def test_port_to_k8s_client_obj(self):
port = Port('http', 80)
self.assertEqual(
port.to_k8s_client_obj(),
k8s.V1ContainerPort(
name='http',
container_port=80
)
)
def test_port(self):
port = Port('http', 80)
k = KubernetesPodOperator(
namespace='default',
image="ubuntu:16.04",
cmds=["bash", "-cx"],
arguments=["echo 10"],
labels={"foo": "bar"},
name="test",
task_id="task",
in_cluster=False,
do_xcom_push=False,
ports=[port],
)
context = create_context(k)
k.execute(context=context)
actual_pod = self.api_client.sanitize_for_serialization(k.pod)
self.expected_pod['spec']['containers'][0]['ports'] = [{
'name':
'http',
'containerPort':
80
}]
assert self.expected_pod == actual_pod
def _extract_ports(ports):
result = []
ports = ports or [] # type: List[Union[k8s.V1ContainerPort, dict]]
for port in ports:
if isinstance(port, k8s.V1ContainerPort):
port = api_client.sanitize_for_serialization(port)
port = Port(name=port.get("name"), container_port=port.get("containerPort"))
elif not isinstance(port, Port):
port = Port(name=port.get("name"), container_port=port.get("containerPort"))
result.append(port)
return result
def test_port_attach_to_pod(self, mock_uuid):
mock_uuid.return_value = '0'
pod = PodGenerator(image='airflow-worker:latest',
name='base').gen_pod()
ports = [Port('https', 443), Port('http', 80)]
k8s_client = ApiClient()
result = append_to_pod(pod, ports)
result = k8s_client.sanitize_for_serialization(result)
self.assertEqual(
{
'apiVersion': 'v1',
'kind': 'Pod',
'metadata': {
'name': 'base-0'
},
'spec': {
'containers': [{
'args': [],
'command': [],
'env': [],
'envFrom': [],
'image':
'airflow-worker:latest',
'imagePullPolicy':
'IfNotPresent',
'name':
'base',
'ports': [{
'name': 'https',
'containerPort': 443
}, {
'name': 'http',
'containerPort': 80
}],
'volumeMounts': [],
}],
'hostNetwork':
False,
'imagePullSecrets': [],
'restartPolicy':
'Never',
'volumes': []
}
}, result)
def test_port_attach_to_pod(self, mock_uuid):
import uuid
static_uuid = uuid.UUID('cf4a56d2-8101-4217-b027-2af6216feb48')
mock_uuid.return_value = static_uuid
pod = PodGenerator(image='airflow-worker:latest',
name='base').gen_pod()
ports = [Port('https', 443), Port('http', 80)]
k8s_client = ApiClient()
result = append_to_pod(pod, ports)
result = k8s_client.sanitize_for_serialization(result)
self.assertEqual(
{
'apiVersion': 'v1',
'kind': 'Pod',
'metadata': {
'name': 'base-' + static_uuid.hex
},
'spec': {
'containers': [{
'args': [],
'command': [],
'env': [],
'envFrom': [],
'image':
'airflow-worker:latest',
'name':
'base',
'ports': [{
'name': 'https',
'containerPort': 443
}, {
'name': 'http',
'containerPort': 80
}],
'volumeMounts': [],
}],
'hostNetwork':
False,
'imagePullSecrets': [],
'volumes': []
}
}, result)
def test_port():
port = Port('http', 80)
k = KubernetesPodOperator(namespace='default',
image="ubuntu:16.04",
cmds=["bash", "-cx"],
arguments=["echo 10"],
labels={"foo": "bar"},
name="test",
task_id="task",
ports=[port])
k.execute(None)
def test_port(self):
port = Port('http', 80)
k = KubernetesPodOperator(namespace='default',
image="ubuntu:16.04",
cmds=["bash", "-cx"],
arguments=["echo 10"],
labels={"foo": "bar"},
name="test",
task_id="task",
ports=[port])
k.execute(None)
actual_pod = self.api_client.sanitize_for_serialization(k.pod)
self.expected_pod['spec']['containers'][0]['ports'] = [{
'name':
'http',
'containerPort':
80
}]
self.assertEqual(self.expected_pod, actual_pod)
def make_task(operator: str, task_params: Dict[str, Any]) -> BaseOperator:
"""
Takes an operator and params and creates an instance of that operator.
:returns: instance of operator object
"""
try:
# class is a Callable https://stackoverflow.com/a/34578836/3679900
operator_obj: Callable[..., BaseOperator] = import_string(operator)
except Exception as err:
raise f"Failed to import operator: {operator}" from err
try:
if operator_obj == PythonOperator:
if not task_params.get(
"python_callable_name") and not task_params.get(
"python_callable_file"):
raise Exception(
"Failed to create task. PythonOperator requires `python_callable_name` \
and `python_callable_file` parameters.")
task_params[
"python_callable"]: Callable = utils.get_python_callable(
task_params["python_callable_name"],
task_params["python_callable_file"],
)
# KubernetesPodOperator
if operator_obj == KubernetesPodOperator:
task_params["secrets"] = ([
Secret(**v) for v in task_params.get("secrets")
] if task_params.get("secrets") is not None else None)
task_params["ports"] = ([
Port(**v) for v in task_params.get("ports")
] if task_params.get("ports") is not None else None)
task_params["volume_mounts"] = ([
VolumeMount(**v) for v in task_params.get("volume_mounts")
] if task_params.get("volume_mounts") is not None else None)
task_params["volumes"] = ([
Volume(**v) for v in task_params.get("volumes")
] if task_params.get("volumes") is not None else None)
task_params["pod_runtime_info_envs"] = ([
PodRuntimeInfoEnv(**v)
for v in task_params.get("pod_runtime_info_envs")
] if task_params.get("pod_runtime_info_envs") is not None else
None)
task_params["full_pod_spec"] = (
V1Pod(**task_params.get("full_pod_spec"))
if task_params.get("full_pod_spec") is not None else None)
task_params["init_containers"] = ([
V1Container(**v)
for v in task_params.get("init_containers")
] if task_params.get("init_containers") is not None else None)
if utils.check_dict_key(task_params, "execution_timeout_secs"):
task_params["execution_timeout"]: timedelta = timedelta(
seconds=task_params["execution_timeout_secs"])
del task_params["execution_timeout_secs"]
# use variables as arguments on operator
if utils.check_dict_key(task_params, "variables_as_arguments"):
variables: List[Dict[str, str]] = task_params.get(
"variables_as_arguments")
for variable in variables:
if Variable.get(variable["variable"],
default_var=None) is not None:
task_params[variable["attribute"]] = Variable.get(
variable["variable"], default_var=None)
del task_params["variables_as_arguments"]
task: BaseOperator = operator_obj(**task_params)
except Exception as err:
raise f"Failed to create {operator_obj} task" from err
return task
def make_task(operator: str, task_params: Dict[str, Any]) -> BaseOperator:
"""
Takes an operator and params and creates an instance of that operator.
:returns: instance of operator object
"""
try:
# class is a Callable https://stackoverflow.com/a/34578836/3679900
operator_obj: Callable[..., BaseOperator] = import_string(operator)
except Exception as err:
raise Exception(f"Failed to import operator: {operator}") from err
try:
if operator_obj in [PythonOperator, BranchPythonOperator]:
if not task_params.get(
"python_callable_name") and not task_params.get(
"python_callable_file"):
raise Exception(
"Failed to create task. PythonOperator and BranchPythonOperator requires \
`python_callable_name` and `python_callable_file` parameters."
)
task_params[
"python_callable"]: Callable = utils.get_python_callable(
task_params["python_callable_name"],
task_params["python_callable_file"],
)
# remove dag-factory specific parameters
# Airflow 2.0 doesn't allow these to be passed to operator
del task_params["python_callable_name"]
del task_params["python_callable_file"]
# Check for the custom success and failure callables in SqlSensor. These are considered
# optional, so no failures in case they aren't found. Note: there's no reason to
# declare both a callable file and a lambda function for success/failure parameter.
# If both are found the object will not throw and error, instead callable file will
# take precedence over the lambda function
if operator_obj in [SqlSensor]:
# Success checks
if task_params.get("success_check_file") and task_params.get(
"success_check_name"):
task_params[
"success"]: Callable = utils.get_python_callable(
task_params["success_check_name"],
task_params["success_check_file"],
)
del task_params["success_check_name"]
del task_params["success_check_file"]
elif task_params.get("success_check_lambda"):
task_params[
"success"]: Callable = utils.get_python_callable_lambda(
task_params["success_check_lambda"])
del task_params["success_check_lambda"]
# Failure checks
if task_params.get("failure_check_file") and task_params.get(
"failure_check_name"):
task_params[
"failure"]: Callable = utils.get_python_callable(
task_params["failure_check_name"],
task_params["failure_check_file"],
)
del task_params["failure_check_name"]
del task_params["failure_check_file"]
elif task_params.get("failure_check_lambda"):
task_params[
"failure"]: Callable = utils.get_python_callable_lambda(
task_params["failure_check_lambda"])
del task_params["failure_check_lambda"]
if operator_obj in [HttpSensor]:
if not (task_params.get("response_check_name")
and task_params.get("response_check_file")
) and not task_params.get("response_check_lambda"):
raise Exception(
"Failed to create task. HttpSensor requires \
`response_check_name` and `response_check_file` parameters \
or `response_check_lambda` parameter.")
if task_params.get("response_check_file"):
task_params[
"response_check"]: Callable = utils.get_python_callable(
task_params["response_check_name"],
task_params["response_check_file"],
)
# remove dag-factory specific parameters
# Airflow 2.0 doesn't allow these to be passed to operator
del task_params["response_check_name"]
del task_params["response_check_file"]
else:
task_params[
"response_check"]: Callable = utils.get_python_callable_lambda(
task_params["response_check_lambda"])
# remove dag-factory specific parameters
# Airflow 2.0 doesn't allow these to be passed to operator
del task_params["response_check_lambda"]
# KubernetesPodOperator
if operator_obj == KubernetesPodOperator:
task_params["secrets"] = ([
Secret(**v) for v in task_params.get("secrets")
] if task_params.get("secrets") is not None else None)
task_params["ports"] = ([
Port(**v) for v in task_params.get("ports")
] if task_params.get("ports") is not None else None)
task_params["volume_mounts"] = ([
VolumeMount(**v) for v in task_params.get("volume_mounts")
] if task_params.get("volume_mounts") is not None else None)
task_params["volumes"] = ([
Volume(**v) for v in task_params.get("volumes")
] if task_params.get("volumes") is not None else None)
task_params["pod_runtime_info_envs"] = ([
PodRuntimeInfoEnv(**v)
for v in task_params.get("pod_runtime_info_envs")
] if task_params.get("pod_runtime_info_envs") is not None else
None)
task_params["full_pod_spec"] = (
V1Pod(**task_params.get("full_pod_spec"))
if task_params.get("full_pod_spec") is not None else None)
task_params["init_containers"] = ([
V1Container(**v)
for v in task_params.get("init_containers")
] if task_params.get("init_containers") is not None else None)
if utils.check_dict_key(task_params, "execution_timeout_secs"):
task_params["execution_timeout"]: timedelta = timedelta(
seconds=task_params["execution_timeout_secs"])
del task_params["execution_timeout_secs"]
if utils.check_dict_key(task_params, "sla_secs"):
task_params["sla"]: timedelta = timedelta(
seconds=task_params["sla_secs"])
del task_params["sla_secs"]
if utils.check_dict_key(task_params, "execution_delta_secs"):
task_params["execution_delta"]: timedelta = timedelta(
seconds=task_params["execution_delta_secs"])
del task_params["execution_delta_secs"]
if utils.check_dict_key(
task_params,
"execution_date_fn_name") and utils.check_dict_key(
task_params, "execution_date_fn_file"):
task_params[
"execution_date_fn"]: Callable = utils.get_python_callable(
task_params["execution_date_fn_name"],
task_params["execution_date_fn_file"],
)
del task_params["execution_date_fn_name"]
del task_params["execution_date_fn_file"]
# on_execute_callback is an Airflow 2.0 feature
if utils.check_dict_key(
task_params, "on_execute_callback"
) and version.parse(AIRFLOW_VERSION) >= version.parse("2.0.0"):
task_params["on_execute_callback"]: Callable = import_string(
task_params["on_execute_callback"])
if utils.check_dict_key(task_params, "on_failure_callback"):
task_params["on_failure_callback"]: Callable = import_string(
task_params["on_failure_callback"])
if utils.check_dict_key(task_params, "on_success_callback"):
task_params["on_success_callback"]: Callable = import_string(
task_params["on_success_callback"])
if utils.check_dict_key(task_params, "on_retry_callback"):
task_params["on_retry_callback"]: Callable = import_string(
task_params["on_retry_callback"])
# use variables as arguments on operator
if utils.check_dict_key(task_params, "variables_as_arguments"):
variables: List[Dict[str, str]] = task_params.get(
"variables_as_arguments")
for variable in variables:
if Variable.get(variable["variable"],
default_var=None) is not None:
task_params[variable["attribute"]] = Variable.get(
variable["variable"], default_var=None)
del task_params["variables_as_arguments"]
task: BaseOperator = operator_obj(**task_params)
except Exception as err:
raise Exception(f"Failed to create {operator_obj} task") from err
return task
# [START howto_operator_k8s_cluster_resources]
secret_file = Secret('volume', '/etc/sql_conn', 'airflow-secrets',
'sql_alchemy_conn')
secret_env = Secret('env', 'SQL_CONN', 'airflow-secrets', 'sql_alchemy_conn')
secret_all_keys = Secret('env', None, 'airflow-secrets-2')
volume_mount = VolumeMount('test-volume',
mount_path='/root/mount_file',
sub_path=None,
read_only=True)
configmaps = ['test-configmap-1', 'test-configmap-2']
volume_config = {'persistentVolumeClaim': {'claimName': 'test-volume'}}
volume = Volume(name='test-volume', configs=volume_config)
# [END howto_operator_k8s_cluster_resources]
port = Port('http', 80)
init_container_volume_mounts = [
k8s.V1VolumeMount(mount_path='/etc/foo',
name='test-volume',
sub_path=None,
read_only=True)
]
init_environments = [
k8s.V1EnvVar(name='key1', value='value1'),
k8s.V1EnvVar(name='key2', value='value2')
]
init_container = k8s.V1Container(
name="init-container",
def test_convert_to_airflow_pod(self):
input_pod = k8s.V1Pod(
metadata=k8s.V1ObjectMeta(name="foo", namespace="bar"),
spec=k8s.V1PodSpec(
init_containers=[
k8s.V1Container(name="init-container",
volume_mounts=[
k8s.V1VolumeMount(mount_path="/tmp",
name="init-secret")
])
],
containers=[
k8s.V1Container(
name="base",
command=["foo"],
image="myimage",
env=[
k8s.V1EnvVar(
name="AIRFLOW_SECRET",
value_from=k8s.V1EnvVarSource(
secret_key_ref=k8s.V1SecretKeySelector(
name="ai", key="secret_key")))
],
ports=[
k8s.V1ContainerPort(
name="myport",
container_port=8080,
)
],
volume_mounts=[
k8s.V1VolumeMount(name="myvolume",
mount_path="/tmp/mount",
read_only="True"),
k8s.V1VolumeMount(name='airflow-config',
mount_path='/config',
sub_path='airflow.cfg',
read_only=True),
k8s.V1VolumeMount(name="airflow-secret",
mount_path="/opt/mount",
read_only=True)
])
],
security_context=k8s.V1PodSecurityContext(
run_as_user=0,
fs_group=0,
),
volumes=[
k8s.V1Volume(name="myvolume"),
k8s.V1Volume(
name="airflow-config",
config_map=k8s.V1ConfigMap(data="airflow-data")),
k8s.V1Volume(name="airflow-secret",
secret=k8s.V1SecretVolumeSource(
secret_name="secret-name", )),
k8s.V1Volume(name="init-secret",
secret=k8s.V1SecretVolumeSource(
secret_name="init-secret", ))
]))
result_pod = _convert_to_airflow_pod(input_pod)
expected = Pod(
name="foo",
namespace="bar",
envs={},
init_containers=[{
'name':
'init-container',
'volumeMounts': [{
'mountPath': '/tmp',
'name': 'init-secret'
}]
}],
cmds=["foo"],
image="myimage",
ports=[Port(name="myport", container_port=8080)],
volume_mounts=[
VolumeMount(name="myvolume",
mount_path="/tmp/mount",
sub_path=None,
read_only="True"),
VolumeMount(name="airflow-config",
read_only=True,
mount_path="/config",
sub_path="airflow.cfg"),
VolumeMount(name="airflow-secret",
mount_path="/opt/mount",
sub_path=None,
read_only=True)
],
secrets=[Secret("env", "AIRFLOW_SECRET", "ai", "secret_key")],
security_context={
'fsGroup': 0,
'runAsUser': 0
},
volumes=[
Volume(name="myvolume", configs={'name': 'myvolume'}),
Volume(name="airflow-config",
configs={
'configMap': {
'data': 'airflow-data'
},
'name': 'airflow-config'
}),
Volume(name='airflow-secret',
configs={
'name': 'airflow-secret',
'secret': {
'secretName': 'secret-name'
}
}),
Volume(name='init-secret',
configs={
'name': 'init-secret',
'secret': {
'secretName': 'init-secret'
}
})
],
)
expected_dict = expected.as_dict()
result_dict = result_pod.as_dict()
print(result_pod.volume_mounts)
parsed_configs = self.pull_out_volumes(result_dict)
result_dict['volumes'] = parsed_configs
self.assertEqual(result_dict['secrets'], expected_dict['secrets'])
self.assertDictEqual(expected_dict, result_dict)
def make_task(operator: str, task_params: Dict[str, Any],
af_vars: Dict[str, Any]) -> BaseOperator:
"""
Takes an operator and params and creates an instance of that operator.
:returns: instance of operator object
"""
try:
# class is a Callable https://stackoverflow.com/a/34578836/3679900
operator_obj: Callable[..., BaseOperator] = import_string(operator)
except Exception as err:
raise Exception(f"Failed to import operator: {operator}") from err
try:
if operator_obj in [
PythonOperator, BranchPythonOperator, PythonSensor
]:
if (not task_params.get("python_callable")
and not task_params.get("python_callable_name")
and not task_params.get("python_callable_file")):
# pylint: disable=line-too-long
raise Exception(
"Failed to create task. PythonOperator, BranchPythonOperator and PythonSensor requires \
`python_callable_name` and `python_callable_file` "
"parameters.\nOptionally you can load python_callable "
"from a file. with the special pyyaml notation:\n"
" python_callable_file: !!python/name:my_module.my_func"
)
if not task_params.get("python_callable"):
task_params[
"python_callable"]: Callable = utils.get_python_callable(
task_params["python_callable_name"],
task_params["python_callable_file"],
)
# remove dag-factory specific parameters
# Airflow 2.0 doesn't allow these to be passed to operator
del task_params["python_callable_name"]
del task_params["python_callable_file"]
# Check for the custom success and failure callables in SqlSensor. These are considered
# optional, so no failures in case they aren't found. Note: there's no reason to
# declare both a callable file and a lambda function for success/failure parameter.
# If both are found the object will not throw and error, instead callable file will
# take precedence over the lambda function
if operator_obj in [SqlSensor]:
# Success checks
if task_params.get("success_check_file") and task_params.get(
"success_check_name"):
task_params[
"success"]: Callable = utils.get_python_callable(
task_params["success_check_name"],
task_params["success_check_file"],
)
del task_params["success_check_name"]
del task_params["success_check_file"]
elif task_params.get("success_check_lambda"):
task_params[
"success"]: Callable = utils.get_python_callable_lambda(
task_params["success_check_lambda"])
del task_params["success_check_lambda"]
# Failure checks
if task_params.get("failure_check_file") and task_params.get(
"failure_check_name"):
task_params[
"failure"]: Callable = utils.get_python_callable(
task_params["failure_check_name"],
task_params["failure_check_file"],
)
del task_params["failure_check_name"]
del task_params["failure_check_file"]
elif task_params.get("failure_check_lambda"):
task_params[
"failure"]: Callable = utils.get_python_callable_lambda(
task_params["failure_check_lambda"])
del task_params["failure_check_lambda"]
if operator_obj in [HttpSensor]:
if not (task_params.get("response_check_name")
and task_params.get("response_check_file")
) and not task_params.get("response_check_lambda"):
raise Exception(
"Failed to create task. HttpSensor requires \
`response_check_name` and `response_check_file` parameters \
or `response_check_lambda` parameter.")
if task_params.get("response_check_file"):
task_params[
"response_check"]: Callable = utils.get_python_callable(
task_params["response_check_name"],
task_params["response_check_file"],
)
# remove dag-factory specific parameters
# Airflow 2.0 doesn't allow these to be passed to operator
del task_params["response_check_name"]
del task_params["response_check_file"]
else:
task_params[
"response_check"]: Callable = utils.get_python_callable_lambda(
task_params["response_check_lambda"])
# remove dag-factory specific parameters
# Airflow 2.0 doesn't allow these to be passed to operator
del task_params["response_check_lambda"]
# KubernetesPodOperator
if operator_obj == KubernetesPodOperator:
task_params["secrets"] = ([
Secret(**v) for v in task_params.get("secrets")
] if task_params.get("secrets") is not None else None)
task_params["ports"] = ([
Port(**v) for v in task_params.get("ports")
] if task_params.get("ports") is not None else None)
task_params["volume_mounts"] = ([
VolumeMount(**v) for v in task_params.get("volume_mounts")
] if task_params.get("volume_mounts") is not None else None)
task_params["volumes"] = ([
Volume(**v) for v in task_params.get("volumes")
] if task_params.get("volumes") is not None else None)
task_params["pod_runtime_info_envs"] = ([
PodRuntimeInfoEnv(**v)
for v in task_params.get("pod_runtime_info_envs")
] if task_params.get("pod_runtime_info_envs") is not None else
None)
task_params["full_pod_spec"] = (
V1Pod(**task_params.get("full_pod_spec"))
if task_params.get("full_pod_spec") is not None else None)
task_params["init_containers"] = ([
V1Container(**v)
for v in task_params.get("init_containers")
] if task_params.get("init_containers") is not None else None)
if operator_obj == DockerOperator:
if task_params.get("environment") is not None:
task_params["environment"] = {
k: os.environ.get(v, v)
for k, v in task_params["environment"].items()
}
if operator_obj == EcsOperator:
for c in task_params["overrides"]["containerOverrides"]:
if c.get('environment') is not None:
for env in c['environment']:
env['value'] = os.environ.get(
env['value'], env['value'])
if 'ECS_SECURITY_GROUPS' in af_vars and 'network_configuration' in task_params:
task_params["network_configuration"]["awsvpcConfiguration"]['securityGroups'] \
= af_vars['ECS_SECURITY_GROUPS']
if 'ECS_SUBNETS' in af_vars and 'network_configuration' in task_params:
task_params['network_configuration'][
"awsvpcConfiguration"]["subnets"] = af_vars[
"ECS_SUBNETS"]
if af_vars.get('ECS_CLUSTER'):
task_params['cluster'] = af_vars["ECS_CLUSTER"]
task_params['task_definition'] = (
af_vars.get('ECS_CLUSTER') + '_' +
task_params['task_definition']).lower()
task_params['awslogs_group'] = \
task_params['awslogs_group'] + '/' + af_vars.get('ECS_CLUSTER').lower()
if utils.check_dict_key(task_params, "execution_timeout_secs"):
task_params["execution_timeout"]: timedelta = timedelta(
seconds=task_params["execution_timeout_secs"])
del task_params["execution_timeout_secs"]
if utils.check_dict_key(task_params, "sla_secs"):
task_params["sla"]: timedelta = timedelta(
seconds=task_params["sla_secs"])
del task_params["sla_secs"]
if utils.check_dict_key(task_params, "execution_delta_secs"):
task_params["execution_delta"]: timedelta = timedelta(
seconds=task_params["execution_delta_secs"])
del task_params["execution_delta_secs"]
if utils.check_dict_key(
task_params,
"execution_date_fn_name") and utils.check_dict_key(
task_params, "execution_date_fn_file"):
task_params[
"execution_date_fn"]: Callable = utils.get_python_callable(
task_params["execution_date_fn_name"],
task_params["execution_date_fn_file"],
)
del task_params["execution_date_fn_name"]
del task_params["execution_date_fn_file"]
# on_execute_callback is an Airflow 2.0 feature
if utils.check_dict_key(
task_params, "on_execute_callback"
) and version.parse(AIRFLOW_VERSION) >= version.parse("2.0.0"):
task_params["on_execute_callback"]: Callable = import_string(
task_params["on_execute_callback"])
if utils.check_dict_key(task_params, "on_failure_callback"):
task_params["on_failure_callback"]: Callable = import_string(
task_params["on_failure_callback"])
if utils.check_dict_key(task_params, "on_success_callback"):
task_params["on_success_callback"]: Callable = import_string(
task_params["on_success_callback"])
if utils.check_dict_key(task_params, "on_retry_callback"):
task_params["on_retry_callback"]: Callable = import_string(
task_params["on_retry_callback"])
# use variables as arguments on operator
if utils.check_dict_key(task_params, "variables_as_arguments"):
variables: List[Dict[str, str]] = task_params.get(
"variables_as_arguments")
for variable in variables:
if Variable.get(variable["variable"],
default_var=None) is not None:
task_params[variable["attribute"]] = Variable.get(
variable["variable"], default_var=None)
del task_params["variables_as_arguments"]
# use variables as arguments on operator
if utils.check_dict_key(task_params, "af_vars_as_arguments"):
variables: List[Dict[str, str]] = task_params.get(
"af_vars_as_arguments")
for variable in variables:
if af_vars.get(variable["variable"], None) is not None:
task_params[variable["attribute"]] = af_vars.get(
variable["variable"], None)
del task_params["af_vars_as_arguments"]
task: BaseOperator = operator_obj(**task_params)
except Exception as err:
raise Exception(f"Failed to create {operator_obj} task") from err
return task
