Summary + Thesis Draft #1

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Python is a distinguished, class-driven programming language with flexible behaviour that executes code line-by-line (Python Software Foundation, n.d.). Its straightforward and easy-to-learn syntax prioritises readability, making it a great choice of programming for new learners (Simplilearn, n.d.). According to Thakur (2022), Python provides a variety of libraries (e.g. Standard library) that facilitate integration with other computer languages like C, JSON, Java, and more. This cross-platform compatibility makes it highly adaptable. In addition, Python is accessible for everyone to use, encouraging innovation and community collaboration. With its strong community support, ample resources for learning and troubleshooting are available (Simplilearn, n.d.). Its flexibility and versatility enable it to be applied to a wide range of applications making it well sought out by beginners and professionals alike. These features allow Python to be used for various functions, including data analysis (Hande, 2024), automation (Coursera, 2024), scientific computing (Python for Scientific Computing, 2017), and more.


Building on Python’s flexibility and strong functionalities, its applications in civil engineering are notable. Integrating Python into a field which requires data analysis and complex scientific computations can significantly benefit the workflow by streamlining tasks like automating repetitive calculations and analysing large datasets with precision and efficiency. However, while it is an essential tool which fosters innovation and enhances productivity, some limitations—such as the learning curve for new tools and adaptation to evolving technologies—remain.


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