Fabric API - Jobs

run_job, wait_for_job, get_job and cancel_job, the job types for notebooks, pipelines and report refreshes, and the statuses.

Running a notebook, running a pipeline and refreshing a report's data are all jobs in Fabric, and the four methods below start, wait for, check and cancel them. Each method takes the workspace ID and the ID of the item the job belongs to.

Job types

Item	Job type	What it does
Notebook	`RunNotebook`	Runs the notebook once
Pipeline	`Pipeline`	Runs the pipeline once
A report's dataset	`DefaultSemanticModelRefresh`	Refreshes the report's data from the tables it reads

Statuses

get_job reports one of these in status:

Status	Meaning
`NotStarted`	Accepted, not yet running
`InProgress`	Running
`Completed`	Ended without error
`Failed`	Ended with an error, details in `failureReason`
`Cancelled`	Stopped with `cancel_job` or from Fabric
`Deduped`	Not started, because the same job was already running

The first two mean the job is still going, everything else means it has ended.

run_job

conn.run_job(workspace_id, item_id, job_type, payload=None)

Starts a job and returns without waiting for it.

Parameter	Type	Meaning
`workspace_id`	str	The workspace the item is in
`item_id`	str	The notebook, pipeline or dataset
`job_type`	str	One of the job types above
`payload`	dict	Parameters for the job, or none

Returns the job's ID as a string, for get_job and cancel_job.

Parameters go under executionData. A notebook takes them with a value and a type each, a pipeline takes plain values:

# -*- coding: utf-8 -*-

# Zato
from zato.server.service import Service

class RunNotebook(Service):

    def handle(self):

        workspace_id = '262ddd3d-3d0d-4495-b80f-6dddda1e23a1'
        notebook_id = 'ba7b1e23-b680-4fe7-a982-2a979b125604'

        conn = self.microsoft.fabric['Zato Fabric']

        payload = {
            'executionData': {
                'parameters': {
                    'location': {'value': 'Riverside', 'type': 'string'},
                    'days_ahead': {'value': '1', 'type': 'int'},
                }
            }
        }

        job_id = conn.run_job(workspace_id, notebook_id, 'RunNotebook', payload)

        self.response.payload = {'job_id': job_id}

payload = {
    'executionData': {
        'parameters': {
            'source_table': 'admissions',
            'target_table': 'occupancy',
        }
    }
}

job_id = conn.run_job(workspace_id, pipeline_id, 'Pipeline', payload)

A report refresh takes no parameters:

job_id = conn.run_job(workspace_id, dataset_id, 'DefaultSemanticModelRefresh')

wait_for_job

conn.wait_for_job(workspace_id, item_id, job_id, timeout=1800, interval=10.0)

Waits until a job ends and returns its final state, checking with get_job every interval seconds.

Parameter	Type	Meaning
`workspace_id`	str	The workspace the item is in
`item_id`	str	The item the job belongs to
`job_id`	str	The ID `run_job` returned
`timeout`	int	How many seconds to wait at most, 30 minutes by default
`interval`	float	How many seconds between two checks, 10 by default

Returns the same dict as get_job once the status is Completed. A job that ends with any other status raises an exception with the job's details, and so does one that is still running when the timeout passes, the job itself keeps running in Fabric then.

# -*- coding: utf-8 -*-

# Zato
from zato.server.service import Service

class RunAndWait(Service):

    def handle(self):

        workspace_id = '262ddd3d-3d0d-4495-b80f-6dddda1e23a1'
        pipeline_id = 'bf4868aa-05c8-4213-ab4d-8dcbe3189767'

        conn = self.microsoft.fabric['Zato Fabric']

        job_id = conn.run_job(workspace_id, pipeline_id, 'Pipeline')
        job = conn.wait_for_job(workspace_id, pipeline_id, job_id, timeout=600)

        self.response.payload = {'status': job['status'], 'ended': job['endTimeUtc']}

{"status": "Completed", "ended": "2026-09-02T02:34:11Z"}

get_job

conn.get_job(workspace_id, item_id, job_id)

Returns the job's current state without waiting for it.

Parameter	Type	Meaning
`workspace_id`	str	The workspace the item is in
`item_id`	str	The item the job belongs to
`job_id`	str	The ID `run_job` returned

Returns a dict with id, itemId, jobType, invokeType, status, startTimeUtc, endTimeUtc and, for a failed job, failureReason.

# -*- coding: utf-8 -*-

# Zato
from zato.server.service import Service

class GetJob(Service):

    input = 'job_id'

    def handle(self):

        workspace_id = '262ddd3d-3d0d-4495-b80f-6dddda1e23a1'
        notebook_id = 'ba7b1e23-b680-4fe7-a982-2a979b125604'

        # The ID of a job that run_job returned earlier
        job_id = self.request.input.job_id

        conn = self.microsoft.fabric['Zato Fabric']

        job = conn.get_job(workspace_id, notebook_id, job_id)

        self.response.payload = {
            'status': job['status'],
            'started': job['startTimeUtc'],
            'ended': job['endTimeUtc'],
        }

{"status": "Completed", "started": "2026-09-02T02:30:04Z", "ended": "2026-09-02T02:34:11Z"}

cancel_job

conn.cancel_job(workspace_id, item_id, job_id)

Stops a running job. Returns nothing, the job's status becomes Cancelled once it has stopped.

Parameter	Type	Meaning
`workspace_id`	str	The workspace the item is in
`item_id`	str	The item the job belongs to
`job_id`	str	The ID `run_job` returned

# -*- coding: utf-8 -*-

# Zato
from zato.server.service import Service

class CancelJob(Service):

    input = 'job_id'

    def handle(self):

        workspace_id = '262ddd3d-3d0d-4495-b80f-6dddda1e23a1'
        notebook_id = 'ba7b1e23-b680-4fe7-a982-2a979b125604'

        # The ID of a job that run_job returned earlier
        job_id = self.request.input.job_id

        conn = self.microsoft.fabric['Zato Fabric']

        conn.cancel_job(workspace_id, notebook_id, job_id)

Page	What it covers
Fabric notebooks and pipelines	run_job and wait_for_job for a notebook, a pipeline and a report refresh
Fabric API - Workspaces	Finding the item IDs the jobs need