Top 5 Python Code Linters for every Data Scientist

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 into any product. It becomes really necessary to improve code quality. Linters are necessary for every programming language

Bandit. As you now Python is a dynamic programming language that performs auto garbage collection. All these features help in maintaining code quality but linter gives add on this. This article will help you in finding Top 5 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 –

  1. Pylint –

Python-code-Linters-PyLints.
Python-code-Linters-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 hole in the code implementation as well . For example the interface is properly implemented or not and all dependent modules are imported or not etc . This helps coder / programmer top identify basic code health check while development .

2. flake8 –

Python-code-Linters-flake8
Python-code-Linters-flake8

Quite similar to the above one . Basically it covers most the feature available in the above tool . I will suggest you to go through it . Because covering all the feature 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 format 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 –

Python-code-Linters-Pylama
Python-code-Linters-Pylama

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

6.Bandit

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

Bandit

How important is 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 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 some time just to have things.

Conclusion –

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 article on how to use linters in Python codebase.

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