~391 indicators across 15 categories: channels, core, cycles, dynamics, errors, filters, momentum, numerics, oscillators, reversals, statistics, trends (FIR & IIR), volatility, volume
Zero-copy FFI — ctypes bridge to pre-compiled NativeAOT shared library
NumPy native — all inputs/outputs are float64 arrays
Optional pandas support — pass pd.Series in, get pd.Series out with preserved index
pandas-ta compatible — quantalib._compat provides alias mapping for drop-in migration

Installation

pip install quantalib

Note: The NativeAOT shared library (quantalib_native.dll / .so / .dylib) must be present in quantalib/native/<platform>/. Pre-built binaries are included in wheel distributions.

Quick Start

import numpy as np
import quantalib as qtl

close = np.random.randn(200).cumsum() + 100

# Simple Moving Average
sma = qtl.sma(close, length=20)

# Bollinger Bands (multi-output → tuple or DataFrame)
upper, mid, lower = qtl.bbands(close, length=20, std=2.0)

# With pandas
import pandas as pd
s = pd.Series(close, name="close")
rsi = qtl.rsi(s, length=14)  # returns pd.Series with preserved index

Categories

Category	Module	Examples
Channels	`channels`	bbands, kchannel, dchannel, aberr
Core	`core`	ha, midpoint, avgprice, typprice
Cycles	`cycles`	ht_dcperiod, ht_sine, cg, dsp
Dynamics	`dynamics`	adx, aroon, ichimoku, supertrend
Errors	`errors`	mse, rmse, mae, mape, huber
Filters	`filters`	kalman, sgf, hp, butter2, wavelet
Momentum	`momentum`	rsi, macd, roc, mom, tsi
Numerics	`numerics`	fft, normalize, sigmoid, slope
Oscillators	`oscillators`	stoch, cci, fisher, qqe, willr
Reversals	`reversals`	psar, pivot, fractals, swings
Statistics	`statistics`	zscore, correlation, entropy, linreg
Trends FIR	`trends_fir`	sma, wma, hma, alma, trima
Trends IIR	`trends_iir`	ema, dema, tema, kama, jma
Volatility	`volatility`	atr, bbw, stddev, hv, tr
Volume	`volume`	obv, vwma, mfi, cmf, adl

Local Development

cd python/
python -m venv .venv && .venv/Scripts/activate  # or source .venv/bin/activate
pip install -e ".[dev]"
pytest

Building the native library

dotnet publish python.csproj -c Release

License

MIT