feat: refresh benchmark coverage and harden CI tooling
Refresh the benchmark and performance surface across the repo. This updates the benchmark wrappers and helper scripts, regenerates the checked-in benchmark and perf-contract artifacts, and folds in the related roadmap, compatibility, and example notebook changes that belong with this performance-focused pass. Harden the Python CI and local pre-push flow so the same checks pass reliably in both places. The workflow and pre-push script now use module-safe uv typecheck invocations, the Python test environment installs the optional MCP dependency needed by the MCP server tests, and one-off root benchmark outputs are ignored to keep the repo clean. Align local tooling with the current project configuration by updating the Ruff pre-commit hook, tightening the API typing and MCP server helpers, and refreshing the lockfile to pick up the audited PyJWT fix while preserving the rest of the staged source changes.
This commit is contained in:
Pratik Bhadane
+18
-18
@@ -77,7 +77,7 @@ from __future__ import annotations
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import math
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import os
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from typing import Any, Dict, List, Optional
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from typing import Any
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import numpy as np
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@@ -117,12 +117,12 @@ app = FastAPI(
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# ---------------------------------------------------------------------------
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def _nan_to_none(arr: np.ndarray) -> List[Optional[float]]:
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def _nan_to_none(arr: np.ndarray) -> list[float | None]:
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"""Convert numpy array to list, replacing NaN/Inf with None."""
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return [None if not math.isfinite(v) else float(v) for v in arr]
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def _validate_series(close: List[float]) -> np.ndarray:
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def _validate_series(close: list[float]) -> np.ndarray:
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if len(close) > MAX_SERIES_LENGTH:
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raise HTTPException(
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status_code=413,
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@@ -142,54 +142,54 @@ def _validate_series(close: List[float]) -> np.ndarray:
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class IndicatorRequest(BaseModel):
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close: List[float] = Field(..., description="Close price series")
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close: list[float] = Field(..., description="Close price series")
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timeperiod: int = Field(default=14, ge=1, description="Look-back period")
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@field_validator("close")
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@classmethod
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def close_must_be_finite(cls, v: List[float]) -> List[float]:
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def close_must_be_finite(cls, v: list[float]) -> list[float]:
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if not all(math.isfinite(x) for x in v):
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raise ValueError("close series must contain only finite values")
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return v
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class MACDRequest(BaseModel):
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close: List[float] = Field(..., description="Close price series")
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close: list[float] = Field(..., description="Close price series")
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fastperiod: int = Field(default=12, ge=1)
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slowperiod: int = Field(default=26, ge=1)
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signalperiod: int = Field(default=9, ge=1)
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@field_validator("close")
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@classmethod
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def close_must_be_finite(cls, v: List[float]) -> List[float]:
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def close_must_be_finite(cls, v: list[float]) -> list[float]:
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if not all(math.isfinite(x) for x in v):
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raise ValueError("close series must contain only finite values")
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return v
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class BBANDSRequest(BaseModel):
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close: List[float] = Field(..., description="Close price series")
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close: list[float] = Field(..., description="Close price series")
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timeperiod: int = Field(default=5, ge=2)
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nbdevup: float = Field(default=2.0, gt=0)
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nbdevdn: float = Field(default=2.0, gt=0)
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@field_validator("close")
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@classmethod
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def close_must_be_finite(cls, v: List[float]) -> List[float]:
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def close_must_be_finite(cls, v: list[float]) -> list[float]:
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if not all(math.isfinite(x) for x in v):
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raise ValueError("close series must contain only finite values")
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return v
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class BacktestRequest(BaseModel):
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close: List[float] = Field(..., description="Close price series")
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close: list[float] = Field(..., description="Close price series")
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strategy: str = Field(default="rsi_30_70")
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commission_per_trade: float = Field(default=0.0, ge=0.0)
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slippage_bps: float = Field(default=0.0, ge=0.0)
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@field_validator("close")
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@classmethod
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def close_must_be_finite(cls, v: List[float]) -> List[float]:
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def close_must_be_finite(cls, v: list[float]) -> list[float]:
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if not all(math.isfinite(x) for x in v):
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raise ValueError("close series must contain only finite values")
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return v
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@@ -201,13 +201,13 @@ class BacktestRequest(BaseModel):
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@app.get("/health", summary="Health check")
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def health() -> Dict[str, str]:
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def health() -> dict[str, str]:
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"""Readiness / liveness probe."""
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return {"status": "ok", "version": app.version}
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@app.post("/indicators/sma", summary="Simple Moving Average")
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def compute_sma(req: IndicatorRequest) -> Dict[str, Any]:
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def compute_sma(req: IndicatorRequest) -> dict[str, Any]:
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"""Compute Simple Moving Average (SMA).
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Returns ``result``: list of floats (null for warm-up bars).
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@@ -218,7 +218,7 @@ def compute_sma(req: IndicatorRequest) -> Dict[str, Any]:
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@app.post("/indicators/ema", summary="Exponential Moving Average")
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def compute_ema(req: IndicatorRequest) -> Dict[str, Any]:
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def compute_ema(req: IndicatorRequest) -> dict[str, Any]:
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"""Compute Exponential Moving Average (EMA)."""
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c = _validate_series(req.close)
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out = np.asarray(ft.EMA(c, timeperiod=req.timeperiod), dtype=np.float64)
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@@ -226,7 +226,7 @@ def compute_ema(req: IndicatorRequest) -> Dict[str, Any]:
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@app.post("/indicators/rsi", summary="Relative Strength Index")
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def compute_rsi(req: IndicatorRequest) -> Dict[str, Any]:
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def compute_rsi(req: IndicatorRequest) -> dict[str, Any]:
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"""Compute Relative Strength Index (RSI)."""
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c = _validate_series(req.close)
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out = np.asarray(ft.RSI(c, timeperiod=req.timeperiod), dtype=np.float64)
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@@ -234,7 +234,7 @@ def compute_rsi(req: IndicatorRequest) -> Dict[str, Any]:
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@app.post("/indicators/macd", summary="MACD")
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def compute_macd(req: MACDRequest) -> Dict[str, Any]:
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def compute_macd(req: MACDRequest) -> dict[str, Any]:
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"""Compute MACD (line, signal, histogram).
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Returns ``result`` with keys ``macd``, ``signal``, ``hist``.
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@@ -256,7 +256,7 @@ def compute_macd(req: MACDRequest) -> Dict[str, Any]:
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@app.post("/indicators/bbands", summary="Bollinger Bands")
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def compute_bbands(req: BBANDSRequest) -> Dict[str, Any]:
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def compute_bbands(req: BBANDSRequest) -> dict[str, Any]:
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"""Compute Bollinger Bands (upper, middle, lower).
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Returns ``result`` with keys ``upper``, ``middle``, ``lower``.
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@@ -278,7 +278,7 @@ def compute_bbands(req: BBANDSRequest) -> Dict[str, Any]:
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@app.post("/backtest", summary="Vectorized backtest")
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def run_backtest(req: BacktestRequest) -> Dict[str, Any]:
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def run_backtest(req: BacktestRequest) -> dict[str, Any]:
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"""Run a vectorized backtest using a named strategy.
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Strategies: ``rsi_30_70``, ``sma_crossover``, ``macd_crossover``.
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