pabloferrari / agile-engine-test

Agile Engine Test

Image gallery Search

Intro

Imagine that you are involved in the development of a large file storage system. Special feature here is storing photos and images. We need to provide our users with the possibility to search stored images based on attribute fields.

Requirements

• We need to see your own code.
• The app should load and cache photos from our API endpoint http://interview.agileengine.com
• Obtain a valid Bearer token with valid API key (don't forget to implement invalid token handler and renewal)

  POST http://interview.agileengine.com/auth

Body: { "apiKey": "23567b218376f79d9415" }
Response: { "token": "ce09287c97bf310284be3c97619158cfed026004" }

• The app should fetch paginated photo feed in JSON format with the following REST API call (GET):
  GET /images
  Headers: Authorization: Bearer ce09287c97bf310284be3c97619158cfed026004
  Following pages can be retrieved by appending ‘page=N’ parameter:
  GET /images?page=2
  No redundant REST API calls should be triggered by the app.

• The app should fetch more photo details (photographer name, better resolution, hashtags) by the following REST API call (GET): GET /images/${id}
• The app should fetch the entire load of images information upon initialization and perform cache reload once in a defined (configurable) period of time.
• The app should provide a new endpoint: GET /search/${searchTerm}, that will return all the photos with any of the meta fields (author, camera, tags, etc) matching the search term. - The info should be fetched from the local cache, not the external API.
• You are free to choose the way you maintain local cache (any implementation of the cache, DB, etc). The search algorithm, however, should be implemented by you.
• We value code readability and consistency, and usage of modern community best practices and architectural approaches, as well, as functionality correctness. So pay attention to code quality.
• Target completion time is about 2 hours. We would rather see what you were able to do in 2 hours than a full-blown algorithm you’ve spent days implementing. Note that in addition to quality, time used is also factored into scoring the task.

Solution

Run proyect as node service

1 - npm install

2 - cp .env .env.example

3 - npm install

4 - Run MongoDB on port 27017

5 - npm start

Run proyect with docker compose

1 - npm install

2 - docker-compose up -d

Endpoints

- Get images

GET http://localhost:3000/api/images

- Get image by id

GET http://localhost:3000/api/images/:id

- Search Image by Author, Tag, Camera

GET http://localhost:3000/api/search/:searchTerm