--- name: python-style-guide description: Comprehensive Python programming guidelines based on Google's Python Style Guide. Use when Claude needs to write Python code, review Python code for style issues, refactor Python code, or provide Python programming guidance. Covers language rules (imports, exceptions, type annotations), style rules (naming conventions, formatting, docstrings), and best practices for clean, maintainable Python code. license: Complete terms in LICENSE.txt --- # Python Style Guide Comprehensive guidelines for writing clean, maintainable Python code based on [Google's Python Style Guide](https://google.github.io/styleguide/pyguide.html). ## 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: 1. Use type annotations for all functions 2. Follow naming conventions consistently 3. Write clear docstrings for all public APIs 4. Keep functions focused and reasonably sized 5. Use comprehensions for simple cases 6. Prefer implicit false in boolean contexts 7. Use f-strings for formatting 8. Always use context managers for resources 9. Run pylint and fix issues 10. **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