DatasourceFlowsUpdateDataflowConfigTriggerProperties

pydantic model openapi_client.models.datasource_flows_update_dataflow_config_trigger_properties.DatasourceFlowsUpdateDataflowConfigTriggerProperties

Schedule settings for a SaaS scheduled flow. Required fields when TriggerType is scheduled are scheduleExpression, dataPullMode, scheduleStartTime, and scheduleEndTime. Removed when TriggerType is changed to ondemand.

Fields:
field schedule_expression: Optional[StrictStr] = None (alias 'scheduleExpression')

Cron or rate expression for the scheduled SaaS flow.

field data_pull_mode: Optional[StrictStr] = None (alias 'dataPullMode')

Complete or Incremental. Complete is only allowed for daily or longer schedules.

field schedule_start_time: Optional[StrictStr] = None (alias 'scheduleStartTime')

Schedule start time in YYYY-MM-DDTHH:MM:SS format.

field schedule_end_time: Optional[StrictStr] = None (alias 'scheduleEndTime')

Schedule end time in YYYY-MM-DDTHH:MM:SS format.

field schedule_offset: Optional[StrictStr] = None (alias 'scheduleOffset')

Optional schedule offset as HH:MM:SS. Allowed range is 00:00:00 to 10:00:00.

to_str()

Returns the string representation of the model using alias

Return type:

str

to_json()

Returns the JSON representation of the model using alias

Return type:

str

classmethod from_json(json_str)

Create an instance of DatasourceFlowsUpdateDataflowConfigTriggerProperties from a JSON string

Return type:

Optional[Self]

to_dict()

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic’s self.model_dump(by_alias=True):

  • None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

Return type:

Dict[str, Any]

classmethod from_dict(obj)

Create an instance of DatasourceFlowsUpdateDataflowConfigTriggerProperties from a dict

Return type:

Optional[Self]