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Python Environments (option)

By installing Python, you can use pyROOT and TSrim directly from Python. However, Python is not required to use artemis_crib, so you may skip this section if you do not plan to use Python.

Why Manage Python Environments?

Managing Python environments and dependencies is crucial to avoid compatibility issues. Some configurations may work in specific environments but fail in others due to mismatched dependencies. To address this, we recommend using tools that handle dependencies efficiently and isolate environments.

Tool Description
pyenv Manages multiple Python versions and switches between them on the same machine.
poetry A dependency manager and build system for Python projects.
pipenv Combines pip and virtualenv for managing dependencies and virtual environments.
mise1 Runtime manager (e.g., Python, Node.js, Java, Go). Ideal for multi-tool projects.
uv A fast Python project manager (10-100x faster than pip), unifying tools like pip, poetry, and pyenv.

Using uv for a Global Python Environment

This section explains how to use uv to set up a global Python environment, required for tools like pyROOT. uv typically creates project-specific virtual environments, but here we focus on configuring a global virtual environment. For other methods, refer to the respective tool's documentation.

Step 1: Install uv

Install uv using the following command:

curl -LsSf https://astral.sh/uv/install.sh | sh

Follow the instructions to complete the installation and configure your environment (e.g., adding uv to PATH).

Verify the installation:

uv --version

Step 2: Install Python using uv

Install a specific Python version:

uv python install 3.12
  • Replace 3.12 with the desired Python version.
  • To view available versions:
uv python list
Currently, Python installed via `uv` cannot be globally accessed via the `python` command. This feature is expected in future releases. For now, use `uv venv` to create a global virtual environment.

Step 3: Create a Global Virtual Environment

To create a global virtual environment:

cd $HOME
uv venv

This creates a .venv directory in $HOME.

Step 4: Persist the Environment Activation

Edit your shell configuration file to activate the virtual environment at startup:

vi $HOME/.zshrc

Add:

# Activate the global uv virtual environment
if [[ -d "$HOME/.venv" ]]; then
    source "$HOME/.venv/bin/activate"
fi

Apply the changes:

source $HOME/.zshrc

Verify the Python executable:

which python

Ensure the output is .venv/bin/python.

Step 5: Add Common Packages

Install commonly used Python packages into the virtual environment:

uv pip install numpy pandas

Additional information

  1. The author (okawak) uses a combination of mise and uv to manage Python environments. If your projects involve multiple tools, such as Python and Node.js, mise is highly effective for unified management. However, if you work exclusively with Python, uv is a simpler and more focused option. ↩