The Job (API reference) class is a generic representation of jobs running through a project’s queue. Many tasks involved in modeling, such as creating a new model or computing feature impact for a model, will use a job to track the worker usage and progress of the associated task.

Checking the Contents of the Queue

To see what jobs running or waiting in the queue for a project, use the Project.get_all_jobs method.

from datarobot.enums import QUEUE_STATUS

jobs_list = project.get_all_jobs()  # gives all jobs queued or inprogress
jobs_by_type = {}
for job in jobs_list:
    if job.job_type not in jobs_by_type:
        jobs_by_type[job.job_type] = [0, 0]
    if job.status == QUEUE_STATUS.QUEUE:
        jobs_by_type[job.job_type][0] += 1
        jobs_by_type[job.job_type][1] += 1
for type in jobs_by_type:
    (num_queued, num_inprogress) = jobs_by_type[type]
    print('{} jobs: {} queued, {} inprogress'.format(type, num_queued, num_inprogress)')

Cancelling a Job

If a job is taking too long to run or no longer necessary, it can be cancelled easily from the Job object.

from datarobot.enums import QUEUE_STATUS

bad_jobs = project.get_all_jobs(status=QUEUE_STATUS.QUEUE)
for job in bad_jobs:

Retrieving Results From a Job

Once you’ve found a particular job of interest, you can retrieve the results once it is complete. Note that the type of the returned object will vary depending on the job_type. All return types are documented in Job.get_result.

from datarobot.enums import JOB_TYPE

time_to_wait = 60 * 60  # how long to wait for the job to finish (in seconds) - i.e. an hour
assert my_job.job_type == JOB_TYPE.MODEL
my_model = my_job.get_result_when_complete(max_wait=time_to_wait)