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