After the installation completes, you must initialize the configuration. HXCoreOL relies on a .yaml or .json configuration file to define data paths and API endpoints. Generate a default config: hxcoreol --init
Update the "Base_Directory" and "Logs_Path" to match your local folder structure. Step 4: Verification and First Run hxcoreol install
Getting HXCoreOL up and running is a straightforward process once you understand the dependencies and environment requirements. This guide covers the complete installation lifecycle, from system preparation to verifying your first successful run. After the installation completes, you must initialize the
Installing HXCoreOL provides a robust foundation for your data processing tasks. By following the virtual environment approach and running the diagnostic check, you minimize the risk of runtime errors. Keep your installation updated regularly by running pip install --upgrade hxcoreol to access the latest features and security patches. Step 4: Verification and First Run Getting HXCoreOL
OS: Linux (Ubuntu 20.04+ recommended), macOS, or Windows via WSL2. Python: Version 3.8 or higher. Package Manager: pip (latest version) or Conda.
The primary method for installation is via the official package repository. Ensure your network allows connections to public registries. Execute the following command: pip install hxcoreol
It is highly recommended to install HXCoreOL within a virtual environment. This prevents version conflicts with other Python projects on your system. To create a virtual environment, run: python -m venv hxcore_env Activate the environment: Linux/macOS: source hxcore_env/bin/activate Windows: .\hxcore_env\Scripts\activate Step 2: The HXCoreOL Installation Process