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Immutability has been getting popular these last years, especially with the rise of not only functional programming and but also JS frameworks such as React.
It's an important concept for many reasons, but I won't get into it in this blog post because it's not the point. Although I would urge you to either read The Dao of Immutability or watch Jon Skeet's The changing state of immutability in c# video, which explain it in details.
If you ever wondered how you could dynamically filter and/or sort your queries without having to write a huge switch statement with all the possible properties and operations, you've come to the right place!
Today we'll see how we can generate these types of operations at runtime and on the fly.
Yesterday, Prashanth Govindarajan posted an article about DataFrame on the .NET Blog. I got excited and wanted to try the library as soon as I could. In this post, I will explain what the library is intended for and what are my thoughts on it.
The package The DataFrame related classes were introduced in the package Microsoft.
A few days ago I needed a way to connect to a server using a Socks5 proxy but couldn't find an up-to-date implementation for .NET Core, so I decided to give it a go myself.
The implementation is pretty straightforward and easy, I got inspired from starksoft-aspen and followed the official RFC.
Assuming you are familiar with C#;
If I give you a Type and tell you to create an object with it, you would automatically think of Activator.CreateInstance right?
What if I tell you that instanciating a Type using Expression Trees is much faster?
The code for the benchmarks is in this repository.