class_docstr: Information to schedule a DagRun.
  
  Instances of this will be returned by timetables when they are asked to
  schedule a DagRun creation.
class_docstr_tok: ["Information","to","schedule","a","DagRun",".","Instances","of","this","will","be","returned","by","timetables","when","they","are","asked","to","schedule","a","DagRun","creation","."]
docstr: Represent a run on a continuous schedule.
  
  In such a schedule, each data interval starts right after the previous
  one ends, and each run is scheduled right after the interval ends. This
  applies to all schedules prior to AIP-39 except ``@once`` and ``None``.
docstr_tok: ["Represent","a","run","on","a","continuous","schedule",".","In","such","a","schedule",",","each","data","interval","starts","right","after","the","previous","one","ends",",","and","each","run","is","scheduled","right","after","the","interval","ends",".","This","applies","to","all","schedules","prior","to","AIP-39","except","``","@","once","``","and","``","None","``","."]
code: def interval(cls, start: DateTime, end: DateTime) -> DagRunInfo:
      """Represent a run on a continuous schedule.
  
      In such a schedule, each data interval starts right after the previous
      one ends, and each run is scheduled right after the interval ends. This
      applies to all schedules prior to AIP-39 except ``@once`` and ``None``.
      """
      return cls(run_after=end, data_interval=DataInterval(start, end))
  
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, Any, NamedTuple, Sequence
  from warnings import warn
  from airflow.typing_compat import Protocol, runtime_checkable
label_desc: Use image node_id 2 for calling the DagRunInfo obj's underlying member method code with example usage: obj.interval(cls, start, end) and returns: cls