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       |john@test.org  |true       |
|Mary       |mary@test.org  |true       |
|Richard    |               |false      |
|Alison     |alison@test.org|false      |

When  spends 
Then their order total will be 

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:

// let john = Registered ( "John", Some "john@test.org", true )

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 "john@test.org", IsEligible = true )
let mary = Registered ( Name = "Mary", Email = Some "mary@test.org", IsEligible = true )
let richard = Registered ( Name = "Richard", Email = None, IsEligible = false )
let alison = Registered ( Name = "Alison", Email = Some "alison@test.org", 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 "mary@test.org"
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!

Blog 8/10/23

Machine Learning Pipelines

In this first part, we explain the basics of machine learning pipelines and showcase what they could look like in simple form. Learn about the differences between software development and machine learning as well as which common problems you can tackle with them.

Blog

Functional Validation in F# Using Applicatives

Learn how to implement functional validation in F# using applicatives. Handle multiple errors elegantly with Railway-Oriented Programming and concise functional patterns.

Blog

Celebrating Homai - Using AI for Good

Our colleague Aigiz Kunafin has achieved an outstanding milestone - importance of his side-project Homai was acknowledged by the “AI for Good” Initiative of United Nations.

Blog 3/17/22

Using NLP libraries for post-processing

Learn how to analyse sticky notes in miro from event stormings and how this analysis can be carried out with the help of the spaCy library.

Blog

Using GCP Cloud Functions with F#

Learn how to build and test Google Cloud Functions in F#, using dependency injection, configuration, and pub/sub messaging for real-world cloud apps.

Blog

Using Historical Data to Simulate Truck Journey

Discover how historical truck data and Python simulations can predict journey times and CO₂ emissions, helping logistics become smarter and greener.

Blog 5/1/21

Ways of Creating Single Case Discriminated Unions in F#

There are quite a few ways of creating single case discriminated unions in F# and this makes them popular for wrapping primitives. In this post, I will go through a number of the approaches that I have seen.

Blog 6/24/21

Using a Skill/Will matrix for personal career development

Discover how a Skill/Will Matrix helps employees identify strengths and areas for growth, boosting personal and professional development.

News 1/20/25

beBOLD becomes part of TIMETOACT GROUP

Cologne/Hamburg, January 20, 2025 – TIMETOACT GROUP has acquired beBOLD, a consultancy specializing in cloud transformation projects. The managing directors will continue to lead the company.

Service

Digital Architecture

In order to survive in a dynamic and highly competitive market, you need to be able to adapt your business processes, products and services efficiently to the needs and expectations of your customers

Kompetenz 1/21/25

Digital Maturity

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

Service

Process Transformation, Integration & Automation

Using Process Transformation, Integration & Automation to react quickly to market changes and sustainably improve competitiveness.

Service

Customer Experience​ & Retention​

Promote long-term customer relationships through targeted retention strategies based on excellent customer experience.

Navigationsbild zu Data Science
Service

AI & Data Science

We offer comprehensive solutions in the fields of data science, machine learning and AI that are tailored to your specific challenges and goals.

Service

Decision Automation

We offer a comprehensive service in the field of decision automation, ranging from consulting and design to implementation and operation

Service

Adoption & Change Management

Realize the full potential of your investments, overcome resistance and achieve sustainable change with Adoption & Change Management.

News 11/4/24

EverIT becomes part of catworkx and TIMETOACT GROUP

Cologne/Budapest, 4 November 2024 – catworkx (part of TIMETOACT GROUP), a leading partner for Enterprise integration based on the Atlassian platform, is acquiring EverIT, a specialized Hungarian based Atlassian Partner. Together, the companies will build on their long-standing relationship and expand catworkx’s leading market position into Central Eastern Europe and strengthen catworkx’s global offering. The parties agreed not to disclose the details of the transaction.

Standort

Site Singapore

Walldorf Consulting Asia Pacific Pte. Ltd; 3 Harbourfront Place; #11-01, Harbourfront Tower 2; Singapore 099254; Phone: +65 6350 5603 E-Mail: info@walldorfconsulting.com

Training
Service

Training

Do you have a special topic you want to be trained in? Please contact us. We will find and arrange the right training offer for you.

News 1/26/21

The IPG Group becomes part of the TIMETOACT GROUP

The TIMETOACT GROUP acquires the majority of the shares of IPG Information Process Group Holding AG, based in Winterthur. Through the acquisition, the competencies for Identity and Access Management (IAM) solutions in the DACH market are combined.

Bleiben Sie mit dem TIMETOACT GROUP Newsletter auf dem Laufenden!