Comparative evaluation of performance-boosting tools for Python

Jakub Swacha

Abstract


The Python programming language has a number of advantages, such as simple and clear syntax, concise and readable code, and open source implementation with a lot of extensions available, that makes it a great tool for teaching programming to students. Unfortunately, Python, as a very high level interpreted programming language, is relatively slow, which becomes a nuisance when executing computationally intensive programs. There is, however, a number of tools aimed at speeding-up execution of programs written in Python, such as Just-in-Time compilers and automatic translators to statically compiled programming languages. In this paper a comparative evaluation of such tools is done with a focus on the attained performance boost.

Full Text:

PDF


DOI: http://dx.doi.org/10.2478/v10065-011-0022-7
Date of publication: 2011-01-01 00:00:00
Date of submission: 2016-04-28 09:02:46


Statistics


Total abstract view - 482
Downloads (from 2020-06-17) - PDF - 0

Indicators



Refbacks

  • There are currently no refbacks.


Copyright (c) 2015 Annales UMCS Sectio AI Informatica

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.