze them
// This would involve:
// 1. Checking if the transaction is calling a Uniswap-like contract
// 2. Decoding the swap function call
// 3. Extracting the token addresses and amounts
// 4. Calculating potential price impact
return nil
}
// GetPendingTransactions retrieves pending transactions from the mempool
func (m *ArbitrumMonitor) GetPendingTransactions(ctx context.Context) ([]*types.Transaction, error) {
// This is a simplified implementation
// In practice, you might need to use a different approach to access pending transactions
// Query for pending transactions
txs := make([]*types.Transaction, 0)
// Note: ethclient doesn't directly expose pending transactions
// You might need to use a different approach or a custom RPC call
return txs, nil
}

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package scanner
import (
"math/big"
"github.com/holiman/uint256"
)
// MarketScanner scans markets for price movement opportunities
type MarketScanner struct {
// Configuration fields would go here
}
// NewMarketScanner creates a new market scanner
func NewMarketScanner() *MarketScanner {
return &MarketScanner{}
}
// PriceMovement represents a potential price movement
type PriceMovement struct {
Token0 string // Token address
Token1 string // Token address
Pool string // Pool address
AmountIn *big.Int // Amount of token being swapped in
AmountOut *big.Int // Amount of token being swapped out
PriceImpact float64 // Calculated price impact
TickBefore int // Tick before the swap
TickAfter int // Tick after the swap
}
// SwapDetails contains details about a detected swap
type SwapDetails struct {
PoolAddress string
Token0 string
Token1 string
Amount0In *big.Int
Amount0Out *big.Int
Amount1In *big.Int
Amount1Out *big.Int
SqrtPriceX96 *uint256.Int
Liquidity *uint256.Int
Tick int
}
// AnalyzeSwap analyzes a swap to determine if it's large enough to move the price
func (s *MarketScanner) AnalyzeSwap(swap SwapDetails) (*PriceMovement, error) {
// This is a simplified implementation
// In practice, you would need to:
// 1. Calculate the price before the swap
// 2. Calculate the price after the swap
// 3. Determine the price impact
priceMovement := &PriceMovement{
Token0: swap.Token0,
Token1: swap.Token1,
Pool: swap.PoolAddress,
AmountIn: new(big.Int).Add(swap.Amount0In, swap.Amount1In),
AmountOut: new(big.Int).Add(swap.Amount0Out, swap.Amount1Out),
TickBefore: swap.Tick,
// TickAfter would be calculated based on the swap size and liquidity
}
// Calculate price impact (simplified)
// In practice, this would involve more complex calculations
if priceMovement.AmountIn.Cmp(big.NewInt(0)) > 0 {
impact := new(big.Float).Quo(
new(big.Float).SetInt(priceMovement.AmountOut),
new(big.Float).SetInt(priceMovement.AmountIn),
)
priceImpact, _ := impact.Float64()
priceMovement.PriceImpact = priceImpact
}
return priceMovement, nil
}
// IsSignificantMovement determines if a price movement is significant enough to exploit
func (s *MarketScanner) IsSignificantMovement(movement *PriceMovement, threshold float64) bool {
// Check if the price impact is above our threshold
return movement.PriceImpact > threshold
}
// CalculateTickAfterSwap calculates the tick after a swap occurs
func (s *MarketScanner) CalculateTickAfterSwap(
currentTick int,
liquidity *uint256.Int,
amountIn *big.Int,
zeroForOne bool, // true if swapping token0 for token1
) int {
// This is a simplified implementation
// In practice, you would need to use the Uniswap V3 math formulas
// The actual calculation would involve:
// 1. Converting amounts to sqrt prices
// 2. Using the liquidity to determine the price movement
// 3. Calculating the new tick based on the price movement
// For now, we'll return a placeholder
return currentTick
}
// FindArbitrageOpportunities looks for arbitrage opportunities based on price movements
func (s *MarketScanner) FindArbitrageOpportunities(movements []*PriceMovement) []ArbitrageOpportunity {
opportunities := make([]ArbitrageOpportunity, 0)
// This would contain logic to:
// 1. Compare prices across different pools
// 2. Calculate potential profit after gas costs
// 3. Identify triangular arbitrage opportunities
// 4. Check if the opportunity is profitable
return opportunities
}
// ArbitrageOpportunity represents a potential arbitrage opportunity
type ArbitrageOpportunity struct {
Path []string // Token path for the arbitrage
Pools []string // Pools involved in the arbitrage
Profit *big.Int // Estimated profit in wei
GasEstimate *big.Int // Estimated gas cost
ROI float64 // Return on investment percentage
}

130
pkg/uniswap/pricing.go Normal file
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package uniswap
import (
"math/big"
"github.com/holiman/uint256"
)
const (
// Q96 represents 2^96 used in Uniswap V3 sqrtPriceX96 calculations
Q96 = 79228162514264337593543950336 // 2^96
// Tick spacing for different fee tiers
LowTickSpacing = 10
MediumTickSpacing = 60
HighTickSpacing = 200
)
// SqrtPriceX96ToPrice converts sqrtPriceX96 to a price
// Price is represented as token1/token0
func SqrtPriceX96ToPrice(sqrtPriceX96 *big.Int) *big.Float {
// price = (sqrtPriceX96 / 2^96)^2
// price = sqrtPriceX96^2 / 2^192
// Convert to big.Float for precision
sqrtPrice := new(big.Float).SetInt(sqrtPriceX96)
// Calculate sqrtPrice^2
price := new(big.Float).Mul(sqrtPrice, sqrtPrice)
// Divide by 2^192 (which is (2^96)^2)
q192 := new(big.Float).SetInt(new(big.Int).Exp(big.NewInt(2), big.NewInt(192), nil))
price.Quo(price, q192)
return price
}
// PriceToSqrtPriceX96 converts a price to sqrtPriceX96
func PriceToSqrtPriceX96(price *big.Float) *big.Int {
// sqrtPriceX96 = sqrt(price) * 2^96
// Calculate sqrt(price)
sqrtPrice := new(big.Float).Sqrt(price)
// Multiply by 2^96
q96 := new(big.Float).SetInt(new(big.Int).Exp(big.NewInt(2), big.NewInt(96), nil))
sqrtPrice.Mul(sqrtPrice, q96)
// Convert to big.Int
sqrtPriceX96 := new(big.Int)
sqrtPrice.Int(sqrtPriceX96)
return sqrtPriceX96
}
// TickToSqrtPriceX96 converts a tick to sqrtPriceX96
func TickToSqrtPriceX96(tick int) *big.Int {
// sqrtPriceX96 = 1.0001^(tick/2) * 2^96
// Calculate 1.0001^(tick/2)
base := new(big.Float).SetFloat64(1.0001)
tickF := new(big.Float).SetFloat64(float64(tick) / 2.0)
power := new(big.Float).Pow(base, tickF)
// Multiply by 2^96
q96 := new(big.Float).SetInt(new(big.Int).Exp(big.NewInt(2), big.NewInt(96), nil))
sqrtPrice := new(big.Float).Mul(power, q96)
// Convert to big.Int
sqrtPriceX96 := new(big.Int)
sqrtPrice.Int(sqrtPriceX96)
return sqrtPriceX96
}
// SqrtPriceX96ToTick converts sqrtPriceX96 to a tick
func SqrtPriceX96ToTick(sqrtPriceX96 *big.Int) int {
// tick = log_1.0001(sqrtPriceX96 / 2^96)^2
// tick = log_1.0001(price)
// tick = 2 * log_1.0001(sqrtPriceX96 / 2^96)
if sqrtPriceX96.Cmp(big.NewInt(0)) <= 0 {
return 0 // Invalid input
}
// Convert to big.Float
sqrtPrice := new(big.Float).SetInt(sqrtPriceX96)
q96 := new(big.Float).SetInt(new(big.Int).SetInt64(Q96))
// Calculate sqrtPriceX96 / 2^96
ratio := new(big.Float).Quo(sqrtPrice, q96)
// Calculate (sqrtPriceX96 / 2^96)^2 to get price
price := new(big.Float).Mul(ratio, ratio)
// Calculate log_1.0001(price)
// log_1.0001(x) = ln(x) / ln(1.0001)
lnPrice := new(big.Float).Log(price)
lnBase := new(big.Float).Log(new(big.Float).SetFloat64(1.0001))
logRatio := new(big.Float).Quo(lnPrice, lnBase)
// Convert to int
tick, _ := logRatio.Int64()
return int(tick)
}
// GetTickAtSqrtPrice calculates the tick for a given sqrtPriceX96 using uint256
func GetTickAtSqrtPrice(sqrtPriceX96 *uint256.Int) int {
// This is a simplified implementation
// In practice, you would use a more precise logarithmic calculation
// Convert to big.Int for calculation
sqrtPriceBig := sqrtPriceX96.ToBig()
return SqrtPriceX96ToTick(sqrtPriceBig)
}
// GetNextTick calculates the next initialized tick
func GetNextTick(currentTick int, tickSpacing int) int {
// Round down to nearest tick spacing
tick := ((currentTick / tickSpacing) + 1) * tickSpacing
return tick
}
// GetPreviousTick calculates the previous initialized tick
func GetPreviousTick(currentTick int, tickSpacing int) int {
// Round down to nearest tick spacing
tick := (currentTick / tickSpacing) * tickSpacing
return tick
}

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scripts/build.sh Executable file
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#!/bin/bash
# build.sh - Build the MEV bot
echo "Building MEV bot..."
# Create bin directory if it doesn't exist
mkdir -p bin
# Build the application
go build -o bin/mev-bot cmd/mev-bot/main.go
if [ $? -eq 0 ]; then
echo "Build successful! Binary created at bin/mev-bot"
else
echo "Build failed!"
exit 1
fi

16
scripts/run.sh Executable file
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#!/bin/bash
# run.sh - Run the MEV bot
echo "Running MEV bot..."
# Build the application first
./scripts/build.sh
if [ $? -eq 0 ]; then
# Run the application
./bin/mev-bot start
else
echo "Failed to build the application!"
exit 1
fi

15
scripts/test.sh Executable file
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#!/bin/bash
# test.sh - Run tests for the MEV bot
echo "Running tests..."
# Run all tests
go test -v ./...
if [ $? -eq 0 ]; then
echo "All tests passed!"
else
echo "Some tests failed!"
exit 1
fi