ai-agent

qlib: Accelerate Quant Research with AI‑Powered Modeling

Founder‑level quant teams use qlib to prototype, test, and deploy AI‑driven trading models—from supervised learning to RL—in minutes. Backed by 49k+ GitHub stars.

From the repo · “Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.”

49,590 stars+221★ this week7,828 forksPythonGuide quality 9/10 · reviewed Oct 5Install verified Sep 21Updated 10/14/2026100% free · open source
What it does

Qlib provides a platform for founders in finance and fintech to conduct AI-powered quant research and backtest trading strategies

When to use it
  • •When you need to backtest a trading strategy before deploying it in a live market
  • •When you want to analyze and compare the performance of different trading algorithms
  • •When you need to integrate machine learning models into your quantitative trading workflow
Ready-to-paste prompt
python scripts/backtest.py -c scripts/config_backend.yaml -m LSTM -d btc
Heads up: Qlib requires a specific version of Python (3.7 or later) and may not work correctly with earlier versions, so ensure you have the correct version installed before trying to use it
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✅ Light setup✓ Install verified 9/21/2026

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Claude Code
mkdir -p ~/.claude/skills/qlib && curl -fsSL https://workflowstacks.com/api/skills/qlib/claude-skill -o ~/.claude/skills/qlib/SKILL.md
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How qlib: Accelerate Quant Research with AI‑Powered Modeling works
Codeflow
Free to inspect

Qlib: Accelerate Quant Research with AI‑Powered Modeling is a very large Python project (~67k lines across 298 code files, plus 40 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit a month ago, MIT license, has a test suite.

Size
Very large codebase
~67k lines · 298 code files · days to read — use, don't read
Setup
One-command install
Installs like a normal app. Reading the code is optional.
Runs on
Python · Docker
No API keys detected
Python 99%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    pyproject.toml
    Dependencies and the commands it exposes
  3. 3
    qlib/__init__.py
    Inside qlib/ — the main logic begins here
  4. 4
    examples/README.md
    A worked example — copy this to get going
What's in each folder
qlib/Core code — the actual logic234 files
examples/Examples you can copy192 files
docs/Documentation77 files
scripts/Helper scripts43 files
tests/Tests — proof it works40 files
.github/CI / automation (GitHub Actions)13 files
READMEHas testsDocumentedCI checksDocker readyExamples includedMIT licenseUpdated this month
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Details
Creator
microsoft
Language
Python
Category
ai-agent
Published
8/14/2020

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