In this post, I will describe how to port a desktop application from .NET Framework to .NET Core. I picked a WinForms application as an example. Steps for WPF application are similar and I’ll describe what needs to be done different for WPF as we go. I will also show how you can keep using the WinForms designer in Visual Studio even though it is under development and is not yet available for .NET Core projects. 

interface ILogger
{
    void Log(string message);
}

class ConsoleLogger : ILogger
{
    public void Log(string message)
    {
        Console.WriteLine(message);
    }
}

interface ILogger
{
    void Log(string message);
    void Log(Exception exception) => Console.WriteLine(exception);
}

    interface IDeveloper
    {
        void LearnNewLanguage(string language, DateTime dueDate);

        void LearnNewLanguage(string language)
        {
            // default implementation
            LearnNewLanguage(language, DateTime.Now.AddMonths(6));
        }
    }

    class BackendDev : IDeveloper // compiles OK
    {
        public void LearnNewLanguage(string language, DateTime dueDate)
        {
            // Learning new language...
        }
    }

IDeveloper dev1 = new BackendDev();
dev1.LearnNewLanguage("Rust");

var dev2 = new BackendDev();
dev2.LearnNewLanguage("Rust");
 

 There is no argument given that corresponds to the required formal parameter 'dueDate' of 'BackendDev.LearnNewLanguage(string, DateTime)' (CS7036) [ConsoleApp]

using System;

namespace ConsoleApp
{
    public interface IDev
    {
        void LearnNewLanguage(string language) => Console.Write($"Learning {language} in a default way.");
    }

    public interface IBackendDev : IDev
    {
        void LearnNewLanguage(string language) => Console.Write($"Learning {language} in a backend way.");
    }

    public interface IFrontendDev : IDev
    {
        void LearnNewLanguage(string language) => Console.Write($"Learning {language} in a frontend way.");
    }

    public interface IFullStackDev : IBackendDev, IFrontendDev { }

    public class Dev : IFullStackDev { }
}

IFullStackDev dev = new Dev();
dev.LearnNewLanguage("TypeScript");

The call is ambiguous between the following methods or properties: 'IBackendDev.LearnNewLanguage(string)' and 'IFrontendDev.LearnNewLanguage(string)' (CS0121)

namespace MyNamespace
{
    public interface IMyInterface
    {
        IList<int> Values { get; set; }
    }

    public static class MyInterfaceExtensions
    {
        public static int CountGreaterThan(this IMyInterface myInterface, int threshold)
        {
            return myInterface.Values?.Where(p => p > threshold).Count() ?? 0;
        }
    }
}

var myImplementation = new MyInterfaceImplementation();
// Note that there's no typecast to IMyInterface required
var countGreaterThanFive = myImplementation.CountGreaterThan(5);

Ready to get started with Visual Studio 2017? This is your course! Join the experts and get the details, from installation to debugging, in this practical Visual Studio 2017 deep dive.

See how to download and install Visual Studio in standalone and networked environments, along with some of the configuration options, such as choosing your workloads (types of apps or services, languages, and platforms), customizing the installation, and installing language packs. Then, take a tour of the Visual Studio IDE, including all the basics you need to get started with your development projects. Finally, explore debugging in Visual Studio, and learn how to use its features to investigate problems in your code.

- .NET Core
- Node.js
- Docker
- Elasticsearch: A distributed and open source search engine based on Lucene. A blazing fast NoSQL database with replication capabilities, it is the most widely known component of the ELK stack, together with Kibana (for reporting and visualizations), Logstash (for data import) and Beats (for data shipping). Even Azure Search uses it behind the covers. Free but some tools are paid. Get it from http://elastic.co.
- ECMAScript 2015
- HTML5
- Kafka
- TypeScript
- MongoDB
- Git
- Nginx
- Octopus Deploy
- Azure
- Amazon Web Services
- Linux
- Visual Studio Code
- Xamarin
- Google Analytics
- SQL Server 2016
- Let’s Encrypt
- TensorFlow
- GitLab
- Redis 

In this post, we are going to write about what we consider to be the best practices while developing the .NET Core Web API project. How we can make it better and how to make it more maintainable.

We are going to go through the following sections:

• Startup Class and the Service Configuration
• Project Organization
• Environment Based Settings
• Data Access Layer
• Controllers
• Actions
• Microsoft.AspNetCore.All Meta-Package
• Routing
• Logging
• CryptoHelper
• Content Negotiation
• Using JWT
• Conclusion