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  # 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.
  
  """
  This module contains Google DataFusion hook.
  """
  import json
  import os
  from time import monotonic, sleep
  from typing import Any, Dict, List, Optional, Sequence, Union
  from urllib.parse import quote, urlencode
  
  import google.auth
  from google.api_core.retry import exponential_sleep_generator
  from googleapiclient.discovery import Resource, build
  
  from airflow.exceptions import AirflowException
  from airflow.providers.google.common.hooks.base_google import GoogleBaseHook
  
  Operation = Dict[str, Any]
  
  
  class PipelineStates:
      """Data Fusion pipeline states"""
  
      PENDING = "PENDING"
      STARTING = "STARTING"
      RUNNING = "RUNNING"
      SUSPENDED = "SUSPENDED"
      RESUMING = "RESUMING"
      COMPLETED = "COMPLETED"
      FAILED = "FAILED"
      KILLED = "KILLED"
      REJECTED = "REJECTED"
  
  
  FAILURE_STATES = [PipelineStates.FAILED, PipelineStates.KILLED, PipelineStates.REJECTED]
  SUCCESS_STATES = [PipelineStates.COMPLETED]
  
  
  class DataFusionHook(GoogleBaseHook):
      """
      Hook for Google DataFusion.
      """
  
      _conn = None  # type: Optional[Resource]
  
      def __init__(
          self,
          api_version: str = "v1beta1",
          gcp_conn_id: str = "google_cloud_default",
          delegate_to: Optional[str] = None,
          impersonation_chain: Optional[Union[str, Sequence[str]]] = None,
      ) -> None:
          super().__init__(
              gcp_conn_id=gcp_conn_id,
              delegate_to=delegate_to,
              impersonation_chain=impersonation_chain,
          )
          self.api_version = api_version
  
      def wait_for_operation(self, operation: Dict[str, Any]) -> Dict[str, Any]:
          """
          Waits for long-lasting operation to complete.
          """
          for time_to_wait in exponential_sleep_generator(initial=10, maximum=120):
              sleep(time_to_wait)
              operation = (
                  self.get_conn()  # pylint: disable=no-member
                  .projects()
                  .locations()
                  .operations()
                  .get(name=operation.get("name"))
                  .execute()
              )
              if operation.get("done"):
                  break
          if "error" in operation:
              raise AirflowException(operation["error"])
          return operation["response"]
  
      def wait_for_pipeline_state(
          self,
          pipeline_name: str,
          pipeline_id: str,
          instance_url: str,
          namespace: str = "default",
          success_states: Optional[List[str]] = None,
          failure_states: Optional[List[str]] = None,
          timeout: int = 5 * 60,
      ) -> None:
          """
          Polls pipeline state and raises an exception if the state is one of
          `failure_states` or the operation timed_out.
          """
          failure_states = failure_states or FAILURE_STATES
          success_states = success_states or SUCCESS_STATES
          start_time = monotonic()
          current_state = None
          while monotonic() - start_time < timeout:
              try:
                  current_state = self._get_workflow_state(
                      pipeline_name=pipeline_name,
                      pipeline_id=pipeline_id,
                      instance_url=instance_url,
                      namespace=namespace,
                  )
              except AirflowException:
                  pass  # Because the pipeline may not be visible in system yet
              if current_state in success_states:
                  return
              if current_state in failure_states:
                  raise AirflowException(
                      f"Pipeline {pipeline_name} state {current_state} is not " f"one of {success_states}"
                  )
              sleep(30)
  
          # Time is up!
          raise AirflowException(
              f"Pipeline {pipeline_name} state {current_state} is not "
              f"one of {success_states} after {timeout}s"
          )
  
      @staticmethod
      def _name(project_id: str, location: str, instance_name: str) -> str:
          return f"projects/{project_id}/locations/{location}/instances/{instance_name}"
  
      @staticmethod
      def _parent(project_id: str, location: str) -> str:
          return f"projects/{project_id}/locations/{location}"
  
      @staticmethod
      def _base_url(instance_url: str, namespace: str) -> str:
          return os.path.join(instance_url, "v3", "namespaces", quote(namespace), "apps")
  
      def _cdap_request(
          self, url: str, method: str, body: Optional[Union[List, Dict]] = None
      ) -> google.auth.transport.Response:
          headers: Dict[str, str] = {"Content-Type": "application/json"}
          request = google.auth.transport.requests.Request()
  
          credentials = self._get_credentials()
          credentials.before_request(request=request, method=method, url=url, headers=headers)
  
          payload = json.dumps(body) if body else None
  
          response = request(method=method, url=url, headers=headers, body=payload)
          return response
  
      def get_conn(self) -> Resource:
          """
          Retrieves connection to DataFusion.
          """
          if not self._conn:
              http_authorized = self._authorize()
              self._conn = build(
                  "datafusion",
                  self.api_version,
                  http=http_authorized,
                  cache_discovery=False,
              )
          return self._conn
  
      @GoogleBaseHook.fallback_to_default_project_id
      def restart_instance(self, instance_name: str, location: str, project_id: str) -> Operation:
          """
          Restart a single Data Fusion instance.
          At the end of an operation instance is fully restarted.
  
          :param instance_name: The name of the instance to restart.
          :type instance_name: str
          :param location: The Cloud Data Fusion location in which to handle the request.
          :type location: str
          :param project_id: The ID of the Google Cloud project that the instance belongs to.
          :type project_id: str
          """
          operation = (
              self.get_conn()  # pylint: disable=no-member
              .projects()
              .locations()
              .instances()
              .restart(name=self._name(project_id, location, instance_name))
              .execute(num_retries=self.num_retries)
          )
          return operation
  
      @GoogleBaseHook.fallback_to_default_project_id
      def delete_instance(self, instance_name: str, location: str, project_id: str) -> Operation:
          """
          Deletes a single Date Fusion instance.
  
          :param instance_name: The name of the instance to delete.
          :type instance_name: str
          :param location: The Cloud Data Fusion location in which to handle the request.
          :type location: str
          :param project_id: The ID of the Google Cloud project that the instance belongs to.
          :type project_id: str
          """
          operation = (
              self.get_conn()  # pylint: disable=no-member
              .projects()
              .locations()
              .instances()
              .delete(name=self._name(project_id, location, instance_name))
              .execute(num_retries=self.num_retries)
          )
          return operation
  
      @GoogleBaseHook.fallback_to_default_project_id
      def create_instance(
          self,
          instance_name: str,
          instance: Dict[str, Any],
          location: str,
          project_id: str,
      ) -> Operation:
          """
          Creates a new Data Fusion instance in the specified project and location.
  
          :param instance_name: The name of the instance to create.
          :type instance_name: str
          :param instance: An instance of Instance.
              https://cloud.google.com/data-fusion/docs/reference/rest/v1beta1/projects.locations.instances#Instance
          :type instance: Dict[str, Any]
          :param location: The Cloud Data Fusion location in which to handle the request.
          :type location: str
          :param project_id: The ID of the Google Cloud project that the instance belongs to.
          :type project_id: str
          """
          operation = (
              self.get_conn()  # pylint: disable=no-member
              .projects()
              .locations()
              .instances()
              .create(
                  parent=self._parent(project_id, location),
                  body=instance,
                  instanceId=instance_name,
              )
              .execute(num_retries=self.num_retries)
          )
          return operation
  
      @GoogleBaseHook.fallback_to_default_project_id
      def get_instance(self, instance_name: str, location: str, project_id: str) -> Dict[str, Any]:
          """
          Gets details of a single Data Fusion instance.
  
          :param instance_name: The name of the instance.
          :type instance_name: str
          :param location: The Cloud Data Fusion location in which to handle the request.
          :type location: str
          :param project_id: The ID of the Google Cloud project that the instance belongs to.
          :type project_id: str
          """
          instance = (
              self.get_conn()  # pylint: disable=no-member
              .projects()
              .locations()
              .instances()
              .get(name=self._name(project_id, location, instance_name))
              .execute(num_retries=self.num_retries)
          )
          return instance
  
      @GoogleBaseHook.fallback_to_default_project_id
      def patch_instance(
          self,
          instance_name: str,
          instance: Dict[str, Any],
          update_mask: str,
          location: str,
          project_id: str,
      ) -> Operation:
          """
          Updates a single Data Fusion instance.
  
          :param instance_name: The name of the instance to create.
          :type instance_name: str
          :param instance: An instance of Instance.
              https://cloud.google.com/data-fusion/docs/reference/rest/v1beta1/projects.locations.instances#Instance
          :type instance: Dict[str, Any]
          :param update_mask: Field mask is used to specify the fields that the update will overwrite
              in an instance resource. The fields specified in the updateMask are relative to the resource,
              not the full request. A field will be overwritten if it is in the mask. If the user does not
              provide a mask, all the supported fields (labels and options currently) will be overwritten.
              A comma-separated list of fully qualified names of fields. Example: "user.displayName,photo".
              https://developers.google.com/protocol-buffers/docs/reference/google.protobuf?_ga=2.205612571.-968688242.1573564810#google.protobuf.FieldMask
          :type update_mask: str
          :param location: The Cloud Data Fusion location in which to handle the request.
          :type location: str
          :param project_id: The ID of the Google Cloud project that the instance belongs to.
          :type project_id: str
          """
          operation = (
              self.get_conn()  # pylint: disable=no-member
              .projects()
              .locations()
              .instances()
              .patch(
                  name=self._name(project_id, location, instance_name),
                  updateMask=update_mask,
                  body=instance,
              )
              .execute(num_retries=self.num_retries)
          )
          return operation
  
      def create_pipeline(
          self,
          pipeline_name: str,
          pipeline: Dict[str, Any],
          instance_url: str,
          namespace: str = "default",
      ) -> None:
          """
          Creates a Cloud Data Fusion pipeline.
  
          :param pipeline_name: Your pipeline name.
          :type pipeline_name: str
          :param pipeline: The pipeline definition. For more information check:
              https://docs.cdap.io/cdap/current/en/developer-manual/pipelines/developing-pipelines.html#pipeline-configuration-file-format
          :type pipeline: Dict[str, Any]
          :param instance_url: Endpoint on which the REST APIs is accessible for the instance.
          :type instance_url: str
          :param namespace: if your pipeline belongs to a Basic edition instance, the namespace ID
              is always default. If your pipeline belongs to an Enterprise edition instance, you
              can create a namespace.
          :type namespace: str
          """
          url = os.path.join(self._base_url(instance_url, namespace), quote(pipeline_name))
          response = self._cdap_request(url=url, method="PUT", body=pipeline)
          if response.status != 200:
              raise AirflowException(f"Creating a pipeline failed with code {response.status}")
  
      def delete_pipeline(
          self,
          pipeline_name: str,
          instance_url: str,
          version_id: Optional[str] = None,
          namespace: str = "default",
      ) -> None:
          """
          Deletes a Cloud Data Fusion pipeline.
  
          :param pipeline_name: Your pipeline name.
          :type pipeline_name: str
          :param version_id: Version of pipeline to delete
          :type version_id: Optional[str]
          :param instance_url: Endpoint on which the REST APIs is accessible for the instance.
          :type instance_url: str
          :param namespace: f your pipeline belongs to a Basic edition instance, the namespace ID
              is always default. If your pipeline belongs to an Enterprise edition instance, you
              can create a namespace.
          :type namespace: str
          """
          url = os.path.join(self._base_url(instance_url, namespace), quote(pipeline_name))
          if version_id:
              url = os.path.join(url, "versions", version_id)
  
          response = self._cdap_request(url=url, method="DELETE", body=None)
          if response.status != 200:
              raise AirflowException(f"Deleting a pipeline failed with code {response.status}")
  
      def list_pipelines(
          self,
          instance_url: str,
          artifact_name: Optional[str] = None,
          artifact_version: Optional[str] = None,
          namespace: str = "default",
      ) -> dict:
          """
          Lists Cloud Data Fusion pipelines.
  
          :param artifact_version: Artifact version to filter instances
          :type artifact_version: Optional[str]
          :param artifact_name: Artifact name to filter instances
          :type artifact_name: Optional[str]
          :param instance_url: Endpoint on which the REST APIs is accessible for the instance.
          :type instance_url: str
          :param namespace: f your pipeline belongs to a Basic edition instance, the namespace ID
              is always default. If your pipeline belongs to an Enterprise edition instance, you
              can create a namespace.
          :type namespace: str
          """
          url = self._base_url(instance_url, namespace)
          query: Dict[str, str] = {}
          if artifact_name:
              query = {"artifactName": artifact_name}
          if artifact_version:
              query = {"artifactVersion": artifact_version}
          if query:
              url = os.path.join(url, urlencode(query))
  
          response = self._cdap_request(url=url, method="GET", body=None)
          if response.status != 200:
              raise AirflowException(f"Listing pipelines failed with code {response.status}")
          return json.loads(response.data)
  
      def _get_workflow_state(
          self,
          pipeline_name: str,
          instance_url: str,
          pipeline_id: str,
          namespace: str = "default",
      ) -> str:
          url = os.path.join(
              self._base_url(instance_url, namespace),
              quote(pipeline_name),
              "workflows",
              "DataPipelineWorkflow",
              "runs",
              quote(pipeline_id),
          )
          response = self._cdap_request(url=url, method="GET")
          if response.status != 200:
              raise AirflowException(f"Retrieving a pipeline state failed with code {response.status}")
          workflow = json.loads(response.data)
          return workflow["status"]
  
      def start_pipeline(
          self,
          pipeline_name: str,
          instance_url: str,
          namespace: str = "default",
          runtime_args: Optional[Dict[str, Any]] = None,
      ) -> str:
          """
          Starts a Cloud Data Fusion pipeline. Works for both batch and stream pipelines.
  
          :param pipeline_name: Your pipeline name.
          :type pipeline_name: str
          :param instance_url: Endpoint on which the REST APIs is accessible for the instance.
          :type instance_url: str
          :param runtime_args: Optional runtime JSON args to be passed to the pipeline
          :type runtime_args: Optional[Dict[str, Any]]
          :param namespace: f your pipeline belongs to a Basic edition instance, the namespace ID
              is always default. If your pipeline belongs to an Enterprise edition instance, you
              can create a namespace.
          :type namespace: str
          """
          # TODO: This API endpoint starts multiple pipelines. There will eventually be a fix
          #  return the run Id as part of the API request to run a single pipeline.
          #  https://github.com/apache/airflow/pull/8954#discussion_r438223116
          url = os.path.join(
              instance_url,
              "v3",
              "namespaces",
              quote(namespace),
              "start",
          )
          runtime_args = runtime_args or {}
          body = [
              {
                  "appId": pipeline_name,
                  "programType": "workflow",
                  "programId": "DataPipelineWorkflow",
                  "runtimeargs": runtime_args,
              }
          ]
          response = self._cdap_request(url=url, method="POST", body=body)
          if response.status != 200:
              raise AirflowException(f"Starting a pipeline failed with code {response.status}")
  
          response_json = json.loads(response.data)
          pipeline_id = response_json[0]["runId"]
          self.wait_for_pipeline_state(
              success_states=SUCCESS_STATES + [PipelineStates.RUNNING],
              pipeline_name=pipeline_name,
              pipeline_id=pipeline_id,
              namespace=namespace,
              instance_url=instance_url,
          )
          return pipeline_id
  
      def stop_pipeline(self, pipeline_name: str, instance_url: str, namespace: str = "default") -> None:
          """
          Stops a Cloud Data Fusion pipeline. Works for both batch and stream pipelines.
  
          :param pipeline_name: Your pipeline name.
          :type pipeline_name: str
          :param instance_url: Endpoint on which the REST APIs is accessible for the instance.
          :type instance_url: str
          :param namespace: f your pipeline belongs to a Basic edition instance, the namespace ID
              is always default. If your pipeline belongs to an Enterprise edition instance, you
              can create a namespace.
          :type namespace: str
          """
          url = os.path.join(
              self._base_url(instance_url, namespace),
              quote(pipeline_name),
              "workflows",
              "DataPipelineWorkflow",
              "stop",
          )
          response = self._cdap_request(url=url, method="POST")
          if response.status != 200:
              raise AirflowException(f"Stopping a pipeline failed with code {response.status}")
  