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annotate env/lib/python3.7/site-packages/boto/datapipeline/layer1.py @ 2:6af9afd405e9 draft

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"planemo upload commit 0a63dd5f4d38a1f6944587f52a8cd79874177fc1"
author shellac
date Thu, 14 May 2020 14:56:58 -0400
parents 26e78fe6e8c4
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1 # Copyright (c) 2013 Amazon.com, Inc. or its affiliates. All Rights Reserved
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2 #
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3 # Permission is hereby granted, free of charge, to any person obtaining a
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4 # copy of this software and associated documentation files (the
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5 # "Software"), to deal in the Software without restriction, including
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6 # without limitation the rights to use, copy, modify, merge, publish, dis-
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7 # tribute, sublicense, and/or sell copies of the Software, and to permit
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8 # persons to whom the Software is furnished to do so, subject to the fol-
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9 # lowing conditions:
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10 #
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11 # The above copyright notice and this permission notice shall be included
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12 # in all copies or substantial portions of the Software.
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13 #
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14 # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
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15 # OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABIL-
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16 # ITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
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17 # SHALL THE AUTHOR BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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18 # WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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19 # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
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20 # IN THE SOFTWARE.
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21 #
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22
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23 import boto
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24 from boto.compat import json
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25 from boto.connection import AWSQueryConnection
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26 from boto.regioninfo import RegionInfo
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27 from boto.exception import JSONResponseError
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28 from boto.datapipeline import exceptions
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29
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30
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31 class DataPipelineConnection(AWSQueryConnection):
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32 """
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33 This is the AWS Data Pipeline API Reference . This guide provides
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34 descriptions and samples of the AWS Data Pipeline API.
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35
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36 AWS Data Pipeline is a web service that configures and manages a
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37 data-driven workflow called a pipeline. AWS Data Pipeline handles
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38 the details of scheduling and ensuring that data dependencies are
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39 met so your application can focus on processing the data.
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40
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41 The AWS Data Pipeline API implements two main sets of
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42 functionality. The first set of actions configure the pipeline in
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43 the web service. You call these actions to create a pipeline and
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44 define data sources, schedules, dependencies, and the transforms
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45 to be performed on the data.
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46
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47 The second set of actions are used by a task runner application
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48 that calls the AWS Data Pipeline API to receive the next task
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49 ready for processing. The logic for performing the task, such as
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50 querying the data, running data analysis, or converting the data
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51 from one format to another, is contained within the task runner.
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52 The task runner performs the task assigned to it by the web
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53 service, reporting progress to the web service as it does so. When
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54 the task is done, the task runner reports the final success or
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55 failure of the task to the web service.
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56
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57 AWS Data Pipeline provides an open-source implementation of a task
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58 runner called AWS Data Pipeline Task Runner. AWS Data Pipeline
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59 Task Runner provides logic for common data management scenarios,
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60 such as performing database queries and running data analysis
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61 using Amazon Elastic MapReduce (Amazon EMR). You can use AWS Data
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62 Pipeline Task Runner as your task runner, or you can write your
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63 own task runner to provide custom data management.
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64
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65 The AWS Data Pipeline API uses the Signature Version 4 protocol
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66 for signing requests. For more information about how to sign a
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67 request with this protocol, see `Signature Version 4 Signing
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68 Process`_. In the code examples in this reference, the Signature
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69 Version 4 Request parameters are represented as AuthParams.
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70 """
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71 APIVersion = "2012-10-29"
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72 DefaultRegionName = "us-east-1"
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73 DefaultRegionEndpoint = "datapipeline.us-east-1.amazonaws.com"
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74 ServiceName = "DataPipeline"
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75 TargetPrefix = "DataPipeline"
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76 ResponseError = JSONResponseError
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77
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78 _faults = {
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79 "PipelineDeletedException": exceptions.PipelineDeletedException,
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80 "InvalidRequestException": exceptions.InvalidRequestException,
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81 "TaskNotFoundException": exceptions.TaskNotFoundException,
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82 "PipelineNotFoundException": exceptions.PipelineNotFoundException,
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83 "InternalServiceError": exceptions.InternalServiceError,
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84 }
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85
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86 def __init__(self, **kwargs):
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87 region = kwargs.pop('region', None)
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88 if not region:
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89 region = RegionInfo(self, self.DefaultRegionName,
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90 self.DefaultRegionEndpoint)
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91 kwargs['host'] = region.endpoint
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92 super(DataPipelineConnection, self).__init__(**kwargs)
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93 self.region = region
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94
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95 def _required_auth_capability(self):
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96 return ['hmac-v4']
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97
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98 def activate_pipeline(self, pipeline_id):
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99 """
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100 Validates a pipeline and initiates processing. If the pipeline
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101 does not pass validation, activation fails.
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102
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103 Call this action to start processing pipeline tasks of a
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104 pipeline you've created using the CreatePipeline and
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105 PutPipelineDefinition actions. A pipeline cannot be modified
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106 after it has been successfully activated.
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107
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108 :type pipeline_id: string
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109 :param pipeline_id: The identifier of the pipeline to activate.
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110
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111 """
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112 params = {'pipelineId': pipeline_id, }
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113 return self.make_request(action='ActivatePipeline',
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114 body=json.dumps(params))
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115
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116 def create_pipeline(self, name, unique_id, description=None):
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117 """
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118 Creates a new empty pipeline. When this action succeeds, you
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119 can then use the PutPipelineDefinition action to populate the
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120 pipeline.
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121
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122 :type name: string
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123 :param name: The name of the new pipeline. You can use the same name
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124 for multiple pipelines associated with your AWS account, because
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125 AWS Data Pipeline assigns each new pipeline a unique pipeline
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126 identifier.
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127
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128 :type unique_id: string
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129 :param unique_id: A unique identifier that you specify. This identifier
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130 is not the same as the pipeline identifier assigned by AWS Data
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131 Pipeline. You are responsible for defining the format and ensuring
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132 the uniqueness of this identifier. You use this parameter to ensure
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133 idempotency during repeated calls to CreatePipeline. For example,
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134 if the first call to CreatePipeline does not return a clear
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135 success, you can pass in the same unique identifier and pipeline
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136 name combination on a subsequent call to CreatePipeline.
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137 CreatePipeline ensures that if a pipeline already exists with the
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138 same name and unique identifier, a new pipeline will not be
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139 created. Instead, you'll receive the pipeline identifier from the
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140 previous attempt. The uniqueness of the name and unique identifier
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141 combination is scoped to the AWS account or IAM user credentials.
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142
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143 :type description: string
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144 :param description: The description of the new pipeline.
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145
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146 """
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147 params = {'name': name, 'uniqueId': unique_id, }
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148 if description is not None:
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149 params['description'] = description
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150 return self.make_request(action='CreatePipeline',
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151 body=json.dumps(params))
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152
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153 def delete_pipeline(self, pipeline_id):
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154 """
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155 Permanently deletes a pipeline, its pipeline definition and
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156 its run history. You cannot query or restore a deleted
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157 pipeline. AWS Data Pipeline will attempt to cancel instances
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158 associated with the pipeline that are currently being
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159 processed by task runners. Deleting a pipeline cannot be
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160 undone.
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161
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162 To temporarily pause a pipeline instead of deleting it, call
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163 SetStatus with the status set to Pause on individual
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164 components. Components that are paused by SetStatus can be
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165 resumed.
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166
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167 :type pipeline_id: string
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168 :param pipeline_id: The identifier of the pipeline to be deleted.
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169
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170 """
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171 params = {'pipelineId': pipeline_id, }
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172 return self.make_request(action='DeletePipeline',
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173 body=json.dumps(params))
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174
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175 def describe_objects(self, object_ids, pipeline_id, marker=None,
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176 evaluate_expressions=None):
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177 """
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178 Returns the object definitions for a set of objects associated
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179 with the pipeline. Object definitions are composed of a set of
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180 fields that define the properties of the object.
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181
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182 :type pipeline_id: string
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183 :param pipeline_id: Identifier of the pipeline that contains the object
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184 definitions.
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185
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186 :type object_ids: list
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187 :param object_ids: Identifiers of the pipeline objects that contain the
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188 definitions to be described. You can pass as many as 25 identifiers
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189 in a single call to DescribeObjects.
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190
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191 :type evaluate_expressions: boolean
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192 :param evaluate_expressions: Indicates whether any expressions in the
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193 object should be evaluated when the object descriptions are
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194 returned.
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195
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196 :type marker: string
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197 :param marker: The starting point for the results to be returned. The
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198 first time you call DescribeObjects, this value should be empty. As
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199 long as the action returns `HasMoreResults` as `True`, you can call
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200 DescribeObjects again and pass the marker value from the response
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201 to retrieve the next set of results.
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202
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203 """
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204 params = {
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205 'pipelineId': pipeline_id,
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206 'objectIds': object_ids,
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207 }
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208 if evaluate_expressions is not None:
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209 params['evaluateExpressions'] = evaluate_expressions
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210 if marker is not None:
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211 params['marker'] = marker
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212 return self.make_request(action='DescribeObjects',
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213 body=json.dumps(params))
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214
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215 def describe_pipelines(self, pipeline_ids):
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216 """
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217 Retrieve metadata about one or more pipelines. The information
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218 retrieved includes the name of the pipeline, the pipeline
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219 identifier, its current state, and the user account that owns
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220 the pipeline. Using account credentials, you can retrieve
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221 metadata about pipelines that you or your IAM users have
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222 created. If you are using an IAM user account, you can
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223 retrieve metadata about only those pipelines you have read
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224 permission for.
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225
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226 To retrieve the full pipeline definition instead of metadata
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227 about the pipeline, call the GetPipelineDefinition action.
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228
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229 :type pipeline_ids: list
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230 :param pipeline_ids: Identifiers of the pipelines to describe. You can
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231 pass as many as 25 identifiers in a single call to
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232 DescribePipelines. You can obtain pipeline identifiers by calling
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233 ListPipelines.
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234
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235 """
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236 params = {'pipelineIds': pipeline_ids, }
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237 return self.make_request(action='DescribePipelines',
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238 body=json.dumps(params))
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239
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240 def evaluate_expression(self, pipeline_id, expression, object_id):
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241 """
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242 Evaluates a string in the context of a specified object. A
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243 task runner can use this action to evaluate SQL queries stored
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244 in Amazon S3.
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245
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246 :type pipeline_id: string
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247 :param pipeline_id: The identifier of the pipeline.
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248
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249 :type object_id: string
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250 :param object_id: The identifier of the object.
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251
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252 :type expression: string
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253 :param expression: The expression to evaluate.
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254
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255 """
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256 params = {
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257 'pipelineId': pipeline_id,
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258 'objectId': object_id,
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259 'expression': expression,
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260 }
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261 return self.make_request(action='EvaluateExpression',
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262 body=json.dumps(params))
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263
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264 def get_pipeline_definition(self, pipeline_id, version=None):
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265 """
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266 Returns the definition of the specified pipeline. You can call
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267 GetPipelineDefinition to retrieve the pipeline definition you
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268 provided using PutPipelineDefinition.
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269
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270 :type pipeline_id: string
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271 :param pipeline_id: The identifier of the pipeline.
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272
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273 :type version: string
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274 :param version: The version of the pipeline definition to retrieve.
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275 This parameter accepts the values `latest` (default) and `active`.
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276 Where `latest` indicates the last definition saved to the pipeline
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277 and `active` indicates the last definition of the pipeline that was
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278 activated.
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279
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280 """
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281 params = {'pipelineId': pipeline_id, }
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282 if version is not None:
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283 params['version'] = version
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284 return self.make_request(action='GetPipelineDefinition',
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285 body=json.dumps(params))
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286
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287 def list_pipelines(self, marker=None):
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288 """
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289 Returns a list of pipeline identifiers for all active
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290 pipelines. Identifiers are returned only for pipelines you
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291 have permission to access.
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292
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293 :type marker: string
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294 :param marker: The starting point for the results to be returned. The
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295 first time you call ListPipelines, this value should be empty. As
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296 long as the action returns `HasMoreResults` as `True`, you can call
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297 ListPipelines again and pass the marker value from the response to
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298 retrieve the next set of results.
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299
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300 """
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301 params = {}
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302 if marker is not None:
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303 params['marker'] = marker
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304 return self.make_request(action='ListPipelines',
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305 body=json.dumps(params))
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306
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307 def poll_for_task(self, worker_group, hostname=None,
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308 instance_identity=None):
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309 """
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310 Task runners call this action to receive a task to perform
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311 from AWS Data Pipeline. The task runner specifies which tasks
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312 it can perform by setting a value for the workerGroup
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313 parameter of the PollForTask call. The task returned by
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314 PollForTask may come from any of the pipelines that match the
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315 workerGroup value passed in by the task runner and that was
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316 launched using the IAM user credentials specified by the task
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317 runner.
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318
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319 If tasks are ready in the work queue, PollForTask returns a
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320 response immediately. If no tasks are available in the queue,
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321 PollForTask uses long-polling and holds on to a poll
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322 connection for up to a 90 seconds during which time the first
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323 newly scheduled task is handed to the task runner. To
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324 accomodate this, set the socket timeout in your task runner to
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325 90 seconds. The task runner should not call PollForTask again
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326 on the same `workerGroup` until it receives a response, and
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327 this may take up to 90 seconds.
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328
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329 :type worker_group: string
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330 :param worker_group: Indicates the type of task the task runner is
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331 configured to accept and process. The worker group is set as a
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332 field on objects in the pipeline when they are created. You can
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333 only specify a single value for `workerGroup` in the call to
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334 PollForTask. There are no wildcard values permitted in
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335 `workerGroup`, the string must be an exact, case-sensitive, match.
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336
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337 :type hostname: string
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338 :param hostname: The public DNS name of the calling task runner.
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339
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340 :type instance_identity: dict
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341 :param instance_identity: Identity information for the Amazon EC2
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342 instance that is hosting the task runner. You can get this value by
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343 calling the URI, `http://169.254.169.254/latest/meta-data/instance-
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344 id`, from the EC2 instance. For more information, go to `Instance
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345 Metadata`_ in the Amazon Elastic Compute Cloud User Guide. Passing
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346 in this value proves that your task runner is running on an EC2
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347 instance, and ensures the proper AWS Data Pipeline service charges
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348 are applied to your pipeline.
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349
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350 """
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351 params = {'workerGroup': worker_group, }
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352 if hostname is not None:
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353 params['hostname'] = hostname
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354 if instance_identity is not None:
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355 params['instanceIdentity'] = instance_identity
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356 return self.make_request(action='PollForTask',
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357 body=json.dumps(params))
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358
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359 def put_pipeline_definition(self, pipeline_objects, pipeline_id):
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360 """
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361 Adds tasks, schedules, and preconditions that control the
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362 behavior of the pipeline. You can use PutPipelineDefinition to
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363 populate a new pipeline or to update an existing pipeline that
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364 has not yet been activated.
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365
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366 PutPipelineDefinition also validates the configuration as it
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367 adds it to the pipeline. Changes to the pipeline are saved
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368 unless one of the following three validation errors exists in
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369 the pipeline.
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370
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371 #. An object is missing a name or identifier field.
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372 #. A string or reference field is empty.
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373 #. The number of objects in the pipeline exceeds the maximum
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374 allowed objects.
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375
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376
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377
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378 Pipeline object definitions are passed to the
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379 PutPipelineDefinition action and returned by the
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380 GetPipelineDefinition action.
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381
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382 :type pipeline_id: string
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383 :param pipeline_id: The identifier of the pipeline to be configured.
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384
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385 :type pipeline_objects: list
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386 :param pipeline_objects: The objects that define the pipeline. These
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387 will overwrite the existing pipeline definition.
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388
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389 """
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390 params = {
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391 'pipelineId': pipeline_id,
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392 'pipelineObjects': pipeline_objects,
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393 }
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394 return self.make_request(action='PutPipelineDefinition',
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395 body=json.dumps(params))
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396
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397 def query_objects(self, pipeline_id, sphere, marker=None, query=None,
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398 limit=None):
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399 """
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400 Queries a pipeline for the names of objects that match a
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401 specified set of conditions.
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402
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403 The objects returned by QueryObjects are paginated and then
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404 filtered by the value you set for query. This means the action
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405 may return an empty result set with a value set for marker. If
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406 `HasMoreResults` is set to `True`, you should continue to call
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407 QueryObjects, passing in the returned value for marker, until
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408 `HasMoreResults` returns `False`.
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409
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410 :type pipeline_id: string
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411 :param pipeline_id: Identifier of the pipeline to be queried for object
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412 names.
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413
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414 :type query: dict
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415 :param query: Query that defines the objects to be returned. The Query
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416 object can contain a maximum of ten selectors. The conditions in
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417 the query are limited to top-level String fields in the object.
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418 These filters can be applied to components, instances, and
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419 attempts.
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420
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421 :type sphere: string
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422 :param sphere: Specifies whether the query applies to components or
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423 instances. Allowable values: `COMPONENT`, `INSTANCE`, `ATTEMPT`.
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424
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425 :type marker: string
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426 :param marker: The starting point for the results to be returned. The
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427 first time you call QueryObjects, this value should be empty. As
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428 long as the action returns `HasMoreResults` as `True`, you can call
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429 QueryObjects again and pass the marker value from the response to
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430 retrieve the next set of results.
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431
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432 :type limit: integer
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433 :param limit: Specifies the maximum number of object names that
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434 QueryObjects will return in a single call. The default value is
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435 100.
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436
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437 """
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438 params = {'pipelineId': pipeline_id, 'sphere': sphere, }
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439 if query is not None:
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440 params['query'] = query
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441 if marker is not None:
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442 params['marker'] = marker
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443 if limit is not None:
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444 params['limit'] = limit
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445 return self.make_request(action='QueryObjects',
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446 body=json.dumps(params))
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447
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448 def report_task_progress(self, task_id):
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449 """
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450 Updates the AWS Data Pipeline service on the progress of the
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451 calling task runner. When the task runner is assigned a task,
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452 it should call ReportTaskProgress to acknowledge that it has
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453 the task within 2 minutes. If the web service does not recieve
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454 this acknowledgement within the 2 minute window, it will
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455 assign the task in a subsequent PollForTask call. After this
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456 initial acknowledgement, the task runner only needs to report
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457 progress every 15 minutes to maintain its ownership of the
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458 task. You can change this reporting time from 15 minutes by
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459 specifying a `reportProgressTimeout` field in your pipeline.
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460 If a task runner does not report its status after 5 minutes,
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461 AWS Data Pipeline will assume that the task runner is unable
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462 to process the task and will reassign the task in a subsequent
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463 response to PollForTask. task runners should call
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464 ReportTaskProgress every 60 seconds.
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465
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466 :type task_id: string
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467 :param task_id: Identifier of the task assigned to the task runner.
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468 This value is provided in the TaskObject that the service returns
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469 with the response for the PollForTask action.
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470
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471 """
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472 params = {'taskId': task_id, }
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473 return self.make_request(action='ReportTaskProgress',
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474 body=json.dumps(params))
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475
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476 def report_task_runner_heartbeat(self, taskrunner_id, worker_group=None,
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477 hostname=None):
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478 """
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479 Task runners call ReportTaskRunnerHeartbeat every 15 minutes
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480 to indicate that they are operational. In the case of AWS Data
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481 Pipeline Task Runner launched on a resource managed by AWS
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482 Data Pipeline, the web service can use this call to detect
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483 when the task runner application has failed and restart a new
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484 instance.
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485
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486 :type taskrunner_id: string
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487 :param taskrunner_id: The identifier of the task runner. This value
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488 should be unique across your AWS account. In the case of AWS Data
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489 Pipeline Task Runner launched on a resource managed by AWS Data
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490 Pipeline, the web service provides a unique identifier when it
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491 launches the application. If you have written a custom task runner,
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492 you should assign a unique identifier for the task runner.
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493
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494 :type worker_group: string
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495 :param worker_group: Indicates the type of task the task runner is
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496 configured to accept and process. The worker group is set as a
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497 field on objects in the pipeline when they are created. You can
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498 only specify a single value for `workerGroup` in the call to
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499 ReportTaskRunnerHeartbeat. There are no wildcard values permitted
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500 in `workerGroup`, the string must be an exact, case-sensitive,
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501 match.
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502
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503 :type hostname: string
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504 :param hostname: The public DNS name of the calling task runner.
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505
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506 """
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507 params = {'taskrunnerId': taskrunner_id, }
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508 if worker_group is not None:
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509 params['workerGroup'] = worker_group
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510 if hostname is not None:
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511 params['hostname'] = hostname
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512 return self.make_request(action='ReportTaskRunnerHeartbeat',
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513 body=json.dumps(params))
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514
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515 def set_status(self, object_ids, status, pipeline_id):
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516 """
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517 Requests that the status of an array of physical or logical
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diff changeset
518 pipeline objects be updated in the pipeline. This update may
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diff changeset
519 not occur immediately, but is eventually consistent. The
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diff changeset
520 status that can be set depends on the type of object.
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521
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522 :type pipeline_id: string
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523 :param pipeline_id: Identifies the pipeline that contains the objects.
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524
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525 :type object_ids: list
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526 :param object_ids: Identifies an array of objects. The corresponding
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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527 objects can be either physical or components, but not a mix of both
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528 types.
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diff changeset
529
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530 :type status: string
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531 :param status: Specifies the status to be set on all the objects in
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532 `objectIds`. For components, this can be either `PAUSE` or
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533 `RESUME`. For instances, this can be either `CANCEL`, `RERUN`, or
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534 `MARK_FINISHED`.
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535
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536 """
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537 params = {
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538 'pipelineId': pipeline_id,
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539 'objectIds': object_ids,
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540 'status': status,
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541 }
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542 return self.make_request(action='SetStatus',
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543 body=json.dumps(params))
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544
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545 def set_task_status(self, task_id, task_status, error_id=None,
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546 error_message=None, error_stack_trace=None):
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547 """
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diff changeset
548 Notifies AWS Data Pipeline that a task is completed and
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parents:
diff changeset
549 provides information about the final status. The task runner
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diff changeset
550 calls this action regardless of whether the task was
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diff changeset
551 sucessful. The task runner does not need to call SetTaskStatus
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parents:
diff changeset
552 for tasks that are canceled by the web service during a call
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parents:
diff changeset
553 to ReportTaskProgress.
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diff changeset
554
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555 :type task_id: string
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diff changeset
556 :param task_id: Identifies the task assigned to the task runner. This
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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diff changeset
557 value is set in the TaskObject that is returned by the PollForTask
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diff changeset
558 action.
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diff changeset
559
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diff changeset
560 :type task_status: string
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561 :param task_status: If `FINISHED`, the task successfully completed. If
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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diff changeset
562 `FAILED` the task ended unsuccessfully. The `FALSE` value is used
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diff changeset
563 by preconditions.
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diff changeset
564
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565 :type error_id: string
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566 :param error_id: If an error occurred during the task, this value
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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diff changeset
567 specifies an id value that represents the error. This value is set
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diff changeset
568 on the physical attempt object. It is used to display error
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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parents:
diff changeset
569 information to the user. It should not start with string "Service_"
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parents:
diff changeset
570 which is reserved by the system.
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571
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572 :type error_message: string
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diff changeset
573 :param error_message: If an error occurred during the task, this value
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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parents:
diff changeset
574 specifies a text description of the error. This value is set on the
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diff changeset
575 physical attempt object. It is used to display error information to
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diff changeset
576 the user. The web service does not parse this value.
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diff changeset
577
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578 :type error_stack_trace: string
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diff changeset
579 :param error_stack_trace: If an error occurred during the task, this
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diff changeset
580 value specifies the stack trace associated with the error. This
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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parents:
diff changeset
581 value is set on the physical attempt object. It is used to display
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parents:
diff changeset
582 error information to the user. The web service does not parse this
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diff changeset
583 value.
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584
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585 """
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diff changeset
586 params = {'taskId': task_id, 'taskStatus': task_status, }
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diff changeset
587 if error_id is not None:
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588 params['errorId'] = error_id
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diff changeset
589 if error_message is not None:
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diff changeset
590 params['errorMessage'] = error_message
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parents:
diff changeset
591 if error_stack_trace is not None:
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diff changeset
592 params['errorStackTrace'] = error_stack_trace
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diff changeset
593 return self.make_request(action='SetTaskStatus',
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diff changeset
594 body=json.dumps(params))
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diff changeset
595
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diff changeset
596 def validate_pipeline_definition(self, pipeline_objects, pipeline_id):
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parents:
diff changeset
597 """
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diff changeset
598 Tests the pipeline definition with a set of validation checks
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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parents:
diff changeset
599 to ensure that it is well formed and can run without error.
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diff changeset
600
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diff changeset
601 :type pipeline_id: string
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diff changeset
602 :param pipeline_id: Identifies the pipeline whose definition is to be
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diff changeset
603 validated.
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604
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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605 :type pipeline_objects: list
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diff changeset
606 :param pipeline_objects: A list of objects that define the pipeline
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parents:
diff changeset
607 changes to validate against the pipeline.
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608
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609 """
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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610 params = {
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611 'pipelineId': pipeline_id,
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diff changeset
612 'pipelineObjects': pipeline_objects,
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diff changeset
613 }
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614 return self.make_request(action='ValidatePipelineDefinition',
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diff changeset
615 body=json.dumps(params))
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diff changeset
616
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617 def make_request(self, action, body):
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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618 headers = {
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619 'X-Amz-Target': '%s.%s' % (self.TargetPrefix, action),
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620 'Host': self.region.endpoint,
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621 'Content-Type': 'application/x-amz-json-1.1',
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622 'Content-Length': str(len(body)),
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623 }
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624 http_request = self.build_base_http_request(
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625 method='POST', path='/', auth_path='/', params={},
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626 headers=headers, data=body)
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diff changeset
627 response = self._mexe(http_request, sender=None,
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628 override_num_retries=10)
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629 response_body = response.read().decode('utf-8')
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diff changeset
630 boto.log.debug(response_body)
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631 if response.status == 200:
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632 if response_body:
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633 return json.loads(response_body)
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634 else:
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635 json_body = json.loads(response_body)
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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636 fault_name = json_body.get('__type', None)
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diff changeset
637 exception_class = self._faults.get(fault_name, self.ResponseError)
26e78fe6e8c4 "planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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638 raise exception_class(response.status, response.reason,
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639 body=json_body)