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Self-Care Center

Self-care-center

Abstract:

I built an app that allows users to receive random affirmation messages or mantra messages, depending upon which message type was chosen. Users can save their favorite messages and navigate to a favorited messages page to view them. Users can delete any of messages on the favorites page by clicking a delete button.

Installation Instructions:

  1. Open your terminal.
  2. Navigate to the directory where you would like this project to be stored.
  3. Run git clone [email protected]:Espressogoddess/self-care-source.git.
  4. Run cd self-care-center to move into the project directory.
  5. Run open index.html in terminal to launch the application in the web browser.

Preview of App:

image

Context:

This project was completed in ~12 hours during my third week as a Turing student.

Contributors:

Amber

Learning Goals:

  • Gain knowledge and experience building an app from scratch utilizing HTML, CSS, and JavaScript
  • Know how to utilize HTML and CSS to match a provided comp
  • Understand how to listen to and respond to user events
  • Individualize my programming skill set

Wins + Challenges:

Wins

  • A major win was figuring out the view logic for showing the message depending upon if affirmation or mantra was selected.
  • A win was utilizing pseudocode to help with logic
  • A win was also utilizing a feature branch that only implemented changes that aligned with that branch (which meant saving some features/changes for later while keeping the focus on the respective branch).

Challenges

  • It was challenging to effectively use CSS to alignment elements on the page to match the comp. I overcame this challenge with trial and error.
  • It was challenging to wrap my head around the way in which to utilize the data model as the source of truth and using that to update the DOM. I compared and contrasted various approaches/solutions and analyzed them to figure out if it was using the DOM or data model and it began to make sense.

Languages

  • JavaScript 58.3%
  • HTML 23.8%
  • CSS 17.9%