Stock Indicators for Python. Send in historical price quotes and get back desired technical indicators such as Stochastic RSI, Average True Range, Parabolic SAR, etc. Nothing more.

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  • License: Apache Software License (Apache 2.0)
  • Author: Dave Skender
  • Maintainer: Dong-Geon Lee
  • Tags Stock Indicators , Technical Indicators , Market , Technical Analysis , Algorithmic , Trading , Trade , Momentum , Finance , Algorithm , Algo , AlgoTrading , Financial , Strategy , Chart , Charting , Oscillator , Overlay , Equity , Bitcoin , Crypto , Cryptocurrency , Forex , Quantitative , Historical , Quotes , Accumulation , Distribution , ADL , Aroon , True Range , ATR , Bollinger Bands , Commodity , CCI , Chandelier Exit , Chaikin Money Flow , CMF , MFI , Kaufman Adaptive , Moving Average , Convergence , Divergence , MACD , SMA , EMA , DEMA , TEMA , TRIX , Smoothed , Elder-ray , Bull , Bear , Power , Force , Hurst Exponent , Relative , Strength , Index , RSI , Connors RSI , Stochastic , Directional , Movement , ADX , Donchian , Keltner Channel , Heikin-Ashi , Hilbert Transform Instantaneous Trendline , Hull , HMA , Ichimoku Cloud , On-balance Volume , OBV , Price , PMO , PRS , Parabolic SAR , PSAR , Pivot Points , Rate of Change , ROC , Linear Regression , R-Squared , Renko , Schaff Cycle , Slope , Standard Deviation , Beta , Convexity , Correlation , SuperTrend , Ulcer , Ultimate , Vortex , Williams %R , Alligator , Gator , Fractal , Chaos , Choppiness , Endpoint , WMA , ZigZag
  • Requires: Python >=3.8
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Stock Indicators for Python

Stock Indicators for Python is a PyPI library package that produces financial market technical indicators. Send in historical price quotes and get back desired indicators such as moving averages, Relative Strength Index, Stochastic Oscillator, Parabolic SAR, etc. Nothing more.

It can be used in any market analysis software using standard OHLCV price quotes for equities, commodities, forex, cryptocurrencies, and others. We had trading algorithms, machine learning, and charting systems in mind when originally creating this community library. Stock Indicators for .NET is also available.

Visit our project site for more information:

Getting started

Windows

  1. Install .NET SDK (6.0 or newer):

  2. Install the package:

    pip install stock-indicators

macOS

  1. Install .NET SDK (6.0 or newer):

    brew install dotnet-sdk
dotnet --info  # Verify installation

  2. Install the package:

    pip install stock-indicators

Example usage

from stock_indicators import indicators

# fetch your data
quotes = get_history("MSFT")

# calculate 20-period SMA
results = indicators.get_sma(quotes, 20)

Note: This is a simple example. For a step-by-step guide, see the QuickStart Guide or our documentation site.

Project details

Verified details

These details have been verified by PyPI
Project links
GitHub Statistics
Maintainers
Avatar for DaveSkender from gravatar.com DaveSkender Avatar for LeeDongGeon1996 from gravatar.com LeeDongGeon1996

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These details have not been verified by PyPI
Project links
Meta
  • License: Apache Software License (Apache 2.0)
  • Author: Dave Skender
  • Maintainer: Dong-Geon Lee
  • Tags Stock Indicators , Technical Indicators , Market , Technical Analysis , Algorithmic , Trading , Trade , Momentum , Finance , Algorithm , Algo , AlgoTrading , Financial , Strategy , Chart , Charting , Oscillator , Overlay , Equity , Bitcoin , Crypto , Cryptocurrency , Forex , Quantitative , Historical , Quotes , Accumulation , Distribution , ADL , Aroon , True Range , ATR , Bollinger Bands , Commodity , CCI , Chandelier Exit , Chaikin Money Flow , CMF , MFI , Kaufman Adaptive , Moving Average , Convergence , Divergence , MACD , SMA , EMA , DEMA , TEMA , TRIX , Smoothed , Elder-ray , Bull , Bear , Power , Force , Hurst Exponent , Relative , Strength , Index , RSI , Connors RSI , Stochastic , Directional , Movement , ADX , Donchian , Keltner Channel , Heikin-Ashi , Hilbert Transform Instantaneous Trendline , Hull , HMA , Ichimoku Cloud , On-balance Volume , OBV , Price , PMO , PRS , Parabolic SAR , PSAR , Pivot Points , Rate of Change , ROC , Linear Regression , R-Squared , Renko , Schaff Cycle , Slope , Standard Deviation , Beta , Convexity , Correlation , SuperTrend , Ulcer , Ultimate , Vortex , Williams %R , Alligator , Gator , Fractal , Chaos , Choppiness , Endpoint , WMA , ZigZag
  • Requires: Python >=3.8
Classifiers

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