Docstring Delight: Documenting Your Python Functions

Python's readability is one of its greatest strengths, and docstrings are a crucial part of that. Docstrings are string literals that appear as the first statement in a module, function, class, or method definition. They serve as documentation for your code, explaining what it does, its parameters, and what it returns. This challenge will test your understanding and implementation of well-formed docstrings.

Problem Description

Your task is to implement docstrings for a given set of Python functions. You should adhere to standard Python docstring conventions, specifically focusing on the NumPy/SciPy style or Google style, which are widely adopted and understood by documentation generators like Sphinx.

What needs to be achieved: For each provided function, you must write a docstring that clearly and comprehensively explains:

1. The purpose of the function.
2. The parameters the function accepts (their names, types, and descriptions).
3. What the function returns (its type and description).
4. Any exceptions the function might raise (though for this challenge, we will assume no explicit exception handling is required, focus on documenting potential raises if applicable to the function's logic).

Key requirements:

• Docstrings must be enclosed in triple quotes ("""Docstring goes here""").
• The first line of the docstring should be a concise summary of the function's purpose.
• A blank line should separate the summary line from the rest of the docstring.
• Use appropriate sections for Parameters, Returns, and potentially Raises (if relevant to the function's behavior).
• Clearly indicate the expected type of parameters and return values.

Expected behavior: When a user inspects the function using help(function_name) or by accessing the __doc__ attribute, they should see a well-formatted and informative docstring.

Examples

Example 1: Function definition:

def add_numbers(a, b):
    return a + b

Your implemented docstring should look like:

def add_numbers(a, b):
    """Adds two numbers together.

    Args:
        a (int or float): The first number.
        b (int or float): The second number.

    Returns:
        int or float: The sum of a and b.
    """
    return a + b

Explanation: The docstring clearly states the function's purpose, lists the two parameters with their expected types and descriptions, and describes what the function returns.

Example 2: Function definition:

def greet(name, greeting="Hello"):
    return f"{greeting}, {name}!"

Your implemented docstring should look like:

def greet(name, greeting="Hello"):
    """Generates a personalized greeting.

    Args:
        name (str): The name of the person to greet.
        greeting (str, optional): The greeting phrase to use. Defaults to "Hello".

    Returns:
        str: The complete greeting string.
    """
    return f"{greeting}, {name}!"

Explanation: This docstring handles an optional parameter with a default value, clearly indicating its optional nature and default.

Example 3: Function definition:

def calculate_average(numbers):
    if not numbers:
        return 0.0
    return sum(numbers) / len(numbers)

Your implemented docstring should look like:

def calculate_average(numbers):
    """Calculates the average of a list of numbers.

    If the input list is empty, it returns 0.0.

    Args:
        numbers (list[int or float]): A list of numbers for which to calculate the average.

    Returns:
        float: The average of the numbers in the list, or 0.0 if the list is empty.
    """
    if not numbers:
        return 0.0
    return sum(numbers) / len(numbers)

Explanation: This example demonstrates documenting behavior for an edge case (empty list) and specifying the type for a list containing numeric types.

Constraints

• You will be provided with Python function definitions.
• You must implement docstrings for each of these functions.
• Focus on clarity, completeness, and adherence to standard docstring formatting (e.g., Google or NumPy/SciPy style).
• Do not add any new functionality to the provided functions. Your task is solely documentation.

Notes

• Consider using the Google or NumPy/SciPy style for your docstrings. Both are widely recognized and excellent choices.
• Think about how a new developer would understand what your function does just by reading its docstring.
• Pay attention to parameter types, especially when dealing with collections like lists or when a function can accept multiple types.
• Clearly state any default values for optional parameters.
• The goal is to produce high-quality, readable documentation.