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

Labels

Labels:

Popular posts from this blog

MultiProcessing in Python

  Learning Sections          show MultiProcessing in Python Multiprocessing in Python involves using the multiprocessing module to run multiple processes concurrently, taking advantage of multiple CPU cores. This module provides a higher level of concurrency than threading and is especially useful for CPU-bound tasks. Creating Processes You can create and start a new process by using the multiprocessing module: import multiprocessing def print_numbers (): for i in range ( 10 ): print ( i ) p1 = multiprocessing.Process ( target = print_numbers ) p1 . start () p1 . join () # Wait for the process to complete Using Process Pools The multiprocessing module provides a Pool class, which allows you to manage a pool of worker processes: from multiprocessing import Pool def square ( n ): return n * n with Pool ( 4 ) as pool : result = pool.map ( square , range (...
Read more

Learn Python

  Learning Sections Introduction to Python Comment, escape sequence and print statement in Python Variables and Data Types in Python Typecasting in Python User input in Python String slicing and operations on string in Python String methods in Python If else conditional statements in Python Match case statement in Python For loops in Python While loops in Python Break and continue statement in Python Functions in Python Function Arguments in Python introduction to lists in Python List methods in Python Tuples in Python Operations on tuple in Python f strings in Python Docstrings in Python Recursion in Python Sets in Python Set methods in Python Dictionaries in Python for Loop with else in Python Exception Handling in Python Finally keyword in Python Raising custom errors in Python Short hand if else statements Enumerate Function in Python Virtual Environment in Python How import works in Python if __nam...
Read more

Introduction to Python Programming

  Learning Sections      show History of Python Python was created by Guido van Rossum and first released in 1991. He wanted to create a language that was easy to read and simple to use. The name "Python" comes from the British comedy series "Monty Python's Flying Circus". Key Features of Python Readability: Python's syntax is clear and easy to read. Ease of Learning: Python is straightforward, making it great for beginners. High-Level Language: Python handles much of the complexity of the computer’s operations. Interpreted Language: Python runs code line-by-line, which makes debugging easier. Dynamically Typed: You don’t need to declare variable types. Extensive Standard Library: Python has many built-in modules for various tasks. Portability: ...
Read more