# bbfamily/abu

阿布量化交易系统(股票，期权，期货，比特币，机器学习) 基于python的开源量化交易，量化投资架构

Repository: https://github.com/bbfamily/abu
Canonical: https://ross.abutalabs.com/products/abu
Homepage: http://www.abuquant.com/
Language: Python
License: GPL-3.0
License Family: copyleft
Topics: quant, trade, machine-learning, bitcoin, algorithmic-trading, quantitative-trading, stock, pandas, matplotlib, numpy, trading
Last push: 2026-01-24T09:00:29+00:00

## Health v2 (maintenance only)
Score: 52/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 64, release rhythm 8, longevity 100
- inputs: {"age_days": 3635, "days_push": 221, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 18239, forks 4675 (observed 2026-08-28T04:11:26.484042+00:00)

## What it is
AbuQuant (abupy) is an open-source Python quantitative trading and investment framework supporting stocks, options, futures, and Bitcoin, with built-in machine learning capabilities. It accompanies the book '量化交易之路' (The Road to Quantitative Trading) and includes tutorials, a non-programming UI, and example code.

## Use cases
- backtest trading strategies on stocks, futures, options, and bitcoin
- apply machine learning to quantitative trading signals
- learn quantitative trading with python
- build a personal quant trading framework in python
- analyze candlestick and moving average trading signals
- integrate custom market data sources into a backtesting system

## When to choose
- you want a Python-based quant framework covering multiple asset classes
- you are learning algorithmic trading and want book-aligned example code
- you need backtesting with machine learning signal analysis

## When to avoid
- you need actively maintained compatibility with the latest Python and library versions (project dates to 2016)
- you require reliable built-in market data feeds (original data sources may no longer work)
- you need production live-trading infrastructure or commercial support

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, data-science, trading, data-visualization
- domain: fintech, machine-learning, data-science
- platform: python
- tags: quantitative-trading, algorithmic-trading, backtesting, stocks, futures, options, bitcoin, pandas, abupy

## Member repositories
- bbfamily/abu (main) score 52

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:26.484042+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 2026-08-29T17:02:06.262528+00:00, confidence not recorded.
  - readme: https://github.com/bbfamily/abu (fetched 2026-08-28T04:11:26.484042+00:00, sha 4242796ec9df)
  - homepage: http://www.abuquant.com/ (fetched 2026-08-29T08:00:03.219129+00:00, sha 9192c27a4360)
  - site_page: http://www.abuquant.com/about.html (fetched 2026-08-29T08:00:03.229571+00:00, sha c82cb6466446)
- Data as of 2026-08-30T08:39:29.467469+00:00.