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BoomerConsumer

The Boomer Consumer is a website to pair boomers with millenials and Gen-Z (Zoomers) to help them buy whatever they need at this time of crisis. Specifically, the goal of this website is to match boomers and people who are being affected by COVID-19 with zoomers and healthy people who can volunteer to purchase goods for the more vulnerable.

Boomers can sign up on the website and make a post for what they need. Zoomers can then sign up and look at postings, and filter them by postal code to find the boomer that is nearest to them.

How it works

We used Django with sqlite3 as a backend to the project. The Boomers and Zoomers are saved into the database with all their information. The features of adding and taking a request are done by assigning a zoomer id to the request object whenever it is taken and will be used to track the request. The boomer consumer listing for Zoomers allow Zoomers see the Boomers in the most need in their closest proximity by making a calculating the distance in geological position (latitude and longitude). The geological position is inserted into the database when the user is first created by making a request to a website that converts postal code to geological coordinates. The distance is dynamically calculated to determine how far the user is from the people they are helping or the people that are helping them

How we built it

We used the Django web framework with python3 as the programming language.bootstrap snippets were used for form design.

Challenges we ran into

Sometimes Django can be quite inflexible when it comes to code, so we reached some major roadblocks that we needed to find other ways to implement the same function in a way Django works with. Unfortunately, the website we used to request for the addresses blocked our ip addresses since our testing was very thorough.

What we learned

We learned how to use Django, as well as how to dynamically access variables in a database and save it. We also learned how to make requests to websites and parse the result into python. Next time we'll use Node JS or React