azure-sdk-for-python: Bad body serialization creating a Schedule Trigger in Data Factory

• Package Name: azure-mgmt-datafactory
• Package Version: 1.1.0
• Operating System: Windows
• Python Version: 3.8

Describe the bug Using the library to create a Data Factory trigger, calling DataFactoryManagementClient.triggers.create_or_update method is not serializing the request body correctly

Serialized example:

{
    "type": "ScheduleTrigger",
    "description": "My scheduler trigger",
    "pipelines": [
        {
            "pipelineReference": {
                "type": "PipelineReference",
                "referenceName": "PL_ADW_IMPORT_MASTER"
            },
            "parameters": {
                "datacenter_name": "datacenter1",
                "schedule_name": "schedule1"
            }
        }
    ],
    "typeProperties": {
        "recurrence": {
            "frequency": "Minute",
            "interval": 15,
            "startTime": "2022-12-12T04:00:00.000Z",
            "endTime": "2022-12-12T05:00:00.000Z",
            "timeZone": "UTC"
        }
    }
}

The correct serealized body is:

{
    "properties": {
        "type": "ScheduleTrigger",
        "description": "My scheduler trigger",
        "pipelines": [
            {
                "pipelineReference": {
                    "type": "PipelineReference",
                    "referenceName": "PL_ADW_IMPORT_MASTER"
                },
                "parameters": {
                    "datacenter_name": "datacenter1",
                    "schedule_name": "schedule1"
                }
            }
        ],
        "typeProperties": {
            "recurrence": {
                "frequency": "Minute",
                "interval": 15,
                "startTime": "2022-12-12T04:00:00.000Z",
                "endTime": "2022-12-12T05:00:00.000Z",
                "timeZone": "UTC"
            }
        }
    }
}

To Reproduce Steps to reproduce the behavior:

from azure.identity import DefaultAzureCredential 
from azure.mgmt.resource import ResourceManagementClient
from azure.mgmt.datafactory import DataFactoryManagementClient
from azure.mgmt.datafactory.models import *



def main():
    credential = DefaultAzureCredential()
    adf_client = DataFactoryManagementClient(credential, 'AAAAA-VVVV-SWESDDS-XCV3-3bb145207'
   
    # Create a trigger
    rg_name = 'EUNPADWCANRSG01'
    df_name = 'EUNPADWCANDFA01'
    tr_name = 'mytrigger'
    scheduler_recurrence = ScheduleTriggerRecurrence(frequency='Minute', interval='15',start_time='2022-12-12T04:00:00Z', end_time='2022-12-12T05:00:00Z', time_zone='UTC')
    pipeline_parameters = {'datacenter_name':'datacenter1', 'schedule_name':'schedule1'}
    pipelines_to_run = []
    pipeline_reference = PipelineReference(reference_name='PL_ADW_IMPORT_MASTER')
    pipelines_to_run.append(TriggerPipelineReference(pipeline_reference=pipeline_reference, parameters=pipeline_parameters))
    tr_properties = ScheduleTrigger(description='My scheduler trigger', pipelines = pipelines_to_run, recurrence=scheduler_recurrence)    
    adf_client.triggers.create_or_update(rg_name, df_name, tr_name, tr_properties)

    # Start the trigger
    adf_client.triggers.start(rg_name, df_name, tr_name)

if __name__ == "__main__":
    main()

Expected behavior Running this code,

\azure\mgmt\datafactory\operations_triggers_operations.py trigger an Exception because the response status code is 400

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