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Monday, April 8, 2019

Xamarin New Features in Visual Studio 2019

Introduction:


Visual Studio 2019 publicly available from April 2 2019 and it’s includes many improvements for Xamarin mobile developers in Visual Studio. Microsoft mainly focused on key areas to make more productive when authoring Xamarin apps, including optimizations to build and deployment times as well as improvements to UI authoring experiences.

Let we look today steps by step all the awesome Visual Studio 2019 Xamarin Developer. Visual Studio 2019 and Visual Studio 2019 for Mac are now available so you can start download and start use with awesome VS feature .



Lower disk impact

VS2019 release focuses on the fundamental’s stability and performance. Visual Studio 2017 required minimum 23 GB or more, but visual studio 2019 is now 3.28x smaller in the size, it’s Just 5GB to 7GB and you can do faster installation with lower disk impact, no need to wait very long time for installation.



Solutions creation


Visual studio team improved solutions creation time by up to 2x and solutions load time by 23% on real world profiled solutions.





Android SDK Update:

Managing Android SDKs can be very difficult, especially when working on complex solutions across teams. Some of them not aware, difference between target, compile, and minimum framework version, Visual studio 2017 tried for Android SDK auto update but manually enable from Tool options .

Visual Studio 2019 will automatically analyze our app while project load, determine if you have the necessary Android SDK configuration to build, and offer to install those components for you to resolve any configuration conflicts.



Faster Build and Deployment:

Visual studio 2019 improved Xamarin Build and Deployment, you can check your enterprise application build times are 26.6% faster than Visual studio 2017version and Deployment times are now twice as fast.




Shell Project template

Visual studio 2019 added Shell project template to the Xamairn Form. Shell provides 3 tiers of elements to our application and then gets out of your way to start populating the app with content and features.In Shell template you will get it following


A simplified way to express the high level of your application architecture in a single file (AppShell.xaml)


A hierarchy of common UI navigation patterns that suite your target mobile platforms: flyout menu, bottoms tabs, top tabs


A robust navigation service that provides URI-based routing so you can jump directly to any part of your application with ease


An extensible template-based infrastructure to easily customize elements of your UI



Visual design experiences for iOS and Android

Visual Studio 2019 improved new IntelliSense experience for XAML with matching around the control and property names to ensure you receive the correct suggestion.

The XAML Previewer shows you how your Xamarin.Forms XAML page will look on iOS and Android. When you make changes to your XAML, you'll see them previewed immediately alongside your code. The XAML Previewer is available in Visual Studio and Visual Studio for Mac.

You can now edit common attributes for your Xamarin.Forms controls in the property panel for Visual Studio 2019 on Windows. Open the property panel by going to View → Properties Window. The property panel will show attributes for whatever control is currently in focus in your XAML file.




Summary


In this article, your learned What is new in Xamarin Development in Visual Studio 2019. If you have any questions/ feedback/ issues, please write in the comment box.

Saturday, March 30, 2019

Xamarin FAQ Bot Available in Line App

Xamarin Developer Interview questions and answers Bot is ready to use in Line app. Xamarin FAQ Bot will be ready with 7000+ more Xamarin QnA’s. Now you can start open your Line App and > click on three dot line > Scan the following QR Code to add Xamarin QA bot as a friend.




Tuesday, March 26, 2019

Building Xamarin Mobile Application with Analyzing Customer Feedback using Sentiment Analysis API

Introduction:
Sentiment analysis seeks to understand a subject’s attitude or emotional reaction towards a specific topic or brand. Sentiment analysis does not have to be complicated and technical. It could be something as simple as getting a person in your team to find what is being said about your brand and product on review page and identify how much of it is good and how much of isn’t. There is no need for a big budget and developer into complicated software, the cognitive service text Analytics API is a cloud-based service that provides advanced natural language processing over raw text, and includes four main functions: sentiment analysis, key phrase extraction, language detection, and entity linking.
The most of the companies and brands now use sentiment analysis to find out what people are saying about them on social media. A bad review on social media can destroy a brand’s reputation if ignored or poorly handled. They aren’t simply rating their experience with 1 star or 5 stars. They’re also expressing their thoughts, feeling, expectations in free form text. This can be challenging to handle, especially if your company is getting a lot of feedback. When you have tens or even hundreds of thousands of feedbacks to read and manage, its easy to use cognitive text analytics service API.


The Sentiment Analysis API evaluates text input and returns a sentiment score for each document, ranging from 0 (negative) to 1 (positive). This capability is useful for detecting positive and negative sentiment in social media, customer reviews, and discussion forums. Content is provided by you, models and training data are provided by the service.
Currently, Sentiment Analysis supports English, German, Spanish, and French. Other languages are in preview. In this article, I will show how we can integrate sentiment API from Xamarin Mobile application using visual studio 2019
Text Analytics API Price:
The Text Analytics API can be purchased in units of the S0-S4 tier at a fixed price. Each unit of a tier comes with included quantities of API transactions. If the user exceeds the included quantities, overages are charged at the rate specified in the pricing table below. These overages are prorated and the service is billed on a monthly basis. The included quantities in a tier are reset each month. In the S tier, the service is billed for only the amount of Text Records submitted to the service. You can read more about pricing based on country check out here.
Create Text Analytics API Key:
You need to create an Azure account, generate API key and end point URL based region for implementation to the Xamarin Mobile application.
Step 1: Create Free Azure subscription and Login to portal  
Step 2: Create On “+ Create a resource “> Under Azure Marketplace, select AI + Machine learning and discover the list of available featured. > Select “Text Analytics
Step 3:  On the create page, provide the name, pricing, resource group and click on Create
Step 4:
Wait for a few seconds. After the Cognitive Services account is successfully deployed, click the notification or tile in the dashboard to view the account information. You can copy the Endpoint URL and Key in the Overview section for API calls in our Xamarin applications.


Build Xamarin Forms Application using Visual Studio 2019:
Let's start with creating a new Xamarin Forms Project using Visual Studio 2019. When accessing Visual Studio 2019 for the first time, you will come across a new interface for opening a creating the projects.
Open Run >> Type “Devenev.Exe” and enter >> Create New Project (Ctrl+Shift+N) or select open recent application.
The available templates will appear on a window like below. Select Xamarin Forms application with different mobile platform.
Provide project name, Location and solution name in the following configure new project screen
Select as Blank apps and select the platform
The Solution will be created with all the platform and PCL projects.
PCL UI Design:
The UI will have a few elements on the screen and overlay content view window. Editor control for providing user input value and overlay window for show the result.
You can add Newtonsoft.JSON to solutions. Right click on Solutions > Manage NuGet Packages > select Newtonsoft.Json from Browse tab > click on Install.
<?xml version="1.0" encoding="utf-8" ?>
<ContentPage xmlns="http://xamarin.com/schemas/2014/forms"
            xmlns:x="http://schemas.microsoft.com/winfx/2009/xaml"
            xmlns:local="clr-namespace:MobileFeedback"
            :Class="MobileFeedback.MainPage">

   <ContentPage.Content>

       <AbsoluteLayout>

           <!-- Normal Page Content -->
           <StackLayout AbsoluteLayout.LayoutBounds="0, 0, 1, 1"

                AbsoluteLayout.LayoutFlags="All">
               <Image Source="product.gif"   VerticalOptions="Start" HorizontalOptions="Start"  Margin="0,0,0,0" ></Image>
               <Editor x:Name="txtfeedback" WidthRequest="100"  HeightRequest="200"></Editor>
               <Button Text="Submit" Clicked="Submit_Clicked"></Button>
               
           </StackLayout>

           <!-- Overlay -->

           <ContentView x:Name="overlay"
                AbsoluteLayout.LayoutBounds="0, 0, 1, 1"
                AbsoluteLayout.LayoutFlags="All"
                IsVisible="False"
                BackgroundColor="#C0808080"
                Padding="10, 0">

               <StackLayout Orientation="Vertical"
                  BackgroundColor="White"
                  HeightRequest="175"
                  WidthRequest="300"
                  HorizontalOptions="Center"
                  VerticalOptions="Start"
                  Margin="0,20,0,0" >

                   <Image x:Name="imgstatus" WidthRequest="70" HeightRequest="70"></Image>
                   <Label Text="" x:Name="lblStatus"></Label>

                   <StackLayout Orientation="Horizontal" HorizontalOptions="Center">
                       <Button Text="OK" FontSize="Small"
                       VerticalOptions="CenterAndExpand"
                       HorizontalOptions="Center"
                       Clicked="OnOKButtonClicked" />
                   </StackLayout>
               </StackLayout>
           </ContentView>

       </AbsoluteLayout>

   </ContentPage.Content>

</ContentPage>

Create Document Entity Class:
Create class for Document class, it will deserialize the response and return an object of type TextAnalyticsResponse.The response format defined by the API looks like below document entity
using System;
using System.Collections.Generic;
using System.Text;

namespace MobileFeedback
{
 
    class Document
   {
       public string Id { get; set; }
       public double? Score { get; set; }
   }
   class TextAnalyticsResponse
   {
       public List<Document> Documents { get; set; }
   }

}

Create SentimentAnalysisHelper Helper Class:
You can replace Text Analytics API service endpoint and subscription key. If you don't already have these go back to the previous steps. Below is the complete class you need to add. we have to appended /sentiment to the end of the ApiUri in order to invoke the sentiment operation.
using Newtonsoft.Json;
using System;
using System.Collections.Generic;
using System.Net.Http;
using System.Text;

namespace MobileFeedback
{
   static class SentimentAnalysisHelper
   {
       private const string ApiUri = "<API url>”;
       private const string SubscriptionKey = "<your Key>";
       private const string Text = "The food was delicious and there were wonderful staff.";
       private static readonly HttpClient Client = GetClient();

       private static HttpClient GetClient()
       {
           var client = new HttpClient();
           client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", SubscriptionKey);
           client.DefaultRequestHeaders.Add("ContentType", "application/json");
           client.DefaultRequestHeaders.Add("Accept", "application/json");
           return client;
       }
       private static TextAnalyticsResponse DeserializeTextAnalyticsResponse(string json)
       {
           return JsonConvert.DeserializeObject<TextAnalyticsResponse>(json);
       }
       public static TextAnalyticsResponse GetSentiment(string text)
       {
           var body = JsonConvert.SerializeObject(new
           {
               Documents = new object[]
                 {
       new
       {
         Text = text,
         Id = Guid.NewGuid()
       }
                 }
           });

           using (var content = new ByteArrayContent(Encoding.UTF8.GetBytes(body)))
           {
               var responseMessage = Client.PostAsync(ApiUri, content).Result;
               responseMessage.EnsureSuccessStatusCode();
               var json = responseMessage.Content.ReadAsStringAsync().Result;
               return DeserializeTextAnalyticsResponse(json);
           }
       }
   }
}

You can add following to code behind in the design file. we'll add a method(GetSentiment) to call the Text Analytics API sentiment endpoint. It will deserialize the response and return an object of type TextAnalyticsResponse .The method will take a string text as input, create the request body, and then send it to the Text Analytics API using an HttpClient instance.
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using Xamarin.Forms;
using System.Net.Http;
using System.Threading;

namespace MobileFeedback
{
   public partial class MainPage : ContentPage
   {
      
       public MainPage()
       {
           InitializeComponent();
          
       }

       private  void Submit_Clicked(object sender, EventArgs e)
       {
          
           TextAnalyticsResponse result =  SentimentAnalysisHelper.GetSentiment(txtfeedback.Text);
           double? score = result.Documents.FirstOrDefault().Score;
           if(score < 0.5)
           {
               imgstatus.Source = "bad.png";
               lblStatus.Text = "This is the first time we have heard of this problem. Thank you for pointing it out to us. I assure you we will do our best to prevent it from happening again, We will contact with you regardng the issue";
           }
           else if(score > 0.5 && score < 0.9)
           {
               imgstatus.Source = "okay.png";
               lblStatus.Text = "We are always eager to get feedback from our customers. Thank you for taking the time to write to us.We will improve our service and our team will contact you";
           }
           else if(score> 0.9)
               {
               imgstatus.Source = "happy.png";
               lblStatus.Text = "Your valuable feedback will assist us in our continuing effort to provide our users with the best possible support experience.";
           }
           overlay.IsVisible = true;
       }
       void OnOKButtonClicked(object sender, EventArgs args)
       {

           overlay.IsVisible = false;

       }

       void OnCancelButtonClicked(object sender, EventArgs args)
       {
           overlay.IsVisible = false;
       }
   }

}

We have completed the code for consuming TextAnalytics API. Now, we can select the platform and press F5. The output looks like below

Summary

In this article, you learned how to consuming TextAnalytics API and automate customer feedback without using rating. I hope this article will help you. Please leave your feedback/query using the comments box, if you like this article, please share it with your friends.