5634909f06
Replace _param suppression pattern with actual usage across 21 files: - adaptive-strategy: wire EpistemicConfig/AleatoricConfig into UncertaintyQuantifier, KellyConfig into DrawdownTracker, TLOBConfig into TLOBTransformer - trading_engine/compliance: store config in 26 compliance structs (audit_trails, best_execution, sox, iso27001, transaction_reporting, compliance_reporting, automated_reporting) with public accessors - fxt: store Channel in LoginClient, ConnectionConfig in ConnectionManager - ml: remove unused path param from ReplayBuffer::new(), wire Mamba2Config.target_latency_us into HardwareOptimizer - services: store TrainingConfig in GpuConfigManager, symbol in TechnicalIndicatorCalculator - database: change let _result to let _ (intentional discard) - trading_engine/brokers: store BrokerConnectorConfig in BrokerConnector Result: 0 warnings across all 37+ workspace crates. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Database Crate
Overview
The database crate manages the persistent storage layer for the Foxhunt HFT system, primarily utilizing PostgreSQL. It handles schema definitions, migrations, and provides utilities for storing and querying critical trading data, including time-series market data and audit logs.
Features
- PostgreSQL Schema & Migrations: Defines database schemas for trading events, market data, and user configurations, managed via an integrated migration system.
- Event Streaming & Audit Log: Provides interfaces for recording and querying all significant system events, ensuring a comprehensive audit trail for compliance and post-trade analysis.
- Optimized Time-Series Storage: Implements efficient storage and indexing strategies for high-volume, time-series market data.
- Query Utilities: Offers a set of helper functions and ORM-like abstractions for common data retrieval and manipulation tasks.
- Connection Pooling: Manages database connections efficiently using a connection pool to minimize overhead and improve throughput.
- Data Archiving & Retention: Includes mechanisms for managing data lifecycle, such as archiving old data or implementing retention policies.
Usage
use database::models::{TradeEvent, NewTradeEvent};
use database::connection::establish_connection;
use common::types::{InstrumentId, Price, Quantity};
use chrono::Utc;
// This would typically come from a connection pool
let mut conn = establish_connection().expect("Failed to connect to database");
let new_trade = NewTradeEvent {
timestamp: Utc::now(),
instrument_id: InstrumentId::new("ETHUSD".to_string()),
price: Price::new(3000.50),
quantity: Quantity::new(1.2),
side: "BUY".to_string(),
// ... other fields
};
// Example: Insert a new trade event
// let inserted_trade = database::crud::create_trade_event(&mut conn, new_trade)
// .expect("Failed to insert trade event");
// println!("Inserted trade: {:?}", inserted_trade);
Testing
cargo test --package database
Documentation
Detailed API documentation is available at docs.rs/database.