Scoping: Modules typically define a separate namespace, which helps avoid collisions between identifiers in different areas of a program. This eliminates the need to duplicate code. Reusability: Functionality defined in a single module can be easily reused (through an appropriately defined interface) by other parts of the application. (You may even be able to make changes to a module without having any knowledge of the application outside that module.) This makes it more viable for a team of many programmers to work collaboratively on a large application. If modules are written in a way that minimizes interdependency, there is decreased likelihood that modifications to a single module will have an impact on other parts of the program. Maintainability: Modules are typically designed so that they enforce logical boundaries between different problem domains. This makes development easier and less error-prone. If you’re working on a single module, you’ll have a smaller problem domain to wrap your head around.
Simplicity: Rather than focusing on the entire problem at hand, a module typically focuses on one relatively small portion of the problem. There are several advantages to modularizing code in a large application: Individual modules can then be cobbled together like building blocks to create a larger application. Modular programming refers to the process of breaking a large, unwieldy programming task into separate, smaller, more manageable subtasks or modules. This article explores Python modules and Python packages, two mechanisms that facilitate modular programming. Watch it together with the written tutorial to deepen your understanding: Python Modules and Packages: An Introduction Watch Now This tutorial has a related video course created by the Real Python team.
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