DYNAMIC ARRAYS AND IMPLEMENTATIONS IN PYTHON PROGRAMMING LANGUAGE

Article Sidebar

pdf
Published: Apr 30, 2024
Keywords:
Dynamic arrays, python, data structures, performance optimization, memory management, list comprehension, computational efficiency.

Main Article Content

Yigitaliyev Ro'zimatjon Nodirjonovich

Abstract

Dynamic arrays are a fundamental data structure in computer science, offering flexibility and efficiency in memory management. In Python, dynamic arrays are implemented through the list data structure, providing dynamic resizing and versatile operations. This article delves into the concepts of dynamic arrays, explores their implementations in Python, evaluates their performance characteristics, and discusses best practices for utilization.

Article Details

How to Cite
Yigitaliyev Ro’zimatjon Nodirjonovich. (2024). DYNAMIC ARRAYS AND IMPLEMENTATIONS IN PYTHON PROGRAMMING LANGUAGE. Proceedings of International Conference on Educational Discoveries and Humanities, 3(5), 323–328. Retrieved from https://econferenceseries.com/index.php/icedh/article/view/4610
Issue
Vol. 3 No. 5 (2024): ICEDH
Section
Articles
Creative Commons License

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

References

G. Bavestrelli. A class template for N-dimensional generic resizable arrays. C/C++ Users Journal, 18(12):32–43, December 2000. URL http://www.drdobbs.com/ a-class-template-for-n-dimensional-gener/184401319.

J. Bezanson, S. Karpinski, V. B. Shah, and A. Edelman. Julia: A fast dynamic language for technical computing. arXiv:1209.5145v1, 2012.

V. A. Busam and D. E. Englund. Optimization of expressions in Fortran. Communication of the ACM, 12(12):666–674, 1969. .

R. Choy and A. Edelman. Parallel MATLAB: Doing it right. In Proceedings of the IEEE, volume 93, pages 331–341, 2005. .

P. Cousot and R. Cousot. Abstract interpretation: A unified lattice model for static analysis of programs by construction or approximation of fixpoints. In Proceedings of the 4th ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages, POPL ’77, pages 238–252, New York, NY, USA, 1977. ACM. .

P. Cousot and R. Cousot. Comparing the Galois connection and widening/narrowing approaches to abstract interpretation. In M. Bruynooghe and M. Wirsing, editors, Programming Language Implementation and Logic Programming, volume 631 of Lecture Notes in Computer Science, pages 269–295. Springer Berlin / Heidelberg, 1992.

A. D. Falkoff and K. E. Iverson. The design of APL. SIGAPL APL Quote Quad, 6:5–14, April 1975. .

Garcia and A. Lumsdaine. MultiArray: a C++ library for generic programming with arrays. Software: Practice and Experience, 35(2): 159–188, 2005. .

C. Grelck and S.-B. Scholz. SAC: A functional array language for efficient multi-threaded execution. International Journal of Parallel Programming, 34(4):383–427, 2006. ISSN 0885-7458.