MealSecure

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  Landing page

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  Results page

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  Donate

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  About

Inspiration

We were inspired to create MealSecure to combat the lack of awareness about the inaccessibility of food across the US.

What it does

MealSecure uses data about places with limited access to food to encourage people to support a list of non-profit organizations that work to establish food security for all.

How we built it

We used Pandas to clean/interpret a 2019 USDA database with around 72,000 entries. We used Python, HTML, and CSS.

Challenges we ran into

We struggled with finding this database. At first, we spent a great deal of time researching potential APIs (Google Cloud included).

Accomplishments that we're proud of

We're proud of using Flask to connect our front- and backend.

What we learned

We learned that working without an API is quite difficult. We also learned how to work with GitHub and how to resolve merge conflicts.

What's next for MealSecure

We would like to create a visual representation for the number of people a user's donation would affect so that they can see how much of an impact they can make in their specific communities. We would also like to use APIs to more easily access a greater and more up-to-date pool of data to use.

Built With

• css
• flask
• html
• pandas
• python