SentimentAnalysis - UIViewController

//
//  Twitter SentimentAnalysis
//

import UIKit
import SwifteriOS
import CoreML

class ViewController: UIViewController {

    let swifter = Swifter(
        consumerKey: "<##KEY##>",
        consumerSecret: "<##SECRET##>")

    let sentimentClassifier = TweetSentimentClassifier()

    override func viewDidLoad() {
        super.viewDidLoad()
        searchText.delegate = self
    }

    func sentimentAnalyze( key: String ) {
        swifter.searchTweet(
            using: key,
            lang: "en",
            count: 100,
            tweetMode: .extended,
            success: { results, metadata in
                var tweets = [TweetSentimentClassifierInput]()
                for i in 0..<100 {
                    if let tweet = results[i]["full_text"].string {
                        let tweetForClassification = TweetSentimentClassifierInput(text: tweet)
                        tweets.append( tweetForClassification )
                    }
                }

                do {
                    var sentimentScore = 0
                    let predictions = try self.sentimentClassifier.predictions(inputs: tweets)
                    for prediction in predictions {
                        let sentiment = prediction.label
                        if sentiment == "Pos" {
                            sentimentScore += 1
                        } else if sentiment == "Neg" {
                            sentimentScore -= 1
                        }
                    }
                    print( sentimentScore )
                } catch {}
        }) { _ in }
    }
}

extension ViewController: UITextFieldDelegate {
    func textFieldShouldReturn(_ textField: UITextField) -> Bool {
        textField.resignFirstResponder()
        if let text = textField.text { sentimentAnalyze(key: text ) }
        return true
    }    
}