twister904 / mood-lifter

mood lifter website using public api

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Mood-lifter

![Mood-lifter Banner]

Mood-lifter is a web application designed to brighten your day and provide entertainment when you're feeling bored or in need of a mood boost. This project consists of both the frontend and backend components.

Introduction

Do you ever find yourself feeling bored and in search of something fun, educational, or heartwarming to do? Mood-lifter is here to help! Whether you're looking for an exciting activity to engage in or a cute animal picture to make you smile, this web app has got you covered.

Mood-lifter offers two main features:

  1. Boredom Buster: Find a wide variety of activities to do when you're bored, categorized by type and the number of participants. From educational pursuits to relaxation and DIY projects, Mood-lifter has it all.

  2. Animal Lover's Delight: Enjoy adorable images of cats, dogs, and birds to lift your spirits. You can even select the specific animal type you want to see.

Technologies Used

  • Express.js: A web application framework for Node.js.
  • Axios: A promise-based HTTP client for making requests to external APIs.
  • EJS: A simple templating engine for generating HTML with JavaScript.

Installation

To set up your own instance of Mood-lifter, follow these steps:

  1. Clone the Repository: git clone https://github.com/twister904/mood-lifter.git

  2. Navigate to the Project Folder:

  3. Navigate to the Project Folder:

  4. Install Required Modules: npm install This command will install all the necessary Node.js modules and dependencies required for the project.

  5. Start the Server: nodemon index.js This command will start the server using Nodemon, which helps in automatically restarting the server whenever changes are made to the code.

Your Mood-lifter server will be up and running, and you can access the website at http://localhost:3000 in your web browser. Enjoy your Mood-lifting experience!

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mood lifter website using public api


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Language:EJS 45.5%Language:CSS 31.2%Language:JavaScript 23.2%