This project is a Python wrapper for the TA-Lib library, providing a technical analysis library for computing moving averages, momentum, and volatility metrics for financial time series analysis. It serves as a financial indicator calculator that processes price and volume arrays to generate technical signals and pattern recognition.
The main features of ta-lib/ta-lib-python are: Technical Indicator Calculators, Incremental Indicator Calculation, Technical Analysis Libraries, Algorithmic Trading Platforms, Streaming Data Processing, Python Library Wrappers, Technical Analysis, Quantitative Financial Modeling.
Open-source alternatives to ta-lib/ta-lib-python include: mrjbq7/ta-lib — This project is a Python wrapper for the TA-Lib C library, serving as a financial technical analysis library and… backtrader/backtrader — Backtrader is a Python backtesting framework and algorithmic trading platform. It provides a toolkit for developing… borisbanushev/stockpredictionai — This project is a collection of predictive models and quantitative tools for stock price forecasting. It implements a… deviavir/zenbot — Zenbot is an automated cryptocurrency trading bot designed to execute trades on exchanges based on technical analysis… edtechre/pybroker — pybroker is a Python algorithmic trading framework and quantitative technical analysis library designed for… fasiondog/hikyuu — Hikyuu is a quantitative trading framework designed for developing, backtesting, and executing systematic trading…
This project is a Python wrapper for the TA-Lib C library, serving as a financial technical analysis library and quantitative trading tool. It provides a collection of mathematical functions designed to analyze market price movements, identify trading signals, and recognize candlestick patterns within financial data. The library focuses on the computation of trend, momentum, and volume metrics. It includes specialized tools for candlestick pattern recognition to detect recurring price action shapes in both historical and real-time data. The system integrates with NumPy arrays to process cont
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