Look to these free tools to ensure that your Python code complies with recommended Python coding conventions and code quality standards
In theory, any Python code is OK as long as it’s syntactically correct and runs as intended. In practice, you want to adopt a consistent style across your projects, preferably one guided by Python’s own style recommendations. The good news is you don’t have to do this by hand. The Python ecosystem contains a variety of tooling, from the highly focused to the wide-ranging, to ensure that Python source code adheres to style conventions.
In this article we’ll examine four popular tools for checking Python code styles, plus one for reformatting code to be consistent. Python IDEs like PyCharm or Visual Studio Code support them either natively or with an extension, so they can be readily integrated into your development workflow.
PEP 8 is the document that spells out Python’s coding conventions — everything from whether to use tabs or spaces when indenting (use four spaces, problem solved) to how to name variables and objects. Pycodestyle is the Python module that checks Python code against the PEP 8 recommendations and delivers a report on where the analyzed code is out of spec.
Pycodestyle doesn’t provide automatic fixes for issues; that’s on you. But Pycodestyle is highly configurable, allowing you to suppress specific kinds of errors or parse only specific files in a source tree. And just about every IDE with Python support also supports Pycodestyle, so it’s the easy choice for universal compatibility, if not functionality.
Many Python code linters can work as modules in Python, and Pycodestyle is no exception. You can use it to verify code programmatically, for instance as part of a test suite.
*Best for: *Basic verification of PEP 8 conformance.
Static code analysis is a method of debugging by examining source code before a program is run. It's done by analyzing a set of code against a set (or multiple sets) of coding rules. Static code analysis and static analysis are often used interchangeably, along with source code analysis.
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.
Today you're going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates. We gonna use Python OS remove( ) method to remove the duplicates on our drive. Well, that's simple you just call remove ( ) with a parameter of the name of the file you wanna remove done.
In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.
Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc.. You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like __init__, __call__, __str__ etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).