Implementing a Swap Routing Mechanism in Rust

In this article, we’ll explore how to implement a swap routing mechanism in Rust. We’ll create a simplified version of a decentralized exchange (DEX) aggregator that finds the best trade paths across multiple liquidity pools. We’ll leverage Rust’s powerful features for performance and safety while building this system.

Prerequisites

Before we dive in, make sure you have Rust installed. You can install Rust using rustup:

curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

Project Setup

Let’s start by setting up a new Rust project:

cargo new dex_aggregator
cd dex_aggregator

We’ll add a few dependencies to our Cargo.toml file for handling HTTP requests and JSON parsing:

[dependencies]
reqwest = { version = "0.11", features = ["blocking", "json"] }
serde = { version = "1.0", features = ["derive"] }
serde_json = "1.0"

Defining the Data Structures

First, we’ll define the data structures to represent liquidity pools and trade paths. We’ll use Serde for JSON serialization and deserialization.

use serde::{Deserialize, Serialize};
use std::collections::HashMap;

#[derive(Debug, Serialize, Deserialize)]
struct LiquidityPool {
    token_a: String,
    token_b: String,
    reserve_a: f64,
    reserve_b: f64,
    fee: f64,
}

#[derive(Debug, Serialize, Deserialize)]
struct TradePath {
    pools: Vec<LiquidityPool>,
    amount_in: f64,
    amount_out: f64,
}

Fetching Liquidity Pools

We’ll create a function to fetch liquidity pools from a mock API. In a real-world scenario, you would fetch this data from multiple DEXs.

fn fetch_liquidity_pools() -> Result<Vec<LiquidityPool>, Box<dyn std::error::Error>> {
    let url = "https://api.mockdex.com/liquidity_pools";
    let response = reqwest::blocking::get(url)?;
    let pools: Vec<LiquidityPool> = response.json()?;
    Ok(pools)
}

Calculating the Output Amount

Next, we’ll implement a function to calculate the output amount for a given input amount using the constant product formula (x * y = k).

fn calculate_output(pool: &LiquidityPool, amount_in: f64, token_in: &str) -> f64 {
    let (reserve_in, reserve_out) = if token_in == pool.token_a {
        (pool.reserve_a, pool.reserve_b)
    } else {
        (pool.reserve_b, pool.reserve_a)
    };

let amount_in_with_fee = amount_in * (1.0 - pool.fee);
    let new_reserve_in = reserve_in + amount_in_with_fee;
    let new_reserve_out = reserve_out * reserve_in / new_reserve_in;
    reserve_out - new_reserve_out
}

Finding the Best Trade Path

We’ll create a function to find the best trade path across multiple liquidity pools. This function will consider direct swaps and multi-hop swaps.

fn find_best_trade_path(pools: &[LiquidityPool], token_in: &str, token_out: &str, amount_in: f64) -> Option<TradePath> {
    let mut best_path = None;
    let mut best_amount_out = 0.0;

    for pool in pools {
        if pool.token_a == token_in && pool.token_b == token_out || pool.token_b == token_in && pool.token_a == token_out {
            let amount_out = calculate_output(pool, amount_in, token_in);
            if amount_out > best_amount_out {
                best_amount_out = amount_out;
                best_path = Some(TradePath {
                    pools: vec![pool.clone()],
                    amount_in,
                    amount_out,
                });
            }
        }
    }

    for pool1 in pools {
        for pool2 in pools {
            if pool1.token_a == token_in && pool1.token_b != token_out && pool2.token_a == pool1.token_b && pool2.token_b == token_out
                || pool1.token_b == token_in && pool1.token_a != token_out && pool2.token_b == pool1.token_a && pool2.token_a == token_out {
                    let intermediate_token = if pool1.token_a == token_in { &pool1.token_b } else { &pool1.token_a };
                    let amount_intermediate = calculate_output(pool1, amount_in, token_in);
                    let amount_out = calculate_output(pool2, amount_intermediate, intermediate_token);
                    if amount_out > best_amount_out {
                        best_amount_out = amount_out;
                        best_path = Some(TradePath {
                            pools: vec![pool1.clone(), pool2.clone()],
                            amount_in,
                            amount_out,
                        });
                    }
            }
        }
    }

    best_path
}

Main Function

Finally, we’ll implement the main function to tie everything together. This function will fetch liquidity pools, find the best trade path, and print the result.

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let pools = fetch_liquidity_pools()?;

    let token_in = "ETH";
    let token_out = "DAI";
    let amount_in = 1.0;
    if let Some(best_path) = find_best_trade_path(&pools, token_in, token_out, amount_in) {
        println!("Best trade path found:");
        for pool in &best_path.pools {
            println!("{:?}", pool);
        }
        println!("Input Amount: {}", best_path.amount_in);
        println!("Output Amount: {}", best_path.amount_out);
    } else {
        println!("No suitable trade path found.");
    }
    Ok(())
}

Enhancements and Extensions

In the previous section, we built a basic swap routing mechanism in Rust. Now, let’s explore potential enhancements and extensions to make this implementation more robust and closer to real-world applications.

1. Handling Multiple Liquidity Pools and DEXs

We can extend the system to aggregate liquidity from multiple DEXs. This involves fetching liquidity pool data from various sources and integrating it into the routing mechanism.

2. Incorporating Additional Fees and Gas Costs

In a real-world scenario, trades incur gas costs and additional fees. These should be considered when calculating the optimal trade path.

3. Improving Pathfinding Algorithms

We can improve the pathfinding algorithm to consider more complex routing strategies, such as splitting trades across multiple paths or considering different intermediate tokens.

Enhancing the Routing Mechanism

Adding Support for Multiple DEXs

Let’s modify the fetch_liquidity_pools function to aggregate data from multiple DEXs:

fn fetch_liquidity_pools() -> Result<Vec<LiquidityPool>, Box<dyn std::error::Error>> {
    let dex_urls = vec![
        "https://api.mockdex1.com/liquidity_pools",
        "https://api.mockdex2.com/liquidity_pools",
    ];

let mut pools = Vec::new();
    for url in dex_urls {
        let response = reqwest::blocking::get(url)?;
        let mut dex_pools: Vec<LiquidityPool> = response.json()?;
        pools.append(&mut dex_pools);
    }
    Ok(pools)
}

Incorporating Gas Costs

Let’s add a function to estimate gas costs and include it in the pathfinding process:

fn estimate_gas_cost(pools: &[LiquidityPool]) -> f64 {
    // Simplified gas cost estimation
    pools.len() as f64 * 0.005  // Assume each swap costs 0.005 ETH in gas
}

We will modify the find_best_trade_path function to consider gas costs:

fn find_best_trade_path(pools: &[LiquidityPool], token_in: &str, token_out: &str, amount_in: f64) -> Option<TradePath> {
    let mut best_path = None;
    let mut best_amount_out = 0.0;

    for pool in pools {
          if pool.token_a == token_in && pool.token_b == token_out || pool.token_b == token_in && pool.token_a == token_out {
            let amount_out = calculate_output(pool, amount_in, token_in);
            let gas_cost = estimate_gas_cost(&[pool.clone()]);
            let effective_amount_out = amount_out - gas_cost;
            if effective_amount_out > best_amount_out {
                best_amount_out = effective_amount_out;
                best_path = Some(TradePath {
                    pools: vec![pool.clone()],
                    amount_in,
                    amount_out: effective_amount_out,
                });
            }
        }
    }

    for pool1 in pools {
        for pool2 in pools {
            if pool1.token_a == token_in && pool1.token_b != token_out && pool2.token_a == pool1.token_b && pool2.token_b == token_out
                || pool1.token_b == token_in && pool1.token_a != token_out && pool2.token_b == pool1.token_a && pool2.token_a == token_out {
                    let intermediate_token = if pool1.token_a == token_in { &pool1.token_b } else { &pool1.token_a };
                    let amount_intermediate = calculate_output(pool1, amount_in, token_in);
                    let amount_out = calculate_output(pool2, amount_intermediate, intermediate_token);
                    let gas_cost = estimate_gas_cost(&[pool1.clone(), pool2.clone()]);
                    let effective_amount_out = amount_out - gas_cost;
                    if effective_amount_out > best_amount_out {
                        best_amount_out = effective_amount_out;
                        best_path = Some(TradePath {
                            pools: vec![pool1.clone(), pool2.clone()],
                            amount_in,
                            amount_out: effective_amount_out,
                        });
                    }
            }
        }
    }
    best_path
}

Improving Pathfinding Algorithm

To further enhance the pathfinding algorithm, we can consider more complex strategies, such as splitting trades across multiple paths to minimize slippage and maximize returns. This requires a more sophisticated approach to evaluating potential trade paths.

For simplicity, let’s demonstrate a basic version of splitting trades:

fn find_best_trade_path(pools: &[LiquidityPool], token_in: &str, token_out: &str, amount_in: f64) -> Option<TradePath> {
    let mut best_path = None;
    let mut best_amount_out = 0.0;

    for pool in pools {
        if pool.token_a == token_in && pool.token_b == token_out || pool.token_b == token_in && pool.token_a == token_out {
            let amount_out = calculate_output(pool, amount_in, token_in);
            let gas_cost = estimate_gas_cost(&[pool.clone()]);
            let effective_amount_out = amount_out - gas_cost;
            if effective_amount_out > best_amount_out {
                best_amount_out = effective_amount_out;
                best_path = Some(TradePath {
                    pools: vec![pool.clone()],
                    amount_in,
                    amount_out: effective_amount_out,
                });
            }
        }
    }

    for pool1 in pools {
        for pool2 in pools {
            if pool1.token_a == token_in && pool1.token_b != token_out && pool2.token_a == pool1.token_b && pool2.token_b == token_out
                || pool1.token_b == token_in && pool1.token_a != token_out && pool2.token_b == pool1.token_a && pool2.token_a == token_out {
                    let intermediate_token = if pool1.token_a == token_in { &pool1.token_b } else { &pool1.token_a };
                    let amount_intermediate = calculate_output(pool1, amount_in, token_in);
                    let amount_out = calculate_output(pool2, amount_intermediate, intermediate_token);
                    let gas_cost = estimate_gas_cost(&[pool1.clone(), pool2.clone()]);
                    let effective_amount_out = amount_out - gas_cost;
                    if effective_amount_out > best_amount_out {
                        best_amount_out = effective_amount_out;
                        best_path = Some(TradePath {
                            pools: vec![pool1.clone(), pool2.clone()],
                            amount_in,
                            amount_out: effective_amount_out,
                        });
                    }
            }
        }
    }

    // Example of splitting trades (for simplicity, splitting into two equal parts)
    if amount_in > 2.0 {
        let half_amount_in = amount_in / 2.0;
        let path1 = find_best_trade_path(pools, token_in, token_out, half_amount_in);
        let path2 = find_best_trade_path(pools, token_in, token_out, half_amount_in);
        if let (Some(path1), Some(path2)) = (path1, path2) {
            let total_amount_out = path1.amount_out + path2.amount_out;
            if total_amount_out > best_amount_out {
                best_amount_out = total_amount_out;
                best_path = Some(TradePath {
                    pools: [path1.pools, path2.pools].concat(),
                    amount_in,
                    amount_out: total_amount_out,
                });
            }
        }
    }
    best_path
}

Final Main Function

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let pools = fetch_liquidity_pools()?;

    let token_in = "ETH";
    let token_out = "DAI";
    let amount_in = 1.0;
    if let Some(best_path) = find_best_trade_path(&pools, token_in, token_out, amount_in) {
        println!("Best trade path found:");
        for pool in &best_path.pools {
            println!("{:?}", pool);
        }
        println!("Input Amount: {}", best_path.amount_in);
        println!("Output Amount: {}", best_path.amount_out);
    } else {
        println!("No suitable trade path found.");
    }
    Ok(())
}

Conclusion

In this article, we have implemented and enhanced a swap routing mechanism in Rust. We started with a basic routing mechanism and extended it to handle multiple DEXs, incorporate gas costs, and improve the pathfinding algorithm.

This implementation serves as a foundation for building more sophisticated swap routing systems in decentralized finance (DeFi) applications. By leveraging Rust’s performance and safety features, we can create efficient and reliable systems that provide optimal trading paths across various liquidity pools.