Ross ROSS = Recommend OSS · open-source software intelligence for agents

VeighNa

Some data may be outdated — see provenance labels.

基于Python的开源量化交易平台开发框架 observed · 2026-10-05

github.com/vnpy/vnpy · homepage · Python · MIT (permissive) observed · 2026-10-05

Health v2 · maintenance only

83/100

  • Activity 98
  • Release rhythm 53
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.

  • gap_med: 91
  • age_days: 4251
  • days_rel: 159
  • days_push: 16
  • n_releases_24m: 6

Full methodology

Adoption not part of the score

45695 stars · 12497 forks observed · 2026-10-05

What it is AI-extracted, prompt v1, taxonomy v1, 2026-09-28, confidence 0.97

VeighNa (vnpy) is an open‑source Python framework for building quantitative trading systems. It provides a modular architecture, data‑feed adapters, strategy libraries, and GUI/CLI tools for research, backtesting, and live trading.

Use cases

  • Develop and deploy algorithmic trading strategies in Python.
  • Backtest CTA, spread, and option strategies on historical market data.
  • Connect to multiple broker gateways (CTP, IB, RQData, etc.) for live trading.
  • Create machine‑learning‑driven factor models and research pipelines.
  • Record and manage real‑time market data streams for analysis.

When to choose

  • You need a fully open‑source, Python‑centric quant trading platform.
  • Your workflow requires both GUI and CLI interfaces for strategy development.
  • You want built‑in support for multiple data providers and broker APIs.
  • You plan to integrate machine‑learning models into trading strategies.

When to avoid

  • You require ultra‑low‑latency execution in a compiled language like C++.
  • Your deployment target is a non‑Python environment or a managed SaaS only solution.
  • You need a turnkey cloud service without any self‑hosting or configuration.

Facets

framework · maturity active

api-framework cli gui http-server data-science machine-learning trading python windows cross-platform cli quant algotrading finance fintech ml backtesting datafeed option-trading portfolio-management ai-powered linux macos gui

10 sources

Member repositories

For agents

markdown · JSON · MCP: product_card(name="vnpy/vnpy")

Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem