pytafast

A high-performance Python wrapper for TA-Lib built with nanobind. Provides 150+ technical analysis functions with pandas/numpy support and async capabilities.

Features

🚀 High Performance — C++ bindings via nanobind with GIL release for true parallelism
📊 Full TA-Lib Coverage — 150+ indicators including overlaps, momentum, volatility, volume, statistics, cycle indicators, and 61 candlestick patterns
🐼 Pandas Native — Seamless support for both numpy.ndarray and pandas.Series (preserves index)
⚡ Async Support — All functions available as async via pytafast.aio
🔒 GSL Powered Safety — Uses Microsoft GSL (gsl::not_null, gsl::span) to prevent buffer overflows and null pointer dereferences in C++
📦 Drop-in Replacement — Same API as ta-lib-python, easy migration

Installation

pip install pytafast

Build from Source

git clone --recursive https://github.com/twn39/pytafast.git
cd pytafast
pip install -v -e .

Quick Start

Basic Usage with NumPy

import numpy as np
import pytafast

# Generate sample price data
np.random.seed(42)
close = np.cumsum(np.random.randn(200)) + 100

# Moving Averages
sma = pytafast.SMA(close, timeperiod=20)
ema = pytafast.EMA(close, timeperiod=12)
wma = pytafast.WMA(close, timeperiod=10)

Momentum Indicators

# RSI — Relative Strength Index
rsi = pytafast.RSI(close, timeperiod=14)

# MACD — returns 3 arrays: macd line, signal line, histogram
macd, signal, hist = pytafast.MACD(close, fastperiod=12, slowperiod=26, signalperiod=9)

# Stochastic Oscillator — requires high, low, close
high = close + np.abs(np.random.randn(200)) * 2
low = close - np.abs(np.random.randn(200)) * 2
slowk, slowd = pytafast.STOCH(high, low, close, fastk_period=5, slowk_period=3, slowd_period=3)

# ADX — Average Directional Index
adx = pytafast.ADX(high, low, close, timeperiod=14)

Bollinger Bands & Volatility

# Bollinger Bands — returns upper, middle, lower bands
upper, middle, lower = pytafast.BBANDS(close, timeperiod=20, nbdevup=2.0, nbdevdn=2.0)

# ATR — Average True Range
atr = pytafast.ATR(high, low, close, timeperiod=14)

Volume Indicators

volume = np.random.random(200) * 1_000_000

# On-Balance Volume
obv = pytafast.OBV(close, volume)

# Chaikin A/D Line
ad = pytafast.AD(high, low, close, volume)

# Money Flow Index
mfi = pytafast.MFI(high, low, close, volume, timeperiod=14)

Statistics & Math

# Linear Regression
linreg = pytafast.LINEARREG(close, timeperiod=14)
slope = pytafast.LINEARREG_SLOPE(close, timeperiod=14)

# Correlation between two series
beta = pytafast.BETA(close, ema, timeperiod=5)
correl = pytafast.CORREL(close, ema, timeperiod=30)

# Standard Deviation
stddev = pytafast.STDDEV(close, timeperiod=20, nbdev=1.0)

Candlestick Pattern Recognition

# Generate OHLC data
open_ = close + np.random.randn(200) * 0.5

# Detect patterns — returns integer array (100=bullish, -100=bearish, 0=none)
engulfing = pytafast.CDLENGULFING(open_, high, low, close)
doji = pytafast.CDLDOJI(open_, high, low, close)
hammer = pytafast.CDLHAMMER(open_, high, low, close)
morning_star = pytafast.CDLMORNINGSTAR(open_, high, low, close, penetration=0.3)

# Find bullish signals
bullish_idx = np.where(engulfing == 100)[0]

Pandas Support

import pandas as pd

# Create a DataFrame of stock prices
df = pd.DataFrame({
    "open": open_,
    "high": high,
    "low": low,
    "close": close,
    "volume": volume,
}, index=pd.date_range("2024-01-01", periods=200, freq="D"))

# All functions accept and return pd.Series, preserving the DatetimeIndex
df["sma_20"] = pytafast.SMA(df["close"], timeperiod=20)
df["rsi_14"] = pytafast.RSI(df["close"], timeperiod=14)
df["atr_14"] = pytafast.ATR(df["high"], df["low"], df["close"], timeperiod=14)

upper, middle, lower = pytafast.BBANDS(df["close"], timeperiod=20)
df["bb_upper"] = upper
df["bb_lower"] = lower

Async Support

import asyncio
import pytafast

async def compute_indicators(close, high, low, volume):
    """Compute multiple indicators concurrently."""
    sma, rsi, macd_result, atr = await asyncio.gather(
        pytafast.aio.SMA(close, timeperiod=20),
        pytafast.aio.RSI(close, timeperiod=14),
        pytafast.aio.MACD(close),
        pytafast.aio.ATR(high, low, close, timeperiod=14),
    )
    macd, signal, hist = macd_result
    return sma, rsi, macd, atr

# asyncio.run(compute_indicators(close, high, low, volume))

Cycle Indicators

# Hilbert Transform indicators for cycle analysis
ht_period = pytafast.HT_DCPERIOD(close)
ht_trendline = pytafast.HT_TRENDLINE(close)
sine, leadsine = pytafast.HT_SINE(close)
trend_mode = pytafast.HT_TRENDMODE(close)  # 1 = trend, 0 = cycle

API Reference

All functions accept numpy.ndarray (float64) or pandas.Series. When a pandas.Series is provided, the function returns a pandas.Series with the same index.

Overlap Studies

Function	Signature	Description
SMA	`SMA(real, timeperiod=30)`	Simple Moving Average
EMA	`EMA(real, timeperiod=30)`	Exponential Moving Average
WMA	`WMA(real, timeperiod=30)`	Weighted Moving Average
DEMA	`DEMA(real, timeperiod=30)`	Double Exponential Moving Average
TEMA	`TEMA(real, timeperiod=30)`	Triple Exponential Moving Average
TRIMA	`TRIMA(real, timeperiod=30)`	Triangular Moving Average
KAMA	`KAMA(real, timeperiod=30)`	Kaufman Adaptive Moving Average
MAMA	`MAMA(real, fastlimit=0.5, slowlimit=0.05)`	MESA Adaptive Moving Average. Returns `(mama, fama)`
T3	`T3(real, timeperiod=5, vfactor=0.7)`	Triple Exponential Moving Average (T3)
BBANDS	`BBANDS(real, timeperiod=5, nbdevup=2.0, nbdevdn=2.0, matype=0)`	Bollinger Bands. Returns `(upper, middle, lower)`
MA	`MA(real, timeperiod=30, matype=0)`	Moving Average (generic)
SAR	`SAR(high, low, acceleration=0.02, maximum=0.2)`	Parabolic SAR
MIDPOINT	`MIDPOINT(real, timeperiod=14)`	Midpoint over period
MIDPRICE	`MIDPRICE(high, low, timeperiod=14)`	Midprice over period

Momentum Indicators

Function	Signature	Description
RSI	`RSI(real, timeperiod=14)`	Relative Strength Index
MACD	`MACD(real, fastperiod=12, slowperiod=26, signalperiod=9)`	Returns `(macd, signal, hist)`
MACDEXT	`MACDEXT(real, fastperiod=12, fastmatype=0, slowperiod=26, slowmatype=0, signalperiod=9, signalmatype=0)`	MACD with controllable MA types. Returns `(macd, signal, hist)`
MACDFIX	`MACDFIX(real, signalperiod=9)`	MACD Fix 12/26. Returns `(macd, signal, hist)`
STOCH	`STOCH(high, low, close, fastk_period=5, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0)`	Returns `(slowk, slowd)`
STOCHF	`STOCHF(high, low, close, fastk_period=5, fastd_period=3, fastd_matype=0)`	Returns `(fastk, fastd)`
STOCHRSI	`STOCHRSI(real, timeperiod=14, fastk_period=5, fastd_period=3, fastd_matype=0)`	Returns `(fastk, fastd)`
ADX	`ADX(high, low, close, timeperiod=14)`	Average Directional Index
ADXR	`ADXR(high, low, close, timeperiod=14)`	Average Directional Index Rating
CCI	`CCI(high, low, close, timeperiod=14)`	Commodity Channel Index
MFI	`MFI(high, low, close, volume, timeperiod=14)`	Money Flow Index
ROC	`ROC(real, timeperiod=10)`	Rate of change : ((price/prevPrice)-1)*100
ROCP	`ROCP(real, timeperiod=10)`	Rate of change Percentage: (price-prevPrice)/prevPrice
ROCR	`ROCR(real, timeperiod=10)`	Rate of change ratio: (price/prevPrice)
ROCR100	`ROCR100(real, timeperiod=10)`	Rate of change ratio 100: (price/prevPrice)*100
MOM	`MOM(real, timeperiod=10)`	Momentum
WILLR	`WILLR(high, low, close, timeperiod=14)`	Williams' %R
CMO	`CMO(real, timeperiod=14)`	Chande Momentum Oscillator
DX	`DX(high, low, close, timeperiod=14)`	Directional Movement Index
MINUS_DI	`MINUS_DI(high, low, close, timeperiod=14)`	Minus Directional Indicator
MINUS_DM	`MINUS_DM(high, low, timeperiod=14)`	Minus Directional Movement
PLUS_DI	`PLUS_DI(high, low, close, timeperiod=14)`	Plus Directional Indicator
PLUS_DM	`PLUS_DM(high, low, timeperiod=14)`	Plus Directional Movement
APO	`APO(real, fastperiod=12, slowperiod=26, matype=0)`	Absolute Price Oscillator
PPO	`PPO(real, fastperiod=12, slowperiod=26, matype=0)`	Percentage Price Oscillator
AROON	`AROON(high, low, timeperiod=14)`	Returns `(aroondown, aroonup)`
AROONOSC	`AROONOSC(high, low, timeperiod=14)`	Aroon Oscillator
ULTOSC	`ULTOSC(high, low, close, timeperiod1=7, timeperiod2=14, timeperiod3=28)`	Ultimate Oscillator
BOP	`BOP(open, high, low, close)`	Balance Of Power
TRIX	`TRIX(real, timeperiod=30)`	1-day Rate-Of-Change (ROC) of a Triple Smooth EMA

Volatility Indicators

Function	Signature	Description
ATR	`ATR(high, low, close, timeperiod=14)`	Average True Range
NATR	`NATR(high, low, close, timeperiod=14)`	Normalized Average True Range
TRANGE	`TRANGE(high, low, close)`	True Range

Volume Indicators

Function	Signature	Description
OBV	`OBV(real, volume)`	On Balance Volume
AD	`AD(high, low, close, volume)`	Chaikin A/D Line
ADOSC	`ADOSC(high, low, close, volume, fastperiod=3, slowperiod=10)`	Chaikin A/D Oscillator

Price Transform

Function	Signature	Description
AVGPRICE	`AVGPRICE(open, high, low, close)`	Average Price
MEDPRICE	`MEDPRICE(high, low)`	Median Price
TYPPRICE	`TYPPRICE(high, low, close)`	Typical Price
WCLPRICE	`WCLPRICE(high, low, close)`	Weighted Close Price

Statistics

Function	Signature	Description
STDDEV	`STDDEV(real, timeperiod=5, nbdev=1.0)`	Standard Deviation
VAR	`VAR(real, timeperiod=5, nbdev=1.0)`	Variance
BETA	`BETA(real0, real1, timeperiod=5)`	Beta
CORREL	`CORREL(real0, real1, timeperiod=30)`	Pearson's Correlation Coefficient (r)
LINEARREG	`LINEARREG(real, timeperiod=14)`	Linear Regression
LINEARREG_ANGLE	`LINEARREG_ANGLE(real, timeperiod=14)`	Linear Regression Angle
LINEARREG_INTERCEPT	`LINEARREG_INTERCEPT(real, timeperiod=14)`	Linear Regression Intercept
LINEARREG_SLOPE	`LINEARREG_SLOPE(real, timeperiod=14)`	Linear Regression Slope
TSF	`TSF(real, timeperiod=14)`	Time Series Forecast
AVGDEV	`AVGDEV(real, timeperiod=14)`	Average Deviation
MAX	`MAX(real, timeperiod=30)`	Highest value over a specified period
MIN	`MIN(real, timeperiod=30)`	Lowest value over a specified period
SUM	`SUM(real, timeperiod=30)`	Summation
MINMAX	`MINMAX(real, timeperiod=30)`	Returns `(min, max)`
MINMAXINDEX	`MINMAXINDEX(real, timeperiod=30)`	Returns `(minidx, maxidx)`

Cycle Indicators

Function	Signature	Description
HT_DCPERIOD	`HT_DCPERIOD(real)`	Hilbert Transform - Dominant Cycle Period
HT_DCPHASE	`HT_DCPHASE(real)`	Hilbert Transform - Dominant Cycle Phase
HT_PHASOR	`HT_PHASOR(real)`	Hilbert Transform - Phasor Components. Returns `(inphase, quadrature)`
HT_SINE	`HT_SINE(real)`	Hilbert Transform - SineWave. Returns `(sine, leadsine)`
HT_TRENDLINE	`HT_TRENDLINE(real)`	Hilbert Transform - Instantaneous Trendline
HT_TRENDMODE	`HT_TRENDMODE(real)`	Hilbert Transform - Trend vs Cycle Mode

Math Operators

Function	Signature	Description
ADD	`ADD(real0, real1)`	Vector Arithmetic Addition
SUB	`SUB(real0, real1)`	Vector Arithmetic Subtraction
MULT	`MULT(real0, real1)`	Vector Arithmetic Multiplication
DIV	`DIV(real0, real1)`	Vector Arithmetic Division

Math Transforms

All take a single real array: ACOS, ASIN, ATAN, CEIL, COS, COSH, EXP, FLOOR, LN, LOG10, SIN, SINH, SQRT, TAN, TANH

Candlestick Patterns

All candlestick functions accept (open, high, low, close) and return an integer array (100, -100, or 0).

Standard patterns: CDL2CROWS, CDL3BLACKCROWS, CDL3INSIDE, CDL3LINESTRIKE, CDL3OUTSIDE, CDL3STARSINSOUTH, CDL3WHITESOLDIERS, CDLADVANCEBLOCK, CDLBELTHOLD, CDLBREAKAWAY, CDLCLOSINGMARUBOZU, CDLCONCEALBABYSWALL, CDLCOUNTERATTACK, CDLDOJI, CDLDOJISTAR, CDLDRAGONFLYDOJI, CDLENGULFING, CDLGAPSIDESIDEWHITE, CDLGRAVESTONEDOJI, CDLHAMMER, CDLHANGINGMAN, CDLHARAMI, CDLHARAMICROSS, CDLHIGHWAVE, CDLHIKKAKE, CDLHIKKAKEMOD, CDLHOMINGPIGEON, CDLIDENTICAL3CROWS, CDLINNECK, CDLINVERTEDHAMMER, CDLKICKING, CDLKICKINGBYLENGTH, CDLLADDERBOTTOM, CDLLONGLEGGEDDOJI, CDLLONGLINE, CDLMARUBOZU, CDLMATCHINGLOW, CDLONNECK, CDLPIERCING, CDLRICKSHAWMAN, CDLRISEFALL3METHODS, CDLSEPARATINGLINES, CDLSHOOTINGSTAR, CDLSHORTLINE, CDLSPINNINGTOP, CDLSTALLEDPATTERN, CDLSTICKSANDWICH, CDLTAKURI, CDLTASUKIGAP, CDLTHRUSTING, CDLTRISTAR, CDLUNIQUE3RIVER, CDLUPSIDEGAP2CROWS, CDLXSIDEGAP3METHODS

Patterns with optional penetration parameter: CDLABANDONEDBABY(..., penetration=0.3), CDLDARKCLOUDCOVER(..., penetration=0.5), CDLEVENINGDOJISTAR(..., penetration=0.3), CDLEVENINGSTAR(..., penetration=0.3), CDLMATHOLD(..., penetration=0.5), CDLMORNINGDOJISTAR(..., penetration=0.3), CDLMORNINGSTAR(..., penetration=0.3)

Performance

pytafast achieves superior performance compared to the official ta-lib-python in Pandas, multi-threaded, and complex calculation scenarios. Benchmarked on 100,000 data points:

Multi-threading Throughput

Thanks to efficient GIL release in C++, pytafast scales near-linearly with CPU cores. Benchmark results in a 4-thread concurrent environment:

Benchmark (4 Threads)	Official Wrapper	pytafast	Throughput Increase
SMA Concurrency	20.1 ms	6.3 ms	3.15x
RSI Concurrency	56.5 ms	16.3 ms	3.46x
MACD Concurrency	75.0 ms	20.7 ms	3.62x

Single-call Efficiency

Category	Representative Indicators	Avg Speedup
Pandas Integration	SMA, EMA, MOM, RSI (Series input)	1.05x - 1.30x
Complex Indicators	ADX, ADXR, ULTOSC, MAMA	1.08x - 1.12x
Overlap Studies	SMA, EMA, BBANDS, KAMA, T3	1.02x
Momentum	RSI, MACD, STOCH, CCI, ROC	1.03x
Statistics & Math	LINEARREG, STDDEV, BETA, ADD	1.04x
Overall Consistency	All 150+ functions	100% Match

Key Highlights:

MOM (Pandas): pytafast is 30% faster than official wrapper.
ADX (NumPy): pytafast is 11% faster due to lower binding overhead.
Safety: Integrated Microsoft GSL ensures robust memory management for large-scale financial data.

Recommendation: Use pytafast for multi-threaded backtesting or high-concurrency web servers to unlock full CPU potential.

API Compatibility

pytafast follows the same function signatures as the official TA-Lib Python wrapper, making it a drop-in replacement in most cases.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Name		Name	Last commit message	Last commit date
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.github/workflows		.github/workflows
src		src
tests		tests
third_party		third_party
.clang-format		.clang-format
.clang-tidy		.clang-tidy
.gitignore		.gitignore
.gitmodules		.gitmodules
.python-version		.python-version
AGENTS.md		AGENTS.md
CMakeLists.txt		CMakeLists.txt
LICENSE		LICENSE
README.md		README.md
pyproject.toml		pyproject.toml
uv.lock		uv.lock

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pytafast

Features

Installation

Build from Source

Quick Start

Basic Usage with NumPy

Momentum Indicators

Bollinger Bands & Volatility

Volume Indicators

Statistics & Math

Candlestick Pattern Recognition

Pandas Support

Async Support

Cycle Indicators

API Reference

Overlap Studies

Momentum Indicators

Volatility Indicators

Volume Indicators

Price Transform

Statistics

Cycle Indicators

Math Operators

Math Transforms

Candlestick Patterns

Performance

Multi-threading Throughput

Single-call Efficiency

API Compatibility

License

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