machinelearningiface

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Published: Nov 20, 2024 License: Apache-2.0, Apache-2.0 Imports: 3 Imported by: 0

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Overview

Package machinelearningiface provides an interface to enable mocking the Amazon Machine Learning service client for testing your code.

It is important to note that this interface will have breaking changes when the service model is updated and adds new API operations, paginators, and waiters.

Index

Constants

This section is empty.

Variables

This section is empty.

Functions

This section is empty.

Types

type MachineLearningAPI

type MachineLearningAPI interface {
	AddTags(*machinelearning.AddTagsInput) (*machinelearning.AddTagsOutput, error)
	AddTagsWithContext(aws.Context, *machinelearning.AddTagsInput, ...request.Option) (*machinelearning.AddTagsOutput, error)
	AddTagsRequest(*machinelearning.AddTagsInput) (*request.Request, *machinelearning.AddTagsOutput)

	CreateBatchPrediction(*machinelearning.CreateBatchPredictionInput) (*machinelearning.CreateBatchPredictionOutput, error)
	CreateBatchPredictionWithContext(aws.Context, *machinelearning.CreateBatchPredictionInput, ...request.Option) (*machinelearning.CreateBatchPredictionOutput, error)
	CreateBatchPredictionRequest(*machinelearning.CreateBatchPredictionInput) (*request.Request, *machinelearning.CreateBatchPredictionOutput)

	CreateDataSourceFromRDS(*machinelearning.CreateDataSourceFromRDSInput) (*machinelearning.CreateDataSourceFromRDSOutput, error)
	CreateDataSourceFromRDSWithContext(aws.Context, *machinelearning.CreateDataSourceFromRDSInput, ...request.Option) (*machinelearning.CreateDataSourceFromRDSOutput, error)
	CreateDataSourceFromRDSRequest(*machinelearning.CreateDataSourceFromRDSInput) (*request.Request, *machinelearning.CreateDataSourceFromRDSOutput)

	CreateDataSourceFromRedshift(*machinelearning.CreateDataSourceFromRedshiftInput) (*machinelearning.CreateDataSourceFromRedshiftOutput, error)
	CreateDataSourceFromRedshiftWithContext(aws.Context, *machinelearning.CreateDataSourceFromRedshiftInput, ...request.Option) (*machinelearning.CreateDataSourceFromRedshiftOutput, error)
	CreateDataSourceFromRedshiftRequest(*machinelearning.CreateDataSourceFromRedshiftInput) (*request.Request, *machinelearning.CreateDataSourceFromRedshiftOutput)

	CreateDataSourceFromS3(*machinelearning.CreateDataSourceFromS3Input) (*machinelearning.CreateDataSourceFromS3Output, error)
	CreateDataSourceFromS3WithContext(aws.Context, *machinelearning.CreateDataSourceFromS3Input, ...request.Option) (*machinelearning.CreateDataSourceFromS3Output, error)
	CreateDataSourceFromS3Request(*machinelearning.CreateDataSourceFromS3Input) (*request.Request, *machinelearning.CreateDataSourceFromS3Output)

	CreateEvaluation(*machinelearning.CreateEvaluationInput) (*machinelearning.CreateEvaluationOutput, error)
	CreateEvaluationWithContext(aws.Context, *machinelearning.CreateEvaluationInput, ...request.Option) (*machinelearning.CreateEvaluationOutput, error)
	CreateEvaluationRequest(*machinelearning.CreateEvaluationInput) (*request.Request, *machinelearning.CreateEvaluationOutput)

	CreateMLModel(*machinelearning.CreateMLModelInput) (*machinelearning.CreateMLModelOutput, error)
	CreateMLModelWithContext(aws.Context, *machinelearning.CreateMLModelInput, ...request.Option) (*machinelearning.CreateMLModelOutput, error)
	CreateMLModelRequest(*machinelearning.CreateMLModelInput) (*request.Request, *machinelearning.CreateMLModelOutput)

	CreateRealtimeEndpoint(*machinelearning.CreateRealtimeEndpointInput) (*machinelearning.CreateRealtimeEndpointOutput, error)
	CreateRealtimeEndpointWithContext(aws.Context, *machinelearning.CreateRealtimeEndpointInput, ...request.Option) (*machinelearning.CreateRealtimeEndpointOutput, error)
	CreateRealtimeEndpointRequest(*machinelearning.CreateRealtimeEndpointInput) (*request.Request, *machinelearning.CreateRealtimeEndpointOutput)

	DeleteBatchPrediction(*machinelearning.DeleteBatchPredictionInput) (*machinelearning.DeleteBatchPredictionOutput, error)
	DeleteBatchPredictionWithContext(aws.Context, *machinelearning.DeleteBatchPredictionInput, ...request.Option) (*machinelearning.DeleteBatchPredictionOutput, error)
	DeleteBatchPredictionRequest(*machinelearning.DeleteBatchPredictionInput) (*request.Request, *machinelearning.DeleteBatchPredictionOutput)

	DeleteDataSource(*machinelearning.DeleteDataSourceInput) (*machinelearning.DeleteDataSourceOutput, error)
	DeleteDataSourceWithContext(aws.Context, *machinelearning.DeleteDataSourceInput, ...request.Option) (*machinelearning.DeleteDataSourceOutput, error)
	DeleteDataSourceRequest(*machinelearning.DeleteDataSourceInput) (*request.Request, *machinelearning.DeleteDataSourceOutput)

	DeleteEvaluation(*machinelearning.DeleteEvaluationInput) (*machinelearning.DeleteEvaluationOutput, error)
	DeleteEvaluationWithContext(aws.Context, *machinelearning.DeleteEvaluationInput, ...request.Option) (*machinelearning.DeleteEvaluationOutput, error)
	DeleteEvaluationRequest(*machinelearning.DeleteEvaluationInput) (*request.Request, *machinelearning.DeleteEvaluationOutput)

	DeleteMLModel(*machinelearning.DeleteMLModelInput) (*machinelearning.DeleteMLModelOutput, error)
	DeleteMLModelWithContext(aws.Context, *machinelearning.DeleteMLModelInput, ...request.Option) (*machinelearning.DeleteMLModelOutput, error)
	DeleteMLModelRequest(*machinelearning.DeleteMLModelInput) (*request.Request, *machinelearning.DeleteMLModelOutput)

	DeleteRealtimeEndpoint(*machinelearning.DeleteRealtimeEndpointInput) (*machinelearning.DeleteRealtimeEndpointOutput, error)
	DeleteRealtimeEndpointWithContext(aws.Context, *machinelearning.DeleteRealtimeEndpointInput, ...request.Option) (*machinelearning.DeleteRealtimeEndpointOutput, error)
	DeleteRealtimeEndpointRequest(*machinelearning.DeleteRealtimeEndpointInput) (*request.Request, *machinelearning.DeleteRealtimeEndpointOutput)

	DeleteTags(*machinelearning.DeleteTagsInput) (*machinelearning.DeleteTagsOutput, error)
	DeleteTagsWithContext(aws.Context, *machinelearning.DeleteTagsInput, ...request.Option) (*machinelearning.DeleteTagsOutput, error)
	DeleteTagsRequest(*machinelearning.DeleteTagsInput) (*request.Request, *machinelearning.DeleteTagsOutput)

	DescribeBatchPredictions(*machinelearning.DescribeBatchPredictionsInput) (*machinelearning.DescribeBatchPredictionsOutput, error)
	DescribeBatchPredictionsWithContext(aws.Context, *machinelearning.DescribeBatchPredictionsInput, ...request.Option) (*machinelearning.DescribeBatchPredictionsOutput, error)
	DescribeBatchPredictionsRequest(*machinelearning.DescribeBatchPredictionsInput) (*request.Request, *machinelearning.DescribeBatchPredictionsOutput)

	DescribeBatchPredictionsPages(*machinelearning.DescribeBatchPredictionsInput, func(*machinelearning.DescribeBatchPredictionsOutput, bool) bool) error
	DescribeBatchPredictionsPagesWithContext(aws.Context, *machinelearning.DescribeBatchPredictionsInput, func(*machinelearning.DescribeBatchPredictionsOutput, bool) bool, ...request.Option) error

	DescribeDataSources(*machinelearning.DescribeDataSourcesInput) (*machinelearning.DescribeDataSourcesOutput, error)
	DescribeDataSourcesWithContext(aws.Context, *machinelearning.DescribeDataSourcesInput, ...request.Option) (*machinelearning.DescribeDataSourcesOutput, error)
	DescribeDataSourcesRequest(*machinelearning.DescribeDataSourcesInput) (*request.Request, *machinelearning.DescribeDataSourcesOutput)

	DescribeDataSourcesPages(*machinelearning.DescribeDataSourcesInput, func(*machinelearning.DescribeDataSourcesOutput, bool) bool) error
	DescribeDataSourcesPagesWithContext(aws.Context, *machinelearning.DescribeDataSourcesInput, func(*machinelearning.DescribeDataSourcesOutput, bool) bool, ...request.Option) error

	DescribeEvaluations(*machinelearning.DescribeEvaluationsInput) (*machinelearning.DescribeEvaluationsOutput, error)
	DescribeEvaluationsWithContext(aws.Context, *machinelearning.DescribeEvaluationsInput, ...request.Option) (*machinelearning.DescribeEvaluationsOutput, error)
	DescribeEvaluationsRequest(*machinelearning.DescribeEvaluationsInput) (*request.Request, *machinelearning.DescribeEvaluationsOutput)

	DescribeEvaluationsPages(*machinelearning.DescribeEvaluationsInput, func(*machinelearning.DescribeEvaluationsOutput, bool) bool) error
	DescribeEvaluationsPagesWithContext(aws.Context, *machinelearning.DescribeEvaluationsInput, func(*machinelearning.DescribeEvaluationsOutput, bool) bool, ...request.Option) error

	DescribeMLModels(*machinelearning.DescribeMLModelsInput) (*machinelearning.DescribeMLModelsOutput, error)
	DescribeMLModelsWithContext(aws.Context, *machinelearning.DescribeMLModelsInput, ...request.Option) (*machinelearning.DescribeMLModelsOutput, error)
	DescribeMLModelsRequest(*machinelearning.DescribeMLModelsInput) (*request.Request, *machinelearning.DescribeMLModelsOutput)

	DescribeMLModelsPages(*machinelearning.DescribeMLModelsInput, func(*machinelearning.DescribeMLModelsOutput, bool) bool) error
	DescribeMLModelsPagesWithContext(aws.Context, *machinelearning.DescribeMLModelsInput, func(*machinelearning.DescribeMLModelsOutput, bool) bool, ...request.Option) error

	DescribeTags(*machinelearning.DescribeTagsInput) (*machinelearning.DescribeTagsOutput, error)
	DescribeTagsWithContext(aws.Context, *machinelearning.DescribeTagsInput, ...request.Option) (*machinelearning.DescribeTagsOutput, error)
	DescribeTagsRequest(*machinelearning.DescribeTagsInput) (*request.Request, *machinelearning.DescribeTagsOutput)

	GetBatchPrediction(*machinelearning.GetBatchPredictionInput) (*machinelearning.GetBatchPredictionOutput, error)
	GetBatchPredictionWithContext(aws.Context, *machinelearning.GetBatchPredictionInput, ...request.Option) (*machinelearning.GetBatchPredictionOutput, error)
	GetBatchPredictionRequest(*machinelearning.GetBatchPredictionInput) (*request.Request, *machinelearning.GetBatchPredictionOutput)

	GetDataSource(*machinelearning.GetDataSourceInput) (*machinelearning.GetDataSourceOutput, error)
	GetDataSourceWithContext(aws.Context, *machinelearning.GetDataSourceInput, ...request.Option) (*machinelearning.GetDataSourceOutput, error)
	GetDataSourceRequest(*machinelearning.GetDataSourceInput) (*request.Request, *machinelearning.GetDataSourceOutput)

	GetEvaluation(*machinelearning.GetEvaluationInput) (*machinelearning.GetEvaluationOutput, error)
	GetEvaluationWithContext(aws.Context, *machinelearning.GetEvaluationInput, ...request.Option) (*machinelearning.GetEvaluationOutput, error)
	GetEvaluationRequest(*machinelearning.GetEvaluationInput) (*request.Request, *machinelearning.GetEvaluationOutput)

	GetMLModel(*machinelearning.GetMLModelInput) (*machinelearning.GetMLModelOutput, error)
	GetMLModelWithContext(aws.Context, *machinelearning.GetMLModelInput, ...request.Option) (*machinelearning.GetMLModelOutput, error)
	GetMLModelRequest(*machinelearning.GetMLModelInput) (*request.Request, *machinelearning.GetMLModelOutput)

	Predict(*machinelearning.PredictInput) (*machinelearning.PredictOutput, error)
	PredictWithContext(aws.Context, *machinelearning.PredictInput, ...request.Option) (*machinelearning.PredictOutput, error)
	PredictRequest(*machinelearning.PredictInput) (*request.Request, *machinelearning.PredictOutput)

	UpdateBatchPrediction(*machinelearning.UpdateBatchPredictionInput) (*machinelearning.UpdateBatchPredictionOutput, error)
	UpdateBatchPredictionWithContext(aws.Context, *machinelearning.UpdateBatchPredictionInput, ...request.Option) (*machinelearning.UpdateBatchPredictionOutput, error)
	UpdateBatchPredictionRequest(*machinelearning.UpdateBatchPredictionInput) (*request.Request, *machinelearning.UpdateBatchPredictionOutput)

	UpdateDataSource(*machinelearning.UpdateDataSourceInput) (*machinelearning.UpdateDataSourceOutput, error)
	UpdateDataSourceWithContext(aws.Context, *machinelearning.UpdateDataSourceInput, ...request.Option) (*machinelearning.UpdateDataSourceOutput, error)
	UpdateDataSourceRequest(*machinelearning.UpdateDataSourceInput) (*request.Request, *machinelearning.UpdateDataSourceOutput)

	UpdateEvaluation(*machinelearning.UpdateEvaluationInput) (*machinelearning.UpdateEvaluationOutput, error)
	UpdateEvaluationWithContext(aws.Context, *machinelearning.UpdateEvaluationInput, ...request.Option) (*machinelearning.UpdateEvaluationOutput, error)
	UpdateEvaluationRequest(*machinelearning.UpdateEvaluationInput) (*request.Request, *machinelearning.UpdateEvaluationOutput)

	UpdateMLModel(*machinelearning.UpdateMLModelInput) (*machinelearning.UpdateMLModelOutput, error)
	UpdateMLModelWithContext(aws.Context, *machinelearning.UpdateMLModelInput, ...request.Option) (*machinelearning.UpdateMLModelOutput, error)
	UpdateMLModelRequest(*machinelearning.UpdateMLModelInput) (*request.Request, *machinelearning.UpdateMLModelOutput)

	WaitUntilBatchPredictionAvailable(*machinelearning.DescribeBatchPredictionsInput) error
	WaitUntilBatchPredictionAvailableWithContext(aws.Context, *machinelearning.DescribeBatchPredictionsInput, ...request.WaiterOption) error

	WaitUntilDataSourceAvailable(*machinelearning.DescribeDataSourcesInput) error
	WaitUntilDataSourceAvailableWithContext(aws.Context, *machinelearning.DescribeDataSourcesInput, ...request.WaiterOption) error

	WaitUntilEvaluationAvailable(*machinelearning.DescribeEvaluationsInput) error
	WaitUntilEvaluationAvailableWithContext(aws.Context, *machinelearning.DescribeEvaluationsInput, ...request.WaiterOption) error

	WaitUntilMLModelAvailable(*machinelearning.DescribeMLModelsInput) error
	WaitUntilMLModelAvailableWithContext(aws.Context, *machinelearning.DescribeMLModelsInput, ...request.WaiterOption) error
}

MachineLearningAPI provides an interface to enable mocking the machinelearning.MachineLearning service client's API operation, paginators, and waiters. This make unit testing your code that calls out to the SDK's service client's calls easier.

The best way to use this interface is so the SDK's service client's calls can be stubbed out for unit testing your code with the SDK without needing to inject custom request handlers into the SDK's request pipeline.

// myFunc uses an SDK service client to make a request to
// Amazon Machine Learning.
func myFunc(svc machinelearningiface.MachineLearningAPI) bool {
    // Make svc.AddTags request
}

func main() {
    sess := session.New()
    svc := machinelearning.New(sess)

    myFunc(svc)
}

In your _test.go file:

// Define a mock struct to be used in your unit tests of myFunc.
type mockMachineLearningClient struct {
    machinelearningiface.MachineLearningAPI
}
func (m *mockMachineLearningClient) AddTags(input *machinelearning.AddTagsInput) (*machinelearning.AddTagsOutput, error) {
    // mock response/functionality
}

func TestMyFunc(t *testing.T) {
    // Setup Test
    mockSvc := &mockMachineLearningClient{}

    myfunc(mockSvc)

    // Verify myFunc's functionality
}

It is important to note that this interface will have breaking changes when the service model is updated and adds new API operations, paginators, and waiters. Its suggested to use the pattern above for testing, or using tooling to generate mocks to satisfy the interfaces.

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