Skip to main content

Match Case Statement in Python

 


Learning Sections     show

Match-Case Statements

In Python 3.10 and later, the match-case statement was introduced as a way to perform pattern matching, similar to switch-case statements in other programming languages. It allows you to check the value of a variable against multiple patterns and execute corresponding blocks of code.

Basic Match-Case Statement

The match statement is followed by an expression and several case clauses. Each case specifies a pattern and an action to be taken if the pattern matches the value of the expression.


# Basic match-case statement example
command = "start"

match command:
    case "start":
        print("Starting...")
    case "stop":
        print("Stopping...")
    case "pause":
        print("Pausing...")
    case _:
        print("Unknown command")

Matching Multiple Patterns

Using the pipe symbol |, you can match multiple patterns in a single case clause.


# Matching multiple patterns example
status = "open"

match status:
    case "open" | "opened":
        print("The status is open.")
    case "closed" | "shut":
        print("The status is closed.")
    case _:
        print("Unknown status")

Using Guards in Case Clauses

Guards allow you to add additional conditions to a case clause using the if keyword.


# Using guards in case clauses example
number = 42

match number:
    case x if x >> 0:
        print("The number is positive")
    case x if x == 0:
        print("The number is zero")
    case x if x < 0:
        print("The number is negative")

Pattern Matching with Data Structures

The match-case statement can also be used to match patterns in data structures like lists and tuples.


# Pattern matching with lists example
data = [1, 2, 3]

match data:
    case [1, 2, 3]:
        print("Matched [1, 2, 3]")
    case [4, 5, 6]:
        print("Matched [4, 5, 6]")
    case _:
        print("No match")
    

# Pattern matching with tuples example
point = (4, 5)

match point:
    case (0, 0):
        print("The point is at the origin")
    case (x, y):
        print(f"The point is at ({x}, {y})")
Labels:

Popular posts from this blog

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 ...
Read more

Classes and Objects in Python

  Learning Sections          show Classes and Objects in Python In Python, a class is a blueprint for creating objects. An object is an instance of a class. Classes allow you to logically group data and functions in a way that is easy to manage and reuse. 1. Defining a Class To define a class in Python, you use the class keyword followed by the class name and a colon. Inside the class, you can define attributes and methods. Example: # Define a class class Person : # Class attribute species = 'Human' # Class method def greet ( self ): return 'Hello, I am a person.' # Create an object of the class person1 = Person () # Access class attribute print ( person1 . species ) # Output: Human # Call class method print ( person1 . greet ()) # Output: Hello, I am a person. 2. Creating Objects To create an object of a class, you simply call the class name followed by paren...
Read more

Exception Handling in Python

  Learning sections          show Exception Handling in Python Exception handling in Python is done through the use of try , except , else , and finally blocks. This allows you to catch and handle errors gracefully. Below are some examples and explanations: 1. Basic Try-Except The try block lets you test a block of code for errors. The except block lets you handle the error. # Example of basic try-except try : result = 10 / 0 except ZeroDivisionError : print ( "Cannot divide by zero!" ) # Output: # Cannot divide by zero! 2. Handling Multiple Exceptions You can catch multiple exceptions by specifying multiple except blocks. # Example of handling multiple exceptions try : result = 10 / 0 except ZeroDivisionError : print ( "Cannot divide by zero!" ) except TypeError : print ( "Invalid operation!" ) # Output: # Cannot divide by zero! 3. Using Else The e...
Read more