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Writing large-scale Python code requires clean structures, reusable packages, and isolated runtime environments. Let’s cover how to handle and configure professional Python projects.

1. Modules and Packages

  • Module: A single Python file (.py) containing code.
  • Package: A directory containing multiple modules and a special file named __init__.py.

Best Practices for Imports

  • Always use Absolute Imports: Avoid relative imports (like from ..utils import db). These are prone to breaking when files are run as standalone scripts. Instead, use the project root path:
  • Avoid from module import *: Clutters your namespace and can overwrite existing functions or variables silently. Import explicitly:

2. Virtual Environments

A virtual environment is a local directory containing its own Python executable and installed dependencies.

Why isolate environments?

By default, standard python installations share global libraries. If Project A needs django 3.2 and Project B needs django 4.2, a global environment will crash. Virtual environments solve this by isolating packages per folder.

Creating and Activating (Standard)

Modern Alternative: uv

uv is an ultra-fast Python package installer and resolver written in Rust by Astral, serving as a drop-in replacement for standard pip tools:

What’s next?

Now that you have completed Advanced Python, let’s learn how to extend Python using standard libraries and external packages!

Extending Python

Learn standard library and external package management