A frequent question I get is how to structure a codebase in F#. There is not much about this topic out there on the Internet. So here is how we structure our code:
Today’s random F# code: Code Structure
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Myths about F#: We tried FP in C#, and it’s unreadable! Yes, but that’s where F# shines.
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Just today, I read on a social media platform that the author doesn’t like that most programming languages incorporate more and more functional features. The post was accompanied by a short example of pattern matching in C# using some of the features introduced in the latest updates. More generally, I hear and read repeatedly from people that tried to write code in a more functional programming style in C# but weren’t happy with the resulting code. The code was just too hard to read...
Myths about F#: Imperative code is simpler than functional code! No, not at all, but you are more used to it.
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A myth about F# that I hear repeatedly is that imperative code (e.g. loops) is simpler than functional code (e.g. folds). On one hand, simplicity is very subjective. On the other hand, simplicity is mostly determined by familiarity.
A typically used example is something like the following:
Simple:
Difficult:
Let’s see what’s wrong with this myth.
Today’s random F# code: Regex Active Pattern in API Validation
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Active patterns make using a Regex in F# neat: The matched groups are returned in the list after the pattern. Here is an example from our codebase:
Pattern found at Active Patterns – F# | Microsoft Learn:
Myths about F#: F# is for FP, C# for OOP! No, F# loves OO.
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Sometimes when I talk to C# developers about F#, they say they don’t want to switch to a functional programming language. When I reply that F# is my favourite object-oriented programming language, they look a bit puzzled. They typically think that F# is for functional programming, while C# is for object-oriented programming. And this is wrong!
Today’s random F# code: Nice test error messages with Unquote and Diffract
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When comparing complex data types in unit test assertions, for example, records with nested lists containing discriminated unions, the error messages quickly get hard to understand. How to spot a single difference?
That’s why I mixed Unquote and D-Edge.Diffract together.
An example unit test from our codebase:
Myths about F#: F# has too many operators! Many, but not more than C#.
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“F# code is full of operators, making the code unreadable.” said a C# developer to me once. And he is not the only person to dislike F# for its operators – not specific operators, but the sheer number of operators there are.
Before continuing reading, take a moment and guess the number of operators in vanilla C# and F#.
Today’s random F# code: Domain modelling with discriminated unions
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F# makes it easy to model a domain with discriminated unions (= it is one of these values) and measures (type-safe numbers). Excerpt from our expenses sub-system:
Myths about F#: F# is for math problems only! No, F# is a general-purpose programming language.
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When I show F# code to non-F#ers, I often get a reaction that goes something like this: “This code looks kind of nice, but we don’t have math problems to solve, so F# is not for us.”
By the way, the code I show typically has nothing to do with math. We don’t solve math problems with F#. We write a business application with it.
So I wonder why I hear this almost every time when I present about F#. Some guesses:
Today’s random F# code: Result instead of exceptions
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Today’s random F# code from our app is about using Results instead of using exceptions.
Do you often need to get some data from the database, but it’s not sure that the requested data exists? And you don’t like using exceptions for this because exceptions are for really unusual things? Then use a Result:
Querying data with the help of Result