Python Style Guide

Comprehensive guidelines for writing clean, maintainable Python code based on Google's Python Style Guide.

Core Philosophy

BE CONSISTENT. Match the style of the code around you. Use these guidelines as defaults, but always prioritize consistency with existing code.

Language Rules

Imports

Use import statements for packages and modules only, not for individual classes or functions.

Yes:

python

from doctor.who import jodie
import sound_effects.utils

No:

python

from sound_effects.utils import EffectsRegistry  # Don't import classes directly

Import Formatting

Group imports: standard library, third-party, application-specific
Alphabetize within each group
Use absolute imports (not relative imports)
One import per line (except for multiple items from typing or collections.abc)

python

# Standard library
import os
import sys

# Third-party
import numpy as np
import tensorflow as tf

# Application-specific
from myproject.backend import api_utils

Exceptions

Use exceptions appropriately. Do not suppress errors with bare except: clauses.

Yes:

python

try:
    result = risky_operation()
except ValueError as e:
    logging.error(f"Invalid value: {e}")
    raise

No:

python

try:
    result = risky_operation()
except:  # Too broad, hides bugs
    pass

Type Annotations

Annotate all function signatures. Type annotations improve code readability and catch errors early.

General rules:

Annotate all public APIs
Use built-in types (list, dict, set) instead of typing.List, etc. (Python 3.9+)
Import typing symbols directly: from typing import Any, Union
Use None instead of type(None) or NoneType

python

def fetch_data(url: str, timeout: int = 30) -> dict[str, Any]:
    """Fetch data from URL."""
    ...

def process_items(items: list[str]) -> None:
    """Process a list of items."""
    ...

Default Argument Values

Never use mutable objects as default values in function definitions.

Yes:

python

def foo(a: int, b: list[int] | None = None) -> None:
    if b is None:
        b = []

No:

python

def foo(a: int, b: list[int] = []) -> None:  # Mutable default - WRONG!
    b.append(a)

True/False Evaluations

Use implicit false where possible. Empty sequences, None, and 0 are false in boolean contexts.

Yes:

python

if not users:  # Preferred
if not some_dict:
if value:

No:

python

if len(users) == 0:  # Verbose
if users == []:
if value == True:  # Never compare to True/False explicitly

Comprehensions & Generators

Use comprehensions and generators for simple cases. Keep them readable.

Yes:

python

result = [x for x in data if x > 0]
squares = (x**2 for x in range(10))

No:

python

# Too complex
result = [
    x.strip().lower() for x in data 
    if x and len(x) > 5 and not x.startswith('#')
    for y in x.split(',') if y
]  # Use a regular loop instead

Lambda Functions

Use lambdas for one-liners only. For anything complex, define a proper function.

Yes:

python

sorted(data, key=lambda x: x.timestamp)

Acceptable but prefer named function:

python

def get_timestamp(item):
    return item.timestamp

sorted(data, key=get_timestamp)

Style Rules

Line Length

Maximum line length: 80 characters. Exceptions allowed for imports, URLs, and long strings that can't be broken.

Indentation

Use 4 spaces per indentation level. Never use tabs.

For hanging indents, align wrapped elements vertically or use 4-space hanging indent:

python

# Aligned with opening delimiter
foo = long_function_name(var_one, var_two,
                         var_three, var_four)

# Hanging indent (4 spaces)
foo = long_function_name(
    var_one, var_two, var_three,
    var_four)

Blank Lines

Two blank lines between top-level definitions
One blank line between method definitions
Use blank lines sparingly within functions to show logical sections

Naming Conventions

Type	Convention	Examples
Packages/Modules	`lower_with_under`	`my_module.py`
Classes	`CapWords`	`MyClass`
Functions/Methods	`lower_with_under()`	`my_function()`
Constants	`CAPS_WITH_UNDER`	`MAX_SIZE`
Variables	`lower_with_under`	`my_var`
Private	`_leading_underscore`	`_private_var`

Avoid:

Single character names except for counters/iterators (i, j, k)
Dashes in any name
__double_leading_and_trailing_underscore__ (reserved for Python)

Comments and Docstrings

Docstring Format

Use Google-style docstrings for all public modules, functions, classes, and methods.

Function docstring:

python

def fetch_smalltable_rows(
    table_handle: smalltable.Table,
    keys: Sequence[bytes | str],
    require_all_keys: bool = False,
) -> Mapping[bytes, tuple[str, ...]]:
    """Fetches rows from a Smalltable.

    Retrieves rows pertaining to the given keys from the Table instance
    represented by table_handle. String keys will be UTF-8 encoded.

    Args:
        table_handle: An open smalltable.Table instance.
        keys: A sequence of strings representing the key of each table
            row to fetch. String keys will be UTF-8 encoded.
        require_all_keys: If True, raise ValueError if any key is missing.

    Returns:
        A dict mapping keys to the corresponding table row data
        fetched. Each row is represented as a tuple of strings.

    Raises:
        IOError: An error occurred accessing the smalltable.
        ValueError: A key is missing and require_all_keys is True.
    """
    ...

Class docstring:

python

class SampleClass:
    """Summary of class here.

    Longer class information...
    Longer class information...

    Attributes:
        likes_spam: A boolean indicating if we like SPAM or not.
        eggs: An integer count of the eggs we have laid.
    """

    def __init__(self, likes_spam: bool = False):
        """Initializes the instance based on spam preference.

        Args:
            likes_spam: Defines if instance exhibits this preference.
        """
        self.likes_spam = likes_spam
        self.eggs = 0

Block and Inline Comments

Use complete sentences with proper capitalization
Block comments indent to the same level as the code
Inline comments should be separated by at least 2 spaces
Use inline comments sparingly

python

# Block comment explaining the following code.
# Can span multiple lines.
x = x + 1  # Inline comment (use sparingly)

Strings

Use f-strings for formatting (Python 3.6+).

Yes:

python

x = f"name: {name}; score: {score}"

Acceptable:

python

x = "name: %s; score: %d" % (name, score)
x = "name: {}; score: {}".format(name, score)

No:

python

x = "name: " + name + "; score: " + str(score)  # Avoid + for formatting

Logging

Use % formatting for logging, not f-strings (allows lazy evaluation):

python

logging.info("Request from %s resulted in %d", ip_address, status_code)

Files and Resources

Always use context managers (with statements) for file operations:

python

with open("file.txt") as f:
    data = f.read()

Statements

Generally avoid multiple statements on one line.

Yes:

python

if foo:
    bar()

No:

python

if foo: bar()  # Avoid

Main

For executable scripts, use:

python

def main():
    ...

if __name__ == "__main__":
    main()

Function Length

Keep functions focused and reasonably sized. If a function exceeds about 40 lines, consider splitting it unless it remains very readable.

Type Annotation Details

Forward Declarations

Use string quotes for forward references:

python

class MyClass:
    def method(self) -> "MyClass":
        return self

Type Aliases

Create aliases for complex types:

python

from typing import TypeAlias

ConnectionOptions: TypeAlias = dict[str, str]
Address: TypeAlias = tuple[str, int]
Server: TypeAlias = tuple[Address, ConnectionOptions]

TypeVars

Use descriptive names for TypeVars:

python

from typing import TypeVar

_T = TypeVar("_T")  # Good: private, unconstrained
AddableType = TypeVar("AddableType", int, float, str)  # Good: descriptive

Generics

Always specify type parameters for generic types:

Yes:

python

def get_names(employee_ids: list[int]) -> dict[int, str]:
    ...

No:

python

def get_names(employee_ids: list) -> dict:  # Missing type parameters
    ...

Imports for Typing

Import typing symbols directly:

python

from collections.abc import Mapping, Sequence
from typing import Any, Union

# Use built-in types for containers (Python 3.9+)
def foo(items: list[str]) -> dict[str, int]:
    ...

Common Patterns

Properties

Use properties for simple attribute access:

python

class Square:
    def __init__(self, side: float):
        self._side = side
    
    @property
    def area(self) -> float:
        return self._side ** 2

Conditional Expressions

Use ternary operators for simple conditions:

python

x = "yes" if condition else "no"

Context Managers

Create custom context managers when appropriate:

python

from contextlib import contextmanager

@contextmanager
def managed_resource(*args, **kwargs):
    resource = acquire_resource(*args, **kwargs)
    try:
        yield resource
    finally:
        release_resource(resource)

Linting

Run pylint on all Python code. Suppress warnings only when necessary with clear explanations:

python

dict = 'something'  # pylint: disable=redefined-builtin

Summary

When writing Python code:

Use type annotations for all functions
Follow naming conventions consistently
Write clear docstrings for all public APIs
Keep functions focused and reasonably sized
Use comprehensions for simple cases
Prefer implicit false in boolean contexts
Use f-strings for formatting
Always use context managers for resources
Run pylint and fix issues
BE CONSISTENT with existing code

Additional Resources

For detailed reference on specific topics, see:

references/advanced_types.md - Advanced type annotation patterns including Protocol, TypedDict, Literal, ParamSpec, and more
references/antipatterns.md - Common Python mistakes and their fixes
references/docstring_examples.md - Comprehensive docstring examples for all Python constructs

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Python Style Guide

Core Philosophy

Language Rules

Imports

Import Formatting

Exceptions

Type Annotations

Default Argument Values

True/False Evaluations

Comprehensions & Generators

Lambda Functions

Style Rules

Line Length

Indentation

Blank Lines

Naming Conventions

Comments and Docstrings

Docstring Format

Block and Inline Comments

Strings

Logging

Files and Resources

Statements

Main

Function Length

Type Annotation Details

Forward Declarations

Type Aliases

TypeVars

Generics

Imports for Typing

Common Patterns

Properties

Conditional Expressions

Context Managers

Linting

Summary

Additional Resources