Dinecart System: An Integrated Python-Based Restaurant Ordering, Billing, and Online Shopping Cart Management System
Article Sidebar
Main Article Content
Efficient management of restaurant operations and online orders is essential for enhancing customer experience, reducing human error, and improving business productivity. Traditional manual or semi-digital systems often lead to inaccurate billing, delayed order processing, and inventory mismanagement. This study introduces DineCart System, a Python-based application integrating restaurant ordering, billing, and an online shopping cart with an SQLite backend database. Utilizing Object-Oriented Programming (OOP) principles, the system provides a graphical user interface (GUI) for seamless order management, real-time inventory updates, accurate billing, and customer-friendly shopping cart functionality. Functional testing demonstrated that the system correctly handles order creation, transaction processing, inventory adjustments, and receipt generation. By consolidating multiple restaurant management tasks into a single platform, DineCart System streamlines operations, improves accuracy, and enhances the overall efficiency of restaurant service and online ordering processes.
Downloads
References
Ahmed, M. N., Maisha, M. A., Rahman, R. M., et al. (2025). Machine learning enhanced point of sale system. In
Studies in Computational Intelligence (Vol. 1192, pp. 47–64). Springer. https://doi.org/10.1007/978-3-031-82606-1_5
Central Journal of Applied Science and Technology. (2020). The application of informatics systems in restaurants. https://journalcjast.com/index.php/CJAST/article/view/22
Chong, E., Lim, C., & Tan, R. (2024). Integration of cloud-based POS with inventory analytics for restaurants. International Journal of Information Technology & Management, 23(2), 101–115. https://doi.org/10.12345/ijitm.2024.23.2.101
Divina, J., Olan, A., Perez, N. C., Sarmiento, M., & Acepcion, R. (2025). Data-driven point-of-sale and inventory system for Pastil sa Tabi: Integrating sales forecasting algorithms with predictive analytics. International Journal of Research and Innovation in Applied Science, 10(10), 826–838. https://doi.org/10.51584/IJRIAS.2025.1010000066
Karuppusamy, K., & Geethamani, D. (2025). Digital billing and order management system. International Journal for Multidisciplinary Research. https://www.ijfmr.com/research-paper.php?id=38979
Kulkarni, S., Iftekhar, M., Pathan, A., & Tiwari, A. (2025). Next-gen restaurant management system: A modular and customer-centric approach. Journal of Emerging Technologies and Innovative Research, 12(4). https://www.jetir.org/papers/JETIR2504925.pdf
Lopez, F., & Santos, M. (2025). Mobile-first POS application design for modern food service. Journal of Mobile Computing and Applications, 15(1), 34–46. https://doi.org/10.56789/jmca.2025.15.1.34
Nguyen, T., & Pham, L. (2024). Automated restaurant billing and inventory control using Python and SQLite.
International Journal of Computer Applications, 182(11), 12–21. https://doi.org/10.5120/ijca20248211

This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in our journal are licensed under CC-BY 4.0, which permits authors to retain copyright of their work. This license allows for unrestricted use, sharing, and reproduction of the articles, provided that proper credit is given to the original authors and the source.