Python 3.8’s New Features and Improvements

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In Python 3.10, structural pattern matching is a new feature that allows for more concise and expressive code when working with complex data structures. Here are some examples:

Example 1: Matching a tuple with specific values
Suppose you have a function that takes in a list of tuples representing coordinates on a map, and you want to extract the x-coordinate from each tuple. With structural pattern matching, this can be done using the following code:

# Defining a function named "get_x" that takes in a tuple named "point" as a parameter
def get_x(point):
    # Using structural pattern matching to match the tuple "point" with the following case
    # The case specifies that the tuple should have two values, "x" and "y"
    match point:
        case (x, y):
            # Returning the value of "x" from the matched tuple
            return x

In this example, we’re using a `match` statement to check if the input tuple matches a specific pattern. If it does, we extract the first element of that tuple and return it as the result.

Example 2: Matching a list with specific elements
Suppose you have a function that takes in a list representing a set of numbers, and you want to find out if any of those numbers are greater than 10. With structural pattern matching, this can be done using the following code:

# This function checks if any number in a given list is greater than 10
def has_greater_than_ten(numbers):
    # Using structural pattern matching to match the given list
    match numbers:
        # If the list contains only one element and it is greater than 10, return True
        case [x] if x > 10:
            return True
        # If the list contains more than one element and any of them is greater than 10, return True
        case _ when len(_) > 1 and any(n > 10 for n in _):
            return True
        # If none of the above cases match, return False
        case _:
            return False

In this example, we’re using a `match` statement to check if the input list matches one of two specific patterns. If it does, we perform some logic based on that pattern and return the result as appropriate.

Example 3: Matching a dictionary with specific keys
Suppose you have a function that takes in a dictionary representing user preferences, and you want to extract the value associated with a specific key. With structural pattern matching, this can be done using the following code:

# This function takes in a dictionary representing user preferences and returns the value associated with a specific key.
def get_preference(user):
    # Using structural pattern matching to match the value of 'type' key in the user dictionary.
    match user['type']:
        # If the value of 'type' key is 'basic', return the value associated with the 'color' key.
        case 'basic':
            return user['color']
        # If the value of 'type' key is not 'basic', raise a ValueError.
        case _:
            raise ValueError("Invalid preference type")

In this example, we’re using a `match` statement to check if the input dictionary matches one of two specific patterns. If it does, we extract the value associated with that pattern and return it as appropriate.

These are just a few examples of how structural pattern matching can be used in Python 3.10. With this new feature, you can write more concise and expressive code when working with complex data structures.

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