There is a reason Python’s popularity has spread far and wide in the current tech landscape. Among modern programming languages, it is perhaps the most accessible for novices. And with that accessibility, it also offers plenty of power. Web development, data science, scientific computing — you can accomplish many a task with Python.
As Python has advanced over the years, its developers have put great amounts of effort into maintaining its readability and conciseness. Though many of its features may require a bit of extra effort to learn, the return on clarity and beauty in your code is beyond worth it.
In this article, we’ll look at two such features: match statements and string/list slicing. We’ll go over how each one works in detail, as well as consider some examples to build familiarity with the syntax and semantics.
Now then, let’s get into it.
Match Statements
Match statements — available in Python as of version 3.10 — are a way of checking equality of conditions and performing some action based on the conditions [1]. If you are coming from another language such as C or JavaScript, you might already be familiar with the concept as switch statements.
In principle, match statements are similar to conditional statements, but they do provide a couple of useful advantages. Let’s start by looking at the basic structure via a comparison with conditionals; then, we’ll talk about the advantages.
You might write the following conditional statement to check someone’s name for a bank account:
name = "Yen"if name == "Yen":
print("This is your account.")
elif name == "Ben":
print("This is your sister's account.")
else:
print("Fraud attempt.")
Translated to a match statement, this would look like the following:
name = "Yen"match name:
case "Yen":
print("This is your account.")
case "Ben":
print("This is your sister's account.")
case _:
print("Fraud…
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