16a Configuring Python & Pip

ABSTRACT

To contribute to the CAPIBARA Collaboration, you need a functional Python environment. This tutorial guides you through installing Python and pip—the industry-standard package manager used to install essential scientific libraries like NumPy, Pandas, and Matplotlib.

Prerequisites

Before configuring Python, ensure you are comfortable with the command line:

• 11_unix
• 12_terminal

1. Introduction

Python is the backbone of modern research and engineering. While many systems come with Python pre-installed, you often need to verify the version and ensure pip is available to manage external dependencies.

2. Checking Your System

Most macOS and Linux distributions include Python out of the box. Open your terminal and run:

python3 --version

If you see a version number (e.g., Python 3.10.x), it is installed. You should also check for pip:

pip3 --version

Why "python3" instead of "python"?

On many systems, the command python still refers to the obsolete Python 2.7. Always use python3 and pip3 to ensure you are using the modern version of the language.

3. Installation

If the commands above returned an error, follow the steps for your operating system.

3.1 Linux (Ubuntu/Debian)

Update your local package index and install Python via apt:

sudo apt update
sudo apt install python3 python3-pip

3.2 macOS

The best way to manage Python on macOS is through Homebrew.

1. Install Homebrew (if you haven’t):

   /bin/bash -c "$(curl -fsSL [https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh](https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh))"

2. Install Python:

   brew install python

4. Common pip Commands

Once pip is installed, you will use it to download the “building blocks” of your code.

Action	Command
Install a package	pip install <package-name>
Upgrade a package	pip install --upgrade <package-name>
Uninstall a package	pip uninstall <package-name>
List installed packages	pip list
Show package info	pip show <package-name>

Practice

Try installing a common library used for math: pip install numpy

5. Learning Resources

While you follow our internal guides, we recommend these external resources to deepen your understanding:

1. Intro to Python Course: A notebook-based course focusing on scientific Python.
2. Official Python Tutorial: The definitive guide from the creators of Python.
3. Python Tutor: A great tool to visualize how your code executes line-by-line.

6. Verification

To ensure everything is linked correctly, run:

• which python3: This shows the file path where Python is installed.
• python3 -c "print('Ready!')": This runs a tiny snippet of code to confirm the engine is working.

SUCCESS

Python is now alive on your machine! However, installing every package globally can lead to “dependency hell” where different projects conflict with each other. To avoid this, proceed to 42_configuring_conda_venv to learn about Virtual Environments. Before that you can go to the second part of this tutorial: 16b_python_basics to learn the fundamentals of coding Python.