Coding Style

Python code is read far more often than it’s written, so coding style is really about communication. Consistent naming, clear structure, and straightforward control flow make code easier to scan, review, and maintain.

Instead of debating subjective style choices in every review, you can lean on shared conventions and automated tools so that humans focus on behavior and design while guidelines and tooling cover the basics.

In this context, you can summarize the best practices as shown below:

  • Apply the PEP 8 style guide. Follow PEP 8 since it’s Python’s official style guide. It includes conventions for naming, code organization, and readability. When you follow it, your code looks familiar to other Python developers, which makes collaboration, review, and long-term maintenance easier.
  • Use automated formatters and linters. Tools like Black, Ruff, or flake8 help enforce consistent style automatically. They remove subjective decisions from code reviews and let you focus on correctness and design instead of formatting details.
  • Use names that reveal intent. Prefer descriptive variable and function names over abbreviations and single-letter names. If a reader has to decode your naming choices, they’ll spend more time understanding the code and less time improving it.
  • Favor readable, straightforward logic. Keep functions small, avoid deeply nested conditionals, and write code that clearly communicates why it exists. This practice reduces cognitive load, speeds up debugging, and makes future changes safer and quicker.
  • Document behavior with docstrings when it helps. Use docstrings to explain what a function, class, or module does and what callers can expect.

To illustrate how applying some of these best practices can improve your code, consider the following code example:

🔴 Avoid this:

Python 
def f(d):
    out = []
    for x in d:
        if x["status"] == "active" and x["age"] >= 18:
            out.append(x["email"].strip().lower())
    return out

This code works, but the function and parameter names don’t communicate their intent clearly. The logic is also packed into a loop without any cues about what the function returns or why it exists.

✅ Favor this:

Python 
def get_active_adult_emails(users):
    """Return normalized emails for active users who are at least 18."""

    emails = []
    for user in users:
        if user["status"] != "active":
            continue
        if user["age"] < 18:
            continue

        emails.append(user["email"].strip().lower())

    return emails

Now, the function name clearly communicates its intent. Early continue statements make the code quicker to understand, and the docstring clarifies behavior for callers.

How to Write Beautiful Python Code With PEP 8

Tutorial

How to Write Beautiful Python Code With PEP 8

Learn how to write high-quality, readable code by using the Python style guidelines laid out in PEP 8. Following these guidelines helps you make a great impression when sharing your work with potential employers and collaborators.

intermediate best-practices

For additional information on related topics, take a look at the following resources:

By Leodanis Pozo Ramos • Updated Dec. 23, 2025 • Reviewed by Brenda Weleschuk and Bartosz Zaczyński
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