backtrader: High-performance Python backtesting & live-trading framework

by cloudQuant · MCP Server · ★ 191

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install backtrader

pip install back-trader-cpp
git clone https://github.com/cloudQuant/backtrader.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 68/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

algorithmic-tradingbacktestingcryptocurrencydata-analysisfinancefuturesindicatorslive-tradingpythonquant

Quick Facts

Stars191
Forks44
LanguagePython
CategoryMCP Server
LicenseGPL-3.0
Quality Score68/100
Last Updated2026-09-28
Created2024-12-20
Platformsbrowser, mcp, python
Est. Tokens~23k

About backtrader

🚀 Backtrader Professional Python Algorithmic Trading Backtesting Framework English | 中文 📖 Documentation (EN) · 📖 中文文档 · 🌐 GitHub Pages 🐛 Report Bug · 💬 Discussions Installation I have published the pybind11-based Python wheel to PyPI: https://pypi.org/project/back-trader-cpp/ You can install it directly: It currently supports Python 3.8-3.14 and covers macOS, Windows, Linux, and other...

Compatible Skills

These tools work well together with backtrader for enhanced workflows:

  • ai-hedge-fund-crypto — semantic(0.51)+complementary+rare_topics+same_lang+similar_pop+shared_platform (77%)
  • crypto-trading-arena — semantic(0.52)+complementary+rare_topics+same_lang+similar_pop+shared_platform (73%)
  • joinquant-skill — semantic(0.33)+complementary+rare_topics+same_lang+similar_pop+shared_platform (71%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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