mirror of
https://github.com/floor-licker/polyfill-rs.git
synced 2026-08-07 17:57:45 +00:00
floor-licker
95 lines
4.7 KiB
Markdown
95 lines
4.7 KiB
Markdown
|
|
|
|
[](https://crates.io/crates/polyfill-rs)
|
|
[](https://docs.rs/polyfill-rs)
|
|
[](LICENSE)
|
|
|
|
A high-performance drop-in replacement for `polymarket-rs-client` with latency-optimized data structures and zero-allocation hot paths. A 100% API-compatible drop-in replacement for `polymarket-rs-client` with identical method signatures.
|
|
|
|
|
|
## Quick Start
|
|
|
|
Add to your `Cargo.toml`:
|
|
|
|
```toml
|
|
[dependencies]
|
|
polyfill-rs = "0.2.3"
|
|
```
|
|
|
|
Replace your imports:
|
|
|
|
```rust
|
|
// Before: use polymarket_rs_client::{ClobClient, Side, OrderType};
|
|
use polyfill_rs::{ClobClient, Side, OrderType};
|
|
|
|
#[tokio::main]
|
|
async fn main() -> Result<(), Box<dyn std::error::Error>> {
|
|
let client = ClobClient::new("https://clob.polymarket.com");
|
|
let markets = client.get_sampling_markets(None).await?;
|
|
println!("Found {} markets", markets.data.len());
|
|
Ok(())
|
|
}
|
|
```
|
|
|
|
## Performance Comparison
|
|
|
|
**Real-World API Performance (with network I/O)**
|
|
|
|
End-to-end performance with Polymarket's API, including network latency, JSON parsing, and decompression:
|
|
|
|
| Operation | polyfill-rs | polymarket-rs-client | Official Python Client |
|
|
|-----------|-------------|----------------------|------------------------|
|
|
| **Fetch Markets** | **321.6 ms ± 92.9 ms** | 409.3 ms ± 137.6 ms | 1.366 s ± 0.048 s |
|
|
|
|
|
|
**Performance vs Competition:**
|
|
- **21.4% faster** than polymarket-rs-client - 87.6ms improvement
|
|
- **32.5% more consistent** than polymarket-rs-client
|
|
- **4.2x faster** than Official Python Client
|
|
|
|
**Benchmark Methodology:** All benchmarks run side-by-side on the same machine, same network, same time using identical testing methodology (20 iterations, 100ms delay between requests, /simplified-markets endpoint). Best performance achieved with connection keep-alive enabled. See `examples/side_by_side_benchmark.rs` for the complete benchmark implementation.
|
|
|
|
**Computational Performance (pure CPU, no I/O)**
|
|
|
|
| Operation | Performance | Notes |
|
|
|-----------|-------------|-------|
|
|
| **Order Book Updates (1000 ops)** | 159.6 µs ± 32 µs | 6,260 updates/sec, zero-allocation |
|
|
| **Spread/Mid Calculations** | 70 ns ± 77 ns | 14.3M ops/sec, optimized BTreeMap |
|
|
| **JSON Parsing (480KB)** | ~2.3 ms | SIMD-accelerated parsing (1.77x faster than serde_json) |
|
|
|
|
**Key Performance Optimizations:**
|
|
|
|
The 21.4% performance improvement comes from SIMD-accelerated JSON parsing (1.77x faster than serde_json), HTTP/2 tuning with 512KB stream windows optimized for 469KB payloads, integrated DNS caching, connection keep-alive, and buffer pooling to reduce allocation overhead.
|
|
|
|
### Benchmarking Methodology
|
|
|
|
**Side-by-Side Testing:**
|
|
Both clients tested sequentially on identical infrastructure with the same network state, API endpoint, and parameters (20 iterations, 100ms delays). Side-by-side testing reveals polymarket-rs-client's claimed ±22.9ms variance understates actual ±137.6ms variance by 500%.
|
|
|
|
**What We Measure:**
|
|
- Real-world API performance with actual network I/O
|
|
- Statistical analysis with multiple runs (mean ± standard deviation)
|
|
- Connection establishment overhead and warm connection performance
|
|
- Variance analysis to measure consistency
|
|
|
|
### Critical Path Optimizations
|
|
|
|
Fixed-point arithmetic eliminates floating-point pipeline stalls and decimal parsing overhead. Lock-free updates using compare-and-swap operations prevent mutex contention. Cache-aligned structures maintain 64-byte alignment for L1/L2 cache efficiency. SIMD-friendly data layouts enable batch price level processing.
|
|
|
|
### Memory Architecture
|
|
|
|
Pre-allocated pools eliminate allocation latency spikes. Configurable book depth limiting prevents memory bloat. Hot data structures group frequently-accessed fields for cache line efficiency.
|
|
|
|
### Architectural Principles
|
|
|
|
Price data converts to fixed-point at ingress boundaries while maintaining tick-aligned precision. The critical path uses integer arithmetic with branchless operations. Data converts back to IEEE 754 at egress for API compatibility. This enables deterministic execution with predictable instruction counts.
|
|
|
|
### Measured Network Improvements
|
|
|
|
| Optimization Technique | Performance Gain | Use Case |
|
|
|------------------------|------------------|----------|
|
|
| **Optimized HTTP client** | **11% baseline improvement** | Every API call |
|
|
| **Connection pre-warming** | **70% faster subsequent requests** | Application startup |
|
|
| **Request parallelization** | **200% faster batch operations** | Multi-market data fetching |
|
|
| **Circuit breaker resilience** | **Better uptime during instability** | Production trading systems |
|