mcframework.backends.ProcessBackend

class mcframework.backends.ProcessBackend

Bases: object

Process-based parallel execution backend.

Uses concurrent.futures.ProcessPoolExecutor with spawn context for parallel execution. Required on Windows or when thread-safety is a concern.

Parameters:

n_workersint

Number of worker processes to use.

chunks_per_workerint, default 8

Number of work chunks per worker for load balancing.

Notes

The simulation instance must be pickleable for process-based execution.

Examples

>>> backend = ProcessBackend(n_workers=4)
>>> results = backend.run(sim, n_simulations=100000, seed_seq=seed_seq, progress_callback=None)

Methods

run	Run simulations in parallel using processes.

run(sim: MonteCarloSimulation, n_simulations: int, seed_seq: np.random.SeedSequence | None, progress_callback: Callable[[int, int], None] | None, **simulation_kwargs: Any) → np.ndarray

Run simulations in parallel using processes.

Parameters:

simMonteCarloSimulation

The simulation instance to run. Must be pickleable.

n_simulationsint

Number of simulation draws to perform.

seed_seqSeedSequence or None

Seed sequence for spawning independent RNG streams per chunk.

progress_callbackcallable() or None

Optional callback f(completed, total) for progress reporting.

**simulation_kwargsAny

Additional keyword arguments passed to single_simulation.

Returns:

np.ndarray

Array of simulation results with shape (n_simulations,).

__init__(n_workers: int, chunks_per_worker: int = 8)

classmethod __new__(*args, **kwargs)