SDK & API

The eugo.hpc Python API: decorators, resource options, and futures.

Courses

Turn ordinary Python into distributed work with a decorator, then scale it across a cluster.

What @eugo.hpc.distribute actually changes about a function, and why the call site stays clean.

The most common performance mistake in distributed code, and the two-line habit that avoids it.

Use .options() to ask for GPUs on the calls that need them, and only those.

When a task is the wrong shape: keeping an expensive object alive across many calls.

The terms this subject uses, defined.

Actor : A distributed object that holds state across many calls. Created by applying the distribute decorator to a class rather than a function.
distribute decorator : The eugo.hpc decorator that turns a function into a distributed task, or a class into an actor. A decorated call returns a future instead of a value.
eugo.hpc : The Python module holding Eugo’s distributed-compute API. The top-level eugo namespace is deliberately empty; everything lives under eugo.hpc.
Future : A handle to a result that does not exist yet. Calling a distributed function returns a future immediately, while the work happens elsewhere.
get() : The eugo.hpc call that resolves one or more futures into actual values, blocking until they are ready.
options() : The method that sets per-call resource requirements on a distributed function, such as num_cpus or num_gpus.
Task : One unit of distributed work: a single call to a function decorated with the distribute decorator. Tasks are stateless, so each call starts fresh.