airflow_pydantic.Task

pydantic model airflow_pydantic.Task

Bases: TaskArgs, TaskRenderMixin, TaskInstantiateMixin

Show JSON schema

{
   "title": "Task",
   "type": "object",
   "properties": {
      "owner": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "the owner of the task. Using a meaningful description (e.g. user/person/team/role name) to clarify ownership is recommended.",
         "title": "Owner"
      },
      "email": {
         "anyOf": [
            {
               "items": {
                  "type": "string"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "the 'to' email address(es) used in email alerts",
         "title": "Email"
      },
      "email_on_failure": {
         "anyOf": [
            {
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Indicates whether email alerts should be sent when a task failed",
         "title": "Email On Failure"
      },
      "email_on_retry": {
         "anyOf": [
            {
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Indicates whether email alerts should be sent when a task is retried",
         "title": "Email On Retry"
      },
      "retries": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "the number of retries that should be performed before failing the task",
         "title": "Retries"
      },
      "retry_delay": {
         "anyOf": [
            {
               "format": "duration",
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "delay between retries",
         "title": "Retry Delay"
      },
      "retry_exponential_backoff": {
         "anyOf": [
            {
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "allow progressively longer waits between retries by using exponential backoff algorithm on retry delay (delay will be converted into seconds)",
         "title": "Retry Exponential Backoff"
      },
      "max_retry_delay": {
         "anyOf": [
            {
               "format": "duration",
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "maximum delay interval between retries",
         "title": "Max Retry Delay"
      },
      "start_date": {
         "anyOf": [
            {
               "format": "date-time",
               "type": "string"
            },
            {
               "maxItems": 2,
               "minItems": 2,
               "prefixItems": [
                  {
                     "format": "date-time",
                     "type": "string"
                  },
                  {
                     "type": "string"
                  }
               ],
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "The start_date for the task, determines the execution_date for the first task instance. The best practice is to have the start_date rounded to your DAG\u2019s schedule_interval. Daily jobs have their start_date some day at 00:00:00, hourly jobs have their start_date at 00:00 of a specific hour. Note that Airflow simply looks at the latest execution_date and adds the schedule_interval to determine the next execution_date. It is also very important to note that different tasks\u2019 dependencies need to line up in time. If task A depends on task B and their start_date are offset in a way that their execution_date don\u2019t line up, A\u2019s dependencies will never be met. If you are looking to delay a task, for example running a daily task at 2AM, look into the TimeSensor and TimeDeltaSensor. We advise against using dynamic start_date and recommend using fixed ones. Read the FAQ entry about start_date for more information.",
         "title": "Start Date"
      },
      "end_date": {
         "anyOf": [
            {
               "format": "date-time",
               "type": "string"
            },
            {
               "maxItems": 2,
               "minItems": 2,
               "prefixItems": [
                  {
                     "format": "date-time",
                     "type": "string"
                  },
                  {
                     "type": "string"
                  }
               ],
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "if specified, the scheduler won\u2019t go beyond this date",
         "title": "End Date"
      },
      "depends_on_past": {
         "anyOf": [
            {
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "when set to true, task instances will run sequentially and only if the previous instance has succeeded or has been skipped. The task instance for the start_date is allowed to run.",
         "title": "Depends On Past"
      },
      "queue": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "which queue to target when running this job. Not all executors implement queue management, the CeleryExecutor does support targeting specific queues.",
         "title": "Queue"
      },
      "pool": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "the slot pool this task should run in, slot pools are a way to limit concurrency for certain tasks",
         "title": "Pool"
      },
      "pool_slots": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "the number of pool slots this task should use (>= 1) Values less than 1 are not allowed",
         "title": "Pool Slots"
      },
      "execution_timeout": {
         "anyOf": [
            {
               "format": "duration",
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "max time allowed for the execution of this task instance, if it goes beyond it will raise and fail.",
         "title": "Execution Timeout"
      },
      "trigger_rule": {
         "anyOf": [
            {
               "$ref": "#/$defs/TriggerRule"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "defines the rule by which dependencies are applied for the task to get triggered."
      },
      "max_active_tis_per_dag": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "When set, a task will be able to limit the concurrent runs across execution_dates.",
         "title": "Max Active Tis Per Dag"
      },
      "max_active_tis_per_dagrun": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "When set, a task will be able to limit the concurrent task instances per DAG run.",
         "title": "Max Active Tis Per Dagrun"
      },
      "do_xcom_push": {
         "anyOf": [
            {
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "if True, an XCom is pushed containing the Operator\u2019s result",
         "title": "Do Xcom Push"
      },
      "multiple_outputs": {
         "anyOf": [
            {
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "if True and do_xcom_push is True, pushes multiple XComs, one for each key in the returned dictionary result. If False and do_xcom_push is True, pushes a single XCom.",
         "title": "Multiple Outputs"
      },
      "doc": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Add documentation or notes to your Task objects that is visible in Task Instance details View in the Webserver. This is a generic field that can be used for any format, but it is recommended to use specific fields for structured formats like Markdown, RST, JSON, or YAML.",
         "title": "Doc"
      },
      "doc_md": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Add documentation in Markdown format or notes to your Task objects that is visible in Task Instance details View in the Webserver.",
         "title": "Doc Md"
      },
      "doc_rst": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Add documentation in RST format or notes to your Task objects that is visible in Task Instance details View in the Webserver.",
         "title": "Doc Rst"
      },
      "doc_json": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Add documentation in JSON format or notes to your Task objects that is visible in Task Instance details View in the Webserver.",
         "title": "Doc Json"
      },
      "doc_yaml": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Add documentation in YAML format or notes to your Task objects that is visible in Task Instance details View in the Webserver.",
         "title": "Doc Yaml"
      },
      "task_display_name": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "The display name of the task which appears on the UI.",
         "title": "Task Display Name"
      },
      "task_id": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "a unique, meaningful id for the task",
         "title": "Task Id"
      },
      "operator": {
         "default": null,
         "title": "Operator"
      },
      "dependencies": {
         "default": null,
         "title": "Dependencies"
      }
   },
   "$defs": {
      "TriggerRule": {
         "description": "Class with task's trigger rules.",
         "enum": [
            "all_success",
            "all_failed",
            "all_done",
            "all_done_setup_success",
            "one_success",
            "one_failed",
            "one_done",
            "none_failed",
            "none_skipped",
            "always",
            "none_failed_min_one_success",
            "all_skipped"
         ],
         "title": "TriggerRule",
         "type": "string"
      }
   }
}

Fields:

• dependencies (List[str | airflow_pydantic.task.Task] | List[str | Tuple[str, str] | Tuple[airflow_pydantic.task.Task, str]] | None)

• operator (type)

• task_id (str | None)

field task_id: str | None = None

a unique, meaningful id for the task

field operator: Annotated[type, BeforeValidator(func=get_import_path, json_schema_input_type=PydanticUndefined), PlainSerializer(func=serialize_path_as_string, return_type=str, when_used=json)] [Required]

airflow operator path

field dependencies: List[str | Task] | List[str | Tuple[str, str] | Tuple[Task, str]] | None = None

dependencies

set_upstream(other: Task | List[Task])

set_downstream(other: Task | List[Task])