text: # -*- coding: utf-8 -*-
  #
  # Licensed to the Apache Software Foundation (ASF) under one
  # or more contributor license agreements.  See the NOTICE file
  # distributed with this work for additional information
  # regarding copyright ownership.  The ASF licenses this file
  # to you under the Apache License, Version 2.0 (the
  # "License"); you may not use this file except in compliance
  # with the License.  You may obtain a copy of the License at
  #
  #   http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing,
  # software distributed under the License is distributed on an
  # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  # KIND, either express or implied.  See the License for the
  # specific language governing permissions and limitations
  # under the License.
  
  import hashlib
  import imp
  import importlib
  import os
  import sys
  import textwrap
  import zipfile
  from collections import namedtuple
  from datetime import datetime, timedelta
  
  from croniter import croniter, CroniterBadCronError, CroniterBadDateError, CroniterNotAlphaError
  from sqlalchemy import or_
  
  from airflow import configuration, settings
  from airflow.dag.base_dag import BaseDagBag
  from airflow.exceptions import AirflowDagCycleException
  from airflow.executors import get_default_executor
  from airflow.stats import Stats
  from airflow.utils import timezone
  from airflow.utils.dag_processing import list_py_file_paths, correct_maybe_zipped
  from airflow.utils.db import provide_session
  from airflow.utils.helpers import pprinttable
  from airflow.utils.log.logging_mixin import LoggingMixin
  from airflow.utils.state import State
  from airflow.utils.timeout import timeout
  
  
  class DagBag(BaseDagBag, LoggingMixin):
      """
      A dagbag is a collection of dags, parsed out of a folder tree and has high
      level configuration settings, like what database to use as a backend and
      what executor to use to fire off tasks. This makes it easier to run
      distinct environments for say production and development, tests, or for
      different teams or security profiles. What would have been system level
      settings are now dagbag level so that one system can run multiple,
      independent settings sets.
  
      :param dag_folder: the folder to scan to find DAGs
      :type dag_folder: unicode
      :param executor: the executor to use when executing task instances
          in this DagBag
      :param include_examples: whether to include the examples that ship
          with airflow or not
      :type include_examples: bool
      :param has_logged: an instance boolean that gets flipped from False to True after a
          file has been skipped. This is to prevent overloading the user with logging
          messages about skipped files. Therefore only once per DagBag is a file logged
          being skipped.
      """
  
      # static class variables to detetct dag cycle
      CYCLE_NEW = 0
      CYCLE_IN_PROGRESS = 1
      CYCLE_DONE = 2
  
      def __init__(
              self,
              dag_folder=None,
              executor=None,
              include_examples=configuration.conf.getboolean('core', 'LOAD_EXAMPLES'),
              safe_mode=configuration.conf.getboolean('core', 'DAG_DISCOVERY_SAFE_MODE')):
  
          # do not use default arg in signature, to fix import cycle on plugin load
          if executor is None:
              executor = get_default_executor()
          dag_folder = dag_folder or settings.DAGS_FOLDER
          self.log.info("Filling up the DagBag from %s", dag_folder)
          self.dag_folder = dag_folder
          self.dags = {}
          # the file's last modified timestamp when we last read it
          self.file_last_changed = {}
          self.executor = executor
          self.import_errors = {}
          self.has_logged = False
  
          self.collect_dags(
              dag_folder=dag_folder,
              include_examples=include_examples,
              safe_mode=safe_mode)
  
      def size(self):
          """
          :return: the amount of dags contained in this dagbag
          """
          return len(self.dags)
  
      @property
      def dag_ids(self):
          return self.dags.keys()
  
      def get_dag(self, dag_id):
          """
          Gets the DAG out of the dictionary, and refreshes it if expired
          """
          from airflow.models.dag import DagModel  # Avoid circular import
  
          # If asking for a known subdag, we want to refresh the parent
          root_dag_id = dag_id
          if dag_id in self.dags:
              dag = self.dags[dag_id]
              if dag.is_subdag:
                  root_dag_id = dag.parent_dag.dag_id
  
          # If the dag corresponding to root_dag_id is absent or expired
          orm_dag = DagModel.get_current(root_dag_id)
          if orm_dag and (
                  root_dag_id not in self.dags or
                  (
                      orm_dag.last_expired and
                      dag.last_loaded < orm_dag.last_expired
                  )
          ):
              # Reprocess source file
              found_dags = self.process_file(
                  filepath=correct_maybe_zipped(orm_dag.fileloc), only_if_updated=False)
  
              # If the source file no longer exports `dag_id`, delete it from self.dags
              if found_dags and dag_id in [found_dag.dag_id for found_dag in found_dags]:
                  return self.dags[dag_id]
              elif dag_id in self.dags:
                  del self.dags[dag_id]
          return self.dags.get(dag_id)
  
      def process_file(self, filepath, only_if_updated=True, safe_mode=True):
          """
          Given a path to a python module or zip file, this method imports
          the module and look for dag objects within it.
          """
          from airflow.models.dag import DAG  # Avoid circular import
  
          found_dags = []
  
          # if the source file no longer exists in the DB or in the filesystem,
          # return an empty list
          # todo: raise exception?
          if filepath is None or not os.path.isfile(filepath):
              return found_dags
  
          try:
              # This failed before in what may have been a git sync
              # race condition
              file_last_changed_on_disk = datetime.fromtimestamp(os.path.getmtime(filepath))
              if only_if_updated \
                      and filepath in self.file_last_changed \
                      and file_last_changed_on_disk == self.file_last_changed[filepath]:
                  return found_dags
  
          except Exception as e:
              self.log.exception(e)
              return found_dags
  
          mods = []
          is_zipfile = zipfile.is_zipfile(filepath)
          if not is_zipfile:
              if safe_mode:
                  with open(filepath, 'rb') as file:
                      content = file.read()
                      if not all([s in content for s in (b'DAG', b'airflow')]):
                          self.file_last_changed[filepath] = file_last_changed_on_disk
                          # Don't want to spam user with skip messages
                          if not self.has_logged:
                              self.has_logged = True
                              self.log.info(
                                  "File %s assumed to contain no DAGs. Skipping.",
                                  filepath)
                          return found_dags
  
              self.log.debug("Importing %s", filepath)
              org_mod_name, _ = os.path.splitext(os.path.split(filepath)[-1])
              mod_name = ('unusual_prefix_' +
                          hashlib.sha1(filepath.encode('utf-8')).hexdigest() +
                          '_' + org_mod_name)
  
              if mod_name in sys.modules:
                  del sys.modules[mod_name]
  
              with timeout(configuration.conf.getint('core', "DAGBAG_IMPORT_TIMEOUT")):
                  try:
                      m = imp.load_source(mod_name, filepath)
                      mods.append(m)
                  except Exception as e:
                      self.log.exception("Failed to import: %s", filepath)
                      self.import_errors[filepath] = str(e)
                      self.file_last_changed[filepath] = file_last_changed_on_disk
  
          else:
              zip_file = zipfile.ZipFile(filepath)
              for mod in zip_file.infolist():
                  head, _ = os.path.split(mod.filename)
                  mod_name, ext = os.path.splitext(mod.filename)
                  if not head and (ext == '.py' or ext == '.pyc'):
                      if mod_name == '__init__':
                          self.log.warning("Found __init__.%s at root of %s", ext, filepath)
                      if safe_mode:
                          with zip_file.open(mod.filename) as zf:
                              self.log.debug("Reading %s from %s", mod.filename, filepath)
                              content = zf.read()
                              if not all([s in content for s in (b'DAG', b'airflow')]):
                                  self.file_last_changed[filepath] = (
                                      file_last_changed_on_disk)
                                  # todo: create ignore list
                                  # Don't want to spam user with skip messages
                                  if not self.has_logged:
                                      self.has_logged = True
                                      self.log.info(
                                          "File %s assumed to contain no DAGs. Skipping.",
                                          filepath)
  
                      if mod_name in sys.modules:
                          del sys.modules[mod_name]
  
                      try:
                          sys.path.insert(0, filepath)
                          m = importlib.import_module(mod_name)
                          mods.append(m)
                      except Exception as e:
                          self.log.exception("Failed to import: %s", filepath)
                          self.import_errors[filepath] = str(e)
                          self.file_last_changed[filepath] = file_last_changed_on_disk
  
          for m in mods:
              for dag in list(m.__dict__.values()):
                  if isinstance(dag, DAG):
                      if not dag.full_filepath:
                          dag.full_filepath = filepath
                          if dag.fileloc != filepath and not is_zipfile:
                              dag.fileloc = filepath
                      try:
                          dag.is_subdag = False
                          self.bag_dag(dag, parent_dag=dag, root_dag=dag)
                          if isinstance(dag._schedule_interval, str):
                              croniter(dag._schedule_interval)
                          found_dags.append(dag)
                          found_dags += dag.subdags
                      except (CroniterBadCronError,
                              CroniterBadDateError,
                              CroniterNotAlphaError) as cron_e:
                          self.log.exception("Failed to bag_dag: %s", dag.full_filepath)
                          self.import_errors[dag.full_filepath] = \
                              "Invalid Cron expression: " + str(cron_e)
                          self.file_last_changed[dag.full_filepath] = \
                              file_last_changed_on_disk
                      except AirflowDagCycleException as cycle_exception:
                          self.log.exception("Failed to bag_dag: %s", dag.full_filepath)
                          self.import_errors[dag.full_filepath] = str(cycle_exception)
                          self.file_last_changed[dag.full_filepath] = \
                              file_last_changed_on_disk
  
          self.file_last_changed[filepath] = file_last_changed_on_disk
          return found_dags
  
      @provide_session
      def kill_zombies(self, session=None):
          """
          Fail zombie tasks, which are tasks that haven't
          had a heartbeat for too long, in the current DagBag.
  
          :param session: DB session.
          :type session: sqlalchemy.orm.session.Session
          """
          # Avoid circular import
          from airflow.models.taskinstance import TaskInstance as TI
          from airflow.jobs import LocalTaskJob as LJ
  
          # How many seconds do we wait for tasks to heartbeat before mark them as zombies.
          zombie_threshold_secs = (
              configuration.getint('scheduler', 'scheduler_zombie_task_threshold'))
          limit_dttm = timezone.utcnow() - timedelta(
              seconds=zombie_threshold_secs)
          self.log.debug("Failing jobs without heartbeat after %s", limit_dttm)
  
          tis = (
              session.query(TI)
              .join(LJ, TI.job_id == LJ.id)
              .filter(TI.state == State.RUNNING)
              .filter(TI.dag_id.in_(self.dags))
              .filter(
                  or_(
                      LJ.state != State.RUNNING,
                      LJ.latest_heartbeat < limit_dttm,
                  )
              ).all()
          )
          for ti in tis:
              self.log.info("Detected zombie job with dag_id %s, task_id %s, and execution date %s",
                            ti.dag_id, ti.task_id, ti.execution_date.isoformat())
              ti.test_mode = configuration.getboolean('core', 'unit_test_mode')
              ti.task = self.dags[ti.dag_id].get_task(ti.task_id)
              ti.handle_failure("{} detected as zombie".format(ti),
                                ti.test_mode, ti.get_template_context())
              self.log.info('Marked zombie job %s as %s', ti, ti.state)
              Stats.incr('zombies_killed')
          session.commit()
  
      def bag_dag(self, dag, parent_dag, root_dag):
          """
          Adds the DAG into the bag, recurses into sub dags.
          Throws AirflowDagCycleException if a cycle is detected in this dag or its subdags
          """
  
          dag.test_cycle()  # throws if a task cycle is found
  
          dag.resolve_template_files()
          dag.last_loaded = timezone.utcnow()
  
          for task in dag.tasks:
              settings.policy(task)
  
          subdags = dag.subdags
  
          try:
              for subdag in subdags:
                  subdag.full_filepath = dag.full_filepath
                  subdag.parent_dag = dag
                  subdag.is_subdag = True
                  self.bag_dag(subdag, parent_dag=dag, root_dag=root_dag)
  
              self.dags[dag.dag_id] = dag
              self.log.debug('Loaded DAG %s', dag)
          except AirflowDagCycleException as cycle_exception:
              # There was an error in bagging the dag. Remove it from the list of dags
              self.log.exception('Exception bagging dag: %s', dag.dag_id)
              # Only necessary at the root level since DAG.subdags automatically
              # performs DFS to search through all subdags
              if dag == root_dag:
                  for subdag in subdags:
                      if subdag.dag_id in self.dags:
                          del self.dags[subdag.dag_id]
              raise cycle_exception
  
      def collect_dags(
              self,
              dag_folder=None,
              only_if_updated=True,
              include_examples=configuration.conf.getboolean('core', 'LOAD_EXAMPLES'),
              safe_mode=configuration.conf.getboolean('core', 'DAG_DISCOVERY_SAFE_MODE')):
          """
          Given a file path or a folder, this method looks for python modules,
          imports them and adds them to the dagbag collection.
  
          Note that if a ``.airflowignore`` file is found while processing
          the directory, it will behave much like a ``.gitignore``,
          ignoring files that match any of the regex patterns specified
          in the file.
  
          **Note**: The patterns in .airflowignore are treated as
          un-anchored regexes, not shell-like glob patterns.
          """
          start_dttm = timezone.utcnow()
          dag_folder = dag_folder or self.dag_folder
          # Used to store stats around DagBag processing
          stats = []
          FileLoadStat = namedtuple(
              'FileLoadStat', "file duration dag_num task_num dags")
  
          dag_folder = correct_maybe_zipped(dag_folder)
  
          for filepath in list_py_file_paths(dag_folder, safe_mode=safe_mode,
                                             include_examples=include_examples):
              try:
                  ts = timezone.utcnow()
                  found_dags = self.process_file(
                      filepath, only_if_updated=only_if_updated,
                      safe_mode=safe_mode)
                  dag_ids = [dag.dag_id for dag in found_dags]
                  dag_id_names = str(dag_ids)
  
                  td = timezone.utcnow() - ts
                  td = td.total_seconds() + (
                      float(td.microseconds) / 1000000)
                  stats.append(FileLoadStat(
                      filepath.replace(dag_folder, ''),
                      td,
                      len(found_dags),
                      sum([len(dag.tasks) for dag in found_dags]),
                      dag_id_names,
                  ))
              except Exception as e:
                  self.log.exception(e)
          Stats.gauge(
              'collect_dags', (timezone.utcnow() - start_dttm).total_seconds(), 1)
          Stats.gauge(
              'dagbag_size', len(self.dags), 1)
          Stats.gauge(
              'dagbag_import_errors', len(self.import_errors), 1)
          self.dagbag_stats = sorted(
              stats, key=lambda x: x.duration, reverse=True)
          for file_stat in self.dagbag_stats:
              # file_stat.file similar format: /subdir/dag_name.py
              filename = file_stat.file.split('/')[-1].replace('.py', '')
              Stats.timing('dag.loading-duration.{}'.
                           format(filename),
                           file_stat.duration)
  
      def dagbag_report(self):
          """Prints a report around DagBag loading stats"""
          report = textwrap.dedent("""\n
          -------------------------------------------------------------------
          DagBag loading stats for {dag_folder}
          -------------------------------------------------------------------
          Number of DAGs: {dag_num}
          Total task number: {task_num}
          DagBag parsing time: {duration}
          {table}
          """)
          stats = self.dagbag_stats
          return report.format(
              dag_folder=self.dag_folder,
              duration=sum([o.duration for o in stats]),
              dag_num=sum([o.dag_num for o in stats]),
              task_num=sum([o.task_num for o in stats]),
              table=pprinttable(stats),
          )
  