# 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.
from __future__ import annotations
import hashlib
import json
import re
import uuid
from datetime import datetime, timedelta
from typing import TYPE_CHECKING, Sequence
import pytz
from google.api_core.exceptions import AlreadyExists
from google.api_core.gapic_v1.method import DEFAULT, _MethodDefault
from google.api_core.retry import Retry
from google.cloud.workflows.executions_v1beta import Execution
from google.cloud.workflows_v1beta import Workflow
from google.protobuf.field_mask_pb2 import FieldMask
from airflow.models import BaseOperator
from airflow.providers.google.cloud.hooks.workflows import WorkflowsHook
from airflow.providers.google.cloud.links.workflows import (
WorkflowsExecutionLink,
WorkflowsListOfWorkflowsLink,
WorkflowsWorkflowDetailsLink,
)
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class WorkflowsCreateWorkflowOperator(BaseOperator):
"""
Creates a new workflow. If a workflow with the specified name
already exists in the specified project and location, the long
running operation will return
[ALREADY_EXISTS][google.rpc.Code.ALREADY_EXISTS] error.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:WorkflowsCreateWorkflowOperator`
:param workflow: Required. Workflow to be created.
:param workflow_id: Required. The ID of the workflow to be created.
:param project_id: Required. The ID of the Google Cloud project the cluster belongs to.
:param location: Required. The GCP region in which to handle the request.
:param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be
retried.
:param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if
``retry`` is specified, the timeout applies to each individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
[docs] template_fields: Sequence[str] = ("location", "workflow", "workflow_id")
[docs] template_fields_renderers = {"workflow": "json"}
def __init__(
self,
*,
workflow: dict,
workflow_id: str,
location: str,
project_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
force_rerun: bool = False,
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.workflow = workflow
self.workflow_id = workflow_id
self.location = location
self.project_id = project_id
self.retry = retry
self.timeout = timeout
self.metadata = metadata
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
self.force_rerun = force_rerun
def _workflow_id(self, context):
if self.workflow_id and not self.force_rerun:
# If users provide workflow id then assuring the idempotency
# is on their side
return self.workflow_id
if self.force_rerun:
hash_base = str(uuid.uuid4())
else:
hash_base = json.dumps(self.workflow, sort_keys=True)
# We are limited by allowed length of workflow_id so
# we use hash of whole information
exec_date = context["execution_date"].isoformat()
base = f"airflow_{self.dag_id}_{self.task_id}_{exec_date}_{hash_base}"
workflow_id = hashlib.md5(base.encode()).hexdigest()
return re.sub(r"[:\-+.]", "_", workflow_id)
[docs] def execute(self, context: Context):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
workflow_id = self._workflow_id(context)
self.log.info("Creating workflow")
try:
operation = hook.create_workflow(
workflow=self.workflow,
workflow_id=workflow_id,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
workflow = operation.result()
except AlreadyExists:
workflow = hook.get_workflow(
workflow_id=workflow_id,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
WorkflowsWorkflowDetailsLink.persist(
context=context,
task_instance=self,
location_id=self.location,
workflow_id=self.workflow_id,
project_id=self.project_id or hook.project_id,
)
return Workflow.to_dict(workflow)
[docs]class WorkflowsUpdateWorkflowOperator(BaseOperator):
"""
Updates an existing workflow.
Running this method has no impact on already running
executions of the workflow. A new revision of the
workflow may be created as a result of a successful
update operation. In that case, such revision will be
used in new workflow executions.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:WorkflowsUpdateWorkflowOperator`
:param workflow_id: Required. The ID of the workflow to be updated.
:param location: Required. The GCP region in which to handle the request.
:param project_id: Required. The ID of the Google Cloud project the cluster belongs to.
:param update_mask: List of fields to be updated. If not present,
the entire workflow will be updated.
:param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be
retried.
:param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if
``retry`` is specified, the timeout applies to each individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
[docs] template_fields: Sequence[str] = ("workflow_id", "update_mask")
[docs] template_fields_renderers = {"update_mask": "json"}
def __init__(
self,
*,
workflow_id: str,
location: str,
project_id: str | None = None,
update_mask: FieldMask | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.workflow_id = workflow_id
self.location = location
self.project_id = project_id
self.update_mask = update_mask
self.retry = retry
self.timeout = timeout
self.metadata = metadata
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
workflow = hook.get_workflow(
workflow_id=self.workflow_id,
project_id=self.project_id,
location=self.location,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
self.log.info("Updating workflow")
operation = hook.update_workflow(
workflow=workflow,
update_mask=self.update_mask,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
workflow = operation.result()
WorkflowsWorkflowDetailsLink.persist(
context=context,
task_instance=self,
location_id=self.location,
workflow_id=self.workflow_id,
project_id=self.project_id or hook.project_id,
)
return Workflow.to_dict(workflow)
[docs]class WorkflowsDeleteWorkflowOperator(BaseOperator):
"""
Deletes a workflow with the specified name.
This method also cancels and deletes all running
executions of the workflow.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:WorkflowsDeleteWorkflowOperator`
:param workflow_id: Required. The ID of the workflow to be created.
:param project_id: Required. The ID of the Google Cloud project the cluster belongs to.
:param location: Required. The GCP region in which to handle the request.
:param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be
retried.
:param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if
``retry`` is specified, the timeout applies to each individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
[docs] template_fields: Sequence[str] = ("location", "workflow_id")
def __init__(
self,
*,
workflow_id: str,
location: str,
project_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.workflow_id = workflow_id
self.location = location
self.project_id = project_id
self.retry = retry
self.timeout = timeout
self.metadata = metadata
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
self.log.info("Deleting workflow %s", self.workflow_id)
operation = hook.delete_workflow(
workflow_id=self.workflow_id,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
operation.result()
[docs]class WorkflowsListWorkflowsOperator(BaseOperator):
"""
Lists Workflows in a given project and location.
The default order is not specified.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:WorkflowsListWorkflowsOperator`
:param filter_: Filter to restrict results to specific workflows.
:param order_by: Comma-separated list of fields that
specifies the order of the results. Default sorting order for a field is ascending.
To specify descending order for a field, append a "desc" suffix.
If not specified, the results will be returned in an unspecified order.
:param project_id: Required. The ID of the Google Cloud project the cluster belongs to.
:param location: Required. The GCP region in which to handle the request.
:param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be
retried.
:param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if
``retry`` is specified, the timeout applies to each individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
[docs] template_fields: Sequence[str] = ("location", "order_by", "filter_")
def __init__(
self,
*,
location: str,
project_id: str | None = None,
filter_: str | None = None,
order_by: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.filter_ = filter_
self.order_by = order_by
self.location = location
self.project_id = project_id
self.retry = retry
self.timeout = timeout
self.metadata = metadata
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
self.log.info("Retrieving workflows")
workflows_iter = hook.list_workflows(
filter_=self.filter_,
order_by=self.order_by,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
WorkflowsListOfWorkflowsLink.persist(
context=context,
task_instance=self,
project_id=self.project_id or hook.project_id,
)
return [Workflow.to_dict(w) for w in workflows_iter]
[docs]class WorkflowsGetWorkflowOperator(BaseOperator):
"""
Gets details of a single Workflow.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:WorkflowsGetWorkflowOperator`
:param workflow_id: Required. The ID of the workflow to be created.
:param project_id: Required. The ID of the Google Cloud project the cluster belongs to.
:param location: Required. The GCP region in which to handle the request.
:param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be
retried.
:param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if
``retry`` is specified, the timeout applies to each individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
[docs] template_fields: Sequence[str] = ("location", "workflow_id")
def __init__(
self,
*,
workflow_id: str,
location: str,
project_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.workflow_id = workflow_id
self.location = location
self.project_id = project_id
self.retry = retry
self.timeout = timeout
self.metadata = metadata
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
self.log.info("Retrieving workflow")
workflow = hook.get_workflow(
workflow_id=self.workflow_id,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
WorkflowsWorkflowDetailsLink.persist(
context=context,
task_instance=self,
location_id=self.location,
workflow_id=self.workflow_id,
project_id=self.project_id or hook.project_id,
)
return Workflow.to_dict(workflow)
[docs]class WorkflowsCreateExecutionOperator(BaseOperator):
"""
Creates a new execution using the latest revision of
the given workflow.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:WorkflowsCreateExecutionOperator`
:param execution: Required. Execution to be created.
:param workflow_id: Required. The ID of the workflow.
:param project_id: Required. The ID of the Google Cloud project the cluster belongs to.
:param location: Required. The GCP region in which to handle the request.
:param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be
retried.
:param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if
``retry`` is specified, the timeout applies to each individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
[docs] template_fields: Sequence[str] = ("location", "workflow_id", "execution")
[docs] template_fields_renderers = {"execution": "json"}
def __init__(
self,
*,
workflow_id: str,
execution: dict,
location: str,
project_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.workflow_id = workflow_id
self.execution = execution
self.location = location
self.project_id = project_id
self.retry = retry
self.timeout = timeout
self.metadata = metadata
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
self.log.info("Creating execution")
execution = hook.create_execution(
workflow_id=self.workflow_id,
execution=self.execution,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
execution_id = execution.name.split("/")[-1]
self.xcom_push(context, key="execution_id", value=execution_id)
WorkflowsExecutionLink.persist(
context=context,
task_instance=self,
location_id=self.location,
workflow_id=self.workflow_id,
execution_id=execution_id,
project_id=self.project_id or hook.project_id,
)
return Execution.to_dict(execution)
[docs]class WorkflowsCancelExecutionOperator(BaseOperator):
"""
Cancels an execution using the given ``workflow_id`` and ``execution_id``.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:WorkflowsCancelExecutionOperator`
:param workflow_id: Required. The ID of the workflow.
:param execution_id: Required. The ID of the execution.
:param project_id: Required. The ID of the Google Cloud project the cluster belongs to.
:param location: Required. The GCP region in which to handle the request.
:param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be
retried.
:param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if
``retry`` is specified, the timeout applies to each individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
[docs] template_fields: Sequence[str] = ("location", "workflow_id", "execution_id")
def __init__(
self,
*,
workflow_id: str,
execution_id: str,
location: str,
project_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.workflow_id = workflow_id
self.execution_id = execution_id
self.location = location
self.project_id = project_id
self.retry = retry
self.timeout = timeout
self.metadata = metadata
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
self.log.info("Canceling execution %s", self.execution_id)
execution = hook.cancel_execution(
workflow_id=self.workflow_id,
execution_id=self.execution_id,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
WorkflowsExecutionLink.persist(
context=context,
task_instance=self,
location_id=self.location,
workflow_id=self.workflow_id,
execution_id=self.execution_id,
project_id=self.project_id or hook.project_id,
)
return Execution.to_dict(execution)
[docs]class WorkflowsListExecutionsOperator(BaseOperator):
"""
Returns a list of executions which belong to the
workflow with the given name. The method returns
executions of all workflow revisions. Returned
executions are ordered by their start time (newest
first).
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:WorkflowsListExecutionsOperator`
:param workflow_id: Required. The ID of the workflow to be created.
:param start_date_filter: If passed only executions older that this date will be returned.
By default operators return executions from last 60 minutes
:param project_id: Required. The ID of the Google Cloud project the cluster belongs to.
:param location: Required. The GCP region in which to handle the request.
:param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be
retried.
:param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if
``retry`` is specified, the timeout applies to each individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
[docs] template_fields: Sequence[str] = ("location", "workflow_id")
def __init__(
self,
*,
workflow_id: str,
location: str,
start_date_filter: datetime | None = None,
project_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.workflow_id = workflow_id
self.location = location
self.start_date_filter = start_date_filter or datetime.now(tz=pytz.UTC) - timedelta(minutes=60)
self.project_id = project_id
self.retry = retry
self.timeout = timeout
self.metadata = metadata
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
self.log.info("Retrieving executions for workflow %s", self.workflow_id)
execution_iter = hook.list_executions(
workflow_id=self.workflow_id,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
WorkflowsWorkflowDetailsLink.persist(
context=context,
task_instance=self,
location_id=self.location,
workflow_id=self.workflow_id,
project_id=self.project_id or hook.project_id,
)
return [Execution.to_dict(e) for e in execution_iter if e.start_time > self.start_date_filter]
[docs]class WorkflowsGetExecutionOperator(BaseOperator):
"""
Returns an execution for the given ``workflow_id`` and ``execution_id``.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:WorkflowsGetExecutionOperator`
:param workflow_id: Required. The ID of the workflow.
:param execution_id: Required. The ID of the execution.
:param project_id: Required. The ID of the Google Cloud project the cluster belongs to.
:param location: Required. The GCP region in which to handle the request.
:param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be
retried.
:param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if
``retry`` is specified, the timeout applies to each individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
[docs] template_fields: Sequence[str] = ("location", "workflow_id", "execution_id")
def __init__(
self,
*,
workflow_id: str,
execution_id: str,
location: str,
project_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.workflow_id = workflow_id
self.execution_id = execution_id
self.location = location
self.project_id = project_id
self.retry = retry
self.timeout = timeout
self.metadata = metadata
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: Context):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
self.log.info("Retrieving execution %s for workflow %s", self.execution_id, self.workflow_id)
execution = hook.get_execution(
workflow_id=self.workflow_id,
execution_id=self.execution_id,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
WorkflowsExecutionLink.persist(
context=context,
task_instance=self,
location_id=self.location,
workflow_id=self.workflow_id,
execution_id=self.execution_id,
project_id=self.project_id or hook.project_id,
)
return Execution.to_dict(execution)
