Configuration¶

RHAPSODY uses a flexible configuration system for its session and backends.

Session Configuration¶

The Session object is primarily configured through its constructor:

Parameter	Type	Default	Description
`backends`	`list`	`None`	List of initialized backend objects.
`uid`	`str`	`None`	Unique ID for the session (generated if None).
`work_dir`	`str`	`None`	Working directory for task files (defaults to CWD).

Backend Configuration¶

Each backend has its own set of parameters.

Concurrent Backend¶

Local execution using Python's concurrent.futures.

from concurrent.futures import ThreadPoolExecutor
from rhapsody.backends import ConcurrentExecutionBackend

# Default uses ThreadPoolExecutor
backend = ConcurrentExecutionBackend(name="local")

# Or provide a custom executor
executor = ThreadPoolExecutor(max_workers=8)
backend = ConcurrentExecutionBackend(name="local", executor=executor)

Dask Backend¶

Distributed execution using Dask clusters.

DaskExecutionBackend(
    resources={"n_workers": 4, "memory_limit": "2GB"},
    cluster=pre_existing_cluster_obj, # Optional
    client=pre_existing_client_obj    # Optional
)

Preconfigured Clusters

If both cluster and client are omitted, Rhapsody will create a new LocalCluster using the provided resources.

Dragon Backend¶

High-performance execution using the Dragon runtime.

from rhapsody.backends import DragonExecutionBackendV3

backend = DragonExecutionBackendV3(
    name="dragon",
    num_workers=16,               # Total worker processes
    disable_telemetry=False,       # Enable/disable Dragon telemetry
    disable_background_batching=False, # Enable/disable background monitoring
    disable_batch_submission=False # Toggle batch vs individual submission
)

Batch vs. Stream Submission

The disable_batch_submission parameter controls how tasks are sent to the Dragon runtime:

Batch Mode (False): High throughput. Groups tasks into a single multi-task batch.
Stream Mode (True): Individual monitoring. Each task is submitted and tracked as a separate Dragon batch.

# Batch Mode (Recommended for many small tasks)
backend = await DragonExecutionBackendV3(disable_batch_submission=False)
await session.submit_tasks([t1, t2]) # Single submission

# Stream Mode (Better for isolated task tracking)
backend = await DragonExecutionBackendV3(disable_batch_submission=True)
await session.submit_tasks([t1, t2]) # Two separate submissions

Dragon Versions

While DragonExecutionBackendV3 is recommended for most users and will be always maintained, V1 and V2 are also available for legacy compatibility.

RADICAL-Pilot Backend¶

Large-scale HPC execution using RADICAL-Pilot.

RadicalExecutionBackend(
    resources={
        "resource": "local.localhost",
        "runtime": 30, # minutes
        "cores": 128
    }
)

Environment Variables¶

RHAPSODY respects the following environment variables:

RHAPSODY_LOG_LEVEL: Set to DEBUG, INFO, WARNING, ERROR, or CRITICAL.
RHAPSODY_WORK_DIR: Base directory for job artifacts.

Logging

You can also enable logging programmatically:

from rhapsody import enable_logging
enable_logging(level="DEBUG")