🟢 Linux: Install Tools
Installation instructions for required tools on Linux systems.
Linux distributions vary, so follow the vendor-recommended steps for your system.
WHY?
Professional analytics projects depend on local tools for running code, managing packages, checking quality, and working with GitHub repositories.
Installing the required tools creates a consistent project environment across machines and operating systems.
Correct tool installation reduces setup errors and makes later commands predictable.
Required Tools
1. Git
Most Linux distributions include Git in their package manager.
Official instructions: https://git-scm.com/book/en/v2/Getting-Started-Installing-Git
WHY?
Git tracks changes in project files over time.
It records what changed, when it changed, and who made the change.
Git is used with GitHub, but they are different.
- Git is version control software that runs on a machine.
- GitHub is a cloud platform that stores Git projects online.
2. Visual Studio Code
Follow Microsoft's official Linux setup instructions for your distribution: https://code.visualstudio.com/docs/setup/linux
WHY?
Visual Studio Code is a code editor used to open, inspect, edit, and run project files.
It provides an integrated terminal, which allows project commands to be run from inside the same workspace.
The code command makes it possible to open a project folder in VS Code directly from the terminal.
3. uv (Python environment and dependency manager)
Follow the official installation instructions from Astral: https://docs.astral.sh/uv/getting-started/installation/
WHY?
uv manages the Python version and project packages used by a project.
Using uv helps each project install the correct Python version and packages from the project configuration in pyproject.toml and keeps project Python separate from any other Python being used on the machine.
If you worked with older Python projects, you might have used pip to manage required packages and venv to manage the virtual environment kept in the local .venv folder.
We moved to uv because:
- it is fast
- it uses the same commands on Windows, macOS, and Linux
- it creates and updates the local .venv project environment
- it can install and manage the Python version for the project
- it reduces the number of separate Python setup tools needed
Verify
After installation, open a terminal and run:
shell
git --version
code --version
uv --version