Source code for airflow.providers.google.cloud.operators.life_sciences

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"""Operators that interact with Google Cloud Life Sciences service."""

from typing import TYPE_CHECKING, Optional, Sequence, Union

from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from airflow.providers.google.cloud.hooks.life_sciences import LifeSciencesHook

if TYPE_CHECKING:
    from airflow.utils.context import Context


[docs]class LifeSciencesRunPipelineOperator(BaseOperator): """ Runs a Life Sciences Pipeline .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:LifeSciencesRunPipelineOperator` :param body: The request body :param location: The location of the project :param project_id: ID of the Google Cloud project if None then default project_id is used. :param gcp_conn_id: The connection ID to use to connect to Google Cloud. :param api_version: API version used (for example v2beta). :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """
[docs] template_fields: Sequence[str] = ( "body", "gcp_conn_id", "api_version", "impersonation_chain",
) def __init__( self, *, body: dict, location: str, project_id: Optional[str] = None, gcp_conn_id: str = "google_cloud_default", api_version: str = "v2beta", impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.body = body self.location = location self.project_id = project_id self.gcp_conn_id = gcp_conn_id self.api_version = api_version self._validate_inputs() self.impersonation_chain = impersonation_chain def _validate_inputs(self) -> None: if not self.body: raise AirflowException("The required parameter 'body' is missing") if not self.location: raise AirflowException("The required parameter 'location' is missing")
[docs] def execute(self, context: 'Context') -> dict: hook = LifeSciencesHook( gcp_conn_id=self.gcp_conn_id, api_version=self.api_version, impersonation_chain=self.impersonation_chain, ) return hook.run_pipeline(body=self.body, location=self.location, project_id=self.project_id)

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