What should be included in a **Python module docstring**?

General Discussions
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1

What should be included in a Python module docstring?

I’ve read both PEP 8 and PEP 257, and I’ve written plenty of docstrings for functions and classes, but I’m still a bit unsure about what should go into a module docstring.

I assume, at the very least, it should document the functions and classes exported by the module, but I’ve also noticed some modules include author names, copyright information, and other details. Could anyone provide an example of how a well-structured Python module docstring should look?

2

Python’s approach to function parameter types is incredibly flexible due to its dynamic nature. Unlike statically typed languages, you don’t need to declare parameter types explicitly. You can pass any type of argument to a function, and Python will determine how to handle it at runtime.

For instance:

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

print(greet("Alice"))  # Works with a string
print(greet(42))       # Also works with an integer

This flexibility makes Python great for rapid development but can occasionally lead to unexpected behavior if you’re not careful.

3

Building on Joe’s point, while Python doesn’t enforce parameter types, you can improve code clarity and catch potential errors early by using type hints. Introduced in Python 3.5, type hints allow you to specify the expected types of function parameters and return values.

Here’s how it works:

def greet(name: str) -> str:
    return f"Hello, {name}!"

print(greet("Alice"))  # Works fine
# print(greet(42))     # Will still run but may not make sense logically

Though type hints are optional and not enforced at runtime, tools like mypy can analyze your code statically to ensure type consistency.

4

Rima brings up a great point about type hints. To take it further, Python’s standard library includes the typing module, which provides advanced type hinting capabilities like Union, Optional, and Callable. These allow you to handle more complex scenarios elegantly.

For example:

from typing import Union

def process_data(data: Union[int, str]) -> str:
    if isinstance(data, int):
        return f"Processed number: {data}"
    elif isinstance(data, str):
        return f"Processed text: {data}"

print(process_data(42))    # "Processed number: 42"
print(process_data("hi"))  # "Processed text: hi"

Using such features helps make your code more robust and developer-friendly, especially in larger projects. This balance between Python’s flexibility and optional type safety is one of the reasons it’s so widely loved.