Project Abstract

Jupyter notebooks are widely used by data scientists, but linear programming can be difficult for complex projects. GRAPHBLOCKS emerges as a game changer by introducing a web-based graphical interface that changes the way data scientists work with their code. This interface uses acyclic graphs (DAGs) to represent code operations as opposed to traditional linear structures. This innovative approach has many benefits: Improve transparency: DAGs are an intuitive way to understand the flow of code in a project. GRAPHBLOCKS promotes a deeper understanding of how the entire codebase works by visualizing the dependencies between different blocks of code. Simplicity is better: the linear structure of notebooks limits code preparation. GRAPHBLOCKS frees data scientists from these limitations. A graphical interface makes it easier for you to configure your code, making it more manageable, especially for complex projects. Collaboration: Data science projects require collaboration. GRAPHBLOCKS promotes collaboration by visualizing the workflow of your code. Team members can understand the project structure, constraints, and individual code contributions, and communicate and collaborate better. The development of GRAPHBLOCKS includes methods such as breakthrough development and user-centered design to meet the specific needs of computer scientists. data In addition, seamless integration with the existing Jupyter core ensures a clean and comfortable working environment. The evaluation confirms the effectiveness of GRAPHBLOCKS, showing significant improvements in efficiency, effectiveness and collaboration between users. In fact, GRAPHBLOCKS acts as a bridge between code and visualization, in the technical aspect and beyond the technical aspects of GRAPHBLOCKS. the data science gap between the knowledge base. This breakthrough paves the way for advances in data science, ultimately accelerating innovation in the field..

Keywords: Web Applications, Software Engineering, programing languages

 Conference Details

Session: Presentation Stream 21 at Presentation Slot 3

Location: GH022 at Wednesday 8th 09:00 – 12:30

Markers: C�cilia Pradic, Joe Macinnes

Course: MSc Advanced Computer Science, Masters PG

Future Plans: I’m looking for an industry placement