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Embed isolated microVM sandboxes directly in your Python code — local (embedded) or smolfleet cloud.

Project description

smol — Python SDK

Embed isolated microVM sandboxes directly in your Python code. Same API locally (embedded engine, no server) or against the smolfleet cloud — the backend is chosen via ConnectOptions / SMOL_CLOUD_TOKEN. Mirrors the Node SDK.

Supported platforms (native local transport): macOS Apple Silicon, and Linux x64/arm64 with glibc ≥ 2.34 (RHEL 9, Ubuntu 22.04+, Debian 12, Amazon Linux 2023; the wheel is tagged manylinux_2_34). The cloud transport works anywhere the wheel installs. Not yet published: macOS Intel, and glibc < 2.34.

from smol import Machine, MachineConfig, ResourceSpec

# Local (embedded microVM) — boots in-process, no server.
with Machine.create(MachineConfig(resources=ResourceSpec(cpus=2, memory_mb=1024, network=True))) as m:
    res = m.run("python:3.12", ["python", "-c", "print(2 ** 10)"])
    res.assert_success()
    print(res.stdout)            # 1024
    m.write_file("/tmp/in.txt", "hi")
    print(m.read_file("/tmp/in.txt").decode())

# Cloud (smolfleet) — same API, just point at the cloud.
from smol import ConnectOptions
with Machine.create(
    MachineConfig(image="alpine:3.20"),
    ConnectOptions(target="cloud", api_key="smk_…"),  # or set SMOL_CLOUD_TOKEN
) as m:
    print(m.exec(["echo", "hi"]).stdout)

Async: AsyncMachine (non-blocking)

Machine is synchronous — each call blocks the calling thread. When you're driving many machines from one event loop (a fleet of disposable workers), use AsyncMachine: the same API, but every I/O method is a coroutine that runs off the loop, so launches and calls overlap instead of serializing.

import asyncio
from smol import AsyncMachine, MachineConfig, ConnectOptions, PortSpec

async def main():
    cfg = MachineConfig(image="alpine:3.20", ports=[PortSpec(host=8080, guest=8080)])
    conn = ConnectOptions(target="cloud")  # or SMOL_CLOUD_TOKEN
    # Launch a fleet concurrently — none blocks the loop.
    machines = await asyncio.gather(*(AsyncMachine.create(cfg, conn) for _ in range(8)))
    try:
        await asyncio.gather(*(m.wait_until_ready() for m in machines))
        # Reach a service inside a vm via the authed connect bridge (no tunnel):
        health = await machines[0].request(8080, "healthz")
    finally:
        await asyncio.gather(*(m.delete() for m in machines))

asyncio.run(main())

Every Machine method has an awaitable counterpart on AsyncMachine (create/connect/exec/wait_until_ready/request/fork/…), plus async with for auto-delete. endpoint(port) stays synchronous — it only builds a URL and does no I/O.

Architecture

  • Pure-Python layer (python/smol): Machine, transports, types, errors — zero third-party deps (the cloud transport uses only urllib).
  • Native core (src/lib.rs, crate smol-py): a pyo3 extension that links the smolvm engine in-process for the local path — the Python analogue of the smol-node NAPI crate. The local API is synchronous (the engine blocks).
  • Cloud transport: a REST client to smolfleet /v1 whose request/response shapes match smolfleet's OpenAPI contract (Bearer smk_…).

Disposable workers: wait for ready, then connect (cloud)

Launching a machine as a disposable agent runtime has two easy-to-miss steps; both are first-class here.

Machine.create() already waits for the machine to be ready — not merely started. state == "started" means the VM process launched; the guest is still booting and is not usable yet. Acting on started is the classic teardown race (works on a slow cold start, times out on a warm one). Gate on the unambiguous signal:

with Machine.create(
    MachineConfig(image="alpine:3.20", ports=[PortSpec(host=8080, guest=8080)]),
    ConnectOptions(target="cloud"),
) as m:
    m.wait_until_ready()           # create() already waited; re-assert if reconnecting
    print(m.ready(), m.ready_at())

    # Reach a service INSIDE the vm through the authenticated connect bridge —
    # no Cloudflare/localhost.run tunnel, no public exposure, no egress allow-list.
    # Have the worker LISTEN on a published port and connect *inbound*:
    print(m.request(8080, "healthz").decode())     # authed HTTP to the guest port
    ep = m.endpoint(8080, "/socket")               # or build a ws:// url for your ws client
    # websocket.connect(ep.ws_url, additional_headers=ep.headers)

API

  • Machine (sync) / AsyncMachine (awaitable, non-blocking) — identical surface; see the async example above.
  • Machine.create(config=None, conn=None) — create and start a machine.
  • machine.exec(command, opts=None) / machine.run(image, command, opts=None)ExecResult
  • machine.read_file(path)bytes / machine.write_file(path, data, mode=None)
  • machine.ready() / machine.ready_at() / machine.wait_until_ready(timeout_s=120, interval_s=1) (cloud)
  • machine.endpoint(port, path=None)PortEndpoint / machine.request(port, path=None, method="GET", data=None)bytes (cloud connect bridge)
  • machine.pull_image(image) / machine.list_images() (local)
  • machine.stop() / machine.delete() / machine.state()
  • Use it as a context manager to auto-delete() on exit.
  • Errors are typed: SmolError (with .code), ExecutionError, NotSupportedError, InvalidConfigError.

ExecResult has .exit_code, .stdout, .stderr, .success, .output, and .assert_success().

Install / build from source

The cloud path is pure Python. The local path needs the native extension, which links libkrun from the sibling smolvm repo (three levels up).

python -m venv .venv && . .venv/bin/activate
pip install maturin
# Build + install the native extension (points at the repo's bundled libkrun):
LIBKRUN_BUNDLE=../../../lib maturin develop

To boot local microVMs the engine needs a code-signed boot helper carrying the macOS com.apple.security.hypervisor entitlement (the Python process itself does not). Point it at one (and the libkrun dir):

SMOLVM_BOOT_BINARY=../../../target/release/smolvm \
SMOLVM_LIB_DIR=../../../lib \
python your_script.py

On Linux the host needs /dev/kvm.

Tests

python tests/test_unit.py        # error parsing + path encoding (no VM/network)
python tests/test_cloud_mock.py  # cloud transport vs a mock /v1 (no VM/network)
python tests/test_async_mock.py  # AsyncMachine vs a mock /v1 (concurrency, no VM/network)
# Local VM boot (needs the native build + the env above):
SMOLVM_BOOT_BINARY= SMOLVM_LIB_DIR= .venv/bin/python tests/test_local_e2e.py

License

Apache-2.0

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