Image Search Abstraction Layer 📷

This service accepts a search string as a parameter and will return a set of images relating to the given search string. The JSON response includes the image's URL, alt text, thumbnail link, and context link. You can also get a list of the most recently submitted search strings.

You can test it at https://img-search-layer-microsrvc.herokuapp.com

A Full Stack Javascript application built using MongoDB, Node.js and Express. An API Project for FreeCodeCamp.

Example Creation Usage

To retrieve a set of images, pass a search term to path https://img-search-layer-microsrvc.herokuapp.com/api/imagesearch/[SEARCHTERM]

You can also paginate through the responses by adding a ? offset=[number] parameter to the URL path.

Valid Image search API call examples

   https://img-search-layer-microsrvc.herokuapp.com/api/imagesearch/puppies
   https://img-search-layer-microsrvc.herokuapp.com/api/imagesearch/puppies?offset=2

Example Creation Output

[
  {
  url: "https://www.dogliciousspa.com/v/vspfiles/assets/images/puppiesplaying.jpg",
  alt_text: "Puppy Socialization, Puppy Class, Training, Dogs, Dog Training ...",
  thumbnailLink: "https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcSwKw73Q78qFF4WA8BrYpA6T_C0cZgd6yvM6QNjQhzJMHrW02vu0UxMjt5h",
  contextLink: "https://www.dogliciousspa.com/category-s/171.htm"
  },
  {
  url: "https://i.ytimg.com/vi/2Y1ZyjGdPeE/maxresdefault.jpg",
  alt_text: "Puppies Talking and Arguing With Their Humans Compilation - YouTube",
  thumbnailLink: "https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcSAoM6k7NCjsTVjuvRXTelL7s8XEI0LNicjVZPz4Wy2FkdFMbPJ7xHX5W8",
  contextLink: "https://www.youtube.com/watch?v=2Y1ZyjGdPeE"
  },
  .
  .
  .
]

To get list of the most recent submitted search strings

Make a request to:

  https://img-search-layer-microsrvc.herokuapp.com/api/recent

To Run Project Locally

Prerequisites

In order to run this project locally, you should have the following installed:

• Node.js
• NPM
• MongoDB

You should also:

1. Create a Google Custom Search Engine https://cse.google.com/cse: Do not specify any sites to search but instead use the "Restrict Pages using Schema.org Types" under the "Advanced options". For the most inclusive set, use the Schema: Thing. In your search engine settings, enable "Image search". Make a note of the CSE ID.

2. Set up a Google Custom Search Engine API: Register a new app and enable Google Custom Search Engine API Google Developers Console. Make a note of the API key.

Installation & Startup

1. Fork this repo

2. Clone the fork

3. Install Dependencies: $ npm install

4. Run your MongoDB server: $ mongod --port 27017 --dbpath=./data

   Note: Your mongoDB is now running at: mongodb://localhost:27017/<your_database_name>

5. Add a .env file to your project's root directory and set MONGO_CONNECTION_STRING to mongodb://localhost:27017/<your_database_name>

   MONGO_CONNECTION_STRING=mongodb://localhost:27017/<your_database_name>

   

6. You wil also need the CSE ID and your Google CSE API Keys in your .env file and name them CSE_ID and CSE_API_KEY, respectively

     CSE_ID=<your_cse_id>
     CSE_API_KEY=<your_google_cse_api_key>

   

7. Start the Server: $ node app.js

8. Visit http://localhost:3000/

Enjoy! 💙