# TA-Lib

Official TA-Lib Core

Repository: https://github.com/TA-Lib/ta-lib
Canonical: https://ross.abutalabs.com/products/ta-lib
Homepage: https://ta-lib.org/
Language: Java
License: BSD-3-Clause
License Family: permissive
Topics: ta-lib, financial, series-analysis, technical-analysis
Last push: 2026-08-26T18:59:28+00:00
Link (homepage): https://ta-lib.org/
Link (site_page): https://ta-lib.org/install
Link (site_page): https://ta-lib.org/functions
Link (site_page): https://ta-lib.org/about
Link (site_page): https://ta-lib.org/install/c

## Health v2 (maintenance only)
Score: 96/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 91, longevity 100
- inputs: {"age_days": 3665, "days_push": 7, "days_rel": 61, "gap_med": 7.5, "n_releases_24m": 5}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1660, forks 296 (observed 2026-08-28T04:05:18.407549+00:00)

## What it is
TA-Lib is a C/C++ library of 200+ battle-tested technical analysis functions (indicators like ADX, MACD, RSI, Bollinger Bands, plus candlestick pattern recognition) for financial market data. ta-lib-python is the most widely used binding, built with Cython and NumPy for 2-4x faster performance than the original SWIG bindings, with Pandas and Polars support.

## Use cases
- calculate RSI and MACD indicators on stock price data
- detect candlestick patterns in OHLC time series
- compute Bollinger Bands for a trading strategy backtest
- perform technical analysis on financial market data in Python
- build quantitative finance signals with 200+ indicators
- efficiently compute moving averages over large numpy arrays

## When to choose
- you need industry-standard, production-proven technical analysis indicators
- you want fast NumPy/Pandas/Polars integration for large market datasets
- you need candlestick pattern recognition (CDL* functions)
- you want a stable, BSD-licensed library battle-tested since 2001

## When to avoid
- you need a pure-Python solution with no C library dependency
- you want modern indicators beyond the classic 200 (consider pandas-ta)
- you need streaming/real-time tick processing (streaming API is still in development)
- you're not working with financial time-series data

## Facets
- artifact type: library
- maturity: active
- function: math, data-science, sdk
- domain: fintech, data-science
- platform: python, cross-platform, cpp
- tags: technical-analysis, financial-indicators, candlestick-patterns, cython, numpy, pandas, polars, trading, quantitative-finance, algorithms

## Member repositories
- TA-Lib/ta-lib (main) score 96
- TA-Lib/ta-lib-python (sdk) score 95

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:18.407549+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:14:16.337766+00:00, confidence not recorded.
  - readme: https://github.com/TA-Lib/ta-lib (fetched 2026-08-28T04:05:18.407549+00:00, sha cb5ba98e2c63)
  - homepage: https://ta-lib.org/ (fetched 2026-08-29T08:11:57.989702+00:00, sha cfd156274e1e)
  - site_page: https://ta-lib.org/install (fetched 2026-08-29T08:11:57.993223+00:00, sha 85c4a75289a4)
  - site_page: https://ta-lib.org/about (fetched 2026-08-29T08:11:57.996746+00:00, sha b5f0232f5f45)
  - site_page: https://ta-lib.org/install/c (fetched 2026-08-29T08:11:57.998748+00:00, sha 5637eceecedd)
  - site_page: https://ta-lib.org/functions (fetched 2026-08-29T08:11:57.994852+00:00, sha 0a43e30f496d)
  - site_page: https://ta-lib.org/faq (fetched 2026-08-29T08:11:58.001069+00:00, sha ecbbc680e7f9)
- Data as of 2026-08-30T08:39:29.467469+00:00.