Skip to main content

Function Arguments in Python

 

Learning Sections     show

Function Arguments in Python

In Python, functions can accept arguments to pass data and variables. Understanding different types of function arguments helps write more flexible and powerful functions. There are several types of arguments that can be used in Python functions:

1. Positional Arguments

Positional arguments are the most common type of arguments in Python. The order in which the arguments are passed matters.

# Function with positional arguments
def add(a, b):
    return a + b

# Calling the function
result = add(5, 3)
print(result)  # Output: 8
    

2. Keyword Arguments

Keyword arguments are passed by explicitly stating the parameter name and value. This allows for arguments to be passed in any order.

# Function with keyword arguments
def greet(name, message):
    print(message + ", " + name + "!")

# Calling the function
greet(message="Good morning", name="Bob")  # Output: Good morning, Bob!
    

3. Default Arguments

Default arguments allow parameters to have a default value if no value is provided during the function call.

# Function with default arguments
def greet(name, message = "Hello"):
    print(message + ", " + name + "!")

# Calling the function
greet("Alice")  # Output: Hello, Alice!
greet("Bob", "Good morning")  # Output: Good morning, Bob!
    

4. Variable-Length Arguments

Python allows functions to accept variable-length arguments using *args for non-keyword arguments and **kwargs for keyword arguments.

# Function with *args
def sum_all(*args):
    total = 0
    for num in args:
        total += num
    return total

# Calling the function
result = sum_all(1, 2, 3, 4)
print(result)  # Output: 10
    

# Function with **kwargs
def print_info(**kwargs):
    for key, value in kwargs.items():
        print(f"{key}: {value}")

# Calling the function
print_info(name="Alice", age=25, city="Wonderland")
    

5. Keyword-Only Arguments

Keyword-only arguments are specified after a single asterisk * in the function definition. These arguments can only be passed using their keyword.

# Function with keyword-only arguments
def greet(name, *, message = "Hello"):
    print(message + ", " + name + "!")

# Calling the function
greet("Alice")  # Output: Hello, Alice!
greet("Bob", message = "Good evening")  # Output: Good evening, Bob!
    

6. Positional-Only Arguments

Positional-only arguments are specified before a single forward slash / in the function definition. These arguments can only be passed by position.

# Function with positional-only arguments
def subtract(a, b, /):
    return a - b

# Calling the function
result = subtract(10, 3)
print(result)  # Output: 7
    

7. Combining Argument Types

Different types of arguments can be combined in a single function definition. The order should be: positional-only arguments, positional arguments, *args, keyword-only arguments, and **kwargs.

# Combining different types of arguments
def combined_example(a, b, /, *, c, **kwargs):
    print(f"a: {a}, b: {b}, c: {c}")
    for key, value in kwargs.items():
        print(f"{key}: {value}")

# Calling the function
combined_example(1, 2, c = 3, d = 4, e = 5)
    

Popular posts from this blog

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...

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 (...

Conclusion and where to go after this

  Conclusion and Where to Go After This Congratulations on completing your Python learning journey! You've covered a wide array of topics, from the basics of syntax and data types to advanced concepts like multithreading, multiprocessing, and decorators. But learning doesn't stop here. Python is a versatile language with many specialized fields where you can apply your skills. Here are some potential paths you can explore next: Machine Learning Machine Learning (ML) is one of the most exciting fields you can dive into. Python's libraries like TensorFlow, Keras, scikit-learn, and PyTorch make it an ideal language for building ML models. You'll learn about supervised and unsupervised learning, deep learning, neural networks, and more. Start with the basics of linear regression and classification, then move on to more complex models like convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Data Structures and Algorithms (DSA)...