Logs and outputs#

Status and spend#

Python

job = client.get("job_387ee42f5e")
print(job.status.value, f"{job.progress:.0%}", job.spend, job.attempts)

Field	Meaning
`status`	`queued`, `running`, `recovering`, `succeeded`, `stopped`, `failed`, `cancelled`
`progress`	Share of `work_units` completed, 0 to 1
`spend`	Dollars spent so far, across all attempts
`attempts`	Machines the job has been placed on
`offer`	The current or last machine: GPU, provider, region, price

Logs#

Python

print(job.logs(tail=50))

Bash

runcompute logs job_387ee42f5e --tail 50

Logs contain RunCompute's own lines (placement, preemption, resume) and your container's output, each prefixed with a time and a source such as [runcompute], [container] or [train].

Events#

Events are the structured version of the lifecycle lines in the log.

Python

for e in job.events():
    print(e["seq"], e["kind"], e["msg"])

Kind	When
`submit`	The job was accepted
`match`	The job was placed on a machine
`checkpoint`	A checkpoint was saved
`preempt`	The provider took the machine back
`resume`	The job restarted from a checkpoint
`budget`	Spend reached the budget and the job stopped
`done`	The job finished
`cancel`	You cancelled it
`error`	No machine fits the remaining budget or constraints

Pass after= with the last seq you saw to get only new events.

Outputs#

Files your job writes under /outputs are kept after it ends.

Python

for out in job.outputs():
    print(out.name, out.size_bytes)

Bash

runcompute outputs job_387ee42f5e