DEV Community

Cover image for Is Your Python For-loop Slow? Use NumPy Instead
Thuwarakesh Murallie
Thuwarakesh Murallie

Posted on

Is Your Python For-loop Slow? Use NumPy Instead

Speed is always a concern for developers — especially for data-savvy work.

As developers, the easiest way to scale up things is using a for-loop. But there are drawbacks to using them for large numerical computations.

This post compares how for-loops perform in such workloads with vectorized alternatives.

Is Your Python For-loop Slow? Use NumPy Instead

Top comments (0)

Eliminate Context Switching and Maximize Productivity

Pieces.app

Pieces Copilot is your personalized workflow assistant, working alongside your favorite apps. Ask questions about entire repositories, generate contextualized code, save and reuse useful snippets, and streamline your development process.

Learn more

👋 Kindness is contagious

Please leave a ❤️ or a friendly comment on this post if you found it helpful!

Okay