Data Science: From School to Work, Part II

In my previous article, I highlighted the importance of effective project management in Python development. Now, let’s shift our focus to the code itself and explore how to write clean, maintainable code — an essential practice in professional and collaborative environments. 

• Readability & Maintainability: Well-structured code is easier to read, understand, and modify. Other developers — or even your future self — can quickly grasp the logic without struggling to decipher messy code.
• Debugging & Troubleshooting: Organized code with clear variable names and structured functions makes it easier to identify and fix bugs efficiently.
• Scalability & Reusability: Modular, well-organized code can be reused across different projects, allowing for seamless scaling without disrupting existing functionality.

So, as you work on your next Python project, remember: 

Half of good code is Clean Code.

Introduction

Python is one of the most popular and versatile Programming languages, appreciated for its simplicity, comprehensibility and large community. Whether web development, data analysis, artificial intelligence or automation of tasks — Python offers powerful and flexible tools that are suitable for a wide range of areas.

However, the efficiency and maintainability of a Python project depends heavily on the practices used by the developers. Poor structuring of the code, a lack of conventions or even a lack of documentation can quickly turn a promising project into a maintenance and development-intensive puzzle. It is precisely this point that makes the difference between student code and professional code.

This article is intended to present the most important best practices for writing high-quality Python code. By following these recommendations, developers can create scripts and applications that are not only functional, but also readable, performant and easily maintainable by third parties.

Adopting these best practices right from the start of a project not only ensures better collaboration within teams, but also prepares your code to evolve with future needs. Whether you’re a beginner or an experienced developer, this guide is designed to support you in all your Python developments.

The code structuration

Good code structuring in Python is essential. There are two main project layouts: flat layout and src layout.

The flat layout places the source code directly in the project root without an additional folder. This approach simplifies the structure and is well-suited for small scripts, quick prototypes, and projects that do not require complex packaging. However, it may lead to unintended import issues when running tests or scripts.

                            
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