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Python Unplugged: A Comparative Study of Seven Energy-Efficient Coding Techniques

  • 2025
  • OriginalPaper
  • Chapter
Published in:
Authors
Eyvaz Ahmadzada
Ah-Lian Kor
Thalita Vergilio
Nawar Jawad
Published in
Decarbonization or Demise – Sustainable Solutions for Resilient Communities
Publisher
Springer Nature Switzerland

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Abstract

This chapter delves into the critical issue of energy consumption in Python programming and presents a comparative study of seven energy-efficient coding techniques. The research aims to identify the most effective methods for reducing Python's energy footprint, which is notably higher than other programming languages. By employing software power measurement tools, the study evaluates the energy usage of various code snippets implementing each technique. The findings reveal significant improvements in energy efficiency for techniques such as built-in functions, lazy evaluation, and caching, while also highlighting the trade-offs between energy efficiency and other code quality factors. The study provides valuable insights into the impact of different programming techniques on energy consumption, offering developers actionable recommendations to create more sustainable software. Additionally, the research contributes to the development of an AI model that can predict the efficiency of software programs before compilation, further advancing the field of energy-aware software development.
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previous chapter SHA256: Comparing the Energy Consumption of Different Implementations
next chapter Comparative Analysis of Energy Efficiency in Virtualization Tools and Underlying Operating Systems
Title
Python Unplugged: A Comparative Study of Seven Energy-Efficient Coding Techniques
Authors
Eyvaz Ahmadzada
Ah-Lian Kor
Thalita Vergilio
Nawar Jawad
Copyright Year
2025
Book
Decarbonization or Demise – Sustainable Solutions for Resilient Communities

Print ISBN: 978-3-031-89194-6

Electronic ISBN: 978-3-031-89195-3

Copyright Year: 2025

DOI
https://doi.org/10.1007/978-3-031-89195-3_31
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