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Run a job through the API#

Login to the API#

First thing you need to do is to authenticate in the API and obtain an access token.

Run job using a previously uploaded dataset#

The endpoint to run a job for a given use case is as follows:

curl -X POST https://api.sandbox.qcentroid.com/problem/problem-urn
-H 'Authorization: Bearer {access_token}'
-H 'Content-Type: application/json'
-d '{"data_file_identifier": "070737d79192e816db1581409256bdefa0a834fb"}'

response = requests.post(
                url="https://api.sandbox.qcentroid.com/problem/maxcut",
                json={"data_file_identifier": "070737d79192e816db1581409256bdefa0a834fb"},
                headers={"Authorization": "Bearer " + access_token})

In the request’s body, you have to include the dataset id, which is a file already uploaded to the platform and that contains the input data for this execution.

After a successful job is launched, the API returns the Job Id to be used later to check its status and get the output.

Job execution response
{
    "detail": "Authorized. Processing file",
    "job": "W4P3Q4YTSDU1"
}

Run job using providing inline data#

If your input data for the execution is not too large (less than 4 MB), you can provide it directly in the request in JSON format.

In this example, we are providing input data for the Max Cut use case:

curl -X POST https://api.sandbox.qcentroid.com/problem/maxcut
-H 'Authorization: Bearer {access_token}'
-H 'Content-Type: application/json'
-d '{ "num_nodes": 6,
    "adj_matrix": [[0, 9, 5, 2, 4, 1],
                    [9, 0, 3, 8, 7, 6],
                    [5, 3, 0, 2, 8, 4],
                    [2, 8, 2, 0, 9, 3],
                    [4, 7, 8, 9, 0, 2],
                    [1, 6, 4, 3, 2, 0]] }'

response = requests.post(
                url="https://api.sandbox.qcentroid.com/problem/maxcut",
                json={  "num_nodes": 6,
                        "adj_matrix": [[0, 9, 5, 2, 4, 1],
                                        [9, 0, 3, 8, 7, 6],
                                        [5, 3, 0, 2, 8, 4],
                                        [2, 8, 2, 0, 9, 3],
                                        [4, 7, 8, 9, 0, 2],
                                        [1, 6, 4, 3, 2, 0]] },
                headers={"Authorization": "Bearer " + access_token})

Tip

Visit the use case’s details page in the web dashboard to check the input data format.

After a successful job is launched, the API returns the Job Id to be used later to check its status and get the output.

Job execution response
{
    "detail": "Authorized. Processing file",
    "job": "W4P3Q4YTSDU1"
}

Check job status#

To check the status of a job, use the following API GET request, providing the Job Id obtained at job execution:

curl -X GET https://api.sandbox.qcentroid.com/job/W4P3Q4YTSDU1
-H 'Authorization: Bearer {access_token}'

response = requests.get(
                url="https://api.sandbox.qcentroid.com/job/W4P3Q4YTSDU1",
                headers={"Authorization": "Bearer " + access_token})

This endpoint returns a JSON object like this one, with all the job details:

Job status response
{
    "job": {
        "W4P3Q4YTSDU1": {
            "status": "PENDING",
            "started_at": "08/15/2024, 10:52:45",
            "end_at": "",
            "executions": {

                ...

            }
        }
    }
}

What’s next#

See the job results in the web dashboard

Visit the API documentation site