Starting from end of last year, I have been working on several UWP projects at work. Few days ago, I’m glad to have the opportunity to borrow a Surface Dial from Riza.
Surface Dial is a revolutionary input device. It was introduced by Microsoft in the 2016 together with Surface Studio. Most of the time, it works awesome on Surface devices. However, that doesn’t mean we can’t use it with our Windows desktop or laptop. As a secondary input device, it can be used together with our mouse or touch. Developers are also welcomed to customize the abilities of the Surface Dial on their UWP apps.
In this article, I will be sharing on how we can use Surface Dial to support a quick menu of commands in an UWP app.
Installing Surface Dial
First of all, we need to make sure our Windows device is on (Yes, UWP currently can only work on Windows machines). Then we need to turn on the Bluetooth on the machine. If our PC doesn’t come with the Bluetooth hardware installed, we can easily add it by purchasing a Bluetooth USB dongle.
After that, we need to turn our Surface Dial on by removing the cover of its bottom and then pressing the button next to the batteries, as shown in the photo below.
🎨 Added Surface Dial to my PC. 🎨
Now we can find the Surface Dial on the “Bluetooth & other devices” window. We can proceed to add it to our PC.
Adding Menu on Surface Dial
For those who attended my sharing in Microsoft Insider Dev Tour 2019 in Kuala Lumpur and Johor Bahru last year, the following UWP app should be familiar to you.
🎨 The UWP demo app done by Justin Liu for Microsoft Insider Dev Tour. 🎨
Now we will proceed to add Surface Dial menu to this page.
In the code-behind of the page, we will have the following global objects.
// Create a reference to the RadialController. radialController = RadialController.CreateForCurrentView(); // Set rotation resolution to 1 degree of sensitivity. radialController.RotationResolutionInDegrees = 1;
What does setting RotationResolutionInDegrees mean here? The value actually is the minimum rotation value required for the RotationChanged event to be fired. So, by setting it to 1, every one degree of rotate on the Surface Dial, the RotationChanged event will be triggered. Also, by default, when the RotationChanged happens, the Surface Dial will vibrate. So it is like massaging your hand when you’re rotating the Surface Dial that has its RotationResolutionInDegrees set to 1.
Then we can proceed to add our menu items to the Surface Dial. Here, we use a font glyph for the custom tool.
However, please take note that, by default, there are built-in menu items for the Surface Dial. So we need to remove them to prevent squeezing in too much menu items to the Surface Dial UI and thus making it harder to control.
To remove the built-in menu items, we just need to reset in the configuration of the Surface Dial. Another thing to take note is that the Surface Dial menu must have at least one menu item, else the default menu items will be restored.
Now there is a funny thing is that if we remove all the built-in menu items before we add our customized menu items, i.e swapping the position of the two blocks of codes above, then we will realize that the default menu items will be restored and our customized menu items will be appended to the default ones, as shown in the screenshot below.
🎨 Oh my tian, the buttons on the Surface Dial menu are so crowded! 🎨
Finally, if we want to handle the events fired from the Surface Dial, for example when users click on it or rotate it, we can use the following handlers.
Please take note that the ButtonClicked event is not triggered when a menu item is selected. Instead we need to do as follows to handle the menu item chosen event.
imageGallery.Invoked += ImageGallery_Invoked;
Result
So, now, with all these few lines of codes, we can have a beautiful Surface Dial control on our UWP app, as shown in the following photo. Yay!
KOSD, or Kopi-O Siew Dai, is a type of Singapore coffee that I enjoy. It is basically a cup of coffee with a little bit of sugar. This series is meant to blog about technical knowledge that I gained while having a small cup of Kopi-O Siew Dai.
The topic that I delivered in the event is “Development and DevOps of Desktop Apps with .NET Core 3.0”. It is a 45-minute talk combining the content from the following three talks.
From coding, converting, to deploying. (Image Credit: .NET Conf 2019)
If you watch the videos above, the total length is about 70 minutes. So covering three of them in a 45-minute talk is a challenge to me. Luckily, I have Sabrina to help me out by co-speaking with me.
If you have watched our session, you will realise it’s quite different from the official .NET Conf. In this post, I am going to brief you through about my thoughts and development process of our talk content.
Let’s Hashtag Together!
In order to make the conference to be more engaging, after discussing with Sabrina, I came out with a desktop app which will shows the recent tweets having #dotnetconfsg hashtag, which looks like the following.
Participants tweeting about our sessions.
To make this “game” more interesting, I announced that the top four participants who earn the highest scores would receive prizes from me. The formula to calculate the score is basically
+1 point for one tweet;
+5 point for one retweet of the tweet;
+5 point for one like of the tweet.
Throughout the conference, we thus had seen a huge number of tweets about our event and speakers. Some of them even tweeted with great photos (I should have given 5 points for great photos too).
In our talk, we used this desktop app as our sample. The app is built in .NET Framework 4.7. Sabrina started the demo with showing how we can modernise it to a .NET Core desktop app. I then covered a bit about Hot Reload, the runtime tools (the small little black bar on top of locally launched WPF app), and DevOps part of desktop app.
I am using the Tweetinvi library to retrieve the tweets easily. I originally tried calling the Tweeter APIs directly from C# and it’s a painful experience. Instead of wasting resources on researching the Tweeter APIs, I change to use Tweetinvi because it allows me to easily get the tweets in just two lines of codes.
To improve the GUI, I use the Material Design in XAML Toolkit. So, I can easily change the WPF application to have dark mode. This is very important to me because I realise light mode isn’t displayed well on the projected screen during the event. So, it now looks as shown in the following screenshot.
New look with Material Design.
By clicking on the “Show Ranking” button at the top-right corner, we can easily tell the scores received by the participants.
The participants are sorted according to the score they receive.
Migrating to .NET Core 3.0
Now with many third-party libraries used in our WPF application, is the desktop app still compatible with .NET Core? Well, to answer this question, there is a tool from Microsoft called Portability Analyzer can give us a detail report on the set of APIs referenced in our apps that are not yet available in NET Core 3.0.
After downloading it and using it to check our application above, we received the following report.
This says that our WPF application is 100% portable to the .NET Core.
The Excel report comes with three tabs, i.e. Portability Summary (the one shown above), Details (empty), and Missing assemblies. There is one item in the report Missing assemblies though, as shown below.
However, if we proceed to use try-convert to migrate our WPF application from .NET Framework to .NET Core, it will be a successful conversion, as shown in the screenshot below.
Converted a .NET Framework project to .NET Core 3.0.
The following screenshot shows how the app looks like after being migrated to .NET Core 3.0. Nothing significant is changed. If you would like to find out what have been changed, please visit the commit of this project on GitHub.
This is a WPF app in .NET Core 3.0.
XAML Islands
There is another thing that I shared in my talk is about XAML Islands. In fact, I talked about XAML Islands in Microsoft Insider Dev Tour too when I was sharing about WinUI.
Microsoft Insider Dev Tour (Image Credit: Microsoft Malaysia – Insider Dev Tour Kuala Lumpur)
XAML Islands is a feature that allows us to host UWP controls in non-UWP desktop applications. The reason of having it is to improve the UX of existing Win32 apps by leveraging UWP controls.
Although the documentation says it is enabled only starting from Windows 10, version 1903. However, if you are using version 1809, XAML Islands feature is also available already, just that not yet stable. So, the best choice is still using version 1903 and above.
In my presentation, since I was using the Windows 10 image hosted on Microsoft Azure VM, the best version I could get is 1809.
You may ask why I am using version 5.1.1 of the Microsoft.Toolkit.Wpf.UI.Controls. On the day of .NET Conf Singapore, the version 6.0 (Preview 9.1) of it is already out. However, when I try to use the library, it threw the exception, as shown in the screenshot below.
Oops, app crashes with Microsoft.Toolkit.Wpf.UI.Controls 6.0 (Preview 9.1).
I could only demonstrated how I used the MapControl in a WPF app with XAML Islands.
Such a beautiful map displayed on WPF app!
Creating Build Pipeline in Azure DevOps
Now, with the codes of our WPF application on GitHub, we can create a Build pipeline for the app on Azure DevOps. This is not a new feature but it is nice to see how we can now build a .NET Core WPF app on Azure DevOps.
Benefits of DevOps (Image Credit: .NET Conf 2019)
There is a template available on Azure DevOps to build .NET Desktop app.
We can apply this template to build .NET Desktop app on Azure DevOps.
However, before we proceed to start the build, we need to make a few changes to it.
Since we will be using dotnet publish later, so the BuildPlatform variable is not necessary and can be removed.
Removing BuildPlatform variable from the pipeline.
Instead, we need to add a new variable called DOTNET_SKIP_FIRST_TIME_EXPERIENCE and set it to true. This is to speed up the build process because by default when we run any .NET Core SDK command on Azure DevOps, it does some caching. However, now we are running this on a hosted build agent, so this caching will never be useful because the agent will be discarded right after the build is completed. Thanks Daniel Jacobson for highlighting this in his video.
Daniel Jacobson (right) explains about Azure DevOps and .NET Core SDK commands. (Image source: YouTube video)
After that, we need to remove all the default steps because we need to start from scratch for .NET Core.
The first step is to install .NET Core SDK 3.0. Remember to state “3.0.x” as the version otherwise if there is a minor update to .NET Core 3.0, we will still be using the outdated one to build.
Step 1: Use .NET Core SDK 3.0
After that, we are going to do dotnet publish.
Starting with .NET Core 2.0, we don’t have to run dotnet restore because it’s run implicitly by all commands that require a restore to occur. Also dotnet publish will build the project, so we do not need to run dotnet build.
Since this is a WPF project, so we have to uncheck the “Publish Web Projects” checkbox, together with the other two checkboxes “Zip Published Projects” and “Add project name to publish path”, as shown in the screenshot below.
Now we proceed to add the next step, which is to publish the artifact. Here we specify $(Build.ArtifactStagingDirectory) as the path of the directory to publish. Then we also specify a user friendly name for the artifact.
Step 3: Publish Pipeline Artifact
Now we can click the “Save & queue” to run this pipeline.
In the published artifact, we will see the following.
Published artifact in our first attempt.
Wow, there are a lot of DLLs! The .exe file alone is only 157KB.
Fortunately, starting from .NET Core 3.0, as long as we specify the following in our csproj file, it will produce a single .exe file.
<PublishSingleFile>true</PublishSingleFile>
However, there is one more thing to take note is that if we miss out the <RuntimeIdentifier>, there will be an error NETSDK1097 which says, “It is not supported to publish an application to a single-file without specifying a RuntimeIdentifier. Please either specify a RuntimeIdentifier or set PublishSingleFile to false.”
<RuntimeIdentifier>win-x86</RuntimeIdentifier>
With this change, when we run the Build pipeline again, we get the following.
Published artifact with <PublishSingleFile>.
We now only have one .exe file but its size has grown from 157KB to 145MB!
WinForms and WPF are now available on VS App Center but still in preview.
So, the artifact generated in Azure DevOps Build pipeline cannot be automatically delivered to VS App Center even after .NET Conf 2019. We now have to do it manually.
Firstly, we need to download the actifact as a zipped file in Azure DevOps.
Secondly, we need to upload the zipped file to the VS App Center in its Releases tab, as shown in the following screenshot.
Setting Build version to 1 because this is our first release of the app.
After keying the release notes, we will be landed on a page to choose who we should distribute the app to. Normally they are our developers, business analysts, and testers. Here, in my example, I only have one group called Collaborator and I am the only one in the group.
We are not allowed to add those who are not in our App Center as testers.
Finally, we will hit the “Distribute” button to release our app to testers. As tester, I will receive the email notifying about the new release.
Yay, new release available for in-house testing.
Analytics with App Center SDK
We can also integrate our WPF desktop app with App Center SDK to further collect data to find out how people use our app as well as the crashes in our app.
To do so, firstly, we need to install the following two Nuget packages. As the support for WPF SDK is still in preview, please remember to check the “Include prerelease” checkbox.
Microsoft.AppCenter.Analytics;
Microsoft.AppCenter.Crashes.
SQLitePLCRaw is being installed when we install the App Center SDK.
Now we can proceed to put the following code in the first window that will be launched in our app. In my case, it is the MainWindow. So, right after the InitializeComponent() is called, the following codes will be executed.
Yup, if you have noticed earlier when we’re installing the App Center SDK, SQLitePCLRaw was being installed also. Just because of the bug in the SDK, this line was not added to the project file and thus we have to manually reference it. Hopefully this bug gets fixed soon.
Now when we launch our WPF app again, the nice dashboard will show there is 1 user. Yay!
+1 active user in our app!
Conclusion
That’s all so far for what I’d like to share in addition to what I have shared in .NET Conf Singapore 2019.
Application Insights is available on Azure Portal as a way for developers to monitor their live web applications and to detect performance anomalies. It has a dashboard with charts to help developers diagnose issues and understand user behaviors on the applications. It works for apps written on multiple programming languages other than .NET too.
Setup of Application Insights on Azure
It is straightforward to setup Application Insights on Azure Portal. If we have already setup a default CI/CD for simple Golang web app, an Application Insights account will be created automatically.
Creating new Application Insights account. The golab002 is automatically created when we setup a new Golang DevOps project on Azure Portal.
Once the Application Insights account is created, we need to get its Instrument Key which is required before any telemetry can be sent via the SDK.
Simplicity in ASP .NET Core
In ASP .NET Core projects, we can easily include Application Insights by including the Nuget package Microsoft.ApplicationInsights.AspNetCore and adding the following highlighted code in Program.cs.
public static IWebHostBuilder CreateWebHostBuilder(string[] args) => WebHost.CreateDefaultBuilder(args) .UseStartup() .UseApplicationInsights();
Introducing Application Insights to Golang application is not as straightforward as doing the same in ASP .NET Core project described above. Here, I will cover only how to use Telemetry.
First of all, we need to download and install the relevant package with the following go get command.
go get github.com/Microsoft/ApplicationInsights-Go/appinsights
Tracing Errors
Previously, we already have a centralized checkError function to handle errors returned from different sources in our code. So, we will have the following code added in the function to send traces back to Application Insights when an error occurs.
So, when there is an error on our application, we will receive a trace record as such on the Metrics of Application Insights as shown below.
An error is captured. In this case, it’s because wrong DB host is stated.
However, doing this way doesn’t give us details such as call stack. Hence, if we want to log an exception in our application, we need to use TrackPanic in the SDK as follows.
// false indicates that we should have this handle the panic, and // not re-throw it. defer appinsights.TrackPanic(client, false)
panic(err) } }
This will capture and report call stack of the panic and display it on Azure Portal. With this, we can easily see which exceptions are occurring and how often.
Traces and exceptions. The details of exception includes call stack.
Tracing Page Views
Besides errors, let’s capture the page views as well so that we can easily tell which handler function is called and how much time is spent in it. To do so, we introduce a new function called handleRequestWithLog.
Now whenever we visit a page or perform an action, the behaviour will be logged on Application Insights, as shown in the following screenshot. As you can see, the server response time is logged too.
Adding new video, deleting video, and viewing homepage actions.
With these records, the Performance chart in Application Insights will be plotted too.
Monitoring the performance of our Golang web application.
Tracing Static File Downloads
Besides the web pages, we are also interested at static files, such as understanding how fast the server responses when the static file is retrieved.
To do so, we first need to introduce a new handler function called staticFile.go.
By doing so, we will start to see the following on Search of Application Insights.
A list of downloaded CSS and JS static files and their corresponding server response time.
Conclusion
In ASP .NET Core applications, we normally need add the UseApplicationInsights as shown below in Program.cs then all the server actions will be automatically traced. However, this is not the case for Golang applications where there is no such convenience.
In January 2019, we also successfully presented our solution during the Singapore .NET Developers Community meetup. Taking the opportunity, I also presented how Azure Key Vault is used in our project to centralize our key and secret management.
Marvin is sharing with the audience about Custom Vision during the meetup.
Hence, in this article, I’d like to share about this project in terms of how we use Cognitive Services and Key Vault.
Code Repository
The code of our project is available in both Azure DevOps and Github. I will update both places to make sure the codes are updated.
The reason I have my codes in both places because the project is originally collaborated in Azure DevOps. However, during meetup, I realized majority of the audience still prefer us to have our codes on Github. Well…
Our “FutureNow” tool where user can use it to analyze text on images.
Custom Vision
What Marvin has contributed fully is to implement a function to detect and identify the handwritten texts in the uploaded image.
To do so, he first created a project in Custom Vision to train the model. In the project, he uploaded many images of paper documents and then labelled the handwritten texts found on the paper.
The part where the system analyzes the uploaded image and finds the handwriting part is in the TagAndAnalyzeService.cs.
In the AnalyzeImageAsync method, we first use the Custom Vision API which is linked to Marvin’s project to identify which parts in the image are “probably” handwritten.
At this point of time, the system still cannot be hundred-percent sure the parts it identifies as handwritten text really contain handwritten text. Hence, the result returns from the API contains a probability value. That’s why we have a percentage bar on our front-end to control the threshold for this probability value to accept only those results having a higher probability value will be accepted.
Handwritten Text Extraction with Computer Vision
After the previous step is done, then we will crop those filtered sections out from the uploaded image and then send each of the smaller image to the text recognition API in Cognitive Service to process the image and to extract out the text.
There is an interesting do…while loop in the method. The loop is basically used to wait for the API to return the image processing results. It turns out that most of the time, the API will not directly return the result. Instead, it will return a JSON object telling us that it’s still processing the image. Only when it returns the JSON object with status set to “Succeeded”, then we know that the analysis result is returned together in the JSON object.
do { var textOperation = response.Headers.GetValues("Operation-Location").FirstOrDefault();
var result = await client.GetAsync(textOperation);
if (!isAnalizying) { return handwrittenAnalyzeResult; } } while (isAnalizying);
In order to display to the user in front-end the results, we will store the cropped images in Azure Blob Storage and then display both the images and their corresponding extracted texts on the web page.
Using Computer Vision to perform OCR can better detect and extract text in an image especially when the image is a screenshot of a computer generated PDF file.
In OpticalCharacterRecognitionService, we simply call the Computer Vision API OCR method with the uploaded image and language set to English by default, then we can easily get the result of the OCR back in JSON format.
Key Vault
Key Vault in this project is mainly for managing the keys and connection string to the Azure Blob Storage.
Secrets of the FutureNow project in the Azure Key Vault.
var azureServiceTokenProvider = new AzureServiceTokenProvider();
var keyVaultClient = new KeyVaultClient(new KeyVaultClient.AuthenticationCallback(azureServiceTokenProvider.KeyVaultTokenCallback));
var secret = await keyVaultClient.GetSecretAsync($"https://futurenow.vault.azure.net/secrets/{ secretName }").ConfigureAwait(false);
According to Microsoft Azure documentation, there are service limits in Key Vault to ensure quality of service provided. Hence, when a service threshold is exceeded, any further requests from the client will not get successful response from Key Vault. Instead, HTTP status code 429 (Too many requests) will be returned.
Regarding this problem, I have raised issues (#22859 and #22860) and submitted a pull request to Microsoft on Github. Currently the PR is not yet approved but both Bryan Lamos and Prashanth Yerramilli have agreed that the code is indeed incorrect. Anyway, in our KeyVaultService class, the code has already been corrected.
EDIT (26 January 2019): The pull request has been approved. =)
Conclusion
Even though this project is just an experimental project for us to understand more about the power of Custom Vision and Computer Vision, I am glad that through this project, I manage to learn additional knowledge about Blob Storage, Azure DevOps, Key Vault, etc. and then later share it with the Singapore .NET Developers Community members.
Special thanks to Marvin for helping me in this project.
cuteprogramming 