client.dag
==========

.. py:module:: client.dag

.. autoapi-nested-parse::

   The DAG captures the interconnected graph of tasks and their dependencies.



Attributes
----------

.. autoapisummary::

   client.dag.logger


Classes
-------

.. autoapisummary::

   client.dag.Dag


Module Contents
---------------

.. py:data:: logger

.. py:class:: Dag(requester: Optional[jobmon.core.requester.Requester] = None)

   Bases: :py:obj:`object`


   The DAG captures the interconnected graph of tasks and their dependencies.

   Directed Acyclic Graph.

   The DAG captures the tasks (nodes) as they are
   related to each other in their dependency structure. The Dag is traversed in
   the order of node dependencies so a workflow run is a single instance of
   traversing through a dag. This object stores the nodes and communicates
   with the server with regard to itself.

   :param requester: url to communicate with the flask services.
   :type requester: str


   .. py:attribute:: nodes
      :type:  Set[jobmon.client.node.Node]


   .. py:attribute:: requester
      :value: None



   .. py:property:: dag_id
      :type: int


      Database unique ID of this DAG.


   .. py:method:: add_node(node: jobmon.client.node.Node) -> None

      Add a node to this dag.

      :param node: Node to add to the dag
      :type node: jobmon.client.node.Node



   .. py:method:: bind(chunk_size: int = 500) -> int

      Retrieve an id for a matching dag from the server.

      If it doesn't exist, first create one, including its edges.



   .. py:method:: validate() -> None

      Validate the nodes and their dependencies.