Just like algae blooms in the ocean and pollen in the spring, there’s been an explosion in the past year or two of new software, related tools and lingo from the IT and mainstream/consumer side. Some ...

Abstract: Programming language source code vulnerability mining is crucial to improving the security of software systems, but current research is mostly focused on the C language field, with little ...

The native just-in-time compiler in Python 3.15 can speed up code by as much as 20% or more, although it’s still experimental. JITing, or “just-in-time” compilation, can make relatively slow ...

Google Colab, also known as Colaboratory, is a free online tool from Google that lets you write and run Python code directly in your browser. It works like Jupyter Notebook but without the hassle of ...

In this tutorial, we explore how we can seamlessly run MATLAB-style code inside Python by connecting Octave with the oct2py library. We set up the environment on Google Colab, exchange data between ...

An array is not useful in places where we have operations like insert in the middle, delete from the middle, and search in unsorted data. If you only search occasionally: Linear search in an array or ...

I completed this a long while ago and have since moved on to further topics in API integration and data structures. I hope this might be useful for you. This is just a cherished memory, not an ...

The Python team at Microsoft is continuing its overhaul of environment management in Visual Studio Code, with the August 2025 release advancing the controlled rollout of the new Python Environments ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

Okay, so what is a free Python IDE online, really? It’s basically your coding command center, but instead of living on your computer, it lives in your browser. Think of it as a streamlined workspace ...

from numpy import * arr1 = array([2,6,8,10,12]) # arr2 = arr1.view() # assign values of 'arr1' to 'arr2' mirroring the address arr2 = arr1.copy() # assign values of arr1 to arr2 w/o mirroring arr1[1] ...