flicKI

FlicKI is a test application that provides the possibility to download and filter images from Flickr. Official public API was used. Regarding Technical Challenge document there were some questions so desicion was to make on my own. On the main screen there is a search text field in the navigation bar. When some tags were written and pressed "Go" on the keyboard one row will be added with first 20 pictures that came up to according tags. If there are no pictures empty row will be created anyway. New tag = new row

Next mandatory requirements are fullfilled:

• Third party libraries are used
• App is pulled to GitHub
• Fetch data from the public API
• Metadata is visible for each image

As some optional:

• Image caching
• Share image
• Open image in browser
• Save image

Step by step development history

• Look into Flickr API, create singleton NetworkHandler class, connect Alamofire;
• Look for ready-to-go solutions for image caching. Connect Kingfisher;
• Decide to use ObjectMapper instead of checking all keys in dictionary manually, connect AlamofireObjectMapper, ObjectMapper, write PhotoResponse and Photo classes for handling Model
• Put some general stuff to storyboard, decide to create collectionView inside tableRow. This tutorial was used;
• Put textField to the Navigation Bar. Now all API calling are served with Activity Indicator from LLSpinner;
• Create DetailViewController with all views. Pass Photo instance to the Detail with the manual segue call from didSelect;
• Look for EXIF data extractor. Put all data to separate TextView that could be hidden/visible by pressing "Info" button;
• Implement UIActivityController passing UIImage to it;
• Create "Go" button for redirecting to the original FLickr web-page

Pods that are used

• Alamofire - HTTP networking library written in Swift;
• AlamofireObjectMapper - An extension to Alamofire which automatically converts JSON response data into swift objects using ObjectMapper;
• ObjectMapper - framework written in Swift that makes it easy for you to convert your model objects (classes and structs) to and from JSON;
• Kingfisher - lightweight, pure-Swift library for downloading and caching images from the web;
• LLSpinner - An easy way to handle full screen activity indicator.