vnpy-export

Convert Vibe-Trading strategy descriptions into executable vnpy Python classes.

15|2|Updated May 1, 2026
One-click install
npx skills add https://github.com/OpenSucker/OpenSucker --skill vnpy-export-opensucker
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: vnpy-export
Source: https://github.com/OpenSucker/OpenSucker/tree/main/skills/vibe_skills/vnpy-export
Command: npx skills add https://github.com/OpenSucker/OpenSucker --skill vnpy-export-opensucker

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires vnpy, vnpy_ctp, and includes scripts (resource) components.

What problem does it solve?

This Skill enables users to export trading strategies developed in Vibe-Trading into executable vnpy code, facilitating backtesting and live deployment.

Core Features & Use Cases

  • Strategy Conversion: Transforms strategy descriptions and configurations into fully compatible vnpy CtaTemplate subclasses.
  • Workflow Integration: Supports exporting from backtest data or strategies described in natural language.
  • Use Case: A quantitative analyst wants to quickly implement a custom MA crossover strategy in vnpy for testing, using this Skill to generate the code automatically.

Quick Start

Provide a strategy description or configuration, and use this Skill to generate the vnpy class for deployment or testing.

Frequently Asked Questions about vnpy-export

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I convert a trading strategy into executable vnpy Python code?

To convert a trading strategy into executable vnpy Python code, use this Skill to transform natural language descriptions or configurations into fully compatible vnpy CtaTemplate subclasses for backtesting and live deployment.

What is the process for generating a vnpy CtaTemplate class from backtest data?

Generating a vnpy CtaTemplate class from backtest data involves supplying your existing strategy outlines or backtest configurations to the converter, which then outputs a fully runnable Python class suitable for live trading environments.

Do I need vnpy and vnpy_ctp libraries installed to run the generated strategy code?

Yes, you need the vnpy and vnpy_ctp libraries installed in your environment, as the generated executable Python classes require these dependencies for proper integration into backtesting and live trading systems.

Can I export a natural language MA crossover strategy directly into vnpy?

Yes, you can export a natural language MA crossover strategy directly into vnpy by providing the strategy description to the converter, which automatically generates the corresponding executable Python class for quantitative testing.

What is the best way to implement a custom quantitative strategy in vnpy for backtesting?

The best way to implement a custom quantitative strategy in vnpy for backtesting is to use this converter to automatically generate the executable Python class from your strategy outline, bypassing manual coding.