Setup-env

This repository contains a set of scripts and configurations to facilitate the setup of development environments similar to Kaggle on different Linux distributions: Ubuntu, Fedora, and Amazon Linux.

Objective

Automate the preparation of data and science environments, installing essential tools such as Python, Docker, Zsh (with plugins), among others, so that the user is ready to start Machine Learning and Data Science work quickly.

Project Structure

• install.sh: Script to prepare Linux environment (installation of Docker, Python, Zsh, etc.).
• LICENSE: Project license (MIT License).

How to Use

The main script install.sh allows you to install multiple components at once using flags.

Available Options

• -n: Non-interactive Mode. Assumes "yes" for all confirmations during installation.
• -z: Install ZSH. Configures ZSH with Oh My Zsh and plugins (syntax highlighting, autosuggestions).
• -p: Install Python. Installs system dependencies and the uv manager with the global Python version.
• -d: Install Docker. Performs Docker installation and configuration on the system.
• -h: Help. Displays the help message with all options.

Examples

To install everything (Zsh, Python, and Docker) in silent mode:

sh <(wget -qO - https://raw.githubusercontent.com/Sette/setup-env/refs/heads/main/install.sh) -z -p -d -n

To install only Zsh and Python:

sh <(wget -qO - https://raw.githubusercontent.com/Sette/setup-env/refs/heads/main/install.sh) -z -p -n

Reload your shell by running:

If using zsh, run:

source ~/.zshrc

If using bash, run:

source ~/.bashrc

(Optional) (Python) Creating a .venv:

uv venv

Activating the .venv:

source .venv/bin/activate

Recommendations for Python development in VS Code:

https://code.visualstudio.com/docs/python/linting

Follow the instructions for each script, as they may require administrator (sudo) permissions.

Prerequisites

• Superuser permission (sudo)
• Internet connection
• Git installed (for some scripts and plugins)

Notes

• Scripts can be adapted to your needs.
• Check the content of each script before running to understand its actions and dependencies.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

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Collaborate by suggesting improvements and reporting issues.