Now that you’ve set up your Python project and are ready to start coding, it’s time to choose the right tool for the job: an Integrated Development Environment (IDE) or a code editor. If you’re coming from PHP, you might be familiar with tools like PHPStorm, Visual Studio Code (VS Code), or Sublime Text. Python has a rich ecosystem of IDEs and editors that offer similar features, with some tailored specifically for Python development.

Python Installers

There are standard methods for installing Python, depending on your platform:

• Windows: Use the official Python installer from python.org, or package managers like Chocolatey.
• macOS: Install via Homebrew with brew install python, or use the official macOS installer.
• Linux: Most distributions include Python by default. For newer versions, use your distribution’s package manager (e.g., apt install python3 on Debian/Ubuntu).

Once installed, Python is ready to use—but here’s where things get tricky.

Your PHP foundation is a powerful starting point!

This course emerged from my own journey learning Python as a PHP developer. If you’ve mastered PHP, you’ll find that a surprising amount of Python code is already readable without even needing to learn its syntax. Python shares concepts and philosophies you’re already familiar with, making the transition smoother than you might expect.

The entire course is designed to leverage your existing PHP knowledge to accelerate your Python learning.

If you’re familiar with PHP’s Composer and its project structure convention, you’ll find Python’s approach both similar and distinct. In this section, we’ll walk through the key steps to set up a Python project, focusing on virtual environments, dependency management, and project structure—concepts that will feel familiar if you’re coming from PHP.

Why Virtual Environments Matter

In PHP, Composer installs dependencies in a vendor/ directory within your project, isolating them from the global system. Python achieves a similar goal using virtual environments. These are self-contained directories that contain all the dependencies and Python versions required for a project, ensuring that your system-wide Python installation remains clean and uncluttered.