DatasourceFlowsDetailsDataflowConfigTriggerProperties

pydantic model openapi_client.models.datasource_flows_details_dataflow_config_trigger_properties.DatasourceFlowsDetailsDataflowConfigTriggerProperties

Schedule settings for a SaaS scheduled flow trigger.

Fields:

• data_pull_mode (str | None)

• schedule_end_time (str | None)

• schedule_expression (str | None)

• schedule_offset (int | None)

• schedule_start_time (str | None)

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[StrictInt] = None (alias 'scheduleOffset')

Schedule offset in seconds for a SaaS scheduled flow. Returned after the API converts the request HH:MM:SS value. Allowed range is 0 to 36000.

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 DatasourceFlowsDetailsDataflowConfigTriggerProperties 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 DatasourceFlowsDetailsDataflowConfigTriggerProperties from a dict

Return type:

Optional[Self]