Installation

This document describes how to install CapyMOA and its dependencies. CapyMOA is tested against Python 3.9, 3.10, and 3.11. Newer versions of Python will likely work but have yet to be tested.

• Installation

  • Environment

  • Dependencies

    • Java (Required)

    • PyTorch (Required)

  • Install CapyMOA

    • Install CapyMOA for Development

Environment

We recommend using a virtual environment to manage your Python 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=3.9
conda activate capymoa

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

Dependencies

Most of the dependencies for CapyMOA are installed automatically with pip. However, there are a few dependencies that need to be installed manually.

Java (Required)

CapyMOA requires Java to be installed and accessible in your environment. 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. Linux users can also install OpenJDK using their distribution’s package manager.

Now that Java is installed, you should see an output similar to the following when you run the command java -version:

openjdk version "17.0.9" 2023-10-17
OpenJDK Runtime Environment (build 17.0.9+8)
OpenJDK 64-Bit Server VM (build 17.0.9+8, mixed mode)

PyTorch (Required)

The CapyMOA algorithms using deep learning require PyTorch. It is not installed by default because different versions are required for different hardware. If you want to use these algorithms, follow the instructions here to get the correct version for your hardware.

For CPU only, you can install PyTorch with:

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

Install CapyMOA

pip install capymoa

Install CapyMOA for Development

If you want to contribute to CapyMOA, you should clone the repository, install development dependencies, and install CapyMOA in editable mode:

git clone git@github.com:adaptive-machine-learning/CapyMOA.git # or your fork
cd CapyMOA
pip install --editable ".[dev]"