Execute Data Pipeline Via API

One additional comment to the solution:

1. If you need to pass parameters to the pipeline, you need to provide a payload/body in the following format:

{   "executionData": {
        "parameters": {
            "YourParameter1": 1,
            "YourParameter2": "Param2
        }
    }
}

Tip: if you want to call Fabric APIs from a Fabrik Notebook you can use the semantic link library. This is also a great way of verifying/testing the API calls directly within Fabric:

# Install sempy version 0.4.0 or higher
!pip install semantic-link --q 

import sempy.fabric as fabric

# Init the sempy client
client = fabric.FabricRestClient()

# Fabric REST API call “Job Scheduler – Run On Demand Item Job”
#    Docs: Job Scheduler - Run On Demand Item Job - REST API (Core) | https://learn.microsoft.com/en-us/rest/api/fabric/core/job-scheduler/run-on-demand-item-job
#    HTTP: POST https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/items/{itemId}/jobs/instances?jobType={jobType}
#    Body/Payload: {"executionData": { ... } }

# Get the default workspace id of the notebook
workspaceId = fabric.get_workspace_id()
itemId = f"yourPipelineUuid"
jobType = f"Pipeline"
payload = {
            "executionData": {
                "parameters": {
                    "YourParamter1": 1,
                    "YourParamter2": "Param2"
                    }
                }
            }

# Call Fabric REST API with semantic link Fabric REST client (sempy)
# Run without payload / no or default pipeline parameters

response = client.post(f"/v1/workspaces/{workspaceId}/items/{itemId}/jobs/instances?jobType={jobType}")

# Run with payload / pipeline parameters
response = client.post(f"/v1/workspaces/{workspaceId}/items/{itemId}/jobs/instances?jobType={jobType}",json= payload)

Unfortunately fabric Data pipeline APIs have yet not been exposed owining to which it is currently not possible to trigger the fabric data pipeline any way other than manual process or scheduled trigger

Hello,

I am getting an error either running a notebook or a pipeline from synapse,