# tkfy920/qstock

qstock由“Python金融量化”公众号开发，试图打造成个人量化投研分析包，目前包括数据获取（data）、可视化(plot)、选股(stock)和量化回测（策略backtest）模块。 qstock将为用户提供简洁的数据接口和规整化后的金融市场数据。可视化模块为用户提供基于web的交互图形的简单接口；  选股模块提供了同花顺的选股数据和自定义选股，包括RPS、MM趋势、财务指标、资金流模型等；  回测模块为大家提供向量化（基于pandas）和基于事件驱动的基本框架和模型。 关注“Python金融量化“微信公众号，获取更多应用信息。

Repository: https://github.com/tkfy920/qstock
Canonical: https://ross.abutalabs.com/products/qstock
Language: Python
License: MIT
License Family: permissive
Last push: 2025-03-16T03:36:35+00:00

## Health v2 (maintenance only)
Score: 37/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 11, release rhythm 35, longevity 100
- inputs: {"age_days": 1423, "days_push": 535, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1930, forks 391 (observed 2026-08-28T04:05:56.065244+00:00)

## What it is
qstock is a Python library for personal quantitative investment research, providing modules for fetching financial market data (from Eastmoney, THS, Sina), interactive web-based visualization, stock screening (RPS, MM trend, financial indicators, fund flow), and backtesting (vectorized pandas-based and event-driven). It offers clean, normalized market data interfaces for Chinese A-shares, futures, ETFs, HK/US stocks, and more.

## Use cases
- fetch realtime Chinese A-share market quotes in python
- backtest a trading strategy with pandas
- screen stocks by RPS or fund flow
- plot interactive candlestick charts of stock prices
- get intraday tick data for a stock
- monitor unusual order flow alerts during trading
- download historical stock data from eastmoney

## When to choose
- you need a simple all-in-one Python toolkit for Chinese market data, screening, and backtesting
- you want clean normalized financial data without writing scrapers
- you are a retail quant doing personal investment research on A-shares

## When to avoid
- you need institutional-grade data reliability or official licensed data feeds
- you require advanced event-driven backtesting with realistic execution modeling
- you work primarily with non-Chinese markets or need guaranteed long-term maintenance

## Facets
- artifact type: library
- maturity: active
- function: data-science, data-visualization, etl, charts
- domain: fintech, data-science, data-visualization, analytics
- platform: python, cross-platform
- tags: quantitative-finance, stock-analysis, backtesting, stock-screening, market-data, chinese-markets, webscraping-data

## Member repositories
- tkfy920/qstock (main) score 37

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:56.065244+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 2026-08-30T03:08:51.209153+00:00, confidence not recorded.
  - readme: https://github.com/tkfy920/qstock (fetched 2026-08-28T04:05:56.065244+00:00, sha 49391c32c472)
  - registry_pypi: https://pypi.org/pypi/qstock/json (fetched 2026-08-29T10:48:18.904449+00:00, sha cfc0b7a129b2)
- Data as of 2026-08-30T08:39:29.467469+00:00.