It’s so pleasant and easy to work with it if it explicitly tells us what was it for and what its functions, code lines, and modules do. We never know when we will return to one of our old projects to modify or improve it. Would you want to contribute to a project in your free time if you had to spend hours to figure out what its different parts do? I wouldn’t.įinally, even if it’s only our private project or a small script, we need the documentation anyway.
They can do it much faster and more efficiently if our code is well-documented. Next, other developers may want to contribute to our projects. It should be more obvious now why good documentation counts. This workload doubles or triples if the package is huge, with functions spread over multiple files. There are some packages with absolutely zero documentation, and it usually takes much more time to understand what is under their hoods and how we can use them. We would need to dig into their code to understand what it does and how we can employ it. Now imagine using these packages without any reference. They also have built-in documentation that we can directly access in your preferred IDE. These two packages have excellent documentation, and users usually don’t have any trouble using them because they contain a lot of examples and tutorials. Remember that we are also end-users when we read pandas documentation or scikit-learn documentation. When we write code, we do it for end-users, developers, and ourselves. The Zen of Python tells us that "Readability counts" and "Explicit is better than implicit." These are necessary characteristics of Python. Why Documentation in Python Is Important?
Python comment software#
AugHow to Use Python Docstrings for Effective Code Documentation Documenting your code is a critical skill for any data scientist or software engineer.
0 kommentar(er)
