5 Unique Python Functions You Probably Haven’t Used (But Should)

Python has some hidden gems — functions that quietly solve big problems but often go unnoticed.

5 Unique Python Functions You Probably Haven’t Used (But Should)

These 5 built-in or standard library functions aren’t commonly used, but they’ve saved me time, simplified logic, and made my code more elegant.

Python is famous for its simplicity, readability, and vast standard library. Most developers stick to the usual suspects like print(), len(), or map().

But dig a little deeper, and you'll find a treasure trove of lesser-known Python functions that can simplify your code and make you look like a wizard in code reviews.

Here are 5 unique Python functions that you probably haven’t used — but absolutely should.

1. any() — Elegance in Simplicity

Let’s say you want to check if at least one item in a list meets a condition. You could write a loop with flags, or you could just use any().

scores = [0, 0, 42, 0] 
if any(score > 0 for score in scores): 
    print("There's at least one non-zero score.")

It’s concise, readable, and expressive.

Works with generators — so it’s memory efficient for large datasets.

2. enumerate() — The Smarter Loop

Tired of maintaining a manual counter in for loops? Enter enumerate().

names = ["Alice", "Bob", "Charlie"] 
for index, name in enumerate(names, start=1): 
    print(f"{index}. {name}")

It Keeps your code clean and Pythonic.

You can even set a custom start index (e.g., start=1 for 1-based indexing).

3. getattr() — Dynamic Attribute Access

Want to access an object’s attribute by name (as a string)? Use getattr().

class Person: 
    def __init__(self, name): 
        self.name = name 
 
p = Person("Aashish") 
attr = "name" 
print(getattr(p, attr))  # Output: Aashish

Perfect for meta-programming and dynamic attribute access.

Avoids if/else clutter when you’re unsure which attribute will be accessed.

4. zip() — Parallel Iteration Made Easy

zip() is your best friend when working with two or more sequences in parallel.

questions = ["Name?", "Age?", "Country?"] 
answers = ["Alice", "25", "Canada"] 
 
for q, a in zip(questions, answers): 
    print(f"{q} {a}")

It Makes parallel iteration elegant.

Stops at the shortest iterable by default (use itertools.zip_longest if you want more control).

5. callable() — Check If Something Can Be Called

This one’s often overlooked but incredibly useful when working with dynamically loaded objects or plugins.

def greet(): 
    return "Hello" 
 
print(callable(greet))  # True 
print(callable("Hello"))  # False

Helps avoid runtime errors by checking if an object is a function, method, or any other callable.

Great for plugin-based architectures or frameworks.

Bonus: Combine Them for Maximum Python Power

Here’s a quick example combining any(), enumerate(), and zip():

names = ["", "Bob", ""] 
ages = [0, 30, 0] 
 
if any(name and age for name, age in zip(names, ages)): 
    for i, (name, age) in enumerate(zip(names, ages), start=1): 
        if name and age: 
            print(f"{i}. {name} is {age} years old.")

Final Thoughts

These unique Python functions aren’t just “nice to know” — they’re tools that can make your code more efficient, expressive, and Pythonic.

If you’re aiming to write cleaner code or improve your problem-solving approach, mastering these hidden gems is a solid investment.

Try sprinkling a few of these into your next project — and watch your code transform from functional to elegant.

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