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Level Up Your Python: Essential Style Guide Tips for Readable & Maintainable Code [Part 2]

Shadab Hussain
FAUN — Developer Community 🐾
14 min readJan 7, 2024

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In the previous blog, we covered Language rules that is the essential grammar of Python, like syntax requirements & keyword usage and we mastered those to ensures our code works properly.

In this blog, beyond the language’s core grammar, a symphony of style awaits. Forget spaghetti code monstrosities — let’s unveil the art of Python aesthetics. We’ll explore the graceful dance of whitespace, where indentation paints the canvas of your program, and naming conventions become the melodic prose guiding the reader’s eye. We’ll delve into the world of comments, whispered insights that illuminate your code’s intent, and discover how elegant formatting can transform your script into a masterpiece. Embrace these style rules, and you’ll not only write code that runs smoothly, but also code that sings, showcasing your mastery and inviting collaboration. So, let’s ditch the drab and embrace the dazzling — prepare to style your Python like a pro!

BASIC SYNTAX AND FORMATTING

SEMICOLONS AND LINE LENGTH

Python does not require semicolons at the end of statements, and its style generally prefers line lengths to be limited to 79 characters to enhance readability and maintainability.

Best Practices:

  • Avoid terminating lines with semicolons and do not use semicolons to place two statements on the same line.
  • Explicit exceptions to the 80 character limit include:
    - Long import statements
    - URLs, pathnames, or long flags in comments
    - Long string module-level constants not containing whitespace
  • Pylint disable comments (e.g., # pylint: disable=invalid-name)

INDENTATION

Python uses indentation to define the scope of code blocks instead of braces or…

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Published in FAUN — Developer Community 🐾

We help developers learn and grow by keeping them up with what matters. 👉 www.faun.dev

Written by Shadab Hussain

MLOps @themathcompany, #AWS Community Builder for #data, #DataScience, #Quantum, #MachineLearning

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