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Speed Up Your Python Code with These Underrated Tricks

Ramkumar M N on May 08, 2025

Python is widely celebrated for its simplicity and readability, making it a favorite among beginners and seasoned developers alike. However, it's a...

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Anmol Baranwal • May 8

Write on medium too!

Ramkumar M N • May 9

Thanks Anmol Baranwal Subscriber!
I’ve been considering it. I would love to start writing on Medium too soon. Appreciate the encouragement

Regards,
Ram

david duymelinck • May 9 • Edited

Instead of a list of options I would preferred to see more explanation why to use one or the other and also more context.

A list comprehension is faster than the map function when not using a lambda. So if you want speed the map example should be

def square(x):
    return x ** 2

numbers = [1, 2, 3, 4, 5]

squared = list(map(square, numbers))

For 4 and 16, the fix is use the right data structure.

Avoid global variables is not only a speed fix, it makes the code more maintainable.

9 and 13 are the same thing, so there are 19 different things.

Between defaultdict and Counter, the latter will be faster as the first is more generic.

Only use @staticmethod and @classmethod when it is appropriate. Don't use them just to avoid class instantiation.

Ramkumar M N • May 9

Hi david duymelinck

Thanks so much for the thoughtful feedback, You're absolutely right. I appreciate you pointing out where more explanation would add value. Also great catch on the overlap between points 9 and 13. l will consolidate that. Feedback like yours really helps improve the quality.

Thanks & Regards,
Ram

davinceleecode • May 8

Thanks for this article! 🔥

Ramkumar M N • May 9

Hi davinceleecode
Thanks for reading. Glad you liked it!

Regards,
Ram

Teddy ASSIH • May 13

Great article. I would have appreciated a little more explanation (such as the data structures and algorithms behind certain python methods) on why you use a specific syntax rather than another.

Ramkumar M N • May 15

Hi Teddy Assih,
Thank you for the feedback. I will update the post with explanations.

Regards,
Ram

Nevo David • May 9

been using python for a bit and some of these little changes really do help, keeps me going back to refactor old code all the time

Ramkumar M N • May 12

Thank you for the acknowledgment Nevo David 😊👍

Anita Olsen • May 12

Thank you so much for this! ✨

Ramkumar M N • May 12

Hi Anita Olsen,
You’re very welcome! I’m glad you found it helpful. 😊👍

Regards,
Ram

Nathan Tarbert • May 13

pretty cool rundown tbh, i always forget about stuff like lru_cache till i see it used - you ever feel like most speed problems only show up when something actually breaks?

Ramkumar M N • May 15

Hi Nathan Tarbert,
Thanks for the comment. I’ve never really faced or noticed that myself. Most of the time, things just run fine unless I’m specifically benchmarking or digging into optimizations.

Regards,
Ram

Nathan Tarbert • May 9

absolutely love little speed tricks like these honestly makes coding way less annoying over time

Ramkumar M N • May 9

Hi Nathan Tarbert

Good to hear that. Refactoring old code with small optimizations can really make a big difference over time. I'm glad the post sparked that motivation!

Thanks & Regards,
Ram

RankmyAI • May 12

Good!

Ramkumar M N • May 12

Thank you RankmyAl