---

What’s Pattern Matching Again?

Pattern Matching (introduced in Python 3.10) lets you match data structures by their shape and content, kind of like switch-case but more powerful.

Example:

def handle(data):
    match data:
        case {"status": 200, "msg": msg}:
            print("Success:", msg)
        case {"status": 404}:
            print("Not Found")
        case _:
            print("Unknown")

handle({"status": 200, "msg": "OK"})

Output:

Success: OK

---

Now What’s New in Python 3.14?

In Python 3.14, guard expressions become more flexible and readable.
Guards allow you to add conditions to patterns —
you can say: “Match this pattern only if a certain condition holds true.”

It’s like combining pattern matching with an if statement — but smarter and cleaner.

---

Example:

def check_number(data):
    match data:
        case {"value": v} if v > 0:
            print("Positive number")
        case {"value": v} if v < 0:
            print("Negative number")
        case {"value": 0}:
            print("Zero")
        case _:
            print("Invalid input")

check_number({"value": 10})

Output:

Positive number

---

Analogy:

Imagine you’re sorting letters –
You don’t just check who it’s addressed to (the pattern),
you also check if it’s urgent or normal (the guard condition).

So you might say:

“If it’s for Alex and it says URGENT – handle immediately.”
“If it’s for Alex but not urgent – handle later.”

That’s what guard expressions do –
they add an extra filter to your matching logic.

---

Why It’s Useful

• Makes code cleaner and more expressive.
• Reduces nested if statements.
• Improves readability in complex decision logic.
• Enables smarter pattern-based data handling.

---

In short:

Python’s pattern matching was already like a smart filter.
Now with guard expressions, it’s like adding custom rules on top of that filter – precise, elegant, and readable.

---

Article written by Harshil Bansal, Team edSlash.