Fundamentals 55 min read

Master Google Python Style Guide: Essential Coding Standards Explained

This comprehensive guide translates Google's Python style guide into clear English, covering everything from naming conventions and imports to docstrings, type annotations, and best practices for functions, classes, and modules, helping developers write clean, consistent, and maintainable Python code.

MaGe Linux Operations
MaGe Linux Operations
MaGe Linux Operations
Master Google Python Style Guide: Essential Coding Standards Explained

1 Introduction

This document is a full translation of the Google Python Style Guide, providing a detailed reference for writing clean, consistent, and maintainable Python code.

2 Python Language Rules

2.1 Lint

Use pylint to enforce style. Suppress warnings with # pylint: disable=... when necessary, but keep the list short.

2.2 Imports

Import each module on its own line. Order imports by groups: future imports, standard library, third‑party libraries, and internal packages. Sort alphabetically within each group.

2.3 Packages

Always import full package paths; avoid relative imports. Use import x.y.z rather than from . import z.

2.4 Exceptions

Raise specific exceptions, avoid catching except: unless absolutely required. Prefer raise ValueError(...) over generic Exception.

2.5 Global Variables

Avoid mutable globals. Use module‑level constants in ALL_CAPS and prefix private globals with an underscore.

2.6 Inner Classes and Functions

Define inner classes/functions only when they are truly scoped to the enclosing function. Keep them small and testable.

2.7 List Comprehensions

Prefer list comprehensions for simple cases; avoid complex nested comprehensions.

2.8 Default Iterators and Operators

Use Python’s implicit iteration (e.g., for x in seq) and membership tests ( in) instead of explicit index checks.

2.9 Generators

Use generators for lazy evaluation. Document yielded values with a Yields: section.

2.10 Lambda Expressions

Use lambda only for simple, single‑expression functions; otherwise define a regular function.

2.11 Conditional Expressions

Use ternary operators for short conditions; otherwise write a full if / else block.

2.12 Default Parameter Values

Never use mutable objects as default values. Use None and assign inside the function when needed.

2.13 Properties

Prefer @property for simple getters/setters to keep the API clean.

2.14 Truthiness

Leverage Python’s implicit boolean evaluation (e.g., if seq:) instead of explicit length checks.

2.15 Deprecated Features

Avoid old Python 2 constructs such as apply, string module functions, and has_key().

2.16 Lexical Scoping

Understand closures and the nonlocal keyword to avoid common pitfalls.

2.17 Decorators

Use decorators sparingly; document their effect and test them thoroughly.

2.18 Threading

Prefer queue.Queue for thread communication and avoid relying on built‑in atomicity.

2.19 Powerful Language Features

Use metaclasses, bytecode manipulation, and dynamic imports only when absolutely necessary.

2.20 Python 3 Migration

Include

from __future__ import absolute_import, division, print_function

in all new code to ease transition to Python 3.

2.21 Type Annotations

Annotate public APIs with PEP‑484 types. Use Optional, Union, and Any appropriately. Prefer def func(x: int) -> str: syntax.

3 Python Code Style Guidelines

3.1 Line Length

Limit lines to 80 characters. Exceptions include long imports, URLs, and # pylint: disable=... comments.

3.2 Indentation

Use 4 spaces per indentation level; never mix tabs.

3.3 Whitespace

No spaces inside parentheses, brackets, or braces. One space after commas, colons, and semicolons.

3.4 Blank Lines

Separate top‑level definitions with two blank lines and methods with one blank line.

3.5 Docstrings

Every module, class, and public function should have a triple‑quoted docstring. Follow the summary line. blank line. detailed description format.

3.6 Naming Conventions

Modules and packages: lower_with_underscores Classes: CapWords Functions and methods: lower_with_underscores() Constants: ALL_CAPS Private names: leading underscore

3.7 Imports

One import per line, grouped as described in section 2.2.

3.8 Strings

Prefer format() or f‑strings for formatting. Use triple‑quoted strings for multi‑line text and avoid concatenating strings with + inside loops.

3.9 Main Guard

Wrap executable code in if __name__ == '__main__': and place logic in a main() function.

3.10 Function Length

Prefer short, focused functions. If a function exceeds ~40 lines, consider refactoring.

4 Final Thoughts

Adopt the style guide consistently across a project to improve readability and maintainability. When contributing to existing code, follow the prevailing style to avoid unnecessary churn.

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Pythoncoding standardsDocumentationpep8style guide
MaGe Linux Operations
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MaGe Linux Operations

Founded in 2009, MaGe Education is a top Chinese high‑end IT training brand. Its graduates earn 12K+ RMB salaries, and the school has trained tens of thousands of students. It offers high‑pay courses in Linux cloud operations, Python full‑stack, automation, data analysis, AI, and Go high‑concurrency architecture. Thanks to quality courses and a solid reputation, it has talent partnerships with numerous internet firms.

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