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  # to you under the Apache License, Version 2.0 (the
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  # under the License.
  
  """Serialized DAG table in database."""
  
  import hashlib
  import logging
  from datetime import datetime, timedelta
  from typing import Any, Dict, List, Optional
  
  import sqlalchemy_jsonfield
  from sqlalchemy import BigInteger, Column, Index, String, and_
  from sqlalchemy.orm import Session, backref, relationship
  from sqlalchemy.sql import exists
  
  from airflow.models.base import ID_LEN, Base
  from airflow.models.dag import DAG, DagModel
  from airflow.models.dagcode import DagCode
  from airflow.models.dagrun import DagRun
  from airflow.serialization.serialized_objects import SerializedDAG
  from airflow.settings import MIN_SERIALIZED_DAG_UPDATE_INTERVAL, json
  from airflow.utils import timezone
  from airflow.utils.session import provide_session
  from airflow.utils.sqlalchemy import UtcDateTime
  
  log = logging.getLogger(__name__)
  
  
  class SerializedDagModel(Base):
      """A table for serialized DAGs.
  
      serialized_dag table is a snapshot of DAG files synchronized by scheduler.
      This feature is controlled by:
  
      * ``[core] min_serialized_dag_update_interval = 30`` (s):
        serialized DAGs are updated in DB when a file gets processed by scheduler,
        to reduce DB write rate, there is a minimal interval of updating serialized DAGs.
      * ``[scheduler] dag_dir_list_interval = 300`` (s):
        interval of deleting serialized DAGs in DB when the files are deleted, suggest
        to use a smaller interval such as 60
  
      It is used by webserver to load dags
      because reading from database is lightweight compared to importing from files,
      it solves the webserver scalability issue.
      """
  
      __tablename__ = 'serialized_dag'
  
      dag_id = Column(String(ID_LEN), primary_key=True)
      fileloc = Column(String(2000), nullable=False)
      # The max length of fileloc exceeds the limit of indexing.
      fileloc_hash = Column(BigInteger, nullable=False)
      data = Column(sqlalchemy_jsonfield.JSONField(json=json), nullable=False)
      last_updated = Column(UtcDateTime, nullable=False)
      dag_hash = Column(String(32), nullable=False)
  
      __table_args__ = (
          Index('idx_fileloc_hash', fileloc_hash, unique=False),
      )
  
      dag_runs = relationship(
          DagRun,
          primaryjoin=dag_id == DagRun.dag_id,
          foreign_keys=dag_id,
          backref=backref('serialized_dag', uselist=False, innerjoin=True),
      )
  
      dag_model = relationship(
          DagModel,
          primaryjoin=dag_id == DagModel.dag_id,  # type: ignore
          foreign_keys=dag_id,
          uselist=False,
          innerjoin=True,
          backref=backref('serialized_dag', uselist=False, innerjoin=True),
      )
  
      def __init__(self, dag: DAG):
          self.dag_id = dag.dag_id
          self.fileloc = dag.full_filepath
          self.fileloc_hash = DagCode.dag_fileloc_hash(self.fileloc)
          self.data = SerializedDAG.to_dict(dag)
          self.last_updated = timezone.utcnow()
          self.dag_hash = hashlib.md5(json.dumps(self.data, sort_keys=True).encode("utf-8")).hexdigest()
  
      def __repr__(self):
          return f"<SerializedDag: {self.dag_id}>"
  
      @classmethod
      @provide_session
      def write_dag(cls, dag: DAG, min_update_interval: Optional[int] = None, session: Session = None):
          """Serializes a DAG and writes it into database.
          If the record already exists, it checks if the Serialized DAG changed or not. If it is
          changed, it updates the record, ignores otherwise.
  
          :param dag: a DAG to be written into database
          :param min_update_interval: minimal interval in seconds to update serialized DAG
          :param session: ORM Session
          """
          # Checks if (Current Time - Time when the DAG was written to DB) < min_update_interval
          # If Yes, does nothing
          # If No or the DAG does not exists, updates / writes Serialized DAG to DB
          if min_update_interval is not None:
              if session.query(exists().where(
                  and_(cls.dag_id == dag.dag_id,
                       (timezone.utcnow() - timedelta(seconds=min_update_interval)) < cls.last_updated))
              ).scalar():
                  return
  
          log.debug("Checking if DAG (%s) changed", dag.dag_id)
          new_serialized_dag = cls(dag)
          serialized_dag_hash_from_db = session.query(
              cls.dag_hash).filter(cls.dag_id == dag.dag_id).scalar()
  
          if serialized_dag_hash_from_db == new_serialized_dag.dag_hash:
              log.debug("Serialized DAG (%s) is unchanged. Skipping writing to DB", dag.dag_id)
              return
  
          log.debug("Writing Serialized DAG: %s to the DB", dag.dag_id)
          session.merge(new_serialized_dag)
          log.debug("DAG: %s written to the DB", dag.dag_id)
  
      @classmethod
      @provide_session
      def read_all_dags(cls, session: Session = None) -> Dict[str, 'SerializedDAG']:
          """Reads all DAGs in serialized_dag table.
  
          :param session: ORM Session
          :returns: a dict of DAGs read from database
          """
          serialized_dags = session.query(cls)
  
          dags = {}
          for row in serialized_dags:
              log.debug("Deserializing DAG: %s", row.dag_id)
              dag = row.dag
  
              # Sanity check.
              if dag.dag_id == row.dag_id:
                  dags[row.dag_id] = dag
              else:
                  log.warning(
                      "dag_id Mismatch in DB: Row with dag_id '%s' has Serialised DAG "
                      "with '%s' dag_id", row.dag_id, dag.dag_id)
          return dags
  
      @property
      def dag(self):
          """The DAG deserialized from the ``data`` column"""
          if isinstance(self.data, dict):
              dag = SerializedDAG.from_dict(self.data)  # type: Any
          else:
              dag = SerializedDAG.from_json(self.data)  # noqa
          return dag
  
      @classmethod
      @provide_session
      def remove_dag(cls, dag_id: str, session: Session = None):
          """Deletes a DAG with given dag_id.
  
          :param dag_id: dag_id to be deleted
          :param session: ORM Session
          """
          # pylint: disable=no-member
          session.execute(cls.__table__.delete().where(cls.dag_id == dag_id))
  
      @classmethod
      @provide_session
      def remove_deleted_dags(cls, alive_dag_filelocs: List[str], session=None):
          """Deletes DAGs not included in alive_dag_filelocs.
  
          :param alive_dag_filelocs: file paths of alive DAGs
          :param session: ORM Session
          """
          alive_fileloc_hashes = [
              DagCode.dag_fileloc_hash(fileloc) for fileloc in alive_dag_filelocs]
  
          log.debug("Deleting Serialized DAGs (for which DAG files are deleted) "
                    "from %s table ", cls.__tablename__)
  
          # pylint: disable=no-member
          session.execute(cls.__table__.delete().where(
              and_(cls.fileloc_hash.notin_(alive_fileloc_hashes),
                   cls.fileloc.notin_(alive_dag_filelocs))))
  
      @classmethod
      @provide_session
      def has_dag(cls, dag_id: str, session: Session = None) -> bool:
          """Checks a DAG exist in serialized_dag table.
  
          :param dag_id: the DAG to check
          :param session: ORM Session
          """
          return session.query(exists().where(cls.dag_id == dag_id)).scalar()
  
      @classmethod
      @provide_session
      def get(cls, dag_id: str, session: Session = None) -> Optional['SerializedDagModel']:
          """
          Get the SerializedDAG for the given dag ID.
          It will cope with being passed the ID of a subdag by looking up the
          root dag_id from the DAG table.
  
          :param dag_id: the DAG to fetch
          :param session: ORM Session
          """
          row = session.query(cls).filter(cls.dag_id == dag_id).one_or_none()
          if row:
              return row
  
          # If we didn't find a matching DAG id then ask the DAG table to find
          # out the root dag
          root_dag_id = session.query(
              DagModel.root_dag_id).filter(DagModel.dag_id == dag_id).scalar()
  
          return session.query(cls).filter(cls.dag_id == root_dag_id).one_or_none()
  
      @staticmethod
      @provide_session
      def bulk_sync_to_db(dags: List[DAG], session: Session = None):
          """
          Saves DAGs as Serialized DAG objects in the database. Each
          DAG is saved in a separate database query.
  
          :param dags: the DAG objects to save to the DB
          :type dags: List[airflow.models.dag.DAG]
          :param session: ORM Session
          :type session: Session
          :return: None
          """
          for dag in dags:
              if not dag.is_subdag:
                  SerializedDagModel.write_dag(
                      dag,
                      min_update_interval=MIN_SERIALIZED_DAG_UPDATE_INTERVAL,
                      session=session
                  )
  
      @classmethod
      @provide_session
      def get_last_updated_datetime(cls, dag_id: str, session: Session = None) -> datetime:
          """
          Get the date when the Serialized DAG associated to DAG was last updated
          in serialized_dag table
  
          :param dag_id: DAG ID
          :type dag_id: str
          :param session: ORM Session
          :type session: Session
          """
          return session.query(cls.last_updated).filter(cls.dag_id == dag_id).scalar()
  
      @classmethod
      @provide_session
      def get_latest_version_hash(cls, dag_id: str, session: Session = None) -> str:
          """
          Get the latest DAG version for a given DAG ID.
  
          :param dag_id: DAG ID
          :type dag_id: str
          :param session: ORM Session
          :type session: Session
          :return: DAG Hash
          :rtype: str
          """
          return session.query(cls.dag_hash).filter(cls.dag_id == dag_id).scalar()
  