optimization-job-management.md

author	description	ms.author	ms.date	ms.service	ms.subservice	ms.topic	title	uid
KittyYeungQ	This document provides a basic guide to managing jobs submitted for solving optimization problems in Azure Quantum using Python.	kitty	02/01/2021	azure-quantum	optimization	how-to	Manage optimization jobs	microsoft.quantum.optimization.job-management

Job management

When a problem is submitted to a solver, a Job is created in Azure Quantum. The Workspace provides the following methods for managing jobs:

• get_job: Returns the Job metadata and results for a specific job (based on job id).
• list_jobs: Returns a list of all jobs in the workspace.
• cancel_job: Cancels a specific job.

See Job Cancellation for more information on how cancellation requests are processed.

You can use the list_jobs method to get a list of all jobs in the workspace:

jobs = [job.id for job in workspace.list_jobs()]
print(jobs)

> ['5d2f9cd70f55f149e3ed3aef', '23as12fs5d2f9cd70f55f', '1644428ea8507edb7361']

This shows how to submit a job asynchronously and call get_job to get the metadata (and results) for a previously submitted job, by id:

from azure.quantum.optimization import Problem, ProblemType, Term, ParallelTempering, SimulatedAnnealing

problem = Problem(name="MyOptimizationJob", problem_type=ProblemType.ising)
problem.add_term(c=-9, indices=[0])
problem.add_term(c=-3, indices=[1,0])
problem.add_term(c=5, indices=[2,0])

solver = SimulatedAnnealing(workspace)
job = solver.submit(problem)
print(job.id)

> 5d2f9cd70f55f149e3ed3aef

job = workspace.get_job(job.id)
results = job.get_results()
print(results)

> {'configuration': {'0': 1, '1': 1, '2': -1}, 'cost': -17.0}