QuanTAlib/python

quantalib — Python NativeAOT Wrapper

High-performance Python wrapper for QuanTAlib, a .NET NativeAOT technical analysis library.

Features

• ~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