Using Discriminated Union Labelled Fields

A few weeks ago, I re-discovered labelled fields in discriminated unions. Despite the fact that they look like tuples, they are not.

This is my entry to F# Advent Calendar 2021. Thanks to Sergey Tihon for organising the Advent Calendar each year.

A few weeks ago, I re-discovered labelled fields in discriminated unions:

// Without labels
type Customer =
    | Registered of string * string option * bool
    | Guest of string

// With labels
type Customer =
    | Registered of Name:string * Email:string option * IsEligible:bool
    | Guest of Name:string

I knew that the feature existed but I've usually built specific types, generally records, for each union case, so hadn't really used them in anger before. This isn't a new feature: Field labels in discriminated union case members were introduced in F# 3.1. Despite the fact that they look like tuples, they are not. For example, tuples in F# do not support labels like they do in C#.

In this post, we will look at how to make use of this feature.

Getting Started

We are going to start with a simple business feature:

(*
Feature: Applying a discount

Scenario: Eligible Registered Customers get 10% discount 
when they spend £100 or more

Given the following Registered Customers
|Customer Id|Email          |Is Eligible|
|John       |[email protected]  |true       |
|Mary       |[email protected]  |true       |
|Richard    |               |false      |
|Alison     |[email protected]|false      |

When <Customer Id> spends <Spend>
Then their order total will be <Total>

Examples:
|Customer Id| Spend | Total |
|Mary       |  99.00|  99.00|
|John       | 100.00|  90.00|
|Richard    | 100.00| 100.00|
|Sarah      | 100.00| 100.00|
*)

We are going to create two functions: One to calculate the totals after discount and one to return the email address of eligible customers. Emails are mandatory for Eligible customers and optional for Registered customers.

Creating Labelled Fields

The type design used in this post is specifically designed for the task of discovering how we can work with labelled fields. We start with a simple discriminated union with two union cases:

type Customer =
    | Registered of Name:string * Email:string option * IsEligible:bool
    | Guest of Name:string

Pattern Matching on Labelled Fields

As they look like tuples, can we deconstruct them in a match expression in the same way without the labels? It turns out that you can:


 
let calculateOrderTotal customer spend =
    let discount = 
        match customer with
        | Registered (name, email, isEligible) when isEligible && spend >= 100M -> spend * 0.1M 
        | _ -> 0M
    spend - discount

In this case, I'm only interested in the IsEligible flag, so will wildcards work? Yes they do:

let calculateOrderTotal customer spend =
    let discount = 
        match customer with
        | Registered (_, _, isEligible) when isEligible && spend >= 100M -> spend * 0.1M 
        | _ -> 0M
    spend - discount

Now let's try adding the labels in and get the values like we would with fields on a record type. Sadly, this doesn't work as we get a compiler error:

// Compiler Error
let calculateOrderTotal customer spend =
    let discount = 
        match customer with
        | Registered (Name = name, Email = email, IsEligible = isEligible) when isEligible && spend >= 100M -> spend * 0.1M 
        | _ -> 0M
    spend - discount

As I said earlier, they look like tuples but they aren't. The fix turns out to be simple: Replace the comma separators with semi-colons:

let calculateOrderTotal customer spend =
    let discount = 
        match customer with
        | Registered (Name = name; Email = email; IsEligible = isEligible) when isEligible && spend >= 100M -> spend * 0.1M 
        | _ -> 0M
    spend - discount

As we are not using name and email, can we use wildcards to ignore their data? Yes we can:

let calculateOrderTotal customer spend =
    let discount = 
        match customer with
        | Registered (Name = _; Email = _; IsEligible = isEligible) when isEligible && spend >= 100M -> spend * 0.1M 
        | _ -> 0M
    spend - discount

How about wildcards to ignore the fields? This change gives us a compiler error:

// Compiler Error
let calculateOrderTotal customer spend =
    let discount = 
        match customer with
        | Registered (_; _; IsEligible = isEligible) when isEligible && spend >= 100M -> spend * 0.1M 
        | _ -> 0M
    spend - discount

Again, the fix turns out to be simple: Remove the fields completely from the pattern match:

let calculateOrderTotal customer spend =
    let discount = 
        match customer with
        | Registered (IsEligible = isEligible) when isEligible && spend >= 100M -> spend * 0.1M 
        | _ -> 0M
    spend - discount

That's better but it would be nice if we could apply a filter directly rather than having to get the value and then test it. We can do this with records and thankfully it is available here too:

let calculateOrderTotal customer spend =
    let discount = 
        match customer with
        | Registered (IsEligible = true) when spend >= 100M -> spend * 0.1M 
        | _ -> 0M
    spend - discount

We can also combine the filter and the value getter as shown in the following function where we filter on IsEligible and return the value of the Email field into a local binding:

let tryGetEligibleEmail customer =
    match customer with
    | Registered (IsEligible = true; Email = email) -> Some email 
    | _ -> None

In summary, we use ',' for separating the fields when we don't use the labels in the pattern match and ';' when we do. If we are not interested in a field, don't use it in the match. We can use filters and value getters in the same match.

Creating an Instance of a DU Case

You can create an instance of a union case without specifying the field labels:

Personally, I think it makes more sense to use the labels if you provided them in the first place:

let john = Registered ( Name = "John", Email = Some "[email protected]", IsEligible = true )
let mary = Registered ( Name = "Mary", Email = Some "[email protected]", IsEligible = true )
let richard = Registered ( Name = "Richard", Email = None, IsEligible = false )
let alison = Registered ( Name = "Alison", Email = Some "[email protected]", IsEligible = false )
let sarah = Guest ( Name = "Sarah" )

Verifying these the functions with the instances is trivial. Firstly, the calculateOrderTotal function:

let assertJohn = calculateOrderTotal john 100.0M = 90.0M
let assertMary = calculateOrderTotal mary 99.0M = 99.0M
let assertRichard = calculateOrderTotal richard 100.0M = 100.0M
let assertSarah = calculateOrderTotal sarah 100.0M = 100.0M

and then the tryGetEligibleEmail function:

let assertMaryEmail = tryGetEligibleEmail mary = Some "[email protected]"
let assertRichardEmail = tryGetEligibleEmail richard = None
let assertAlisonEmail = tryGetEligibleEmail alison = None
let assertSarahEmail = tryGetEligibleEmail sarah = None

What Happens If ...

What happens if you decide not to include a label for the Name field?

type Customer =
    | Registered of string * Email:string option * IsEligible:bool
    | Guest of Name:string

The tuple-style pattern match with no labels works fine as does the version with the wildcards:

let calculateOrderTotal customer spend =
    let discount = 
        match customer with
        | Registered (name, email, isEligible) when isEligible && spend >= 100M -> spend * 0.1M 
        | _ -> 0M
    spend - discount

let calculateOrderTotal customer spend =
    let discount = 
        match customer with
        | Registered (_, _, isEligible) when isEligible && spend >= 100M -> spend * 0.1M 
        | _ -> 0M
    spend - discount

Removing the label from the original version with labels causes a compiler error:

// Compiler Error
let calculateOrderTotal customer spend =
    let discount = 
        match customer with
        | Registered (name; Email = email; IsEligible = true) when spend >= 100M -> spend * 0.1M 
        | _ -> 0M
    spend - discount

Removing that field and only using labelled fields works correctly:

let calculateOrderTotal customer spend =
    let discount = 
        match customer with
        | Registered (Email = email; IsEligible = true) when spend >= 100M -> spend * 0.1M 
        | _ -> 0M
    spend - discount

You don't have to supply every field with a label if you aren't going to pattern match on it with that label. I like consistency and would either supply labels to all fields or none at all.

Summary

I hope that you found this short post useful. Even if you decide not to use these features, it is still nice to know that they are available to you.
I have written an ebook called Essential Functional-First F#. All of the royalties go to the F# Software Foundation to support their promotion of the F# language and community around the world.

Follow me on Twitter at @ijrussell!

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Part 1: Data Analysis with ChatGPT

In this new blog series we will give you an overview of how to analyze and visualize data, create code manually and how to make ChatGPT work effectively. Part 1 deals with the following: In the data-driven era, businesses and organizations are constantly seeking ways to extract meaningful insights from their data. One powerful tool that can facilitate this process is ChatGPT, a state-of-the-art natural language processing model developed by OpenAI. In Part 1 pf this blog, we'll explore the proper usage of data analysis with ChatGPT and how it can help you make the most of your data.

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Application Integration & Process Automation

Digitizing and improving business processes and responding agilely to change – more and more companies are facing these kind of challenges. This makes it all the more important to take new business opportunities through integrated and optimized processes based on intelligent, digitally networked systems.

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Managed Service: Mailroom

In the TIMETOACT mailroom, business documents are converted into data in a highly efficient manner and returned securely to the end customer for further processing.

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Cloud Transformation & Container Technologies

Public, private or hybrid? We can help you develop your cloud strategy so you can take full advantage of the technology.

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Software, Mobile and Web App Development

Standard software often cannot completely fulfill a company's own requirements - TIMETOACT therefore develops customized software solutions.

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Digital Maturity

The Digital Maturity Assessment provides tailored strategies for your digital transformation.

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Whether it's the basics of AI, prompt engineering, or potential scouting: our diverse AI workshop offerings provide the right content for every need.

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Artificial Intelligence in Treasury Management

Optimize treasury processes with AI: automated reports, forecasts, and risk management.

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Automated Planning of Transport Routes

Efficient transport route planning through automation and seamless integration.