Today, we’ll share another performance improvement incorporating the latest Python 3.11 version. You can consider this significant advancement over the past versions. Last time, I posted for 3.7 in one of my earlier posts. But, we should diligently update everyone regarding the performance upgrade as it is slowly catching up with some of the finest programming languages.
But, before that, I want to share the latest stats of the machine where I tried these tests (As there is a change of system compared to last time).

Let us explore the base code –
############################################## #### Written By: SATYAKI DE #### #### Written On: 06-May-2021 #### #### Modified On: 30-Oct-2022 #### #### #### #### Objective: Main calling scripts for #### #### normal execution. #### ############################################## from timeit import default_timer as timer def vecCompute(sizeNum): try: total = 0 for i in range(1, sizeNum): for j in range(1, sizeNum): total += i + j return total except Excception as e: x = str(e) print('Error: ', x) return 0 def main(): start = timer() totalM = 0 totalM = vecCompute(100000) print('The result is : ' + str(totalM)) duration = timer() - start print('It took ' + str(duration) + ' seconds to compute') if __name__ == '__main__': main()
And here is the outcome comparison between the 3.10 & 3.11 –


The above screenshot shows an improvement of 23% on an average compared to the previous version.
These performance stats are highly crucial. The result shows how Python is slowly emerging as the universal language for various kinds of work and is now targetting one of the vital threads, i.e., improvement of performance.
So, finally, we have done it.
I’ll bring some more exciting topic in the coming days from the Python verse.
Till then, Happy Avenging! 🙂
Note: All the data & scenario posted here are representational data & scenarios & available over the internet & for educational purpose only.
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