Code Style¶

Respect the project code style.
A summary of the project code style is:
- Spacing: Use spaces between identifiers and other tokens. Modern writing systems use this convention, which emerged around the 7th century of the Common Era, to improve readability. Computer code can generally be written this way too… also to improve readability.
- Line Width: Follow PEP 8 on this: no more than 79 columns for code lines. Consider how long lines affect display on laptops or side-by-side code panes with enlarged font sizes. (Enlarged font sizes are used to reduce eye strain and allow people to code without visual correction.)
- Vertical Compactness: Function definitions, loop bodies, and condition bodies, which consist of a single statement and which are sufficiently short, should be placed on the same line as the statement that introduces the body. Blank lines should not be used to group statements within a function body. If you need to group statements within a function body, then perhaps the function should be refactored. Function bodies should not be longer than thirty lines. I.e., one should not have to scroll to read a function.
Pull requests, which attempt to enforce the Python black style or any style other than the project code style, will be rejected.

Todo

Rust Guidance

Specific Preferences¶

Collections¶

For short collections, keep them on one line:

points = [ ( 1, 2 ), ( 3, 4 ), ( 5, 6 ) ]

config = { 'name': 'example', 'value': 42 }

For longer collections, split elements across lines:

matrix = [
    [ 1, 2, 3, 4 ],
    [ 5, 6, 7, 8 ],
    [ 9, 10, 11, 12 ],
]

settings = {
    'name': 'example',
    'description': 'A longer example that needs multiple lines',
    'values': [ 1, 2, 3, 4, 5 ],
    'nested': {
        'key1': 'value1',
        'key2': 'value2',
    },
}

Class and Function Definitions¶

Keep all arguments on one line if they fit within the line limit:

def simple_function( arg1: int, arg2: str = 'default' ) -> bool:
    return True

When arguments must be split across lines, prefer to group positional and nominative arguments:

def medium_function(
    first_pos, second_pos, third_pos,
    first_named = 'default', second_named = 'other'
) -> None: pass

When grouping would overflow a line, place each argument on its own line:

def complex_function(
    first_very_long_positional_argument: dict,
    second_very_long_positional_argument: list,
    first_named_arg = 'some very long default value',
    second_named_arg = 'another long default value',
) -> None: pass

For single-line function bodies, especially pass, keep them on the same line as the definition when possible:

def simple_operation( value: int ) -> int: return value * 2

def stub_function( data: bytes ) -> None: pass

Imports¶

Prefer function-level imports over module-level imports to prevent module namespace pollution and make functions more relocatable:

def process_data( raw_data: bytes ) -> dict:
    from collections import defaultdict
    from itertools import groupby
    from .utils import decode_packet
    # Function implementation...

When imports must appear at the module level, follow the grouping conventions from PEP 8:

from __future__ import annotations

import collections.abc as cabc
import types
from dataclasses import dataclass
from typing import Optional

import typing_extensions as typx
from third_party import ThirdPartyClass

from .submodule import LocalClass

For multi-line imports, use parentheses with hanging indent. Add a trailing comma to force one-per-line format for very long import lists:

from third_party.submodule import (
    FirstClass, SecondClass, ThirdClass )

from third_party.other import (
    ALongClassName,
    AnotherLongClassName,
    YetAnotherLongClassName,
)

Line Continuation¶

Use parentheses for line continuation. Split at natural points such as dots, operators, or after commas. Keep the closing parenthesis on the same line as the last element unless the collection has a trailing comma:

# Dot operator splits
result = (
    very_long_object_name.first_method_call( )
    .second_method_call( )
    .final_method_call( ) )

# Operator splits
total = (
    first_long_value * second_long_value
    + third_long_value * fourth_long_value )

# Array subscript splits
element = (
    very_long_array_name[ first_complex_index ]
    [ second_complex_index ]
    [ 'nested_key' ] )

# List/dict comprehension splits
squares = [
    value * value
    for value in range( 100 )
    if is_valid( value ) ]

# Multi-line conditional statements
if (
    validate_input( data, strict = True )
    and process_ready( )
): process( data )

Single-Line Statements¶

Keep simple control flow statements on one line when they contain a single simple action:

if not data: return None
while more_items: process_next( )
try: value = next( iterator )
except StopIteration: return

for item in items: yield item
with lock: do_work( )

Similarly, keep simple class and function definitions on one line when their body consists only of pass:

class EmptyMixin: pass

def not_implemented_yet( data: bytes ) -> None: pass

However, if the definition includes type annotations or multiple base classes that would make the line too long, use normal multi-line formatting:

class SimpleContainer(
    Generic[ _T ],
    cabc.Collection,
    metaclass = ImmutableClass
): pass

Strings¶

Use single quotes for string literals unless using f-strings, .format( ) method, or exception and logging messages:

name = 'example'
path = 'C:\\Program Files\\Example'

message = f"Processing {name} at {path}"
formatted = "Value: {:.2f}".format( value )

raise ValueError( "Invalid configuration value" )
logger.error( "Failed to process item" )

Automation¶

The project includes configurations for isort and yapf in pyproject.toml. While these tools help maintain consistent formatting, they do not perfectly match all style guidelines. In cases where automatic formatting produces suboptimal results, manual formatting according to this guide takes precedence.

Cases where manual intervention may be needed:

Complex function definitions with mixed positional and nominative arguments
Multi-line method chains
Nested data structures with mixed single-line and multi-line sections

When in doubt, optimize for readability while staying within the general principles outlined in this guide.