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Journal articles on the topic 'Software python'

Author: Grafiati

Published: 3 June 2025

Last updated: 1 August 2025

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1

Peta, Saphalya. "Python- An Appetite for the Software Industry." International Journal of Programming Languages and Applications 12, no. 4 (2022): 1–14. http://dx.doi.org/10.5121/ijpla.2022.12401.

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Python is a scripting language that's high- positioned, interpreted, interactive, and object- oriented. Python is intended to be a veritably accessible programming language. It generally uses English terms rather than punctuation, and it has smaller syntactical structures than other languages. Python is a must-have skill for scholars and working professionals who want to become exceptional software masterminds, especially if they work in the web development field. It's a freshman-friendly scripting language. Some of the crucial features of Python programming language are- It supports OOP as we

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Peirce, Jonathan W. "PsychoPy—Psychophysics software in Python." Journal of Neuroscience Methods 162, no. 1-2 (2007): 8–13. http://dx.doi.org/10.1016/j.jneumeth.2006.11.017.

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Elserwy, Tamer Bahgat, Tarek Aly, and Basma E. El-Demerdash. "End-user software engineering approach: improve spreadsheets capabilities using Python-based user-defined functions." Indonesian Journal of Electrical Engineering and Computer Science 38, no. 2 (2025): 1024. https://doi.org/10.11591/ijeecs.v38.i2.pp1024-1032.

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<p>End-user computing enables non-developers to handle data and applications, boosting collaboration and productivity. Spreadsheets are a key example of end-user programming environments that are extensively utilized in business for data analysis. However, the functionalities of Excel have limitations compared to specialized programming languages. This study aims to address this shortcoming by proposing a prototype that integrates Python's features into Excel via standalone desktop Python-based user-defined functions (UDFs). This method mitigates potential latency concerns linked to clou

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Tamer, Bahgat Elserwy Tarek Aly Basma E. El-Demerdash. "End-user software engineering approach: improve spreadsheets capabilities using Python-based user-defined functions." Indonesian Journal of Electrical Engineering and Computer Science 38, no. 2 (2025): 1024–32. https://doi.org/10.11591/ijeecs.v38.i2.pp1024-1032.

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End-user computing enables non-developers to handle data and applications, boosting collaboration and productivity. Spreadsheets are a key example of end-user programming environments that are extensively utilized in business for data analysis. However, the functionalities of Excel have limitations compared to specialized programming languages. This study aims to address this shortcoming by proposing a prototype that integrates Python's features into Excel via standalone desktop Python-based user-defined functions (UDFs). This method mitigates potential latency concerns linked to cloud-based s

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Soujanya, Reddy Annapareddy. "Real-World Applications of Python in Firmware and Software Automation." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 10, no. 2 (2024): 1–6. https://doi.org/10.5281/zenodo.14540900.

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Python has become a versatile tool in firmware and software automation, enabling efficient development and testing workflows across various industries. Its simplicity, extensive libraries, and cross-platform support make it ideal for automating tasks like firmware flashing, version verification, and hardware communication. This paper explores real-world applications of Python in firmware and software automation, including integrating serial communication protocols, streamlining build and deployment processes, and implementing test frameworks for embedded systems. It highlights how Python's eco

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LOBARYOV, D., and N. LOBARYOV. "SYNTHESIS OF NONDETERMINISTIC FINITE AUTOMATON FROM REGULAR EXPRESSIONS BY GLUSHKOV'S ALGORITHM IN JFF FORMAT." HERALD OF POLOTSK STATE UNIVERSITY. Series С FUNDAMENTAL SCIENCES, no. 1 (April 18, 2025): 9–13. https://doi.org/10.52928/2070-1624-2025-44-1-9-13.

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The paper presents the results of the implementation of a software tool for synthesizing nondeterministic finite automaton using regular expressions in JFF format. Glushkov's algorithm is used as a method for synthesizing automata. When developing the program, the integrated development environment for the Python – Visual Studio Code, the JFLAP software package for visualizing finite automaton, as well as the Python libraries xml.etree and pythonds were used.

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Zonca, Andrea, Ben Thorne, Nicoletta Krachmalnicoff, and Julian Borrill. "The Python Sky Model 3 software." Journal of Open Source Software 6, no. 67 (2021): 3783. http://dx.doi.org/10.21105/joss.03783.

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Kerr, Cliff C., Paula Sanz-Leon, Romesh G. Abeysuriya, et al. "Sciris: Simplifying scientific software in Python." Journal of Open Source Software 8, no. 88 (2023): 5076. http://dx.doi.org/10.21105/joss.05076.

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Chen, Xiaojie. "Introduction and Analysis of Python Software." Frontiers in Computing and Intelligent Systems 5, no. 2 (2023): 41–43. http://dx.doi.org/10.54097/fcis.v5i2.12348.

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In the context of the era of rapid development of computer and Internet technology, it gives enterprises the possibility of realizing informationization and automation. Due to the traditional office needs to take up a lot of human, material and financial resources, as well as paper filing method is not environmentally friendly, easy to damage, easy to lose, poor security and other shortcomings, has been unable to meet the needs of modern office. With the development of science and technology, Microsoft Office, Adobe Systems PDF and other office software came into being, their role is increasin

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Bouzenia, Islem, Bajaj Piyush Krishan, and Michael Pradel. "DyPyBench: A Benchmark of Executable Python Software." Proceedings of the ACM on Software Engineering 1, FSE (2024): 338–58. http://dx.doi.org/10.1145/3643742.

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Python has emerged as one of the most popular programming languages, extensively utilized in domains such as machine learning, data analysis, and web applications. Python’s dynamic nature and extensive usage make it an attractive candidate for dynamic program analysis. However, unlike for other popular languages, there currently is no comprehensive benchmark suite of executable Python projects, which hinders the development of dynamic analyses. This work addresses this gap by presenting DyPyBench, the first benchmark of Python projects that is large-scale, diverse, ready-to-run (i.e., with ful

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Jo, YeongChang, HyeHyeon Kim, HoonSik Kim, SeongUk Han, and Hyung-Woo Lee. "PyStudy : Python based Self-Study Helper Software." Journal of The Korea Internet of Things Society 2, no. 1 (2016): 41–48. http://dx.doi.org/10.20465/kiots.2016.2.1.041.

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Akeel Hussein Alaasam, Hussein, Ahmed Ali Talib Al-Khazaali, Ali Hussein Aleiwi, and Doaa Wahhab Ibrahim. "Learn Land Features Using Python Language." BIO Web of Conferences 97 (2024): 00111. http://dx.doi.org/10.1051/bioconf/20249700111.

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Python has emerged as an essential programming language for research due to continuous technological advancements that emphasize its role in streamlining scientific workflows. This article elucidates Python's burgeoning impact on researchers across disciplines. Tracing Python's origins and applications within the earth sciences contextualizes its versatility. While acquiring proficiency in Python exceeds this article's scope, discussions detail its utilities for earth science data analysis, visualization, management, and rapid computations. With Python expertise, researchers can engineer custo

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Galli, Massimiliano, Enric Tejedor, and Stefan Wunsch. "A New PyROOT: Modern, Interoperable and More Pythonic." EPJ Web of Conferences 245 (2020): 06004. http://dx.doi.org/10.1051/epjconf/202024506004.

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Python is nowadays one of the most widely-used languages for data science. Its rich ecosystem of libraries together with its simplicity and readability are behind its popularity. HEP is also embracing that trend, often using Python as an interface language to access C++ libraries for the sake of performance. PyROOT, the Python bindings of the ROOT software toolkit, plays a key role here, since it allows to automatically and dynamically invoke C++ code from Python without the generation of any static wrappers beforehand. In that sense, this paper presents the efforts to create a new PyROOT with

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Gupta, Aniket, and Dr Chaya Bagrecha. "A Portfolio Construction on NIFTY AUTO using Python Software." International Journal of Research Publication and Reviews 5, no. 4 (2024): 5749–54. http://dx.doi.org/10.55248/gengpi.5.0424.1075.

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Karam, Mokbel, and Tony Saad. "BuckinghamPy: A Python software for dimensional analysis." SoftwareX 16 (December 2021): 100851. http://dx.doi.org/10.1016/j.softx.2021.100851.

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POPOVIC, M., I. BASICEVIC, M. DJUKIC, and M. POPOVIC. "Fault Tolerant Distributed Python Software Transactional Memory." Advances in Electrical and Computer Engineering 20, no. 4 (2020): 19–28. http://dx.doi.org/10.4316/aece.2020.04003.

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Marowka, Ami. "On parallel software engineering education using python." Education and Information Technologies 23, no. 1 (2017): 357–72. http://dx.doi.org/10.1007/s10639-017-9607-0.

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Verschelde, Jan. "Exporting Ada Software to Python and Julia." ACM SIGAda Ada Letters 42, no. 1 (2022): 76–78. http://dx.doi.org/10.1145/3577949.3577961.

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The objective is to demonstrate the making of Ada software available to Python and Julia programmers using GPRbuild. GPRbuild is the project manager of the GNAT toolchain. With GPRbuild the making of shared object files is fully automated and the software can be readily used in Python and Julia. The application is the build process of PHCpack, a free and open source software package to solve polynomial systems by homotopy continuation methods, written mainly in Ada, with components in C++, available at github at https://github.com/janverschelde/PHCpack.

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Bakker, Wim, Frank van Ruitenbeek, Harald van der Werff, Christoph Hecker, Arjan Dijkstra, and Freek van der Meer. "Hyperspectral Python: HypPy." Algorithms 17, no. 8 (2024): 337. http://dx.doi.org/10.3390/a17080337.

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This paper describes the design, implementation, and usage of a Python package called Hyperspectral Python (HypPy). Proprietary software for processing hyperspectral images is expensive, and tools developed using these packages cannot be freely distributed. The idea of HypPy is to be able to process hyperspectral images using free and open-source software. HypPy was developed using Python and relies on the array-processing capabilities of packages like NumPy and SciPy. HypPy was designed with practical imaging spectrometry in mind and has implemented a number of novel ideas. To name a few of t

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Gajdoš, P. "NEW FEATURES IN SOFTWARE OCFIT." Open European Journal on Variable stars, no. 241 (2023): 1–9. http://dx.doi.org/10.5817/oejv2023-0241.

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Software OCFit is designed for fitting O-C diagrams of eclipsing binaries and transiting exoplanets by standard analytical models (e.g. light-time effect or apsidal motion). The program is written in the modern language Python. A very intuitive graphic user interface is also a part of this software. Moreover, OCFit could be used as a Python package in your own code. Its development started in 2015. GUI was published three years later. Here, we present changes and the newly implemented features in this software since its publishing in 2018 (mainly during the year 2022).

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Politz, Joe Gibbs, Alejandro Martinez, Matthew Milano, et al. "Python." ACM SIGPLAN Notices 48, no. 10 (2013): 217–32. http://dx.doi.org/10.1145/2544173.2509536.

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Arias Vivanco, Daniel, Mariana Defas Itaz, and Esteban Jarrín Sánchez. "Reseña del uso del lenguaje de programación Python en el Desarrollo de Software." Revista Científica Élite 6, no. 2 (2024): 1–6. http://dx.doi.org/10.69603/itsqmet.vol6.n2.2024.90.

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Introduction: This article provides a concise and clear definition of the Python programming language, highlighting its key features and its significance in the current landscape of software development. Python, renowned for its simple and readable syntax, has gained popularity due to its versatility and ease of use. Objective: The primary objective of this study is to answer the question: What role does Python play in current software development and what are its future prospects? This analysis aims to understand the impact of Python on the software industry and assess how its evolution may i

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Rada, Václav, Tomáš Fíla, Petr Zlámal, Daniel Kytýř, and Petr Koudelka. "MULTI-CHANNEL CONTROL SYSTEM FOR IN-SITU LABORATORY LOADING DEVICES." Acta Polytechnica CTU Proceedings 18 (October 23, 2018): 15. http://dx.doi.org/10.14311/app.2018.18.0015.

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In recent years, open-source applications have replaced proprietary software in many fields. Especially open-source software tools based on Linux operating system have wide range of utilization. In terms of CNC solutions, an open-source system LinuxCNC can be used. However, the LinuxCNC control software and the graphical user interface (GUI) could be developed only on top of Hardware Abstraction Layer. Nevertheless, the LinuxCNC community provided Python Interface, which allows for controlling CNC machine using Python programming language, therefore whole control software can be developed in P

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de los Reyes, Raquel, Maximilian Langheinrich, Peter Schwind, et al. "PACO: Python-Based Atmospheric Correction." Sensors 20, no. 5 (2020): 1428. http://dx.doi.org/10.3390/s20051428.

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The atmospheric correction of satellite images based on radiative transfer calculations is a prerequisite for many remote sensing applications. The software package ATCOR, developed at the German Aerospace Center (DLR), is a versatile atmospheric correction software, capable of processing data acquired by many different optical satellite sensors. Based on this well established algorithm, a new Python-based atmospheric correction software has been developed to generate L2A products of Sentinel-2, Landsat-8, and of new space-based hyperspectral sensors such as DESIS (DLR Earth Sensing Imaging Sp

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Proença, Neto Marco, and Sousa Marcos De. "Pytaxon: A Python software for resolving and correcting taxonomic names in biodiversity data." Biodiversity Data Journal 13 (January 8, 2025): e138257. https://doi.org/10.3897/BDJ.13.e138257.

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The standardisation and correction of taxonomic names in large biodiversity databases remain persistent challenges for researchers, as errors in species names can compromise ecological analyses, land-use planning and conservation efforts, particularly when inaccurate data are shared on global biodiversity portals.We present pytaxon, a Python software designed to resolve and correct taxonomic names in biodiversity data by leveraging the Global Names Verifier (GNV) API and employing fuzzy matching techniques to suggest corrections for discrepancies and nomenclatural inconsistencies. The pytaxon

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Graff, David E., and Connor W. Coley. "pyscreener: A Python Wrapper for Computational Docking Software." Journal of Open Source Software 7, no. 71 (2022): 3950. http://dx.doi.org/10.21105/joss.03950.

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Karam, Mokbel, James C. Sutherland, and Tony Saad. "PyModPDE: A python software for modified equation analysis." SoftwareX 12 (July 2020): 100541. http://dx.doi.org/10.1016/j.softx.2020.100541.

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Audet, Pascal, Colin Thomson, Michael Bostock, and Tom Eulenfeld. "Telewavesim: Python software for teleseismic body wave modeling." Journal of Open Source Software 4, no. 44 (2019): 1818. http://dx.doi.org/10.21105/joss.01818.

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Oldag, Drew, Melissa DeLucchi, Wilson Beebe, et al. "A Python Project Template for Healthy Scientific Software." Research Notes of the AAS 8, no. 5 (2024): 141. http://dx.doi.org/10.3847/2515-5172/ad4da1.

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Abstract The creation of “healthy” scientific software is vital for its successful long-term adoption in scientific research. Here healthy code is defined to mean software that is usable, maintainable, and proffers consistently reproducible results. Incorporating tooling and practices to achieve these goals often leads to short-term, yet significant, overhead for new projects. We introduce the LINCC Frameworks Python Project Template, a configurable code template designed for scientific software projects that greatly simplifies adopting best practices by automating the setup and configuration

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Weise, Thomas. "Software - motipy: the Metaheuristic Optimization in Python Library." ACM SIGEVOlution 16, no. 4 (2023): 1–2. http://dx.doi.org/10.1145/3638461.3638464.

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We are thankful for the opportunity to announce our Python package "moptipy," which offers a rich set of tools for implementing, applying, and experimenting with metaheuristic optimization algorithms. Our package has been designed with benchmarking in mind and thus provides very comprehensive experimentation, data collection, and evaluation facilities out of the box. moptipy has the following features: 1. Very comprehensive documentation with many examples, reaching down to literature references inside the code and up to complex example experiments. 2. Several standard search spaces (bit strin

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Klementiev, K. "ParSeq: Python software for comparative data analysis pipelines." Journal of Physics: Conference Series 3010, no. 1 (2025): 012126. https://doi.org/10.1088/1742-6596/3010/1/012126.

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Abstract The package ParSeq is a Python software library for Parallel execution of Sequential data analysis. It implements a general analysis framework that consists of transformation nodes — intermediate stops along the analysis propagation to visualize data, display status and provide user input — and transformations that connect the nodes. ParSeq imports data into an adjustable data model — a collection of data objects that supports grouping, renaming and moving. ParSeq provides tunable data format definitions, plotters for 1D, 2D and 3D data, cross-data analysis routines and flexible widge

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Blank, Douglas, Lisa Meeden, and Deepak Kumar. "Python robotics." ACM SIGCSE Bulletin 35, no. 1 (2003): 317–21. http://dx.doi.org/10.1145/792548.611996.

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Radenski, Atanas. ""Python first"." ACM SIGCSE Bulletin 38, no. 3 (2006): 197–201. http://dx.doi.org/10.1145/1140123.1140177.

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Puneeth, Batchu, Rohil Gali Tanish, and Inturi Srujana. "Python source code Analysis for Bug Detection using Transformers." Engineering and Technology Journal 9, no. 04 (2024): 3772–77. https://doi.org/10.5281/zenodo.10992348.

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Effective bug detection is pivotal in software development, with the identification and localization of defects being crucial for robust applications. In Python-based programs, the conventional bug detection process relies on a Python interpreter, causing workflow interruptions due to sequential error detection. As Python's adoption surges, the demand for efficient bug detection tools intensifies. This paper addresses the challenges associated with bug detection in Python, focusing on the prevalence of built-in type bugs that can lead to code crashes. Building on recent advancements, this surv

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HINSEN, KONRAD. "HIGH-LEVEL PARALLEL SOFTWARE DEVELOPMENT WITH PYTHON AND BSP." Parallel Processing Letters 13, no. 03 (2003): 473–84. http://dx.doi.org/10.1142/s0129626403001434.

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One of the main obstacles to a more widespread use of parallel computing in computational science is the difficulty of implementing, testing, and maintaining parallel programs. The combination of a simple parallel computation model, BSP, and a high-level programming language, Python, simplifies these tasks significantly. It allows the rapid development facilities of Python to be applied to parallel programs, providing interactive development as well as interactive debugging of parallel programs.

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Егунов, В. А., and В. А. Шабаловский. "Using interpretation and compilation techniques to improve software efficiency." Цифровая экономика, no. 3(29) (September 24, 2024): 65–71. http://dx.doi.org/10.34706/de-2024-03-08.

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Статья подробно рассматривает применение методов компиляции и интерпретации кода в разработке программного обеспечения, акцентируя внимание на использовании абстрактных синтаксических деревьев (AST) для оптимизации и профилирования кода на примерах языков C++ и Python. Разъясняется процесс создания интерпретирующих профилировщиков на базе AST, которые интегрируют анализ производительности в процесс исполнения программы. Описываются этапы разработки интерпретаторов и применение инструментов, таких как Clang и Python, для работы с AST. В статье также представлены конкретные примеры построения и

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Wandira, Cintha Ayu, and Yudhiakto Pramudya. "DEVELOPMENT OF A PYTHON-BASED POSITION CALCULATION SYSTEM FOR THE MOON’S VISIBLE POSITION IN EQUATORIAL COORDINATES." EduFisika: Jurnal Pendidikan Fisika 8, no. 3 (2023): 356–62. http://dx.doi.org/10.59052/edufisika.v8i3.29053.

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In the field of astronomy, it is important to know the position of the moon in equatorial coordinates. However, these calculations can be difficult to do manually. Therefore, a system for calculating the visible position of the moon in Python-based equatorial coordinates has been developed. This system uses a suitable algorithm to calculate the visible position of the moon in equatorial coordinates. The calculation results obtained from this system are then compared with the simulation results from the Stellarium software. System for calculating the visible position of the moon in equatorial c

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Hashim, Firas Ali, Qabas Abdal Zahraa, Nadia Mahmood Hussien, and Yasmin Makki Mohialden. "Enhanced Priority-Integrated Mult winner Voting Software." Babylonian Journal of Artificial Intelligence 2024 (April 7, 2024): 27–33. http://dx.doi.org/10.58496/bjai/2024/005.

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Modern democracy values efficient, fair elections. This paper offers Google Cola an embedded interactive multi-winner voting method to improve democracy. Candidates and values can be entered using Python in the Colab. Basic Python algorithms and classes simplify priority candidate multi-winner elections. According to user feedback, event-driven programming modifies candidate priority enabling accurate and effective elections. These embedded system functions prioritize, rank, and aggregate votes. These mathematics facilitate fair and transparent outcome processing. This research demonstrates th

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V C, Dr Mahavishnu, Roopakumar R, Vikhas S G, and Abivishvas A. "Standalone Chatbot Application in Python." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (2022): 1244–50. http://dx.doi.org/10.22214/ijraset.2022.45445.

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Abstract: A chatbot is an artificial intelligence (AI) software that can simulate a conversation (or a chat) with a user in natural language through messaging applications, websites, mobile apps or through the telephone. This software is used to do duties such as replying swiftly to users, informing them, assisting with product purchases, and delivering better customer support. Business groups are increasingly using chatbots because they may minimize customer support costs and handle several consumers at once. However, in order to complete various jobs, chatbots must be as efficient as possibl

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Sugiarto, Sigit, John Nandito Lekitoo, and Ratnah Kurniati MA. "PYTHON IN ORDINARY DIFFERENTIAL EQUATIONS LEARNING." BAREKENG: Jurnal Ilmu Matematika dan Terapan 18, no. 4 (2024): 2531–42. http://dx.doi.org/10.30598/barekengvol18iss4pp2531-2542.

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Using software in mathematics learning can improve students' soft and hard mathematics skills at the high school and college levels. Therefore, using software in the learning process is important, including in learning Differential Equations. This research examines the use of the Python programming language with Jupyter Lab software and the SymPy library in solving ordinary differential equation problems symbolically in the Differential Equations course. The use of the Python programming language in Differential Equations learning includes solving linear ordinary differential equations of firs

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Zhang, Qiang, Lei Xu, Xiangyu Zhang, and Baowen Xu. "Quantifying the interpretation overhead of Python." Science of Computer Programming 215 (March 2022): 102759. http://dx.doi.org/10.1016/j.scico.2021.102759.

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Berciu, Liviu-Marian. "Pydsbuilder – A Dataset Builder Written in Python Django." Studia Universitatis Babeș-Bolyai Informatica 69, no. 2 (2025): 5–22. https://doi.org/10.24193/subbi.2024.2.01.

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Data mining and the analysis of open-source projects have become crucial in recent research, driven by the vast availability of data across multiple programming domains. This paper focuses on two main objectives: first, to present an experience report for designing a software quality data mining tool, and secondly, to provide an open-source solution, PyDs, that facilitates the creation of datasets specifically aimed at analyzing software quality attributes. PyDs, leveraging Python and the Django Framework, provides a comprehensive solution for researchers, encompassing data extraction from rep

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Pejovic, Predrag. "Application of python programming language in measurements." Facta universitatis - series: Electronics and Energetics 32, no. 1 (2019): 1–23. http://dx.doi.org/10.2298/fuee1901001p.

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Application of Python programming language in automation of measurement systems and creating virtual instruments is discussed in this paper. Requirements imposed to the software in order to perform these tasks are listed, and Python modules that support them are presented. Application of proposed techniques are illustrated in seven examples in different application areas. Analysis of software evolution, as well as the evolution of professional education yields conclusion that application of Python in automating measurement systems is promising.

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Oujezsky, Vaclav, and Tomas Horvath. "TRAFFIC ANALYSIS USING NETFLOW AND PYTHON." Informatics Control Measurement in Economy and Environment Protection 7, no. 2 (2017): 5–7. http://dx.doi.org/10.5604/01.3001.0010.4823.

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This article presents an application that is used as NetFlow collector and analyzer. It is a console application created in Python language. A software analyzer detects and analyzes incoming NetFlow messages version 1 and 5 of devices that support them. The output file is a database of information and analysis of the overall UNIX time duration of reported traffic and analysis of NetFlow lifetime. The software is developed to work with Python version 3 and higher and is designed for the Windows operating system.

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Pandey, Pankaj. "Python and Its Implications." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 02 (2025): 1–9. https://doi.org/10.55041/ijsrem41465.

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Python is a versatile, high-level programming language that has significantly influenced modern technology. Known for its simplicity, readability, and extensive library support, Python has become a cornerstone in fields such as web development, data science, artificial intelligence, and automation. Its impact extends beyond software development, playing a vital role in research, education, and industry innovations. This article explores Python’s key features, its widespread applications, and the challenges associated with its use, providing an in-depth understanding of its growing relevance in

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Tursunbek, Sadriddinovich Jalolov. "PARALLEL PROGRAMMING IN PYTHON." TECHNICAL SCIENCE RESEARCH IN UZBEKISTAN 1, no. 5 (2023): 178–83. https://doi.org/10.5281/zenodo.10394762.

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Parallel programming in Python has become increasingly popular as it allows developers to leverage the power of modern hardware by executing multiple tasks simultaneously. This article provides an overview of parallel programming in Python, exploring its benefits, challenges, and best practices. We discuss key concepts such as multi-threading, multi-processing, and libraries such as concurrent.futures and multiprocessing, which enable parallelism in Python. Additionally, we highlight the growing relevance of parallel programming in the context of modern software development and the potential p

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De Pra, Yuri, and Federico Fontana. "Programming Real-Time Sound in Python." Applied Sciences 10, no. 12 (2020): 4214. http://dx.doi.org/10.3390/app10124214.

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For its versatility, Python has become one of the most popular programming languages. In spite of its possibility to straightforwardly link native code with powerful libraries for scientific computing, the use of Python for real-time sound applications development is often neglected in favor of alternative programming languages, which are tailored to the digital music domain. This article introduces Python as a real-time software programming tool to interested readers, including Python developers who are new to the real time or, conversely, sound programmers who have not yet taken this languag

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Williams, Peter K. G., Casey J. Law, and Geoffrey C. Bower. "Rapid Development of Interferometric Software Using MIRIAD and Python." Publications of the Astronomical Society of the Pacific 124, no. 916 (2012): 624–36. http://dx.doi.org/10.1086/666604.

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Jin, Yuping. "Development of Word Cloud Generator Software Based on Python." Procedia Engineering 174 (2017): 788–92. http://dx.doi.org/10.1016/j.proeng.2017.01.223.

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Boudjema, Lotfi, Hanna Aarrass, Marwa Assaf, Marie Morille, Gaelle Martin-Gassin, and Pierre-Marie Gassin. "PySHS: Python Open Source Software for Second Harmonic Scattering." Journal of Chemical Information and Modeling 60, no. 12 (2020): 5912–17. http://dx.doi.org/10.1021/acs.jcim.0c00789.

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