mvm — Python SDK

Declare a microVM workload in Python. Write a function, decorate it, and the mvmctl toolchain bakes it into a Nix-built Firecracker / libkrun microVM image and boots it — no Dockerfile, no SSH, no agent code in your app.

pip install mvm

mvmctl (the Rust host CLI) is distributed separately and does the building, booting, and signing. This package is the authoring surface it reads.

Quick start

# app.py
import mvm as mv

@mv.func(name="adder")
def add(a: int, b: int) -> int:
    return a + b

mvmctl compile app.py     # parse the script (no execution) → flake.nix + launch plan
mvmctl up --flake .       # build the image and boot the microVM

@mv.func is the one-liner: it declares the workload, the app, and a function entrypoint with sane defaults (nix_packages(["python312"]), 1 vCPU / 256 MB / 512 MB rootfs). For full control, declare the pieces explicitly:

import mvm as mv

mv.workload(id="hello")

@mv.app(
    name="hello",
    source=mv.local_path("."),
    image=mv.nix_packages(["python312"]),
    resources=mv.resources(cpu_cores=1, memory_mb=256, rootfs_size_mb=512),
    env={"API_KEY": mv.secret("api-key")},
    before_start=mv.hook("export TZ=UTC"),
    after_start=mv.hook(["curl", "-fsS", "http://localhost:8080/health"]),
)
def main(name: str) -> str:
    return f"hello {name}"

How it builds

mvmctl compile reads your file statically — the decorator and the import mvm line are parsed as data, never executed, so nothing in your module runs on the host. At image-build time the decorator and the import mvm line are stripped from the bundled source, so the guest runs your plain function with no SDK dependency inside the microVM.

You can also emit the canonical Workload IR in-process, for inspection or tests:

import mvm as mv
print(mv.emit_json())     # the IR mvmctl would produce

Lifecycle hooks

Four hook points, each a shell string or an argv list (or a list of them). Addons contribute their own hooks, merged at compile time:

Building blocks

Dev-only runtime

f.remote(...) / mv.session(...) call into a running function-VM, and mv.Sandbox wraps local sandbox primitives. These are development conveniences for build-time emission and introspection. Production microVMs are observed through mvmctl output streams — there are no host-side .remote() calls on the prod path.

Optional extras

pip install 'mvm[schema]'   # pydantic-based schema derivation from type hints

Versioning

The SDK version tracks the mvmctl toolchain version: a workload emitted by mvm X.Y.Z is consumed by mvmctl X.Y.Z. Install matching versions.

Links

• Source & issues: https://github.com/tinylabscom/mvm
• TypeScript SDK: @runmvm/mvm

License

Apache-2.0 — see LICENSE.