feat: expand rust parity, wasm exports, and api conformance
Move several hot Python analysis paths to Rust-backed helpers. This adds Rust implementations for backtest strategy signal generation and the core portfolio loop, options and futures payoff aggregation, Greeks aggregation, ratio calculation, trade extraction, chunked close-only indicator runs, and forward-fill helpers. Wire the Python analysis and data modules to prefer these paths, and add coverage for the new batch fast path. Expand the WASM package to export WMA, ADX, and MFI from ferro_ta_core, refresh the Node examples, benchmarks, and README, and add a Node-vs-Python conformance test so the browser and node surface stays aligned with the main Python package. Introduce a generated cross-surface API manifest in docs/, along with scripts to rebuild and verify it from source exports. Enforce manifest freshness in the Python and WASM CI workflows so release candidates catch surface drift before push.
This commit is contained in:
Pratik Bhadane
@@ -11,10 +11,16 @@ from typing import Any
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import numpy as np
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from numpy.typing import ArrayLike, NDArray
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from ferro_ta._ferro_ta import aggregate_greeks_legs as _rust_aggregate_greeks_legs
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from ferro_ta._ferro_ta import strategy_payoff_dense as _rust_strategy_payoff_dense
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from ferro_ta._ferro_ta import strategy_payoff_legs as _rust_strategy_payoff_legs
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from ferro_ta.analysis.options import OptionGreeks
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from ferro_ta.analysis.options import greeks as option_greeks
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from ferro_ta.analysis.options_strategy import DerivativesStrategy, StrategyLeg
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from ferro_ta.core.exceptions import FerroTAInputError, FerroTAValueError
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from ferro_ta.core.exceptions import (
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FerroTAInputError,
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FerroTAValueError,
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_normalize_rust_error,
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)
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__all__ = [
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"PayoffLeg",
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@@ -79,14 +85,23 @@ def option_leg_payoff(
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) -> NDArray[np.float64]:
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"""Expiry payoff for a single option leg."""
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grid = _coerce_spot_grid(spot_grid)
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sign = _side_sign(side) * float(quantity) * float(multiplier)
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if option_type == "call":
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intrinsic = np.maximum(grid - float(strike), 0.0)
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elif option_type == "put":
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intrinsic = np.maximum(float(strike) - grid, 0.0)
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else:
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_side_sign(side)
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if option_type not in {"call", "put"}:
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raise FerroTAValueError("option_type must be 'call' or 'put'.")
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return sign * (intrinsic - float(premium))
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return np.asarray(
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_rust_strategy_payoff_dense(
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grid,
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np.array([0], dtype=np.int64), # option
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np.array([1 if side == "long" else -1], dtype=np.int64),
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np.array([1 if option_type == "call" else -1], dtype=np.int64),
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np.array([float(strike)], dtype=np.float64),
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np.array([float(premium)], dtype=np.float64),
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np.array([0.0], dtype=np.float64),
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np.array([float(quantity)], dtype=np.float64),
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np.array([float(multiplier)], dtype=np.float64),
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),
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dtype=np.float64,
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)
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def futures_leg_payoff(
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@@ -99,8 +114,21 @@ def futures_leg_payoff(
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) -> NDArray[np.float64]:
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"""P/L profile for a futures leg."""
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grid = _coerce_spot_grid(spot_grid)
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sign = _side_sign(side) * float(quantity) * float(multiplier)
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return sign * (grid - float(entry_price))
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_side_sign(side)
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return np.asarray(
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_rust_strategy_payoff_dense(
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grid,
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np.array([1], dtype=np.int64), # future
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np.array([1 if side == "long" else -1], dtype=np.int64),
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np.array([-1], dtype=np.int64),
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np.array([0.0], dtype=np.float64),
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np.array([0.0], dtype=np.float64),
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np.array([float(entry_price)], dtype=np.float64),
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np.array([float(quantity)], dtype=np.float64),
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np.array([float(multiplier)], dtype=np.float64),
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),
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dtype=np.float64,
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)
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def _mapping_to_leg(mapping: Mapping[str, Any]) -> PayoffLeg:
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@@ -141,31 +169,13 @@ def strategy_payoff(
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"""Aggregate expiry payoff across option and futures legs."""
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grid = _coerce_spot_grid(spot_grid)
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normalized = _normalize_legs(legs, strategy=strategy)
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total = np.zeros_like(grid)
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for leg in normalized:
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if leg.instrument == "option":
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if leg.strike is None:
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raise FerroTAValueError("Option payoff legs require strike.")
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total += option_leg_payoff(
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grid,
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strike=float(leg.strike),
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premium=float(leg.premium),
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option_type=str(leg.option_type),
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side=str(leg.side),
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quantity=float(leg.quantity),
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multiplier=float(leg.multiplier),
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)
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else:
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if leg.entry_price is None:
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raise FerroTAValueError("Futures payoff legs require entry_price.")
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total += futures_leg_payoff(
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grid,
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entry_price=float(leg.entry_price),
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side=str(leg.side),
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quantity=float(leg.quantity),
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multiplier=float(leg.multiplier),
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)
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return total
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if len(normalized) == 0:
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return np.zeros_like(grid)
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try:
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return np.asarray(_rust_strategy_payoff_legs(grid, normalized), dtype=np.float64)
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except ValueError as err:
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_normalize_rust_error(err)
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def aggregate_greeks(
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@@ -176,42 +186,20 @@ def aggregate_greeks(
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) -> OptionGreeks:
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"""Aggregate Greeks across option and futures legs."""
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normalized = _normalize_legs(legs, strategy=strategy)
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totals = {
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"delta": 0.0,
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"gamma": 0.0,
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"vega": 0.0,
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"theta": 0.0,
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"rho": 0.0,
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}
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for leg in normalized:
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leg_sign = _side_sign(leg.side) * float(leg.quantity) * float(leg.multiplier)
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if leg.instrument == "future":
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totals["delta"] += leg_sign
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continue
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if leg.strike is None or leg.volatility is None or leg.time_to_expiry is None:
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raise FerroTAValueError(
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"Option legs require strike, volatility, and time_to_expiry for Greeks aggregation."
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)
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leg_greeks = option_greeks(
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float(spot),
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float(leg.strike),
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float(leg.rate),
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float(leg.time_to_expiry),
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float(leg.volatility),
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option_type=str(leg.option_type),
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model="bsm",
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carry=float(leg.carry),
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if len(normalized) == 0:
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return OptionGreeks(0.0, 0.0, 0.0, 0.0, 0.0)
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try:
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delta, gamma, vega, theta, rho = _rust_aggregate_greeks_legs(
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float(spot), normalized
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)
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totals["delta"] += leg_sign * float(leg_greeks.delta)
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totals["gamma"] += leg_sign * float(leg_greeks.gamma)
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totals["vega"] += leg_sign * float(leg_greeks.vega)
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totals["theta"] += leg_sign * float(leg_greeks.theta)
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totals["rho"] += leg_sign * float(leg_greeks.rho)
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except ValueError as err:
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_normalize_rust_error(err)
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return OptionGreeks(
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totals["delta"],
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totals["gamma"],
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totals["vega"],
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totals["theta"],
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totals["rho"],
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float(delta),
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float(gamma),
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float(vega),
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float(theta),
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float(rho),
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)
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