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DoBeDo

DoBeDo applies the notion of quantified self to the question of how to spend our time if optimizing for happiness. Users track how they feel before and after regular activities to better recognize which ones have the most positive impact on their mood.

At signup, they select up to ten activities to track. Going forward, they record when they plan to do an activity and how they're feeling about doing it. Afterward, once they've done it, they then also log what time they finished and how actually felt doing it. The app then provides a visualization of their expected and actual sentiment toward all recorded occurrences of each activity over time. Also, if the user provides their phone number when signing up for an account, they receive an automated text message reminder if 24 hours have passed since the stated starting time for a planned activity and they haven't yet recorded how they felt about it afterward.

Tech Stack

  • Python
  • Flask
  • Flask-SQLAlchemy
  • PostgreSQL
  • JavaScript
  • Bootstrap
  • jQuery
  • Jinja
  • Chart.js
  • Twilio API

Screenshots and Features

Screenshot of landing page

A user can create an account. Their password is hashed in the database, and providing a phone number indicates they've opted in for text message reminders about outstanding planned activities.

Screenshot of account creation page

Screenshot of sign-in page

A user can indicate up to 10 activities to track.

Screenshot of activity setup page

A user can record what time they plan to start doing one of their activities and how they're feeling about it at that time. They can also record, afterward, how they actually felt when doing it and what time they finished.

Screenshot of Before_activity page

Screenshot of After_activity page

A user can view charts showing expected and actual sentiments toward all occurrences of each activity they're tracking over time from the main page's dashboard.

Screenshot of Dashboard page

TODO

  • Additional data viz or calendar integration leveraging duration data
  • More tests!

About the Developer

Amber recently graduated from the full-stack software engineering fellowship at Hackbright Academy in San Francisco. This is her first web application, and her favorite parts about building it were creating the data model, unbreaking (and sometimes re-breaking and then again unbreaking) things, and coming to really appreciate the convenience and elegance provided by an ORM.

You can learn more here: www.linkedin.com/in/amberstaab/

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