In this part of the article series about Reactive LINQwe're going to implement a slightly more complicated application using the library that I introduced in the previous three articles. We're going to use basic event stream queries from the second article as well as advanced operators introduced in the third part. This time, I'll also show the F# version of all the examples, so we're going to build on the ideas from the first part.
I originally wanted to write the demo only in Visual Basic, because I think that it is really amazig to show an idea that came from functional programming in a language that no one (maybe until recently) connects with functional programming. Then I realized that I really want to show the F# version too, because F# was an inspiration for the whole Reactive LINQ idea and it is interesting alone as well. But finally, I thought that don't showing the C# version may look offensive to many readers (especially since I'm still C# MVP...). So, I ended up writing the game in all three languages, but the code is surprisingly similar in all of them!
In the previous article, I introduced Reactive LINQ.
I explained the different point of view that we can use when working with .NET events. The idea is that
.NET events can be viewed as streams of values. The value is information about the event (such as position
of a mouse click or a mouse movement). These streams can be processed using LINQ queries - we can for example
filter all values that are not interesting for us using
where LINQ clause. For example if we want to handle
clicks only in some specified area.
In the previous article, I talked about basic LINQ query operators such as
and some useful methods that Reactive LINQ provides (for example for merging event streams).
Today, we'll take a look at two more advanced kinds of operations that we can use for working with event streams.
In particular, we'll talk about aggregation operators (that you certainly know from LINQ) and about switching.
Switching is a concept from functional reactive programming and it allows us to change dynamically how the
application behaves. However, I'll explain this in a more detail soon.
In this article, I'm going to use mostly C# (and some Visual Basic). The functionality that I'm describing
in this part isn't part of the standard F#
Event module that I discussed in
the first part. I implemented most of them in F# too, but I'm not going
to write the samples in both of the versions in this part. If you've seen the first two articles, you'll be
definitely able to use the F# versions as well, because they follow exactly the same ideas as the C#/LINQ versions.
I'm going to talk about a larger demo application in the last section and I'll show an F# version as well,
so you'll see some F# examples in the next part. This part serves more as a reference of the available
operators, so you may read only some parts of it, then jump to the last one (to see an exciting example!)
and then come back here.
In this article I'm going to introduce my project Reactive LINQ. This is largely inspired by the ideas that come from functional reactive programming in the Haskell language and from functionality that's available for working in events in F#. I introduced these ideas in my previous article in this mini-series, so if you're interested in learning more about these interesting technologies, you should definitely read the previous article about First class events in F#.
In this article, we're going to look how to apply the same ideas to the C# language and how to use LINQ queries for processing events. This article is just another my article that shows how to implement some idea from functional programmin in C#. I believe this will once again show that the new features in the C# 3.0 aren't just about querying databases, but are more widely useful even in situations that are not directly related to data-processing.
I believe that the LINQ project and changes in C# 3.0 and VB 9 are interesting because they allow rewriting of many ideas from functional programming. An ability to express queries easily is one of these ideas, but it is definitely not the only one. There are many other interesting ideas. The C# 3.0 language isn't primary a functional language, so it isn't easy to discover the idea if you use only C#, but it is possible to implement it if you know the idea already.
I already wrote a few interesting C# examples that were inspired by some functional idea. I'm a big fan of the F# language, so it is not a surprise that I started with an F# version of the problem and then looked at the way to do the same thing in C#. In particular, this is how my article about building dynamic queries in C# came to the existence - the F# version used FLINQ and Quotations and then I demonstrated how to do the same in C# using expression trees. Another example is my article about asynchronous programming in C# using iterators, which shows how to implement something like F# asynchronous workflows using iterators in C# 2.0.
Functional Reactive Programming
Today, I'm going to look at another very interesting idea from functional programming. It is called Functional Reactive Programming and it comes from the Haskell community. You can find a list of related Haskell projects here. However, similar things (though they are not purely functional and simplified) are available in the F# language as well. Don Syme introduced them in his blog post called F# First Class Events: Simplicity and Compositionality in Imperative Reactive Programming. In this article, I'm going to briefly introduce the implementation available in F# and I'll extend it a little bit to allow some more interesting things. In the second article from this series, I'll show how to implement the same thing in C# 3.0 (and in VB 9 too!)
About a year ago, I wrote an article about using lazy computations in C# 3.0. It was published by the C# Community PM Charlie Calvert at the C# Developer Center. The article was a first of two articles where I wanted to demonstrate that C# 3.0 can be used for implementing useful constructs known from functional languages. I realized that I never posted the link to the second article to my blog, so you can find the annotation and link below.
However, I remembered about these two articles because I was just working on chapters 11 and 12 of the Real-world Functional Programming in .NET book that I’m writing. Lazy values, which were the topic of my first article, are discussed in the second part of chapter 11 and IEnumerable and F# sequences are the topic for the first part of chapter 12. Because I already wrote two articles on this topic, I had to think really hard to find better (and still simple enough) examples where these concepts are useful in practice. I also finally have enough space to show how these two concepts relate and talk about some interesting background – for example in Haskell, lazy sequences are in fact just ordinary lists that are lazy thanks to the Haskell nature.
A year ago, I definitely wouldn’t believe that today, I’ll be writing about the same topics, but this time as part of a book that has partly the same goal as these two articles – to show that functional programming ideas are really useful in the real-world and can enrich your programming toolbox (no matter whether you’re using C# or F# language). Anyway, here is the link to the second article – as usual when I look at something that I worked on a long time ago, I think I should rewrite it to make it better :-), but it still gives you an idea what is the book that I’m working on about...