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Unified Diff: tools/telemetry/third_party/gsutil/third_party/boto/boto/datapipeline/layer1.py

Issue 1260493004: Revert "Add gsutil 4.13 to telemetry/third_party" (Closed) Base URL: https://chromium.googlesource.com/chromium/src.git@master
Patch Set: Created 5 years, 5 months ago
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Index: tools/telemetry/third_party/gsutil/third_party/boto/boto/datapipeline/layer1.py
diff --git a/tools/telemetry/third_party/gsutil/third_party/boto/boto/datapipeline/layer1.py b/tools/telemetry/third_party/gsutil/third_party/boto/boto/datapipeline/layer1.py
deleted file mode 100644
index 028fd9d2e31f3865cdd4049828e4fb7a44cadc88..0000000000000000000000000000000000000000
--- a/tools/telemetry/third_party/gsutil/third_party/boto/boto/datapipeline/layer1.py
+++ /dev/null
@@ -1,639 +0,0 @@
-# Copyright (c) 2013 Amazon.com, Inc. or its affiliates. All Rights Reserved
-#
-# Permission is hereby granted, free of charge, to any person obtaining a
-# copy of this software and associated documentation files (the
-# "Software"), to deal in the Software without restriction, including
-# without limitation the rights to use, copy, modify, merge, publish, dis-
-# tribute, sublicense, and/or sell copies of the Software, and to permit
-# persons to whom the Software is furnished to do so, subject to the fol-
-# lowing conditions:
-#
-# The above copyright notice and this permission notice shall be included
-# in all copies or substantial portions of the Software.
-#
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
-# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABIL-
-# ITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
-# SHALL THE AUTHOR BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
-# WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
-# IN THE SOFTWARE.
-#
-
-import boto
-from boto.compat import json
-from boto.connection import AWSQueryConnection
-from boto.regioninfo import RegionInfo
-from boto.exception import JSONResponseError
-from boto.datapipeline import exceptions
-
-
-class DataPipelineConnection(AWSQueryConnection):
- """
- This is the AWS Data Pipeline API Reference . This guide provides
- descriptions and samples of the AWS Data Pipeline API.
-
- AWS Data Pipeline is a web service that configures and manages a
- data-driven workflow called a pipeline. AWS Data Pipeline handles
- the details of scheduling and ensuring that data dependencies are
- met so your application can focus on processing the data.
-
- The AWS Data Pipeline API implements two main sets of
- functionality. The first set of actions configure the pipeline in
- the web service. You call these actions to create a pipeline and
- define data sources, schedules, dependencies, and the transforms
- to be performed on the data.
-
- The second set of actions are used by a task runner application
- that calls the AWS Data Pipeline API to receive the next task
- ready for processing. The logic for performing the task, such as
- querying the data, running data analysis, or converting the data
- from one format to another, is contained within the task runner.
- The task runner performs the task assigned to it by the web
- service, reporting progress to the web service as it does so. When
- the task is done, the task runner reports the final success or
- failure of the task to the web service.
-
- AWS Data Pipeline provides an open-source implementation of a task
- runner called AWS Data Pipeline Task Runner. AWS Data Pipeline
- Task Runner provides logic for common data management scenarios,
- such as performing database queries and running data analysis
- using Amazon Elastic MapReduce (Amazon EMR). You can use AWS Data
- Pipeline Task Runner as your task runner, or you can write your
- own task runner to provide custom data management.
-
- The AWS Data Pipeline API uses the Signature Version 4 protocol
- for signing requests. For more information about how to sign a
- request with this protocol, see `Signature Version 4 Signing
- Process`_. In the code examples in this reference, the Signature
- Version 4 Request parameters are represented as AuthParams.
- """
- APIVersion = "2012-10-29"
- DefaultRegionName = "us-east-1"
- DefaultRegionEndpoint = "datapipeline.us-east-1.amazonaws.com"
- ServiceName = "DataPipeline"
- TargetPrefix = "DataPipeline"
- ResponseError = JSONResponseError
-
- _faults = {
- "PipelineDeletedException": exceptions.PipelineDeletedException,
- "InvalidRequestException": exceptions.InvalidRequestException,
- "TaskNotFoundException": exceptions.TaskNotFoundException,
- "PipelineNotFoundException": exceptions.PipelineNotFoundException,
- "InternalServiceError": exceptions.InternalServiceError,
- }
-
- def __init__(self, **kwargs):
- region = kwargs.pop('region', None)
- if not region:
- region = RegionInfo(self, self.DefaultRegionName,
- self.DefaultRegionEndpoint)
- kwargs['host'] = region.endpoint
- super(DataPipelineConnection, self).__init__(**kwargs)
- self.region = region
-
- def _required_auth_capability(self):
- return ['hmac-v4']
-
- def activate_pipeline(self, pipeline_id):
- """
- Validates a pipeline and initiates processing. If the pipeline
- does not pass validation, activation fails.
-
- Call this action to start processing pipeline tasks of a
- pipeline you've created using the CreatePipeline and
- PutPipelineDefinition actions. A pipeline cannot be modified
- after it has been successfully activated.
-
- :type pipeline_id: string
- :param pipeline_id: The identifier of the pipeline to activate.
-
- """
- params = {'pipelineId': pipeline_id, }
- return self.make_request(action='ActivatePipeline',
- body=json.dumps(params))
-
- def create_pipeline(self, name, unique_id, description=None):
- """
- Creates a new empty pipeline. When this action succeeds, you
- can then use the PutPipelineDefinition action to populate the
- pipeline.
-
- :type name: string
- :param name: The name of the new pipeline. You can use the same name
- for multiple pipelines associated with your AWS account, because
- AWS Data Pipeline assigns each new pipeline a unique pipeline
- identifier.
-
- :type unique_id: string
- :param unique_id: A unique identifier that you specify. This identifier
- is not the same as the pipeline identifier assigned by AWS Data
- Pipeline. You are responsible for defining the format and ensuring
- the uniqueness of this identifier. You use this parameter to ensure
- idempotency during repeated calls to CreatePipeline. For example,
- if the first call to CreatePipeline does not return a clear
- success, you can pass in the same unique identifier and pipeline
- name combination on a subsequent call to CreatePipeline.
- CreatePipeline ensures that if a pipeline already exists with the
- same name and unique identifier, a new pipeline will not be
- created. Instead, you'll receive the pipeline identifier from the
- previous attempt. The uniqueness of the name and unique identifier
- combination is scoped to the AWS account or IAM user credentials.
-
- :type description: string
- :param description: The description of the new pipeline.
-
- """
- params = {'name': name, 'uniqueId': unique_id, }
- if description is not None:
- params['description'] = description
- return self.make_request(action='CreatePipeline',
- body=json.dumps(params))
-
- def delete_pipeline(self, pipeline_id):
- """
- Permanently deletes a pipeline, its pipeline definition and
- its run history. You cannot query or restore a deleted
- pipeline. AWS Data Pipeline will attempt to cancel instances
- associated with the pipeline that are currently being
- processed by task runners. Deleting a pipeline cannot be
- undone.
-
- To temporarily pause a pipeline instead of deleting it, call
- SetStatus with the status set to Pause on individual
- components. Components that are paused by SetStatus can be
- resumed.
-
- :type pipeline_id: string
- :param pipeline_id: The identifier of the pipeline to be deleted.
-
- """
- params = {'pipelineId': pipeline_id, }
- return self.make_request(action='DeletePipeline',
- body=json.dumps(params))
-
- def describe_objects(self, object_ids, pipeline_id, marker=None,
- evaluate_expressions=None):
- """
- Returns the object definitions for a set of objects associated
- with the pipeline. Object definitions are composed of a set of
- fields that define the properties of the object.
-
- :type pipeline_id: string
- :param pipeline_id: Identifier of the pipeline that contains the object
- definitions.
-
- :type object_ids: list
- :param object_ids: Identifiers of the pipeline objects that contain the
- definitions to be described. You can pass as many as 25 identifiers
- in a single call to DescribeObjects.
-
- :type evaluate_expressions: boolean
- :param evaluate_expressions: Indicates whether any expressions in the
- object should be evaluated when the object descriptions are
- returned.
-
- :type marker: string
- :param marker: The starting point for the results to be returned. The
- first time you call DescribeObjects, this value should be empty. As
- long as the action returns `HasMoreResults` as `True`, you can call
- DescribeObjects again and pass the marker value from the response
- to retrieve the next set of results.
-
- """
- params = {
- 'pipelineId': pipeline_id,
- 'objectIds': object_ids,
- }
- if evaluate_expressions is not None:
- params['evaluateExpressions'] = evaluate_expressions
- if marker is not None:
- params['marker'] = marker
- return self.make_request(action='DescribeObjects',
- body=json.dumps(params))
-
- def describe_pipelines(self, pipeline_ids):
- """
- Retrieve metadata about one or more pipelines. The information
- retrieved includes the name of the pipeline, the pipeline
- identifier, its current state, and the user account that owns
- the pipeline. Using account credentials, you can retrieve
- metadata about pipelines that you or your IAM users have
- created. If you are using an IAM user account, you can
- retrieve metadata about only those pipelines you have read
- permission for.
-
- To retrieve the full pipeline definition instead of metadata
- about the pipeline, call the GetPipelineDefinition action.
-
- :type pipeline_ids: list
- :param pipeline_ids: Identifiers of the pipelines to describe. You can
- pass as many as 25 identifiers in a single call to
- DescribePipelines. You can obtain pipeline identifiers by calling
- ListPipelines.
-
- """
- params = {'pipelineIds': pipeline_ids, }
- return self.make_request(action='DescribePipelines',
- body=json.dumps(params))
-
- def evaluate_expression(self, pipeline_id, expression, object_id):
- """
- Evaluates a string in the context of a specified object. A
- task runner can use this action to evaluate SQL queries stored
- in Amazon S3.
-
- :type pipeline_id: string
- :param pipeline_id: The identifier of the pipeline.
-
- :type object_id: string
- :param object_id: The identifier of the object.
-
- :type expression: string
- :param expression: The expression to evaluate.
-
- """
- params = {
- 'pipelineId': pipeline_id,
- 'objectId': object_id,
- 'expression': expression,
- }
- return self.make_request(action='EvaluateExpression',
- body=json.dumps(params))
-
- def get_pipeline_definition(self, pipeline_id, version=None):
- """
- Returns the definition of the specified pipeline. You can call
- GetPipelineDefinition to retrieve the pipeline definition you
- provided using PutPipelineDefinition.
-
- :type pipeline_id: string
- :param pipeline_id: The identifier of the pipeline.
-
- :type version: string
- :param version: The version of the pipeline definition to retrieve.
- This parameter accepts the values `latest` (default) and `active`.
- Where `latest` indicates the last definition saved to the pipeline
- and `active` indicates the last definition of the pipeline that was
- activated.
-
- """
- params = {'pipelineId': pipeline_id, }
- if version is not None:
- params['version'] = version
- return self.make_request(action='GetPipelineDefinition',
- body=json.dumps(params))
-
- def list_pipelines(self, marker=None):
- """
- Returns a list of pipeline identifiers for all active
- pipelines. Identifiers are returned only for pipelines you
- have permission to access.
-
- :type marker: string
- :param marker: The starting point for the results to be returned. The
- first time you call ListPipelines, this value should be empty. As
- long as the action returns `HasMoreResults` as `True`, you can call
- ListPipelines again and pass the marker value from the response to
- retrieve the next set of results.
-
- """
- params = {}
- if marker is not None:
- params['marker'] = marker
- return self.make_request(action='ListPipelines',
- body=json.dumps(params))
-
- def poll_for_task(self, worker_group, hostname=None,
- instance_identity=None):
- """
- Task runners call this action to receive a task to perform
- from AWS Data Pipeline. The task runner specifies which tasks
- it can perform by setting a value for the workerGroup
- parameter of the PollForTask call. The task returned by
- PollForTask may come from any of the pipelines that match the
- workerGroup value passed in by the task runner and that was
- launched using the IAM user credentials specified by the task
- runner.
-
- If tasks are ready in the work queue, PollForTask returns a
- response immediately. If no tasks are available in the queue,
- PollForTask uses long-polling and holds on to a poll
- connection for up to a 90 seconds during which time the first
- newly scheduled task is handed to the task runner. To
- accomodate this, set the socket timeout in your task runner to
- 90 seconds. The task runner should not call PollForTask again
- on the same `workerGroup` until it receives a response, and
- this may take up to 90 seconds.
-
- :type worker_group: string
- :param worker_group: Indicates the type of task the task runner is
- configured to accept and process. The worker group is set as a
- field on objects in the pipeline when they are created. You can
- only specify a single value for `workerGroup` in the call to
- PollForTask. There are no wildcard values permitted in
- `workerGroup`, the string must be an exact, case-sensitive, match.
-
- :type hostname: string
- :param hostname: The public DNS name of the calling task runner.
-
- :type instance_identity: dict
- :param instance_identity: Identity information for the Amazon EC2
- instance that is hosting the task runner. You can get this value by
- calling the URI, `http://169.254.169.254/latest/meta-data/instance-
- id`, from the EC2 instance. For more information, go to `Instance
- Metadata`_ in the Amazon Elastic Compute Cloud User Guide. Passing
- in this value proves that your task runner is running on an EC2
- instance, and ensures the proper AWS Data Pipeline service charges
- are applied to your pipeline.
-
- """
- params = {'workerGroup': worker_group, }
- if hostname is not None:
- params['hostname'] = hostname
- if instance_identity is not None:
- params['instanceIdentity'] = instance_identity
- return self.make_request(action='PollForTask',
- body=json.dumps(params))
-
- def put_pipeline_definition(self, pipeline_objects, pipeline_id):
- """
- Adds tasks, schedules, and preconditions that control the
- behavior of the pipeline. You can use PutPipelineDefinition to
- populate a new pipeline or to update an existing pipeline that
- has not yet been activated.
-
- PutPipelineDefinition also validates the configuration as it
- adds it to the pipeline. Changes to the pipeline are saved
- unless one of the following three validation errors exists in
- the pipeline.
-
- #. An object is missing a name or identifier field.
- #. A string or reference field is empty.
- #. The number of objects in the pipeline exceeds the maximum
- allowed objects.
-
-
-
- Pipeline object definitions are passed to the
- PutPipelineDefinition action and returned by the
- GetPipelineDefinition action.
-
- :type pipeline_id: string
- :param pipeline_id: The identifier of the pipeline to be configured.
-
- :type pipeline_objects: list
- :param pipeline_objects: The objects that define the pipeline. These
- will overwrite the existing pipeline definition.
-
- """
- params = {
- 'pipelineId': pipeline_id,
- 'pipelineObjects': pipeline_objects,
- }
- return self.make_request(action='PutPipelineDefinition',
- body=json.dumps(params))
-
- def query_objects(self, pipeline_id, sphere, marker=None, query=None,
- limit=None):
- """
- Queries a pipeline for the names of objects that match a
- specified set of conditions.
-
- The objects returned by QueryObjects are paginated and then
- filtered by the value you set for query. This means the action
- may return an empty result set with a value set for marker. If
- `HasMoreResults` is set to `True`, you should continue to call
- QueryObjects, passing in the returned value for marker, until
- `HasMoreResults` returns `False`.
-
- :type pipeline_id: string
- :param pipeline_id: Identifier of the pipeline to be queried for object
- names.
-
- :type query: dict
- :param query: Query that defines the objects to be returned. The Query
- object can contain a maximum of ten selectors. The conditions in
- the query are limited to top-level String fields in the object.
- These filters can be applied to components, instances, and
- attempts.
-
- :type sphere: string
- :param sphere: Specifies whether the query applies to components or
- instances. Allowable values: `COMPONENT`, `INSTANCE`, `ATTEMPT`.
-
- :type marker: string
- :param marker: The starting point for the results to be returned. The
- first time you call QueryObjects, this value should be empty. As
- long as the action returns `HasMoreResults` as `True`, you can call
- QueryObjects again and pass the marker value from the response to
- retrieve the next set of results.
-
- :type limit: integer
- :param limit: Specifies the maximum number of object names that
- QueryObjects will return in a single call. The default value is
- 100.
-
- """
- params = {'pipelineId': pipeline_id, 'sphere': sphere, }
- if query is not None:
- params['query'] = query
- if marker is not None:
- params['marker'] = marker
- if limit is not None:
- params['limit'] = limit
- return self.make_request(action='QueryObjects',
- body=json.dumps(params))
-
- def report_task_progress(self, task_id):
- """
- Updates the AWS Data Pipeline service on the progress of the
- calling task runner. When the task runner is assigned a task,
- it should call ReportTaskProgress to acknowledge that it has
- the task within 2 minutes. If the web service does not recieve
- this acknowledgement within the 2 minute window, it will
- assign the task in a subsequent PollForTask call. After this
- initial acknowledgement, the task runner only needs to report
- progress every 15 minutes to maintain its ownership of the
- task. You can change this reporting time from 15 minutes by
- specifying a `reportProgressTimeout` field in your pipeline.
- If a task runner does not report its status after 5 minutes,
- AWS Data Pipeline will assume that the task runner is unable
- to process the task and will reassign the task in a subsequent
- response to PollForTask. task runners should call
- ReportTaskProgress every 60 seconds.
-
- :type task_id: string
- :param task_id: Identifier of the task assigned to the task runner.
- This value is provided in the TaskObject that the service returns
- with the response for the PollForTask action.
-
- """
- params = {'taskId': task_id, }
- return self.make_request(action='ReportTaskProgress',
- body=json.dumps(params))
-
- def report_task_runner_heartbeat(self, taskrunner_id, worker_group=None,
- hostname=None):
- """
- Task runners call ReportTaskRunnerHeartbeat every 15 minutes
- to indicate that they are operational. In the case of AWS Data
- Pipeline Task Runner launched on a resource managed by AWS
- Data Pipeline, the web service can use this call to detect
- when the task runner application has failed and restart a new
- instance.
-
- :type taskrunner_id: string
- :param taskrunner_id: The identifier of the task runner. This value
- should be unique across your AWS account. In the case of AWS Data
- Pipeline Task Runner launched on a resource managed by AWS Data
- Pipeline, the web service provides a unique identifier when it
- launches the application. If you have written a custom task runner,
- you should assign a unique identifier for the task runner.
-
- :type worker_group: string
- :param worker_group: Indicates the type of task the task runner is
- configured to accept and process. The worker group is set as a
- field on objects in the pipeline when they are created. You can
- only specify a single value for `workerGroup` in the call to
- ReportTaskRunnerHeartbeat. There are no wildcard values permitted
- in `workerGroup`, the string must be an exact, case-sensitive,
- match.
-
- :type hostname: string
- :param hostname: The public DNS name of the calling task runner.
-
- """
- params = {'taskrunnerId': taskrunner_id, }
- if worker_group is not None:
- params['workerGroup'] = worker_group
- if hostname is not None:
- params['hostname'] = hostname
- return self.make_request(action='ReportTaskRunnerHeartbeat',
- body=json.dumps(params))
-
- def set_status(self, object_ids, status, pipeline_id):
- """
- Requests that the status of an array of physical or logical
- pipeline objects be updated in the pipeline. This update may
- not occur immediately, but is eventually consistent. The
- status that can be set depends on the type of object.
-
- :type pipeline_id: string
- :param pipeline_id: Identifies the pipeline that contains the objects.
-
- :type object_ids: list
- :param object_ids: Identifies an array of objects. The corresponding
- objects can be either physical or components, but not a mix of both
- types.
-
- :type status: string
- :param status: Specifies the status to be set on all the objects in
- `objectIds`. For components, this can be either `PAUSE` or
- `RESUME`. For instances, this can be either `CANCEL`, `RERUN`, or
- `MARK_FINISHED`.
-
- """
- params = {
- 'pipelineId': pipeline_id,
- 'objectIds': object_ids,
- 'status': status,
- }
- return self.make_request(action='SetStatus',
- body=json.dumps(params))
-
- def set_task_status(self, task_id, task_status, error_id=None,
- error_message=None, error_stack_trace=None):
- """
- Notifies AWS Data Pipeline that a task is completed and
- provides information about the final status. The task runner
- calls this action regardless of whether the task was
- sucessful. The task runner does not need to call SetTaskStatus
- for tasks that are canceled by the web service during a call
- to ReportTaskProgress.
-
- :type task_id: string
- :param task_id: Identifies the task assigned to the task runner. This
- value is set in the TaskObject that is returned by the PollForTask
- action.
-
- :type task_status: string
- :param task_status: If `FINISHED`, the task successfully completed. If
- `FAILED` the task ended unsuccessfully. The `FALSE` value is used
- by preconditions.
-
- :type error_id: string
- :param error_id: If an error occurred during the task, this value
- specifies an id value that represents the error. This value is set
- on the physical attempt object. It is used to display error
- information to the user. It should not start with string "Service_"
- which is reserved by the system.
-
- :type error_message: string
- :param error_message: If an error occurred during the task, this value
- specifies a text description of the error. This value is set on the
- physical attempt object. It is used to display error information to
- the user. The web service does not parse this value.
-
- :type error_stack_trace: string
- :param error_stack_trace: If an error occurred during the task, this
- value specifies the stack trace associated with the error. This
- value is set on the physical attempt object. It is used to display
- error information to the user. The web service does not parse this
- value.
-
- """
- params = {'taskId': task_id, 'taskStatus': task_status, }
- if error_id is not None:
- params['errorId'] = error_id
- if error_message is not None:
- params['errorMessage'] = error_message
- if error_stack_trace is not None:
- params['errorStackTrace'] = error_stack_trace
- return self.make_request(action='SetTaskStatus',
- body=json.dumps(params))
-
- def validate_pipeline_definition(self, pipeline_objects, pipeline_id):
- """
- Tests the pipeline definition with a set of validation checks
- to ensure that it is well formed and can run without error.
-
- :type pipeline_id: string
- :param pipeline_id: Identifies the pipeline whose definition is to be
- validated.
-
- :type pipeline_objects: list
- :param pipeline_objects: A list of objects that define the pipeline
- changes to validate against the pipeline.
-
- """
- params = {
- 'pipelineId': pipeline_id,
- 'pipelineObjects': pipeline_objects,
- }
- return self.make_request(action='ValidatePipelineDefinition',
- body=json.dumps(params))
-
- def make_request(self, action, body):
- headers = {
- 'X-Amz-Target': '%s.%s' % (self.TargetPrefix, action),
- 'Host': self.region.endpoint,
- 'Content-Type': 'application/x-amz-json-1.1',
- 'Content-Length': str(len(body)),
- }
- http_request = self.build_base_http_request(
- method='POST', path='/', auth_path='/', params={},
- headers=headers, data=body)
- response = self._mexe(http_request, sender=None,
- override_num_retries=10)
- response_body = response.read().decode('utf-8')
- boto.log.debug(response_body)
- if response.status == 200:
- if response_body:
- return json.loads(response_body)
- else:
- json_body = json.loads(response_body)
- fault_name = json_body.get('__type', None)
- exception_class = self._faults.get(fault_name, self.ResponseError)
- raise exception_class(response.status, response.reason,
- body=json_body)

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