view env/lib/python3.9/site-packages/boto/datapipeline/layer1.py @ 0:4f3585e2f14b draft default tip

"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"

# Copyright (c) 2013 Amazon.com, Inc. or its affiliates.  All Rights Reserved
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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)