# freqtrade/technical

Various indicators developed or collected for the Freqtrade

Repository: https://github.com/freqtrade/technical
Canonical: https://ross.abutalabs.com/products/technical
Language: Python
License: GPL-3.0
License Family: copyleft
Topics: freqtrade, dataframe, technical-analysis, trading
Last push: 2026-08-20T14:59:11+00:00

## Health v2 (maintenance only)
Score: 89/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 70, longevity 100
- inputs: {"age_days": 3004, "days_push": 13, "days_rel": 43, "gap_med": 102.5, "n_releases_24m": 7}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1030, forks 250 (observed 2026-08-28T04:03:17.806506+00:00)

## What it is
A Python library of technical analysis indicators and utilities built as a companion to the Freqtrade trading bot. It aggregates custom and collected indicators (consensus models, Ichimoku, trendlines, Fibonacci retracements, etc.) plus helpers like timeframe resampling for strategy development.

## Use cases
- compute technical indicators on pandas dataframes for trading strategies
- find a unified API for hundreds of TA indicators
- develop and backtest freqtrade strategies with extra indicators
- calculate trendlines and fibonacci retracements on candle data
- resample OHLCV data across timeframes

## When to choose
- you use Freqtrade and want drop-in indicators for strategy development
- you want a broad collection of indicators beyond TA-Lib in one package

## When to avoid
- you need a general-purpose backtesting engine (use Freqtrade or backtrader)
- you work outside Python/pandas dataframes

## Facets
- artifact type: library
- maturity: active
- function: trading, data-science, developer-tools
- domain: fintech, data-science, analytics
- platform: python, cli
- tags: technical-analysis, trading-indicators, pandas, freqtrade, algorithmic-trading, cryptocurrency

## Member repositories
- freqtrade/technical (main) score 89

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:17.806506+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 2026-08-30T07:07:33.496021+00:00, confidence not recorded.
  - readme: https://github.com/freqtrade/technical (fetched 2026-08-28T04:03:17.806506+00:00, sha 4d155e1ffcea)
  - registry_pypi: https://pypi.org/pypi/technical/json (fetched 2026-08-29T13:07:22.914304+00:00, sha fe7bf414cb7e)
- Data as of 2026-08-30T08:39:29.467469+00:00.