Text Analytics API Part 2

We need to serialize our request data into JSON and 0:00 then send it to the text analytics API URL. 0:03 I wanna to show you a quicker way to use JSON.net to serialize objects 0:07 using the JSON convert class. 0:11 You might have seen it earlier in the JSON.net documentation. 0:13 String request Json = 0:17 JsonConvert.SerializeObject and 0:20 will send it the sentimentRequest. 0:26 There's one small bug I found with our sentiment request class. 0:34 Let's go fix it before we build our request. 0:38 This JSON property needs to be documents. 0:41 Let's go check the JSON response in the docs to make sure it matches. 0:44 There it is, okay, let's get back to our method. 0:49 We need to convert our request based on into a byte array so 0:56 we can pass it to the upload data method. 0:59 Remember when we talked about encoding? 1:02 It's a good practice to use UTFA for sending data over the Web. 1:04 UTFA is the most compatible encoding. 1:08 Let's convert our string into a byte array using UTFA. 1:11 To do that, we can use the Encoding 1:16 class by RequestBytes = 1:21 Encoding utf8.GetBytes, 1:26 and we'll pass it. 1:31 Our requestJson. 1:34 Then we can send it to the URL in our upload data method. 1:37 But our URL is still the old one. 1:43 Let's delete that. 1:46 And we'll put a string placeholder and paste in request bytes. 1:48 We need to go grab the URL from the documentation and 1:53 paste it into the upload data method. 1:55 Here it is. 2:01 Copy and paste. 2:02 Now, we can use the json convert class to deserialize the response. 2:08 But we need a string for that. 2:13 Json convert only deals with strings. 2:14 String sentiments. 2:19 equals encoding dot UTF8 dot Get String. 2:21 And we'll pass it our response. 2:29 And now we can use the deserialize object method on Json convert. 2:31 Sentiment response equals Json convert dot deserialize 2:36 And our type parameter is sentiment response, 2:45 and then we need to pass it the string of sentiments. 2:51 All right looking good. 2:56 Now we need to do something with the sentiments from the news headlines. 2:58 We can add a property to the NewsResult class 3:02 to store the sentiment scores from our text analytics response. 3:05 Let's take a look at the response JSON again. 3:09 The score field has decimals, so which type do you think we should use? 3:14 How about a double? 3:18 It doesn't need to be super precise. 3:20 New search class and 3:25 NewsResult public double 3:28 SentimentScore get set. 3:33 Now let's go back up to main In our program class. 3:38 Let's see where we can call this method. 3:44 How about right after we call GetNewsForPlayer? 3:46 SentimentResponse sentimentResponse 3:51 = GetSentimentResponse And 3:58 we'll pass it our list of news results. 4:03 Then we can loop through the sentiment responses. 4:07 So for each var sentiment in 4:11 sentimentResponse.Sentiments Cause it's a list, 4:15 and then let's add another loop to find the correct news result and 4:25 update the score, foreach (var newsResult in newsResults). 4:30 Will add a check to see if the headline matches the ID of the sentiment and 4:41 then we'll add the score to the news result object. 4:46 So if the news result headline. 4:49 because if you remember we put the Sentiment.id equal to the headline. 4:55 Then we'll add the score to the news result object equals sentiment.score. 5:04 But we need to parse the string from sentiment into a double 5:14 We can use good old Double.TryParse. 5:17 We'll need a double to hold the value. 5:20 If Double.TryParse, and 5:23 in we'll pass it sentiment.Score, and out score. 5:29 And so if that's successful, 5:38 we'll assign newsresult.sentiment score equals score. 5:41 We can get rid of this line right here Okay, and since 5:49 we found a match we can break out of this loop to continue to the next news result. 5:56 Now, let's add the sentiment score to the text that we write to the console, 6:02 Sentiment Score and we'll pass it a 0. 6:07 Since it's at the beginning, and then we'll need to change all these that 6:12 follow, One more 6:16 in the list here. 6:22 So we've got 1, 2, 3, 4, and then we'll need to add the sentiment score On 6:27 the result object, result.SentimentScore, 6:32 and I like to double check the numbers, we go one, two, three, four. 6:38 One, two, three, four, great. 6:42 Let's run it and see what we get All right. 6:47 It looks like our sentiments are there, 6:53 but do you think we should format them a little better? 6:55 The scores are supposed to represent a percentage. 6:59 We can use a numeric format or in our string. 7:02 format method. 7:04 The letter P. 7:05 will format the numeric value into a percentage. 7:06 Stop debugging. 7:10 So a lot like our date formatter, right here we just do a :P. 7:13 Now let's see what we get. 7:17 All right, great. 7:23 It's a percentage. 7:25 You can find more ways to format numbers with the link in the notes. 7:27 It's a lot easier to read. 7:31 Let's see, this is two percent, missing the injured Marco Verratti and 7:34 Claudio [LAUGH] Struggled, 7:38 yeah, I guess that's a low sentiment. 7:43 Let's look at some other ones here, Looking for low ones 7:45 These are all pretty high, 9%. 7:54 Looks like somebody had hand surgery. 7:57 Suffered the injury. 8:02 Yeah, that's pretty low. 8:04 All right, great Fantastic job. 8:05 You learned a lot in this course. 8:11 We learned about file IO and how to read and write files to your computer. 8:13 Then we explored how to parse text data into dates and numbers. 8:17 We use Json.net for serialization and then send 8:21 it over the Web Now you can take what you've learned and build some projects. 8:24 Go find some JSON data that interests you and build an app around it or 8:29 better yet find an API and use it to grab data from the web. 8:33 I've put some project ideas for you in the notes. 8:37 Go forth and build things. 8:40