Top 6 Python Code Linters for every Data Scientist in 2022

Top 5 Python Code Linters for every Data Scientist

Actually, Code Linters are really necessary to use. Usually, during the PoC of any Data Science Project, we do not care about code quality. But when you convert that PoC into a feature and then integrate it into any product. It becomes really necessary to improve code quality. Linters are necessary for every programming language

Bandit. As you know Python is a dynamic programming language that performs auto garbage collection. All these features help in maintaining code quality but linter gives an add-on. This article will help you in finding the Top 6 Python Code Linters.

What is Code Quality?

Just like you watch a movie and after seeing it you can easily say what will be its rating. The rating can be anything from 1 to 10. In the same way code quality is rating. It defines the way of writing code to make it easy to read, reusable, and easy to maintain.

Top 6 Python Code Linters –

Here is the list of the best python linter for you.

  1. Pylint –


It helps in detecting duplicate code. It also helps in maintaining coding standards. Coding standard involves naming convention. If we go deeper it helps in finding holes in the code implementation as well. For example, whether the interface is properly implemented or not whether all dependent modules are imported or not etc. This helps the coder/programmer to identify basic code health checks while developing.

2. flake8 –


Quite similar to the above one. Basically, it covers most of the features available in the above tool. I will suggest you go through it. Because covering all the features in very few lines, will be big injustice.

3. autopep8 –

Python code Linters -autopep8
Python code Linter -autopep8

This utility works as python linter . It auto converts python code into pep8 standard. Basically, by saying it converts into pep 8, I mean it formats the code in pep 8 standard.

4. PyChecker –

Python code Linter -PyChecker.

It is a different kind of Python linters . It basically helps in identifying hidden bugs.

5. Pylama –


Last but not least. Here is the detailed documentation of its usage and implementation.


It is really useful for identifying security concerns in the code. Here are the complete details for the bandit.


How important are Linters in Coding? –

I have read in the community of developers that Linter is just styling. But it is not completely true. Obviously, styling is just a feature of a formator but linters are beyond too it. Actually, in most cases, they provide you a warning, if you resolve them in the early stages. You may easily avoid future production bugs. Especially in the case of dynamically typed programming languages like python. So linters are practices and sometimes just to have things.

Conclusion (best python linter)-

This article helps you in identifying the best python linter for your codebase. Well its always advisable to use linters while developing. This is not necessary only in Data Science but it is advisable everywhere like web development, script generation, etc. The scope of this article was to introduce you to all of them. But yes! We will provide a few more articles on how to use linters in the Python codebase.

But I will request you to subscribe to Data Science Learner in order to get updates on python linters and data science stuff.  We also offer free study material on data science to our newsletter subscribers. Apart from this if you want to contribute content on data science stuff or linter etc. You are most welcome to write us back. There could be a couple of ways like guest posts etc.


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Meet Abhishek ( Chief Editor) , a data scientist with major expertise in NLP and Text Analytics. He has worked on various projects involving text data and have been able to achieve great results. He is currently manages, where he and his team share knowledge and help others learn more about data science.
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