Skip to main content

Docstrings in Python

Learning Sections          show

Docstrings in Python

Docstrings in Python are string literals that appear right after the definition of a function, method, class, or module. They are used to document the functionality of the code.


Single-Line Docstrings

Single-line docstrings are used for very short descriptions. They fit on one line.

"""This is a single-line docstring."""
# Example of a single-line docstring in a function
def add(a, b):
    """Returns the sum of a and b."""
    return a + b

Multi-Line Docstrings

Multi-line docstrings are used for more detailed documentation. They can span multiple lines.

"""This is a multi-line docstring.
It can span multiple lines.
It provides a detailed description of the function, method, class, or module."""
# Example of a multi-line docstring in a function
def subtract(a, b):
    """Return the difference of a and b.

    Parameters:
    a (int or float): The minuend.
    b (int or float): The subtrahend.

    Returns:
    int or float: The difference between a and b.
    """
    return a - b

Accessing Docstrings

Docstrings can be accessed using the __doc__ attribute.

# Accessing docstrings
def multiply(a, b):
    """Return the product of a and b."""
    return a * b

print(multiply.__doc__)  # Output: Return the product of a and b.

Docstrings for Classes

Docstrings can also be used to document classes and their methods.

# Example of docstrings in a class
class MathOperations:
    """Class for various math operations."""
    
    def __init__(self, value):
        """Initialize with a value."""
        self.value = value
    
    def add_to_value(self, addend):
        """Add addend to value and return the result."""
        return self.value + addend

Popular posts from this blog

Inheritance in Python

  Learning Sections          show Inheritance in Python Inheritance is a fundamental concept in object-oriented programming (OOP) that allows a class to inherit attributes and methods from another class. The class that inherits is called the child class or subclass, and the class being inherited from is called the parent class or superclass. Basic Inheritance In Python, a child class inherits from a parent class by specifying the parent class in parentheses after the child class name. Example: class Animal : def __init__ ( self , name ): self . name = name def speak ( self ): raise NotImplementedError ( "Subclass must implement this method" ) class Dog ( Animal ): def speak ( self ): return "Woof!" class Cat ( Animal ): def speak ( self ): return "Meow!" # Create instances of Dog and Cat dog = Dog ( "Buddy" ) cat = Cat ( "Whiskers" ...

Introduction to OOPs in Python

  Learning Sections          show Introduction to Object-Oriented Programming (OOP) Object-Oriented Programming (OOP) is a programming paradigm that organizes software design around objects rather than actions and data rather than logic. It revolves around the concept of "objects", which are instances of classes. These objects encapsulate data, in the form of attributes or properties, and behaviors, in the form of methods or functions. OOP promotes modularity, reusability, and extensibility in software development. Key Concepts of OOP: Class: A class is a blueprint or template for creating objects. It defines the attributes (data) and methods (functions) that will characterize any object instantiated from that class. Object: An object is an instance of a class. It is a concrete realization of the class blueprint, containing actual values instead of placeholders for attributes. Encapsulation: Encapsulation is ...

Generators in Python

  Learning Sections          show Generators in Python Generators are a special type of iterator in Python that allow you to iterate over a sequence of items without storing them all in memory at once. They are useful for generating large sequences of data on-the-fly, or for processing data in a memory-efficient manner. Creating Generators In Python, generators are created using generator functions or generator expressions: # Generator function def my_generator ( n ): for i in range ( n ): yield i # Generator expression my_generator = ( i for i in range ( 10 )) A generator function uses the yield keyword to yield values one at a time, while a generator expression creates an anonymous generator. Iterating Over Generators You can iterate over the values produced by a generator using a for loop: for value in my_generator ( 5 ): print ( value ) This w...