Our team set out to solve the problem of finding the right teammates/friends for gaming as we found that while the amount of people gaming had increased due to the extended lockdowns, the amount of diagnosed cases of depression had nearly tripled in the US alone. To approach this problem, we strived to create a website/product that connected gamers of all backgrounds based on their preference of games. We first thought of creating an algorithm in python to match users’ data using a txt files to store user data and an html-based website with the ability to input data into the txt files for each user. A problem we as a team had overall at the start was the fact that many of us in the team had not used Figma or had much coding experience which meant that we had to jury rig many aspects of software design in a rushed timespan in order to keep on track. Similarly, during the build week, we end up accidently coding several key components multiple times individually which end up wasting precious time and causing errors in our product. In the end we realised that SQL (Structured Query Language) was more efficient in not only storing data but allowed us to manipulate the data much more efficiently and cleaner without having to run through multiple separate python functions. This not only reduced time complexity of the function but allowed easier integration into our html-based website. But, in converting our entire program to SQL we were forced to remove all our python algorithms that we had written which at that point was several days’ worth of python coding. In the end we managed to make a functioning product that can tell users what other users of the websites are playing the same games as them and help connect players together.will add later

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