Match Case Statement in Python

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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})")

Learn Python

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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)...

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