Execution Engines & Jobs

ContextWorker uses pluggable execution engines and a job orchestration layer to run background tasks.

Execution Engines

Worker supports multiple execution backends via the engines/ package:

TemporalEngine

Production-grade durable workflows using Temporal.io:

from contextunity.worker.engines.temporal_engine import TemporalEngine

engine = TemporalEngine(config)
await engine.start()

Temporal workflows survive process restarts, network failures, and server crashes with automatic state persistence and retry.

HueyEngine

Lightweight task queue using Huey for simpler deployments:

from contextunity.worker.engines.huey_engine import HueyEngine

engine = HueyEngine(config)
await engine.start()

Both engines implement the BaseEngine protocol from engines/base.py. The engine is selected via configuration.

Built-in Jobs

Worker includes several built-in job types in jobs/:

Module	Purpose
`orchestrator.py`	Job orchestration and coordination
`retention.py`	Data retention policies and cleanup
`scrum_master.py`	Automated task management and scheduling

Module Registry

Domain-specific plugins register their workflows and activities via the WorkerRegistry:

from contextunity.worker.core.registry import WorkerRegistry, ModuleConfig

registry = WorkerRegistry()
registry.register(ModuleConfig(
    name="harvest",
    workflows=[HarvestWorkflow],
    activities=[fetch_products, transform_data],
))

Modules are discovered at startup and can be filtered via --modules flag.