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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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:
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:
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:
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
Today’s random F# code: validation
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Today’s random F# code from our app is about validating data passed to us over our public API:
Example code showing the usage of FsToolkit.ErrorHandling’s validation computation expression.
Today’s random F# code: Type inference
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Today’s random F# code is about type inference. If you like var, default and new() in C#, you might like F# a lot because F# gives you type inference also for function parameters, return types and generics (grey = IDE showing the inferred function signature):
F# type inference examples