One of the goals of technology is to do more in less time. It is ironic and mind-numbing the amount of time spent on debugging. The bug could be a simple omission or addition staring right at you. You want to curtail as many simple errors as possible and be more productive with the limited time available.

One of the ways to do this is by using a lint or linter.

This article briefly highlights the background of lints, what they are, why you need them, a few examples and some points to note.

Lints: A Brief Background

“Lint” was derived from lint — the tiny bits of fibre and fluff shed by clothing. If you look at your clothes now, there is a good chance that you have lints on them. Textile fibres like cotton and wool are lint producers. Consider putting on more spandex fabrics. Nevermind.😂

Lint, in programming, is made to function like the lint trap in a clothes dryer.

Stephen C. Johnson, a computer scientist at Bell Labs, came up with lint in 1978 while debugging using the C programming language.

In 1979, developers used lint outside Bell Labs for the first time in the seventh version (V7) of Unix.

Over the years, developers have created different versions of lint for other programming languages.

Lints: What Are They?

Lints are tools that point out common programming errors, bugs, style errors and suspicious constructs. They keep programmers within the constraints of programming best practices.

Why You Need Lints

They analyze code
They point out programming errors
They provide suggestions to correct flagged errors
They help maintain a consistent coding style
They reduce errors and improve the overall quality of your code
They can help you accelerate development and reduce costs

Examples of Lints

There are many types of lint available, based on your programming language. These include PC-Lint, Bootlint, pycodestyle, and JSLint, among others.

Some Points to Note

Lints are great, but they are not suitable for all situations. They are great for simple analysis. However, you cannot use them for complex code analysis.

Lints can flag as many errors as there are code lines. This flagging can cause high false positives and false negatives rates.

Lints are not expensive, but they can lead to accumulated costs in developer productivity.

Lints flag errors and keep programmers within the constraints of programming best practices, but most times, programmers cannot replicate these best practices on their own.

How to Install Pycodestyle for Python

To install pycodestyle using your command line, use the code below.

pip install pycodestyle

P.S. This works for Ubuntu 20.4 and GitBash.

Below is a snapshot of pycodestyle checking Python code against some programming conventions.

Lints Can Save You Minutes