ParallelLLC/algorithmic_trading

1"""algotrader 2.0 — a backtester that tries to prove itself wrong.2 3Most backtesting libraries answer "how much would this have made?". This one4answers the question that actually matters before you risk money: "how much of5that was luck?"6 7Quick start::8 9    from algotrader import LabConfig, run_lab10 11    report = run_lab(LabConfig(symbol="SPY", strategy="sma_cross"))12    print(report.verdict["verdict"])13"""14 15from .attribution import build_style_factors, factor_attribution16from .cross_sectional import XS_REGISTRY, get_xs_strategy, list_xs_strategies17from .data import load_ohlcv, simulate_ohlcv18from .engine import run_backtest19from .lab import LabConfig, LabReport, run_arena, run_lab20from .metrics import compute_metrics21from .panel import Panel, load_panel22from .portfolio import rebalance_schedule, run_portfolio_backtest23from .portfolio_lab import PortfolioLabConfig, PortfolioLabReport, run_portfolio_arena, run_portfolio_lab24from .strategies import REGISTRY, get_strategy, list_strategies25from .types import BacktestResult, CostModel, MarketData26from .verdict import reality_score27 28__version__ = "2.1.0"29 30__all__ = [31    "__version__",32    # single asset33    "LabConfig",34    "LabReport",35    "run_lab",36    "run_arena",37    "run_backtest",38    "get_strategy",39    "list_strategies",40    "REGISTRY",41    # multi asset42    "Panel",43    "load_panel",44    "run_portfolio_backtest",45    "rebalance_schedule",46    "PortfolioLabConfig",47    "PortfolioLabReport",48    "run_portfolio_lab",49    "run_portfolio_arena",50    "get_xs_strategy",51    "list_xs_strategies",52    "XS_REGISTRY",53    "build_style_factors",54    "factor_attribution",55    # shared56    "compute_metrics",57    "load_ohlcv",58    "simulate_ohlcv",59    "BacktestResult",60    "CostModel",61    "MarketData",62    "reality_score",63]64