Files
foxhunt/trading_engine
jgrusewski eae3c31e53 fix(clippy): Fix 6 unwrap_used violations in risk/data
Patterns applied:
- Pattern 2: Float comparison (2x: utils.rs, var_edge_cases_tests.rs)
- Pattern 7: Date/time construction (2x: production_streaming.rs, streaming.rs)
- Pattern 1: Duration/time ops (2x: rate limiter, semaphore)
- Pattern 4: Optional field access (1x: position_tracker.rs)

Changes:
- data/src/utils.rs: Float sort with NaN handling
- data/src/providers/benzinga/production_streaming.rs: Rate limiter + semaphore + date/time
- data/src/providers/benzinga/streaming.rs: Date/time construction
- risk/src/position_tracker.rs: Emergency fallback counter
- risk/tests/var_edge_cases_tests.rs: Test helper float sort

Test impact: 0 failures (182/182 passing)
Compilation: Clean (0 errors, 0 warnings)
Time: 25 min (44% under budget)
2025-10-23 14:58:32 +02:00
..

Trading Engine Crate

Overview

The trading_engine crate provides the high-performance core infrastructure essential for High-Frequency Trading (HFT) operations. It focuses on ultra-low latency execution, precise timing, and efficient order management to handle demanding market conditions.

Features

  • Extreme Performance Optimization: Utilizes RDTSC for precise timing, CPU affinity for dedicated core execution, and SIMD instructions for vectorized data processing.
  • Robust Order Management: Manages the lifecycle of orders, from placement to execution and cancellation, ensuring accuracy and low-latency updates.
  • Flexible Execution Engine: Implements a highly optimized engine capable of processing trading strategies and executing orders across various venues.
  • Multi-Broker Connectivity: Seamlessly integrates with multiple brokers, including Interactive Brokers and ICMarkets, via specialized adapters.
  • Event-Sourced Architecture: Employs event sourcing for deterministic state reconstruction, coupled with comprehensive metrics and persistent storage.
  • Concurrent Lock-Free Data Structures: Leverages advanced lock-free data structures to minimize contention and maximize throughput in multi-threaded environments.

Architecture

The trading_engine is structured around several key components:

  • Execution Core: The central logic for strategy evaluation and trade decision-making.
  • Order Manager: Handles all order-related operations, maintaining order state and communicating with broker adapters.
  • Broker Adapters: Abstract interfaces and concrete implementations for connecting to specific trading venues (e.g., IbAdapter, IcMarketsAdapter).
  • Performance Utilities: Modules for RDTSC access, CPU core pinning, and SIMD instruction sets.
  • Event Store: A mechanism for recording all significant events, enabling replay and auditability.
  • Metrics System: Collects and reports performance and operational statistics.
  • Persistence Layer: Stores critical state and event data for recovery and analysis.
  • Concurrency Primitives: Custom lock-free queues, rings, and other data structures.

Usage

To initialize the trading engine and place a simple order:

use trading_engine::{
    engine::TradingEngine,
    order::{Order, OrderSide, OrderType},
    broker::BrokerType,
};

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut engine = TradingEngine::new();
    engine.connect_broker(BrokerType::InteractiveBrokers).await?;

    let order = Order {
        symbol: "ESZ23".to_string(),
        side: OrderSide::Buy,
        order_type: OrderType::Limit,
        quantity: 1,
        price: Some(4500.0),
        // ... other order details
    };

    let order_id = engine.place_order(order).await?;
    println!("Placed order with ID: {}", order_id);

    Ok(())
}

Testing

To run the tests for the trading_engine crate:

cargo test --package trading_engine

Documentation

Comprehensive API documentation is available at docs.rs/trading_engine.