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Hard to Read and Understand Pythonic Idioms? DeIdiom and Explain Them in Non-Idiomatic Equivalent Code

Zejun Zhang, Zhenchang Xing, Dehai Zhao, Qinghua Lu, Xiwei Xu, Liming Zhu

2024Year
7Citations
3Top-tier citations

Abstract

The Python community strives to design pythonic idioms so that Python users can achieve their intent in a more concise and efficient way. According to our analysis of 154 questions about challenges of understanding pythonic idioms on Stack Overflow, we find that Python users face various challenges in comprehending pythonic idioms. And the usage of pythonic idioms in 7,577 GitHub projects reveals the prevalence of pythonic idioms. By using a statistical sampling method, we find pythonic idioms result in not only lexical conciseness but also the creation of variables and functions, which indicates it is not straightforward to map back to non-idiomatic code. And usage of pythonic idioms may even cause potential negative effects such as code redundancy, bugs and performance degradation. To alleviate such readability issues and negative effects, we develop a transforming tool, DeIdiom, to automatically transform idiomatic code into equivalent non-idiomatic code. We test and review over 7,572 idiomatic code instances of nine pythonic idioms (list/set/dict-comprehension, chain-comparison, truth-value-test, loop-else, assign-multi-targets, for-multi-targets, star), the result shows the high accuracy of DeIdiom. Our user study with 20 participants demonstrates that explanatory non-idiomatic code generated by DeIdiom is useful for Python users to understand pythonic idioms correctly and efficiently, and leads to a more positive appreciation of pythonic idioms.

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