Developing Domain-Specific Languages Using Python for Scientific Computing

Authors

Rose Anderson
Research Programmer, United Kingdom.

Keywords:

Domain-Specific Languages, Python, Scientific Computing, DSL Design, Metaprogramming, Computational Frameworks

Synopsis

Domain-Specific Languages (DSLs) have become vital tools for enhancing productivity and expressiveness in scientific computing. This paper explores the utility and methodology of creating DSLs using Python, a language widely adopted for its syntactic clarity and robust scientific libraries. We present a framework for designing, implementing, and deploying Python-based DSLs tailored to specific scientific domains, such as numerical analysis, bioinformatics, and computational physics. The approach highlights best practices in DSL design, integration with existing Python tools (e.g., NumPy, SymPy), and real-world use cases that demonstrate improved workflow efficiency and domain expressivity.

 

 

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IJCA

Published

July 18, 2025

Series

Research paper
Copyright (c) 2025 Rose Anderson (Author)

License

Creative Commons License

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