Core Concepts
Job
Understanding Jobs for grouping and analyzing environment runs
Job
A Job
groups related Environment runs (Trajectories) for organization and analysis.
Overview
Jobs help organize evaluation data, useful for:
- Grouping runs for a specific agent version or experiment.
- Running multiple trials of the same Task.
- Comparing different agent configurations.
- Viewing aggregated results and videos on the HUD platform.
Creating Jobs
1. The @job
Decorator (Recommended)
Decorate an async
function. A new Job is created per function call, and any environments created within using hud.gym.make()
are automatically linked.
name
(str): Job name on the HUD platform.metadata
(dict | None): Optional data for tracking.
2. Manual Creation (create_job
)
Create a Job
object manually and pass it to gym.make()
.
Accessing Job Data
Load a Job
by its ID to retrieve its details and associated Trajectories.
Job Properties
id
(str)name
(str)metadata
(dict | None)created_at
(datetime)status
(str)
Best Practices
- Use
@job
for most scripts. - Use descriptive names and metadata.
- Create separate jobs for distinct experiments.
Related Concepts
- Environment: Runs are linked to Jobs.
- Trajectory: Recordings grouped by Job; accessed via
job.load_trajectories()
. - Task: Defines the scenario for runs within a Job.