Setup

This document describes how to install CapyMOA and its dependencies. CapyMOA is tested against Python 3.10, 3.11, and 3.12. Newer versions of Python will likely work but have yet to be tested.

Once you have installed the Dependencies, you may install CapyMOA using pip (optionally in a Virtual Environment):

pip install capymoa

To verify your installation, run:

python -c "import capymoa; print(capymoa.__version__)"

Virtual Environment

We recommend using a virtual environment to isolate CapyMOA and its dependencies from your other projects. This is especially important if you have other projects that require different versions of the same dependencies.

If you chose to use a virtual environment, you have some choices:

• Python Virtual Environment PyVenv is a built-in tool for creating virtual environments in Python. You can create a new virtual environment with:

  python3 -m venv .capymoa-venv
  source .capymoa-venv/bin/activate
  # On Windows, use `.capymoa-venv\Scripts\activate`
  

• Conda Environment Miniconda is a good choice for managing Python environments. You can install Miniconda from here. Once you have Miniconda installed, you can create a new environment with:

  conda create -n capymoa python=3.11
  conda activate capymoa
  

  When your environment is activated, you can install CapyMOA by following the instructions below.

Dependencies

CapyMOA has some required dependencies that may require manual installation before CapyMOA can be used:

Java

CapyMOA requires a Java runtime. You can check if Java is installed by running the following command in your terminal:

java -version

If Java is not installed, you can download OpenJDK (Open Java Development Kit) from this link, or alternatively the Oracle JDK from this link. You only need to install the Java Runtime (JRE). Linux and macOS users can also install OpenJDK using their distribution’s package manager:

Ubuntu

sudo apt-get install -y default-jre-headless

macOS

brew install openjdk

CapyMOA will attempt to find the Java automatically unless the JAVA_HOME environment variable is set. This allows you to have multiple Java versions or have Java installed outside of the system path.

PyTorch

The CapyMOA algorithms using deep learning require PyTorch. If you want to use these algorithms, follow the instructions here to get the correct version for your hardware. Ensure that you install PyTorch in the same virtual environment where you want to install CapyMOA.

For CPU only, you can install PyTorch with:

pip3 install torch torchvision torchaudio \
   --index-url https://download.pytorch.org/whl/cpu