7 Underrated Python Features That’ll Blow Your Mind 🤯

You’ve probably used Python for years — but I bet you’re not using at least 3 of these powerful features.

7 Underrated Python Features That’ll Blow Your Mind 🤯

Python is a beautiful language — simple, expressive, and powerful. But even if you’ve been using it for years, there’s a good chance you’ve overlooked some of its most delightful features.

We all know the classics: list comprehensions, decorators, f-strings… but what about the hidden gems? The little-known features that can make your code cleaner, faster, and more Pythonic?

Let’s dive into 7 underrated Python features that’ll make you go: “Wait… Python can do that?!”

1. The else Clause on Loops

Most people know else as a buddy to if. But in Python, both for and while loops can also have an else clause.

for item in my_list: 
    if item == target: 
        print("Found!") 
        break 
else: 
    print("Not found.")

The else runs only if the loop wasn’t broken. It’s perfect for search loops or retry mechanisms. Clean, expressive, and rarely used.

2. The __missing__ Method in Dict Subclasses

Ever wanted more control over default dictionary behavior?

Instead of using defaultdict, subclass dict and define a __missing__ method:

class MagicDict(dict): 
    def __missing__(self, key): 
        return f"{key} is not here, try again." 
 
d = MagicDict({"a": 1}) 
print(d["b"])  # 'b is not here, try again.'

You now have full control over what happens when a key is missing — great for DSLs, templates, or fallback logic.

3. Tuple Unpacking in Function Arguments

You probably use tuple unpacking like this:

a, b = (1, 2)

But did you know you can unpack directly in function arguments?

def greet(name, age): 
    print(f"{name} is {age} years old.") 
 
person = ("Alice", 30) 
greet(*person)

It also works with dictionaries:

def greet(name, age): 
    print(f"{name} is {age} years old.") 
 
info = {"name": "Bob", "age": 40} 
greet(**info)

It’s a cleaner way to pass around structured data.

4. The Underscore _ as a Throwaway or Last Expression

Python treats _ in cool ways:

1. Ignore values:

name, _, age = ("Alice", "unused", 25)

2. Last expression result in REPL:

>>> 5 + 3 
8 
>>> _ * 2 
16

This little guy has multiple personalities depending on context.

Very useful in interactive work or destructuring.

5. Function Argument Annotations (Without Enforcing Types)

Python doesn’t enforce type hints, but they serve as excellent documentation tools:

def send_email(to: str, subject: str, retries: int = 3) -> bool: 
    ...

This tells you (and tools like mypy or your IDE) what’s expected — without changing runtime behavior.

Bonus: Use __annotations__ to inspect them:

print(send_email.__annotations__)

Clean, readable, and great for collaboration.

6. The timeit Module for Quick Performance Tests

You don’t need to write custom timers to compare functions. Just use the built-in timeit.

import timeit 
 
time_taken = timeit.timeit("sum(range(1000))", number=1000) 
print(time_taken)

Want to test snippets directly in your terminal or notebook? Use the command line:

python -m timeit "sum(range(1000))"

Speed matters. Python makes it easy to measure.

7. The contextlib Module — Beyond Just with open()

You use with for files, but contextlib lets you create custom context managers:

from contextlib import contextmanager 
 
@contextmanager 
def quiet_mode(): 
    print("Shhh... entering quiet mode") 
    yield 
    print("Back to normal noise levels.") 
 
with quiet_mode(): 
    print("Nothing to see here...")

This is perfect for setup/teardown logic, mocking, logging, and even temporary state changes.

Bonus: no need to create a class — just a generator!

Final Thoughts

Python is packed with little treasures — features that don’t always make the headlines but can seriously level up your coding game.

To recap:

else on loops

__missing__ for smarter dicts

Tuple/dict unpacking in function calls

Versatile _

Argument annotations

timeit for fast benchmarking

contextlib for custom with blocks

Which one blew your mind the most? Or did I miss your favorite Python gem?

Let’s geek out in the comments.

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