Society of St. Andrew "Glean TN" web app

I chose the SoSA project at the Code for Nashville hackathon because I was already on board with the organization's mission to feed the hungry and curb food waste.

Our groups very first pass yielded a temporary solution leveraging Google forms and Google sheets by accessing the programmable code block in Google sheets.

The second stage of the project is a very simple jQuery app which uses Firebase to store user profiles and Formspree to generate an email notification to the SoSA office requesting gleaning. (This version is curently deployed)

The third iteration (in progress) is to migrate the current features to React for ease in extensibility, and the addition of a few more functional parameters as planned in conjunction with our Society of St. Andrew contact.

Yogo!

After taking yoga classes for years, I wanted an easy way to design my own home practice. I made Yogo to assist in the planning and practice of personalized yoga sequences.

Using NodeJS, Express, PostgreSQL, Sequelize, and Pug, Yogo allows a user to create and save yoga sequences for practice at home. The "All Poses" view with search and filter functionality allows any user to research various yoga poses, while the "My Poses" and "My Sequences" sections are only available to an authenticated user. The jQuery sortable plugin helps power the ability to drag and drop sequence cards to rearrange their order, and the new positions are automatically saved to the join table keeping the sequence's user poses. In sequence edit mode, the top panel includes a user's "My Poses" (any move already added to a sequence) for easy repeat access, and a side panel can be opened on the right to add new moves not yet used.

Playing a sequence gives the user a slideshow of their moves in order, so they can practice yoga along with the sequence they have built.

• Backend Capstone (demo November, 2017)

• See on Github

• Status: basic MVP

HANGRR

I built HANGRR to solve a personal recurring food indecision dilemma. I noticed that my inability to come up with a good idea of where to eat worsened as I became more "hangry," and that it would be more useful for me to be given suggestions which I could then reject one by one.

Built with AngularJS and styled with Bootstrap 4, HANGRR geolocates the user with HTML5, then leverages the Google Places API to find and suggest nearby, currently-open restaurants at random. If the user is logged in, the app filters out a Firebase-saved list of user blacklisted items and pushes user's "try-later" saved locations to the top of the suggestion array.

Features in progress include the ability to reject or blacklist entire chains or categories of food ("McDonald's" or "Chinese food") based on user preference or dietary restrictions.

This project continues to be in very slow development.