Specific use of match in Python

Introduced in Python 3.10, amatchstatements, which are similar to those in other languages (eg: C, JAVA).switchmaybecasestatements, but more powerful. Here's an example of a statement that uses Python 3.10'smatchExample of a statement:

def http_error(status):
    match status:
        case 400:
            return "Bad request"
        case 401 | 403 | 404:
            return "Not allowed"
        case 500:
            return "Server error"
        case _:
            return "Something's wrong with the internet"

print(http_error(400))  # Output: Bad request
print(http_error(401))  # Output: Not allowed
print(http_error(500))  # Output: Server error
print(http_error(600))  # exports: Something's wrong with the internet

In this example, thematchstatement willstatusparameter is compared to a series of patterns. These modes can be single values such as400maybe500, or a combination of values such as401 | 403 | 404. If there is no match, it will match to the wildcard character_。

In addition.matchIt can also be used for data structure deconstruction:

# Suppose we have a list of elements of different types
def handle_items(items):
    match items:
        case []:
            print("No items.")
        case [first]:
            print(f"One item: {first}")
        case [first, second]:
            print(f"Two items: {first} and {second}")
        case [first, *rest]:
            print(f"First item: {first}, rest: {rest}")

handle_items([])              # Output: No items.
handle_items(["apple"])       # Output: One item: apple
handle_items(["apple", "banana"]) # exports: Two items: apple and banana
handle_items(["apple", "banana", "cherry"]) # Output: First item: apple, rest: ['banana', 'cherry']

In this example, thematchstatement checkingitemslist, different blocks of code are selected for execution depending on the length and content of the list.

matchAllows developers to write cleaner, more readable code that maps directly to data structures and conditions. This makes dealing with complex data structures, such as nested JSON or complex class instances, more intuitive and safer.

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