2da5bafc0e
- Rename tli/ directory to fxt/, update package + binary name to "fxt" - Replace all `use tli::` → `use fxt::` across 52 Rust files - Update build.rs proto paths (tli/proto → fxt/proto) in 6 services - Update Dockerfiles, CI workflows, deploy.sh for new paths - Delete ~170 legacy shell scripts (kept 15 essential ones) - Delete RunPod Python client (runpod/), tests (tests/runpod/) - Delete foxhunt-deploy crate (RunPod-only deployment tool) - Delete terraform/runpod/ (moved to Scaleway) - Delete ML Python hyperopt scripts (replaced by Rust Argmin PSO) - Delete .gitlab-ci.yml (using GitHub + Gitea) - Remove foxhunt-deploy from workspace members 504 files changed, -74,355 lines of legacy code removed. Workspace compiles clean (0 errors, 0 warnings). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Backtesting Service
Overview
The backtesting_service offers an independent and isolated environment for rigorously testing and validating trading strategies against historical market data. It provides a robust platform for simulating trading performance, analyzing strategy efficacy, and generating comprehensive performance reports before live deployment.
Features
- Independent Backtesting Service: Operates autonomously, allowing for parallel and isolated strategy evaluations.
- gRPC API for Backtest Execution: Exposes a clear API for submitting and managing backtesting jobs.
- Strategy Testing and Validation: Enables comprehensive testing of various trading strategies under different market conditions.
- Performance Reporting: Generates detailed reports including metrics like P&L, Sharpe ratio, drawdown, and win rate.
- Data Replay Engine: Accurately replays historical market data, simulating real-world order book dynamics and trade execution.
- Results Persistence: Stores backtesting results and reports for historical analysis and comparison.
gRPC API
The backtesting_service exposes a gRPC API for initiating and retrieving backtest results. Key endpoints include:
RunBacktest- Submit backtest configuration and strategyGetBacktestResults- Retrieve results for completed backtestsListAvailableStrategies- List registered strategiesGetBacktestReport- Get detailed performance report
Running the service
To run the backtesting_service binary:
cargo run --bin backtesting_service
Data Requirements
The service requires historical market data in Parquet format:
- Data should be stored in the configured data directory
- Supports tick data, order book snapshots, and OHLCV candles
- Data must include instrument, timestamp, and price/quantity fields
Testing
To run the tests for the backtesting_service crate:
cargo test --package backtesting_service
Documentation
Comprehensive API documentation is available at docs.rs/backtesting_service.