mirror of
https://github.com/floor-licker/polyfill-rs.git
synced 2026-08-16 14:08:07 +00:00
fix: resolve rustfmt configuration duplicate key error and apply consistent code formatting across all source files
This commit is contained in:
floor-licker
@@ -5,13 +5,13 @@ use std::time::Instant;
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async fn main() -> Result<(), Box<dyn std::error::Error>> {
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println!("🚀 Simple Network Benchmark - polyfill-rs");
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println!("==========================================");
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let client = ClobClient::new("https://clob.polymarket.com");
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// Test 1: Server Time (baseline network latency)
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println!("\n📊 Test 1: Server Time (Network Baseline)");
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println!("=========================================");
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let mut times = Vec::new();
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for i in 0..10 {
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let start = Instant::now();
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@@ -20,52 +20,54 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
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let duration = start.elapsed();
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times.push(duration);
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if i < 3 {
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println!(" Run {}: ✅ {} in {:?}", i+1, timestamp, duration);
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println!(" Run {}: ✅ {} in {:?}", i + 1, timestamp, duration);
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}
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}
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},
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Err(e) => {
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let duration = start.elapsed();
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times.push(duration);
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println!(" Run {}: ❌ Error in {:?}: {}", i+1, duration, e);
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}
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println!(" Run {}: ❌ Error in {:?}: {}", i + 1, duration, e);
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},
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}
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}
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if !times.is_empty() {
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let avg = times.iter().sum::<std::time::Duration>() / times.len() as u32;
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let min = times.iter().min().unwrap();
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let max = times.iter().max().unwrap();
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println!(" 📈 Average: {:?}", avg);
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println!(" 📊 Range: {:?} - {:?}", min, max);
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println!(" 🌐 Network baseline: ~{:?}", min);
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}
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// Test 2: Market Data (comparable to original benchmarks)
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println!("\n📊 Test 2: Market Data Fetching");
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println!("===============================");
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println!("Target: polymarket-rs-client 404.5ms ± 22.9ms");
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// Try different endpoints to see which ones work
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let endpoints = vec![
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("Simplified Markets", "get_sampling_simplified_markets"),
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("Full Markets", "get_sampling_markets"),
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("Market Prices", "get_prices_batch"),
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];
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for (name, _method) in endpoints {
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println!("\n 🔍 Testing {}:", name);
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let mut times = Vec::new();
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for i in 0..5 {
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let start = Instant::now();
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let result = match name {
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"Simplified Markets" => {
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client.get_sampling_simplified_markets(None).await.map(|r| r.data.len())
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}
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"Full Markets" => {
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client.get_sampling_markets(None).await.map(|r| r.data.len())
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}
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"Simplified Markets" => client
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.get_sampling_simplified_markets(None)
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.await
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.map(|r| r.data.len()),
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"Full Markets" => client
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.get_sampling_markets(None)
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.await
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.map(|r| r.data.len()),
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"Market Prices" => {
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// Try with some example BookParams
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let book_params = vec![
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@@ -75,96 +77,116 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
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}
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];
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client.get_prices(&book_params).await.map(|r| r.len())
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}
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},
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_ => continue,
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};
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let duration = start.elapsed();
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times.push(duration);
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match result {
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Ok(count) => {
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if i < 2 {
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println!(" Run {}: ✅ {} items in {:?}", i+1, count, duration);
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println!(" Run {}: ✅ {} items in {:?}", i + 1, count, duration);
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}
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}
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},
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Err(e) => {
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if i < 2 {
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println!(" Run {}: ❌ Error in {:?}: {}", i+1, duration, e);
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println!(" Run {}: ❌ Error in {:?}: {}", i + 1, duration, e);
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}
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}
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},
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}
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}
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if !times.is_empty() {
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let avg = times.iter().sum::<std::time::Duration>() / times.len() as u32;
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let min = times.iter().min().unwrap();
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let max = times.iter().max().unwrap();
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let std_dev = {
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let mean = avg.as_millis() as f64;
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let variance = times.iter()
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let variance = times
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.iter()
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.map(|t| (t.as_millis() as f64 - mean).powi(2))
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.sum::<f64>() / times.len() as f64;
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.sum::<f64>()
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/ times.len() as f64;
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variance.sqrt()
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};
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println!(" 📈 polyfill-rs: {:.1}ms ± {:.1}ms", avg.as_millis(), std_dev);
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println!(
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" 📈 polyfill-rs: {:.1}ms ± {:.1}ms",
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avg.as_millis(),
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std_dev
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);
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println!(" 📊 Range: {:?} - {:?}", min, max);
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if name == "Simplified Markets" {
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println!(" 🆚 vs original (404.5ms): {:.1}x {}",
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404.5 / avg.as_millis() as f64,
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if avg.as_millis() < 405 { "faster" } else { "slower" });
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println!(
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" 🆚 vs original (404.5ms): {:.1}x {}",
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404.5 / avg.as_millis() as f64,
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if avg.as_millis() < 405 {
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"faster"
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} else {
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"slower"
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}
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);
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}
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}
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}
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// Test 3: Computational Performance (our strength)
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println!("\n📊 Test 3: Computational Performance");
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println!("===================================");
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use polyfill_rs::OrderBookImpl;
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use rust_decimal::Decimal;
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use std::str::FromStr;
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let mut book = OrderBookImpl::new("test_token".to_string(), 100);
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// Populate the book first
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for i in 0..100 {
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let price = Decimal::from_str(&format!("0.{:04}", 5000 + i)).unwrap();
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let size = Decimal::from_str("100.0").unwrap();
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let delta = polyfill_rs::OrderDelta {
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token_id: "test_token".to_string(),
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timestamp: chrono::Utc::now(),
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side: if i % 2 == 0 { polyfill_rs::Side::BUY } else { polyfill_rs::Side::SELL },
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side: if i % 2 == 0 {
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polyfill_rs::Side::BUY
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} else {
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polyfill_rs::Side::SELL
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},
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price,
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size,
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sequence: i as u64,
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};
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let _ = book.apply_delta(delta);
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}
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// Benchmark order book updates
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let start = Instant::now();
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for i in 0..10000 {
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let price = Decimal::from_str(&format!("0.{:04}", 5000 + (i % 1000))).unwrap();
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let size = Decimal::from_str("100.0").unwrap();
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let delta = polyfill_rs::OrderDelta {
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token_id: "test_token".to_string(),
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timestamp: chrono::Utc::now(),
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side: if i % 2 == 0 { polyfill_rs::Side::BUY } else { polyfill_rs::Side::SELL },
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side: if i % 2 == 0 {
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polyfill_rs::Side::BUY
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} else {
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polyfill_rs::Side::SELL
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},
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price,
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size,
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sequence: (i + 1000) as u64,
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};
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let _ = book.apply_delta(delta);
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}
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let book_duration = start.elapsed();
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// Benchmark fast calculations
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let start = Instant::now();
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for _ in 0..1000000 {
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@@ -172,17 +194,23 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
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let _ = book.mid_price_fast();
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}
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let calc_duration = start.elapsed();
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println!(" ⚡ Order book: 10,000 updates in {:?}", book_duration);
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println!(" 📊 Rate: {:.0} updates/second", 10000.0 / book_duration.as_secs_f64());
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println!(
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" 📊 Rate: {:.0} updates/second",
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10000.0 / book_duration.as_secs_f64()
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);
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println!(" ⚡ Fast calcs: 2M operations in {:?}", calc_duration);
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println!(" 📊 Rate: {:.0}M operations/second", 2.0 / calc_duration.as_secs_f64());
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println!(
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" 📊 Rate: {:.0}M operations/second",
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2.0 / calc_duration.as_secs_f64()
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);
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// Test 4: JSON Parsing Performance
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println!("\n📊 Test 4: JSON Parsing Performance");
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println!("==================================");
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let sample_market_json = r#"{
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"condition_id": "21742633143463906290569050155826241533067272736897614950488156847949938836455",
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"question": "Will Donald Trump win the 2024 US Presidential Election?",
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@@ -213,35 +241,41 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
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}
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]
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}"#;
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let start = Instant::now();
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for _ in 0..10000 {
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let _: Result<serde_json::Value, _> = serde_json::from_str(sample_market_json);
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}
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let json_duration = start.elapsed();
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println!(" ⚡ JSON parsing: 10,000 parses in {:?}", json_duration);
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println!(" 📊 Rate: {:.0} parses/second", 10000.0 / json_duration.as_secs_f64());
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println!(" 📊 Per parse: {:.1}µs", json_duration.as_micros() as f64 / 10000.0);
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println!(
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" 📊 Rate: {:.0} parses/second",
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10000.0 / json_duration.as_secs_f64()
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);
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println!(
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" 📊 Per parse: {:.1}µs",
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json_duration.as_micros() as f64 / 10000.0
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);
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println!("\n🎯 Summary");
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println!("=========");
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println!("Network Performance:");
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println!(" • Competitive with polymarket-rs-client baseline");
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println!(" • Network latency dominates end-to-end performance");
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println!(" • Geographic location affects results significantly");
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println!("\nComputational Performance:");
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println!(" • Order book operations: Sub-millisecond");
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println!(" • Fast calculations: Sub-microsecond");
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println!(" • JSON parsing: Microsecond-scale");
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println!(" • Memory efficient: Zero-allocation hot paths");
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println!("\n✨ polyfill-rs provides:");
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println!(" • Same network performance as alternatives");
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println!(" • Superior computational performance");
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println!(" • Memory-optimized data structures");
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println!(" • Fixed-point arithmetic advantages");
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Ok(())
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}
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