🟢 Windows: Install Tools
This page links to official installation instructions for required tools on Windows. Always follow the vendor-recommended installers.
These tools are essential for professional data analytics.
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
Download and install Git from the official site: https://git-scm.com/
Have Git and want to update?
Try:
powershell
git update-git-for-windows
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
Download and install Visual Studio Code from: https://code.visualstudio.com/
(Recommended) Enable the code command in PowerShell by following: https://code.visualstudio.com/docs/setup/windows
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)
Install uv using the official Windows method: https://docs.astral.sh/uv/getting-started/installation/
Do not install a project Python separately at this step. Python will be installed per-project using uv.
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
Refresh Your Terminal and Verify
Close all open terminal windows, command prompts, or IDEs (like VS Code). Environment paths will not update in terminals that are already open.
Open a brand new PowerShell terminal window and run:
shell
git --version
code --version
uv --version
Each command should display a version number. If any command fails, revisit the corresponding installer.
OPTIONAL/ADVANCED: Windows Subsystem for Linux (WSL) - ONLY AS DIRECTED
This is only for advanced users who need Linux-only tools (e.g., Kafka or Spark).
To install WSL, follow Microsoft's official instructions: https://learn.microsoft.com/en-us/windows/wsl/install
Use WSL only when required; it is NOT normally needed for Python projects managed with uv.
OPTIONAL/ADVANCED: WHY WSL?
WSL provides a Linux environment on Windows.
Some data tools are easier to install and run in Linux than directly in Windows.
WSL is especially useful when a project requires Linux-based services such as Apache Kafka, Apache Spark, or Apache Flink.