pythonpine 2.0.1

High-performance vectorized Pine Script indicators for ML and backtesting

PythonPine v2.0 - High-Performance Technical Indicators

Vectorized Pine Script indicators for machine learning and algorithmic trading. 10-100x faster than loop-based implementations.

Features

• ⚡ NumPy/Pandas Vectorization - Millions of bars in seconds
• 🧠 ML Alpha Module - Z-score, percentile rank, fractional differentiation
• 📊 50+ Indicators - RSI, MACD, ATR, Bollinger, SuperTrend, Ichimoku...
• 🔄 Pine Script Parity - Same signatures, same math
• 📈 Price Action - Vectorized pattern detection

Installation

pip install pythonpine

Quick Start

import numpy as np
from pythonpine import rsi, macd, atr, zscore

# Your price data
close = np.random.randn(10000).cumsum() + 100
high = close + np.abs(np.random.randn(10000)) * 0.5
low = close - np.abs(np.random.randn(10000)) * 0.5

# Calculate indicators (returns NumPy arrays)
rsi_values = rsi(close, 14)
macd_line, signal, hist = macd(close)
atr_values = atr(high, low, close, 14)

# ML preprocessing
rsi_zscore = zscore(rsi_values, 20)  # Normalized for ML

ML Alpha Module

from pythonpine import zscore, percentile_rank, log_returns, fractional_diff

# Stationarity transforms
returns = log_returns(close)
frac_diff = fractional_diff(close, d=0.4)  # López de Prado method

# Feature engineering
rsi_z = zscore(rsi(close), 50)  # Z-score normalized RSI
rsi_rank = percentile_rank(rsi(close), 100)  # Percentile rank

Benchmarks

Indicator	Legacy (loop)	V2 (vectorized)	Speedup
RSI	1.2s	0.01s	120x
MACD	0.8s	0.008s	100x
ATR	0.5s	0.005s	100x
Bollinger	0.9s	0.007s	130x

Tested on 1M bars

Indicator Reference

Momentum

• rsi(close, 14) - Relative Strength Index
• macd(close, 12, 26, 9) - MACD line, signal, histogram
• stochastic(close, high, low) - Stochastic Oscillator
• adx(high, low, close) - Average Directional Index
• cci(close, high, low) - Commodity Channel Index

Volatility

• atr(high, low, close, 14) - Average True Range
• bollinger_bands(close, 20, 2) - Upper, lower, middle
• keltner_channel(high, low, close) - Keltner bands
• historical_volatility(close, 20) - HV annualized

Trend

• sma(close, 20) - Simple Moving Average
• ema(close, 20) - Exponential MA
• supertrend(high, low, close) - Trend direction + line
• ichimoku(high, low, close) - Full cloud

Price Action

• engulfing(o, h, l, c) - Returns +1 (bullish), -1 (bearish), 0
• doji(o, h, l, c) - Doji detection
• support_resistance_zones(h, l, c, v) - Volume-based S/R

License

MIT