2026-04-13T06:47:03Zhttps://recercat.cat/oai/requestoai:recercat.cat:2117/3953342025-07-22T23:27:11Zcom_2072_1033col_2072_452951
An empirical study of Python hash tables
Estevao Bazilio, Lucas
Àrees temàtiques de la UPC::Informàtica::Programació
Python (Computer program language)
Python
hash table performance
internal factors
collision resolution
table resizing
linear probing
random probing
load factor management
optimization
efficiency
experimental evaluation
Python (Llenguatge de programació)
This research thesis explores the performance aspects of hash tables in Python, with a specific emphasis on Python sets, examining the internal factors that influence their efficiency. Hash tables are fundamental data structures used extensively in various applications, and their performance plays a crucial role in the overall performance of the systems utilizing them. By investigating the internal factors, such as collision resolution strategies, load factor management, and table resizing techniques, this study aims to identify key optimizations to enhance hash table performance. The research involves experimental evaluations, performance measurements, and comparative analysis to validate the proposed optimizations. The findings contribute to a better understanding of hash table performance in Python and provide guidelines for achieving optimal performance.
2023-06-27
Bachelor thesis
Open Access
Universitat Politècnica de Catalunya