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Posted to commits@airflow.apache.org by GitBox <gi...@apache.org> on 2018/09/05 21:45:59 UTC

[GitHub] troychen728 commented on a change in pull request #3767: [AIRFLOW-2524]Add SageMaker Batch Inference

troychen728 commented on a change in pull request #3767: [AIRFLOW-2524]Add SageMaker Batch Inference
URL: https://github.com/apache/incubator-airflow/pull/3767#discussion_r215435820
 
 

 ##########
 File path: airflow/contrib/sensors/sagemaker_transform_sensor.py
 ##########
 @@ -0,0 +1,69 @@
+# -*- 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.
+
+from airflow.contrib.hooks.sagemaker_hook import SageMakerHook
+from airflow.contrib.sensors.sagemaker_base_sensor import SageMakerBaseSensor
+from airflow.utils.decorators import apply_defaults
+
+
+class SageMakerTransformSensor(SageMakerBaseSensor):
+    """
+    Asks for the state of the transform state until it reaches a terminal state.
+    The sensor will error if the job errors, throwing a AirflowException
+    containing the failure reason.
+
+    :param job_name: job_name of the transform job instance to check the state of
+    :type job_name: string
+    :param region_name: The AWS region_name
+    :type region_name: string
+    """
+
+    template_fields = ['job_name']
+    template_ext = ()
+
+    @apply_defaults
+    def __init__(self,
+                 job_name,
+                 region_name=None,
+                 *args,
+                 **kwargs):
+        super(SageMakerTransformSensor, self).__init__(*args, **kwargs)
+        self.job_name = job_name
+        self.region_name = region_name
+
+    def non_terminal_states(self):
 
 Review comment:
   I'm not so sure why should I or what difference does it make if I make this static. Can you shed a little bit light on this? Thanks. Also, I am sorry but I might not be able to give feedback to the comments very quickly, because I am really busy with school stuff these few days. 

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