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Building Custom Spreadsheet Functions with Python: End-User Software Engineering Approach

Journal of Software Engineering and Applications 2024年第5期17卷 246-258页

作者： Tamer Bahgat elserwy atef tayh nour el-din raslan Tarek Ali Mervat H. Gheith Department of Software Engineering Faculty of Graduate Studies for Statistical Research (FGSSR) Cairo University Giza Egypt Department of Information Systems Higher Institute of Advanced Studies Giza Egypt

End-user computing empowers non-developers to manage data and applications, enhancing collaboration and efficiency. Spreadsheets, a prime example of end-user programming environments widely used in business for data analysis. However, Excel functionalities have limits compared to dedicated programming languages. This paper addresses this gap by proposing a prototype for integrating Python’s capabilities into Excel through on-premises desktop to build custom spreadsheet functions with Python. This approach overcomes potential latency issues associated with cloud-based solutions. This prototype utilizes Excel-DNA and IronPython. Excel-DNA allows creating custom Python functions that seamlessly integrate with Excel’s calculation engine. IronPython enables the execution of these Python (CSFs) directly within Excel. C# and VSTO add-ins form the core components, facilitating communication between Python and Excel. This approach empowers users with a potentially open-ended set of Python (CSFs) for tasks like mathematical calculations, statistical analysis, and even predictive modeling, all within the familiar Excel interface. This prototype demonstrates smooth integration, allowing users to call Python (CSFs) just like standard Excel functions. This research contributes to enhancing spreadsheet capabilities for end-user programmers by leveraging Python’s power within Excel. Future research could explore expanding data analysis capabilities by expanding the (CSFs) functions for complex calculations, statistical analysis, data manipulation, and even external library integration. The possibility of integrating machine learning models through the (CSFs) functions within the familiar Excel environment.

关键词： End-User Software Engineering Custom Spreadsheet Functions (CSFs)

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Enhancing Data Analysis and Automation: Integrating Python with Microsoft Excel for Non-Programmers

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Journal of Software Engineering and Applications 2024年第6期17卷 530-540页

作者： Osama Magdy Ali Mohamed Breik Tarek Aly atef tayh nour el-din raslan Mervat Gheith Software Engineering Department Faculty of Graduate Studies for Statistical Research Cairo University Giza Egypt

Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and informed decision-making across diverse domains. Conversely, Python is indispensable for professional programming due to its versatility, readability, extensive libraries, and robust community support. It enables efficient development, advanced data analysis, data mining, and automation, catering to diverse industries and applications. However, one primary issue when using Microsoft Excel with Python libraries is compatibility and interoperability. While Excel is a widely used tool for data storage and analysis, it may not seamlessly integrate with Python libraries, leading to challenges in reading and writing data, especially in complex or large datasets. Additionally, manipulating Excel files with Python may not always preserve formatting or formulas accurately, potentially affecting data integrity. Moreover, dependency on Excel’s graphical user interface (GUI) for automation can limit scalability and reproducibility compared to Python’s scripting capabilities. This paper covers the integration solution of empowering non-programmers to leverage Python’s capabilities within the familiar Excel environment. This enables users to perform advanced data analysis and automation tasks without requiring extensive programming knowledge. Based on Soliciting feedback from non-programmers who have tested the integration solution, the case study shows how the solution evaluates the ease of implementation, performance, and compatibility of Python with Excel versions.

关键词： Python End-User Approach Microsoft Excel Data Analysis Integration Spreadsheet Programming Data Visualization

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Experimental investigation and numerical modeling of the hydration operation of date fruits

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International Journal of Modeling, Simulation, and Scientific Computing 2017年第2期8卷 55-71页

作者： atef Lakoud Sebastien Curet Mnasser Hassouna Ecole Superieure des Industries Alimentaires de Tunis 58 Av.Alain Savary Tunis El Khadra1003Tunisia L’UNAM Universite ONIRISCNRSGEPEAUMR 6144 site de la GeraudiereNantesF-44322France Ecole Sup´erieure des Industries Alimentaires de Tunis 58 Av.Alain Savary Tunis El Khadra1003Tunisia

Hydration represents the main unit operation in the industrial thermal process of dry *** this work,Tunisian Deglet nour dates were hydrated experimentally at a laboratory scale by using saturated air as it is commonly undertaken in *** study focuses on the modeling of this unit operation in order to control the moisture uptake phenomenon during processing.A physic-based simplified numerical model describing moisture transfer during hydration was implemented in COMSOL rMultiphysics soft*** model considers the real geometry of dates instead of approaching the fruits by simplified *** diffusivities of two types of Deglet nour dry dates characterized by different maturation stages were *** showed a good agreement between experimental and numerically computed values of average moisture *** profile in dates flesh was computed numerically using estimated moisture dif*** numerical model proposed in this work could be therefore employed as a predictive tool to simulate and optimize the hydration operation of dates.

关键词： Moisture diffusivity convective coefficient moisture profile.

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