Job attributes

Every job that runs in Camber has a set of attributes. This attributes report information about the job ID, status, engine, and so on. You can access an engine’s jobs though either the base class, or through a subclass for a specific engine:

import camber
camber.mpi.list_jobs() ## returns MPIJob instances
camber.job.CamberJob.list()

A line of output looks something like this:

 CamberJob({"job_id": 4648, "status": "PENDING", "engine_size": "SMALL", "engine_type": "MPI", "command": "mpirun -np 4 mpi_hello_world", "with_gpu": false}),

`status`

Status	Description
`PENDING`	The job is queued to run. The wait time depends on when the next on-demand is available.
`PROVISIONING`	The job is provisioning.
`INITIALIZING`	The job is initializing.
`RUNNING`	Camber is running the job.
`COMPLETED`	The job has finished.
`FAILED`	The job has failed.
`CANCELLED`	The job was intentionally stopped, such as when user calls `job.clear()` in the middle of a run.

`engine_size`

Engine size is configured through the engine_size parameter of the create_job() instance. Its values can be one of the following.

XMICRO
MICRO
XXSMALL
XSMALL
SMALL
MEDIUM
LARGE

In the context of GPU jobs,XSMALL, MEDIUM, and LARGE are supported currently.

`engine_type`

What type of engine ran. Can be

MPI
MESA
ATHENA
LLM
ESO
CHANGA

`command`

The commmand that the job ran, for example, make.

`with_gpu`

Whether the job ran with GPU.

`tags`

When applicable, the job tags. You can use tags to filter the returned list methods.

camber.mpi.list_jobs(tags="virgo-supercluster")

Glossary