Oskar Dudycz

Pragmatic about programming

Explicit validation in C# just got simpler!

2023-02-05 oskar dudyczCoding Life

cover

Validation is a thriving concept. It enables incredible creativity in developers implementing it in various ways. I explained my general take on How to validate business logic. This time, let’s look at how we could simplify our approach in C# language.

The typical flow of Line of business web application is:

  • User fills a form data in the UI (e.g. web application),
  • Web application serialises it as the web request and calls the Web API endpoint,
  • Web API parses data and runs business logic.

On each step, we should perform validation.

Let’s focus on the last step for now. In ASP.NET, the validation is quite often conflated with parsing and model binding. Historically, .NET devs got accustomed to doing all at once. It may sound like a brilliant idea, but it’s also a pit of performance issues and nasty production bugs to debug. It all goes well while we remember the conventions and follow them precisely. Yet, the number of permutations we may find makes it hard to tame.

The potential solution could be explicit validation, so break the exact flow into parse first, then validate. If you have tried that already, you may think I’m suggesting you become a caveman and do a lot of copy-pasting. Also, you may ask how to achieve human-friendly error messages.

And yeah, I’ve been there and struggled with those issues. But I learned from it. Plus, new stuff in .NET can make this more accessible.

Let’s say we’d like to register a new Product in our product catalogue. We may want to have it strongly typed, like:

public record RegisterProduct(
    ProductId ProductId,
    SKU SKU,
    string Name,
    string? Description
)

public record ProductId(Guid Value)

public record SKU(string Value)

I’m using records and nullable types, as they’re a decent way for modelling data transfer objects.

Yet, they, unfortunately, we can still provide wrong values to our types, e.g.:

var validSKU = new SKU("ZS1023");

var forcedNull = new SKU(null!);

var wrongSKU = new SKU("wrong format");

What to do, then? We can use the Smart Constructor pattern presented in the previous post.

public record SKU(string Value)
{
    public static SKU From(string sku)
    {
        if (sku== null)
            throw new ArgumentNullException(nameof(sku));
        if (string.IsNullOrWhiteSpace(sku) || !Regex.IsMatch(sku, "[A-Z]{2,4}[0-9]{4,18}"))
            throw new ArgumentOutOfRangeException(nameof(sku));

        return new SKU(sku);
    }
}

That can help us to validate SKU creation with the following:

// both calls will throw ArgumentException
var forcedNull = SKU.From(null!);
var wrongSKU = SKU.From("wrong format");

Thanks to nameof(sku), we’ll get information on which field was wrong. We can also map ArgumentException by convention to 400 Bad Request HTTP status.

It won’t guard against such calls:

var worseSKU = sku with { Value = "definitely wrong value" };

var theWorstSKU = sku with { Value = null! };

To do that, we’ll need to implement SKU as:

public record SKU
{
    public string Value { get; }

    [JsonConstructor]
    private SKU(string value) =>
        Value = value;

    public void Deconstruct(out string? value) =>
        value = Value;

    public static SKU From(string sku)
    {
        if (sku== null)
            throw new ArgumentNullException(nameof(sku));
        if (string.IsNullOrWhiteSpace(sku) || !Regex.IsMatch(sku, "[A-Z]{2,4}[0-9]{4,18}"))
            throw new ArgumentOutOfRangeException(nameof(sku));

        return new SKU(sku);
    }
}

By hiding the public constructor, we’re disabling the usage of with, keeping the deconstruction capabilities, and we also enable proper deserialisation.

That’s a lot of code, and maybe it’s better to keep the convention that we’re calling Smart Constructor in our code and leave with that tradeoff.

Still, if we’ll need to write such copy-and-paste validation logic, it would quickly become tedious and, thus: error-prone.

Luckily, as promised, we could do better than that. We’ll use two techniques to achieve it:

Have a look at the following method:

public static class Validation
{
    public static string AssertNotEmpty(
        [NotNull] this string? value,
        [CallerArgumentExpression("value")] string? argumentName = null
    ) =>
        !string.IsNullOrWhiteSpace(value)
            ? value
            : throw new ArgumentOutOfRangeException(argumentName);
}

It’s an extension method that takes a nullable string value and checks if it’s not null or empty, then returns not null value. It’s a classical guard method.

What’s unusual is that we’re using cryptic [CallerArgumentExpression(“value”)] string? argumentName syntax. It tells the compiler that it should try to resolve the argument name of the parameter value from the caller context.

If we use it as:

string? sku = null;

sku.AssertNotEmpty();

Then it’ll automatically use the sku as the parameter name for the ArgumentException. That’s not all!

If we do:

string? sku = "ZS1023";

sku.AssertNotEmpty();

string verifiedSku = sku;

Then using the NotNull argument tells the compiler that if this method runs successfully, the variable is not null.

Note that this will work only for the nullable reference type. For the value types like Guid, we’ll need to use the returned value from the method, but that’s also neat, isn’t it?

public static class Validation
{
    public static Guid AssertNotEmpty(
        [NotNull] this Guid? value,
        [CallerArgumentExpression("value")] string? argumentName = null
    ) =>
        (value != null && value.Value != Guid.Empty)
            ? value.Value
            : throw new ArgumentOutOfRangeException(argumentName);
}

Guid? productId = "ZS1023";

// this will work
Guid verifiedProductId = productId.AssertNotEmpty();

// this won't compile
Guid verifiedProductId = productId;

We can compose those methods and build simple but powerful fleet of validation methods:

public static class Validation
{
    public static Guid AssertNotEmpty(
        [NotNull] this Guid? value,
        [CallerArgumentExpression("value")] string? argumentName = null
    ) =>
        (value != null && value.Value != Guid.Empty)
            ? value.Value
            : throw new ArgumentOutOfRangeException(argumentName);


    public static string AssertNotEmpty(
        [NotNull] this string? value,
        [CallerArgumentExpression("value")] string? argumentName = null
    ) =>
        !string.IsNullOrWhiteSpace(value)
            ? value
            : throw new ArgumentOutOfRangeException(argumentName);


    public static string? AssertNullOrNotEmpty(
        this string? value,
        [CallerArgumentExpression("value")] string? argumentName = null
    ) =>
        value?.AssertNotEmpty(argumentName);

    public static string AssertMatchesRegex(
        [NotNull] this string? value,
        [StringSyntax(StringSyntaxAttribute.Regex)]
        string pattern,
        [CallerArgumentExpression("value")] string? argumentName = null
    ) =>
        Regex.IsMatch(value.AssertNotEmpty(), pattern)
            ? value
            : throw new ArgumentOutOfRangeException(argumentName);

    public static int AssertPositive(
        [NotNull] this int? value,
        [CallerArgumentExpression("value")] string? argumentName = null
    ) =>
        value?.AssertPositive() ?? throw new ArgumentOutOfRangeException(argumentName);

    public static int AssertPositive(
        this int value,
        [CallerArgumentExpression("value")] string? argumentName = null
    ) =>
        value > 0
            ? value
            : throw new ArgumentOutOfRangeException(argumentName);
}

Then our final mapping with smart constructors can look as follows:

public readonly record struct ProductId(Guid Value)
{
    public static ProductId From(Guid? productId) =>
        new(productId.AssertNotEmpty());
}

public readonly record struct SKU(string Value)
{
    public static SKU From(string? sku) =>
        new(sku.AssertMatchesRegex("[A-Z]{2,4}[0-9]{4,18}"));
}

public record RegisterProduct(
    ProductId ProductId,
    SKU SKU,
    string Name,
    string? Description
)
{
    public static RegisterProduct From(Guid? id, string? sku, string? name, string? description) =>
        new(
            ProductId.From(id),
            SKU.From(sku),
            name.AssertNotEmpty(),
            description.AssertNullOrNotEmpty()
        );
}

Then we can use it in the endpoint as follows:

endpoints.MapPost(
        "api/products/",
        async (
            ProductsDBContext dbContext,
            RegisterProductRequest request,
            CancellationToken ct
        ) =>
        {
            var (sku, name, description) = request;
            var productId = Guid.NewGuid();

            var command = RegisterProduct.From(productId, sku, name, description);

            await Handle(
                dbContext.AddAndSave,
                dbContext.ProductWithSKUExists,
                command,
                ct
            );

            return Created($"/api/products/{productId}", productId);
        })
    .Produces(StatusCodes.Status201Created)
    .Produces(StatusCodes.Status400BadRequest);


// we're embracing here that we can expect anything from the UI
public record RegisterProductRequest(
    string SKU,
    string Name,
    string? Description
);

The main downside of this approach may be that it’s fail fast. It’ll throw an exception on the first wrong property. We won’t get a listing of all the incorrect values. Still, that will be fine for the UI-based requests, as we should have validations made there. If the request bypassed them, it either means we forgot to align them or someone made something malicious. For the API-first design, that may be a more significant issue if our convention is to return all errors instead of failing fast.

I believe that such an explicit approach is much safer and clearer. We’re depending on the compiler, getting failures during development, not in runtime. We’re making explicit things that should be explicit and have control over what’s happening.

There are no redundant allocations, and no reflection magic, which is an obvious win.

Keeping validation in the code also creates a better form of documentation, as looking at the class, we see what to expect. Once we create an instance of an object, we can trust it and don’t repeat validation in multiple places.

Of course, such an approach requires consistency and consideration in the types of design, but if we keep it stupidly simple, then such composition can take us pretty far and reduce the headache of unpleasant surprises on production.

Cheers!

Oskar

p.s. Ukraine is still under brutal Russian invasion. A lot of Ukrainian people are hurt, without shelter and need help. You can help in various ways, for instance, directly helping refugees, spreading awareness, putting pressure on your local government or companies. You can also support Ukraine by donating e.g. to Red Cross, Ukraine humanitarian organisation or donate Ambulances for Ukraine.

👋 If you found this article helpful and want to get notification about the next one, subscribe to Architecture Weekly.

✉️ Join over 5000 subscribers, get the best resources to boost your skills, and stay updated with Software Architecture trends!

Loading...
Event-Driven by Oskar Dudycz
Oskar Dudycz For over 15 years, I have been creating IT systems close to the business. I started my career when StackOverflow didn't exist yet. I am a programmer, technical leader, architect. I like to create well-thought-out systems, tools and frameworks that are used in production and make people's lives easier. I believe Event Sourcing, CQRS, and in general, Event-Driven Architectures are a good foundation by which this can be achieved.