A Program for Analyzing the Structure of a Web site Development Using the Parsing Method Based on the Python
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Keywords

Parsing, Website, Structure, Python, Analysis, Manufacturing Innovation, Industrial Innovation

How to Cite

Vladyslav Yevsieiev, Svitlana Maksymova, & Ahmad Alkhalaileh. (2024). A Program for Analyzing the Structure of a Web site Development Using the Parsing Method Based on the Python. Journal of Universal Science Research, 2(4), 172–183. Retrieved from https://universalpublishings.com/index.php/jusr/article/view/5261

Abstract

This article discusses the development of a program in Python to analyze the structure of a website using the parsing method. The work presents the developed algorithm for the program, describes the software and conducts experiments on web site parsing. The program's algorithm includes sending a GET request to a website, receiving and analyzing the HTML code of the page using the BeautifulSoup library. The find_all('a') method was used to analyze the website structure and extract link information. The obtained data was processed and displayed in a convenient format. It allows you to automate the process of analyzing the structure of a website, which can be useful for web developers, SEO specialists and web resource owners.

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References

Omarov, M., Tikhaya, T., & Lyashenko, V. (2019). Internet marketing metrics visualization methodology for related search queries. International Journal of Advanced Trends in Computer Science and Engineering, 8(5), 2277-2281.

Z. Deineko, "Features of Database Types," International Journal of Engineering and Information Systems (IJEAIS), 2021, vol. 5, issue 10, pp. 73-80.

S. Sotnik, T. Shakurova, and V. Lyashenko, “Development Features Web-Applications,” vol. 7, no. 1, pp. 79–85, 2023.

Sotnik, S., Manakov, V. and Lyashenko, V. (2023), “Overview: PHP and MySQL features for creating modern web projects”, International Journal of Academic Information Systems Research, Vol. 7, No. 1, pp. 11-17.

Omarov, M., TYKHA, T., & Lyashenko, V. (2019). Use of Wavelet Techniques in the Study of Internet Marketing Metrics. Eskişehir Technical University Journal of Science and Technology A-Applied Sciences and Engineering, 20, 157-163.

Abu-Jassar, A. T., Attar, H., Yevsieiev, V., Amer, A., Demska, N., Luhach, A. K., & Lyashenko, V. (2022). Electronic User Authentication Key for Access to HMI/SCADA via Unsecured Internet Networks. Computational intelligence and neuroscience, 2022, 5866922.

Al-Sherrawi, M. H., Lyashenko, V., Edaan, E. M., & Sotnik, S. (2018). Corrosion as a source of destruction in construction. International Journal of Civil Engineering and Technology, 9(5), 306-314.

Vasiurenko, O., Lyashenko, V., Baranova, V., & Deineko, Z. (2020). Spatial-Temporal Analysis the Dynamics of Changes on the Foreign Exchange Market: an Empirical Estimates from Ukraine. Journal of Asian Multicultural Research for Economy and Management Study, 1(2), 1-6.

Lyashenko, V., Matarneh, R., & Kobylin, O. (2016). Contrast modification as a tool to study the structure of blood components. Journal of Environmental Science, Computer Science and Engineering & Technology, 5(3), 150-160.

Nevliudov, I., Yevsieiev, V., Lyashenko, V., & Ahmad, M. A. (2021). GUI Elements and Windows Form Formalization Parameters and Events Method to Automate the Process of Additive Cyber-Design CPPS Development. Advances in Dynamical Systems and Applications, 16(2), 441-455.

Mustafa, S. K., Yevsieiev, V., Nevliudov, I., & Lyashenko, V. (2022). HMI Development Automation with GUI Elements for Object-Oriented Programming Languages Implementation. SSRG International Journal of Engineering Trends and Technology, 70(1), 139-145.

Babker, A., & Lyashenko, V. (2018). Identification of megaloblastic anemia cells through the use of image processing techniques. Int J Clin Biomed Res, 4, 1-5.

Mustafa, S. K., Lyashenko, V., Ameer Ahamad, N., Rehan, M., & Ajmal, A. A. (2021). Some aspects of modeling in the study of COVID-19 data. International Journal of Pharmaceutical Research, 4124-4129.

Kuzomin, O., Lyashenko, V., Dudka, O., Radchenko, V., & Vasylenko, O. (2020). Using of ontologies for building databases and knowledge bases for consequences management of emergency. International Journal of Advanced Trends in Computer Science and Engineering, 9(4), 5040-5045.

Khan, A., Ahmad, M., Joshi, S., & Lyashenko, V. (2016). Synthesis of Alumina Fibre by Annealing Method using Coir Fibre. American Chemical Science Journal, 15(2), 1-7.

Al-Sharo Y., & et al. (2023). A Robo-hand prototype design gripping device within the framework of sustainable development. Indian Journal of Engineering, 2023, 20, e37ije1673.

Yevsieiev, V., & et al. (2024). The Canny Algorithm Implementation for Obtaining the Object Contour in a Mobile Robot’s Workspace in Real Time. Journal of Universal Science Research, 2(3), 7-19.

Shcherbyna, V., & et al. (2023). Mobile Robot for Fires Detection Development. Journal of Universal Science Research, 1(11), 17-27.

Yevsieiev, V., & et al. (2024). Object Recognition and Tracking Method in the Mobile Robot’s Workspace in Real Time. Technical Science Research In Uzbekistan, 2(2), 115-124.

Basiuk, V., & et al. (2023). Mobile Robot Position Determining Using Odometry Method. Multidisciplinary Journal of Science and Technology, 3(3), 227-234.

Yevsieiev, V., & et al. (2024). Active Contours Method Implementation for Objects Selection in the Mobile Robot’s Workspace. Journal of Universal Science Research, 2(2), 135-145.

Nikitin, V., & et al (2023). Traffic Signs Recognition System Development. Multidisciplinary Journal of Science and Technology, 3(3), 235-242.

Yevsieiev, V., & et al. (2024). Using Contouring Algorithms to Select Objects in the Robots’ Workspace. Technical Science Research In Uzbekistan, 2(2), 32-42.

Nevliudov, I., & et al. (2023). Mobile Robot Navigation System Based on Ultrasonic Sensors. In 2023 IEEE XXVIII International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED), IEEE, 1, 247-251.

Yevsieiev, V. V., & et al. (2023). Conveyor Belt Object Identification: Mathematical, Algorithmic, and Software Support. Appl. Math. Inf. Sci, 17, 1073-1088.

Al-Sharo, Y. M., Abu-Jassar, A. T., Sotnik, S., & Lyashenko, V. (2023). Generalized Procedure for Determining the Collision-Free Trajectory for a Robotic Arm. Tikrit Journal of Engineering Sciences, 30(2), 142-151.

Lyashenko, V., Laariedh, F., Ayaz, A. M., & Sotnik, S. (2021). Recognition of Voice Commands Based on Neural Network. TEM Journal: Technology, Education, Management, Informatics, 10(2), 583-591.

Lyashenko, V., & Sotnik, S. (2022). Overview of Innovative Walking Robots. International Journal of Academic Engineering Research (IJAER), 6(4), 3-7.

Attar, H., Abu-Jassar, A. T., Lyashenko, V., Al-qerem, A., Sotnik, S., Alharbi, N., & Solyman, A. A. (2023). Proposed synchronous electric motor simulation with built-in permanent magnets for robotic systems. SN Applied Sciences, 5(6), 160.

Lyashenko, V., & et al.. (2021). Semantic Model Workspace Industrial Robot. International Journal of Academic Engineering Research, 5(9), 40-48.

Sotnik, S., Mustafa, S. K., Ahmad, M. A., Lyashenko, V., & Zeleniy, O. (2020). Some features of route planning as the basis in a mobile robot. International Journal of Emerging Trends in Engineering Research, 8(5), 2074-2079.

Alnavar, K., & et al. (2021). Document Parsing Tool for Language Translation and Web Crawling using Django REST Framework. In Journal of Physics: Conference Series, IOP Publishing, 1962(1), 012018.

Nigam, H., & Biswas, P. (2021). Web scraping: from tools to related legislation and implementation using python. In Innovative Data Communication Technologies and Application: Proceedings of ICIDCA 2020, Springer Singapore, 149-164.

Kumar, S., & Roy, U. B. (2023). A technique of data collection: web scraping with python. In Statistical Modeling in Machine Learning, Academic Press, 23-36.

Jin, D. (2021). Image information collection system based on Python Web crawler technology. converter, 606-612.

Roumeliotis, K. I., & Tselikas, N. D. (2023). A Machine Learning Python-Based Search Engine Optimization Audit Software. In Informatics, MDPI, 10(3), 68.

Ablahd, A. Z. (2023). Using python to detect web application vulnerability. Res Militaris, 13(2), 1045-1058.

Andersson, P. (2021). Developing a Python based web scraper: A study on the development of a web scraper for TimeEdit.

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