StreamKit

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  Simple Calculator

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  Graphing Utility Output

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  Whiteboard/Canvas

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  Matlab Calculator Output

Inspiration

The inspiration for StreamKit came from my desire to create a versatile and user-friendly tool that could serve multiple purposes within a single web application. I wanted a platform where I could access a calculator, generate graphs, and use a whiteboard or canvas for various tasks, all seamlessly integrated into one cohesive interface. Aside from that Omni Calculator, Skribbl.io, and Desmos were big inspirations that lead me to want to do this project.

What it does

As a proof of concept, it is a calculator, graphing utility, and a whiteboard/canvas. A more robust form could handle much more complex calculations and visual fidelity.

How I built it

I used Python, Streamlit, Github Codespaces, VSCode, and Matlab to do this project. Not being experienced in using most of these lead to a constant journey of learning the past two days. From figuring out python code and finding the best canvas library for Streamlit I built this project step by. It is mostly basic python with some help of Matlab Engine and some unique libraries.

Challenges I ran into

Not having used Python much and never having used Streamlit meant I had to learn how to used them from scratch. Learning to use Streamlit and Matlab took a long time. Most of the time one thing would break the compatibility with the other. Cloud computing or deploying online was not working because I couldn't get Matlab engine to run over the cloud network which is why I had to host it locally.

Accomplishments that I am proud of

I am proud of making something tangible in the my first hackathon. I am proud of making something functional and close to what I had expected to make. I am happy to have had an educational experience out of it.

What I learned

I learned that Python can be great in terms of ease of coding but it can be very slow at times. I learned to use a lot of cloud computing services and api linking. Matlab was something educational and quite intriguing. I learned to code from a slightly different perspective because Python can be very different from C, Java, or C++ at times. I learned that even the simplest coding problems can take hours of frustration to get through and I also learned that the eureka that awaits at the end of it is what really makes it seem simple in the first place.

What's next for StreamKit

I wish to further develop and learn from the project and make it into a more robust tool.

Built With

• codespaces
• github
• python
• streamlit
• vscode