Solve long-running problems
In the example in Apply solvers to solve optimization problems, a problem was submitted to Azure Quantum and solved synchronously. This is convenient for certain environments, but unsuitable for others where there is a need to either submit a problem and check on it later, or submit many problems and compare the results.
Submit the problem
To submit a problem asynchronously, use the submit method on the solver. This submits a Job which is returned by the method:
solver = ParallelTempering(workspace, timeout=100, seed=11)
job = solver.submit(problem)
print(job.id)
> ea81bb40-682f-11ea-8271-c49dede60d7c
Refresh job status
After submitting the job, you can check on the status of the job by calling the
refresh method. Each time refresh is called, the job metadata gets refreshed.
job.refresh()
print(job.details.status)
> Succeeded
Get the job output
Once the job is in a final state, such as Succeeded, you may download the job output using get_results:
jobId = "ea81bb40-682f-11ea-8271-c49dede60d7c"
job = workspace.get_job(jobId)
result = job.get_results()
print(result)
> {'solutions': [{'configuration': {'0': 1, '1': 1, '2': -1, '3': 1}, 'cost': -32.0}]}
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