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ta

Technical Analysis Library in Python

ta v0.11.0 942.7K downloads/30d#4,674 on PyPI5,141
Permissive license The MIT License (MIT) Active released

What it is and what it does

ta is a technical analysis library that computes financial indicators from time series data (open, close, high, low, volume). It implements 43 indicators across three categories: volume-based (Money Flow Index, On-Balance Volume, Chaikin Money Flow), volatility (Bollinger Bands, Keltner Channel, Average True Range), and trend (moving averages, MACD). The library is designed for feature engineering in quantitative trading and financial analysis pipelines.

The package is stable and moderately popular (top 5000 PyPI packages by downloads), with an active repository and no known security vulnerabilities. However, the source distribution format suggests potential friction at install time. It carries no license restrictions (MIT) but offers limited recent maintenance signals.

Use it for:

  • Build feature sets for machine learning models trained on historical price data.
  • Calculate Bollinger Bands and other volatility indicators for algorithmic trading signals.
  • Compute moving averages and MACD for trend-following strategies.
  • Generate volume-weighted indicators like Money Flow Index for momentum analysis.
  • Backtest trading strategies that rely on technical indicator thresholds.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Computes technical analysis indicators (volume, volatility, trend) from financial time series data for feature engineering in trading and financial analysis workflows.

Yes, with conditions. Install if you need a straightforward technical indicator library for financial feature engineering and can tolerate high install friction (source distribution, potential build requirements). The MIT license is permissive, the codebase is stable, and there are no known vulnerabilities. However, verify Python version compatibility and build requirements before committing to production use.

Install

ta on PyPI

pip

pip install ta

uv

uv add ta

poetry

poetry add ta

Installing ta

Before you install

High install friction: the package distributes as a source tarball (ta-0.11.0.tar.gz) with no runtime dependencies listed, suggesting a compiled extension or build requirement. Last release was over a year ago; repository is active but the gap between releases may indicate maintenance is minimal or reactive rather than proactive.

License in practice

MIT License (permissive) places no restrictions on commercial or private use, modification, or redistribution, provided the license and copyright notice are retained.

Quickstart

from ta.trend import sma_indicator
from ta.volatility import bollinger_hband, bollinger_lband

# Assumes financial time series data is available
sma_result = sma_indicator(close_prices, window=14)
bb_high = bollinger_hband(close_prices, window=20, window_dev=2)

Source distribution (ta-0.11.0.tar.gz) suggests a build environment may be needed at install time; verify build tool availability before installation.

Verify before relying

  • Whether the package requires a C compiler or other build tools to install from source.
  • Current Python version support (classifiers list 3.6 and 3.7, both EOL; actual support unclear).
  • Whether the library depends on external packages like Pandas and Numpy at runtime or build time.

Package facts

License The MIT License (MIT) (permissive)
Python support not specified
Install friction high — source build required
Runtime dependencies none
Maintenance actively maintained — 1,016 days since the last release
Last repo commit
First released
Downloads 942,654/month — #4,674 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: ta-0.11.0.tar.gz

Keywords: technical, analysis

Intended Audience :: Financial and Insurance IndustryLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3.6Programming Language :: Python :: 3.7

Tags

technical analysis indicatorsfinancial time series featurestrading signal calculationMACD bollinger bands ATRstock price analysis libraryfeature engineering finance
financial-analysistime-seriestrading

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