Skip to main content

Fixing ValidationProblemDetails serialization Issues when using the JSON Source Generator in ASP.NET Core

As I gladly accept any kind of performance improvement I can get in my applications, I like to use the System.Text.Json source generator to generate the serialization logic for my Data Transfer Objects.

However after upgrading a project to .NET 8, I started to get errors.

The problem

When using ASP.NET Core's [ApiController] attribute with automatic model validation, the framework automatically returns ValidationProblemDetails objects for validation errors. However, if you've configured your application to use System.Text.Json source generators for performance benefits, you might encounter serialization exceptions like:

System.NotSupportedException: JsonTypeInfo metadata for type 'Microsoft.AspNetCore.Mvc.ValidationProblemDetails' was not provided by TypeInfoResolver of type '[]'. If using source generation, ensure that all root types passed to the serializer have been annotated with 'JsonSerializableAttribute', along with any types that might be serialized polymorphically.

This occurs because the source generator doesn't have the necessary metadata to serialize ValidationProblemDetails or ProblemDetails at compile time.

Turns out I’m not the first one with this problem as I found more details in the following GitHub issue: `[ApiController]` attributes causes exception during serialization of `(Validation)ProblemDetails` when using source-generator-based serialization · Issue #57019 · dotnet/aspnetcore

A solution?

I couldn’t find a better solution, so I fixed it by explicitly adding the Validation types to my JsonSerializerContext:

I don’t know if this is the right solution. So if you know a better way, please let me know!

More information

`[ApiController]` attributes causes exception during serialization of `(Validation)ProblemDetails` when using source-generator-based serialization · Issue #57019 · dotnet/aspnetcore

Optimize your API performance with the System.Text.Json source generator

.NET 8– System.Text.Json serializer error

Popular posts from this blog

Podman– Command execution failed with exit code 125

After updating WSL on one of the developer machines, Podman failed to work. When we took a look through Podman Desktop, we noticed that Podman had stopped running and returned the following error message: Error: Command execution failed with exit code 125 Here are the steps we tried to fix the issue: We started by running podman info to get some extra details on what could be wrong: >podman info OS: windows/amd64 provider: wsl version: 5.3.1 Cannot connect to Podman. Please verify your connection to the Linux system using `podman system connection list`, or try `podman machine init` and `podman machine start` to manage a new Linux VM Error: unable to connect to Podman socket: failed to connect: dial tcp 127.0.0.1:2655: connectex: No connection could be made because the target machine actively refused it. That makes sense as the podman VM was not running. Let’s check the VM: >podman machine list NAME         ...

Azure DevOps/ GitHub emoji

I’m really bad at remembering emoji’s. So here is cheat sheet with all emoji’s that can be used in tools that support the github emoji markdown markup: All credits go to rcaviers who created this list.

VS Code Planning mode

After the introduction of Plan mode in Visual Studio , it now also found its way into VS Code. Planning mode, or as I like to call it 'Hannibal mode', extends GitHub Copilot's Agent Mode capabilities to handle larger, multi-step coding tasks with a structured approach. Instead of jumping straight into code generation, Planning mode creates a detailed execution plan. If you want more details, have a look at my previous post . Putting plan mode into action VS Code takes a different approach compared to Visual Studio when using plan mode. Instead of a configuration setting that you can activate but have limited control over, planning is available as a separate chat mode/agent: I like this approach better than how Visual Studio does it as you have explicit control when plan mode is activated. Instead of immediately diving into execution, the plan agent creates a plan and asks some follow up questions: You can further edit the plan by clicking on ‘Open in Editor’: ...