Category: Misc Languages

Prakhar explains the difference between currying and partial application:

Currying simply means converting a function taking more than one parameter can be into a series of functions with each taking one parameter. Example:

Click through for an example, as well as the difference between currying and partial application. As for why currying is important, this is how we tie together the concept of mathematical functions, which require exactly one parameter (a function being defined as, for every value of the domain, there is one and only one value of the range), with computer science functions, which may have multiple parameters. Currying allows us to bridge that gap without needing to write loads of intermediary functions.

Camilo Reyes shows how to use Dapper:

Dapper is a lightweight shim around ADO.NET for data access via extension methods. To keep this relevant to any real application, there is quite a bit of code, which I won’t be able to show, so I recommend downloading the repo from GitHub. The focus here is to walk through the code API and follow best practices for building a DAL. The set of extension methods can feel overwhelming because there is a lot of functionality to cover.

I recommend general familiarity with LINQ and the List<> generic class in C#. This guide can be used as a reference so you can read one section at a time. At each pause, I encourage you to play with the code and allow the information to sink in.

I tend to like Dapper a lot, as it’s basically a lightweight wrapper around ADO. It’s very efficient as a result and you can also use stored procedures quite easily.

Kuldeepak Gupta shows off pattern matching in Scala:

Pattern Matching is a mechanism of checking a value against a Pattern. It gives a way of checking the given sequence of tokens for the presence of a specific pattern. Here, we match expressions against a pattern.

Compared to the ‘switch’ in C++, C, JAVA, there’s no fall through to the next alternative in Scala pattern matching. A Match error is thrown when no pattern matches.

This is a powerful part of functional programming.

Shubham Shrivastava explains how lambda expressions work in Scala:

Lambda expressions in Scala the syntax for these uses a symbol it’s an equals and a greater than and we refer to this as rocket ( => ). When we’re reading the code the idea of a lambda expression is a short literal expression that defines a function and typically these should not be overly long. so for example I could define a function for squaring values that looks something like this.

Lambda expressions are great in cases where you need to perform an operation exactly one time. If you create a separate function with its own name, there’s always a wonder in the back of a developer’s mind if this thing will get used again, and so it takes up a little bit of cognitive load. A lambda expression answers that conclusively: no, we won’t use this code again.

Randolph West hits on a timely question:

A customer I’ve been working with for a while now has a monolithic ASP.NET MVC web application which we are porting to .NET Core 3.1 (and then almost immediately to .NET 6). One of our biggest changes was getting rid of Entity Framework and replacing it with Dapper, because performance is a feature.

To deflect the ire of EF Core aficionados out there, the answer is still no.

Dapper is a micro-ORM in that it does not do as much “magic” as Entity Framework. This necessitates more work at the data access layer, but we have the trade-off of speed.

I say this is timely because my team is working through this exact thing right now. For future reference, anticipating what my team is working on and writing a blog post which answers a question we have is an outstanding way of getting noticed here.