Part of an iphone application (twitter login + json data parsing) / Swift!
$10-30 USD
Paid on delivery
Not really a complete application, as is pretty much two view controllers I'have been having trouble with and want to use for learn by seeing how people do things.
The quick version of it is:
Make two controllers, a login with twitter one and table view one.
The first controller should have a generic "login with twitter" button, that logs you "in" as a user (not as an application). (OAuth etc)
Then, the twitter api makes a GET friends/ids (1) and a GET followers/ids (2)
to get an up to 5000 list of either. Eventually parsing the data into two arrays I am guessing.
A new array is then created out of ids that exist only in both arrays. So logically this sieves the results down to people/ids that you are following AND are following you.
Then, through GET users/lookup (3)
These IDs are converted into an array of user objects. Incidentally, out of these, the only data I care about is name, screen name and profile images. The rest can be tossed away.
Finally, the user objects of that array are loaded into a table view. The cell composed of the user pictures on the left side, and the name & handle on the right side one on top of the other. See attached image for how it should look.
(No need to do the corner rounding in the image if it is too hard)
I reckon that for someone super experienced with the Twitter api, and basically making table view controller cells this should actually be a breeze.
Notes:
a) It needs to be in Swift
b) I am aware of the GET friends/list GET followers/list calls but as I understand it they are limited to 300 results every 15 minutes. This whole process is basically a way to get around that. Incidentally, if there is a better way to do this I'd love to hear about it.
d) I assume that the process takes some time if theres a lot of results so the status bar should display an iOS spinner while the table is loading.
(1) [url removed, login to view]
(2) [url removed, login to view]
(3) [url removed, login to view]
Project ID: #7705696
