
I developed Netpulse with the aim of deepening my theoretical knowledge of how computer networks work. I wanted to understand in concrete terms how data flows, how packets are structured, and how protocols interact with each other. By creating my own analyzer, I was able to move from the theory of network layers to a real, detailed observation of data traffic.
As the sole developer, I built a complete native application integrating an Electron interface and a data processing backend. I used the Scapy library in Python to drive packet capture and frame analysis. I programmed all the logic needed to dissect Ethernet, IP, TCP, and UDP protocols in order to display structured and understandable information in the application. I also designed the filtering system and network interface selection to provide a functional and intuitive analysis tool.
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My approach was to isolate low-level capture from user rendering to ensure accurate analysis without slowing down the interface. I set up a Flask server that acts as a bridge between the Python capture scripts and the Electron frontend. This architecture allowed me to process packets in real time, transform them into JSON objects, and then send them to the interface for immediate visualization. This forced me to optimize communication between the different processes to efficiently manage potentially large data flows.
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