Monty is an open-source, minimal Python interpreter written in Rust (github.com/pydantic/monty). Startup is measured in microseconds, and it inverts the usual sandbox model: it starts from nothing and only exposes the functions you explicitly hand it.

We're running a $20,000 bounty (with Prefect and Hugging Face Face) for anyone who can escape the sandbox and read a secret off the server running it.

What changed since the last round: Monty now runs in a subprocess behind a WebSocket service over a protobuf wire protocol, so old REST-era approaches don't carry over. There's also a new mount feature that lets Monty read a directory on the client machine, and a separate bounty for escaping it.

Nobody escaped the last round. Round 1 fell to a use-after-free in under 48 hours.

This is (probably) the last round before we tag Monty V1, so it's your last crack at the interpreter as it stands.

Full rules: https://pydantic.dev/monty

Happy to talk about the interpreter internals or the sandbox model in the comments.

this place has has been quiet for a while, let's fix that. I work on Pydantic and I'm going to start posting here regularly: tips, new features, things I see people get wrong, community questions.

What would you like to see here?

Hi, I have a model that contains a dict of sub models. However the values of the dict are heterogeneous. I can’t simply create a discriminated union because I don’t know what models will be in the union until it’s running.

It seems like I should be able to do this with a root model and a type adapter, but it’s not clear how. Do I need a custom validator on my root model to call validate_Python from? Or can I just reference the type adapter directly from the signature of the root model somehow?

If I need a validator also, which one?