python-style-guide

What this skill does

# 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 in application code to avoid circular dependencies. For standard library and third-party packages, importing classes is acceptable.

**Yes:**
```python
from pydantic import BaseModel  # Third-party: Class import OK
from pathlib import Path        # Stdlib: Class import OK
import sound_effects.utils      # App: Module import
from myproject import config    # App: Module import
```

**No:**
```python
from myproject.utils import heavy_function  # App: Avoid direct function import if circular dep risk
```

#### 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: 88 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 **Loguru** for logging with brace-style lazy formatting:

```python
logger.info("Request from {} resulted in {}", ip_address, status_code)
```

**Avoid** standard `logging` with `%` formatting.

### Files and Resources

For simple text operations, prefer `pathlib` methods:

```python
data = Path("file.txt").read_text()
Path("output.txt").write_text("content")
```

For complex operations or non-text files, use context managers:

```python
with open("image.png", "rb") 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