porcelaincode
fc0c756203
- README: remove VectorBT Comparison section and TOC entry, rewrite Overview/Performance as standalone benchmarks, clean metric-mapping table reference, update feature list to 7 strategy types including tick - Cargo.toml / pyproject.toml: rewrite description without VectorBT mention - __init__.py: rewrite module docstring without comparative framing - Rust comments (engine.rs, position.rs, signals/processor.rs, core/types.rs, python/bindings.rs): replace "matching VectorBT behavior/formula/methodology" with plain descriptions of what the code does Co-Authored-By: porcelaincode <contact@alphabench.in>
110 lines
2.4 KiB
Python
110 lines
2.4 KiB
Python
"""
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RaptorBT - High-performance Rust backtesting engine.
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Provides Python bindings for a Rust-based backtesting engine built for
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production quantitative trading:
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- Sub-millisecond execution on thousands of bars
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- Disk footprint: <10MB, startup latency: <10ms
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- 100% deterministic execution (no JIT cache)
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- Native parallelism via Rayon + explicit SIMD
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- Full tick-level simulation (no bar resampling required)
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"""
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from raptorbt._raptorbt import (
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# Config classes
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PyBacktestConfig,
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PyInstrumentConfig,
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PyStopConfig,
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PyTargetConfig,
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# Result classes
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PyBacktestResult,
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PyBacktestMetrics,
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PyTrade,
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# Backtest functions
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run_single_backtest,
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run_basket_backtest,
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run_options_backtest,
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run_pairs_backtest,
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run_multi_backtest,
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run_spread_backtest,
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run_tick_backtest,
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# Batch backtest
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PyBatchSpreadItem,
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batch_spread_backtest,
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# Monte Carlo simulation
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simulate_portfolio_mc,
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# Tick signal functions
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compute_tick_entry_signals,
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compute_tick_exit_signals,
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# Tick feature functions
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tick_spread_pct,
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buy_sell_imbalance_delta,
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return_window,
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realized_vol_rolling,
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oi_position_pct,
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tick_velocity,
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# Indicator functions
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sma,
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ema,
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rsi,
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macd,
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stochastic,
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atr,
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bollinger_bands,
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adx,
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vwap,
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supertrend,
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rolling_min,
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rolling_max,
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)
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__version__ = "0.4.0"
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__all__ = [
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# Config classes
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"PyBacktestConfig",
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"PyInstrumentConfig",
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"PyStopConfig",
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"PyTargetConfig",
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# Result classes
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"PyBacktestResult",
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"PyBacktestMetrics",
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"PyTrade",
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# Backtest functions
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"run_single_backtest",
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"run_basket_backtest",
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"run_options_backtest",
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"run_pairs_backtest",
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"run_multi_backtest",
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"run_spread_backtest",
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"run_tick_backtest",
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# Batch backtest
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"PyBatchSpreadItem",
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"batch_spread_backtest",
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# Monte Carlo simulation
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"simulate_portfolio_mc",
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# Tick signal functions
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"compute_tick_entry_signals",
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"compute_tick_exit_signals",
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# Tick feature functions
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"tick_spread_pct",
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"buy_sell_imbalance_delta",
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"return_window",
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"realized_vol_rolling",
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"oi_position_pct",
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"tick_velocity",
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# Indicator functions
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"sma",
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"ema",
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"rsi",
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"macd",
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"stochastic",
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"atr",
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"bollinger_bands",
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"adx",
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"vwap",
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"supertrend",
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"rolling_min",
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"rolling_max",
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]
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