machinelearningiface

Documentation

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

• type MachineLearningAPI

Types

type MachineLearningAPI

type MachineLearningAPI interface {
	AddTagsRequest(*machinelearning.AddTagsInput) (*request.Request, *machinelearning.AddTagsOutput)

	AddTags(*machinelearning.AddTagsInput) (*machinelearning.AddTagsOutput, error)

	CreateBatchPredictionRequest(*machinelearning.CreateBatchPredictionInput) (*request.Request, *machinelearning.CreateBatchPredictionOutput)

	CreateBatchPrediction(*machinelearning.CreateBatchPredictionInput) (*machinelearning.CreateBatchPredictionOutput, error)

	CreateDataSourceFromRDSRequest(*machinelearning.CreateDataSourceFromRDSInput) (*request.Request, *machinelearning.CreateDataSourceFromRDSOutput)

	CreateDataSourceFromRDS(*machinelearning.CreateDataSourceFromRDSInput) (*machinelearning.CreateDataSourceFromRDSOutput, error)

	CreateDataSourceFromRedshiftRequest(*machinelearning.CreateDataSourceFromRedshiftInput) (*request.Request, *machinelearning.CreateDataSourceFromRedshiftOutput)

	CreateDataSourceFromRedshift(*machinelearning.CreateDataSourceFromRedshiftInput) (*machinelearning.CreateDataSourceFromRedshiftOutput, error)

	CreateDataSourceFromS3Request(*machinelearning.CreateDataSourceFromS3Input) (*request.Request, *machinelearning.CreateDataSourceFromS3Output)

	CreateDataSourceFromS3(*machinelearning.CreateDataSourceFromS3Input) (*machinelearning.CreateDataSourceFromS3Output, error)

	CreateEvaluationRequest(*machinelearning.CreateEvaluationInput) (*request.Request, *machinelearning.CreateEvaluationOutput)

	CreateEvaluation(*machinelearning.CreateEvaluationInput) (*machinelearning.CreateEvaluationOutput, error)

	CreateMLModelRequest(*machinelearning.CreateMLModelInput) (*request.Request, *machinelearning.CreateMLModelOutput)

	CreateMLModel(*machinelearning.CreateMLModelInput) (*machinelearning.CreateMLModelOutput, error)

	CreateRealtimeEndpointRequest(*machinelearning.CreateRealtimeEndpointInput) (*request.Request, *machinelearning.CreateRealtimeEndpointOutput)

	CreateRealtimeEndpoint(*machinelearning.CreateRealtimeEndpointInput) (*machinelearning.CreateRealtimeEndpointOutput, error)

	DeleteBatchPredictionRequest(*machinelearning.DeleteBatchPredictionInput) (*request.Request, *machinelearning.DeleteBatchPredictionOutput)

	DeleteBatchPrediction(*machinelearning.DeleteBatchPredictionInput) (*machinelearning.DeleteBatchPredictionOutput, error)

	DeleteDataSourceRequest(*machinelearning.DeleteDataSourceInput) (*request.Request, *machinelearning.DeleteDataSourceOutput)

	DeleteDataSource(*machinelearning.DeleteDataSourceInput) (*machinelearning.DeleteDataSourceOutput, error)

	DeleteEvaluationRequest(*machinelearning.DeleteEvaluationInput) (*request.Request, *machinelearning.DeleteEvaluationOutput)

	DeleteEvaluation(*machinelearning.DeleteEvaluationInput) (*machinelearning.DeleteEvaluationOutput, error)

	DeleteMLModelRequest(*machinelearning.DeleteMLModelInput) (*request.Request, *machinelearning.DeleteMLModelOutput)

	DeleteMLModel(*machinelearning.DeleteMLModelInput) (*machinelearning.DeleteMLModelOutput, error)

	DeleteRealtimeEndpointRequest(*machinelearning.DeleteRealtimeEndpointInput) (*request.Request, *machinelearning.DeleteRealtimeEndpointOutput)

	DeleteRealtimeEndpoint(*machinelearning.DeleteRealtimeEndpointInput) (*machinelearning.DeleteRealtimeEndpointOutput, error)

	DeleteTagsRequest(*machinelearning.DeleteTagsInput) (*request.Request, *machinelearning.DeleteTagsOutput)

	DeleteTags(*machinelearning.DeleteTagsInput) (*machinelearning.DeleteTagsOutput, error)

	DescribeBatchPredictionsRequest(*machinelearning.DescribeBatchPredictionsInput) (*request.Request, *machinelearning.DescribeBatchPredictionsOutput)

	DescribeBatchPredictions(*machinelearning.DescribeBatchPredictionsInput) (*machinelearning.DescribeBatchPredictionsOutput, error)

	DescribeBatchPredictionsPages(*machinelearning.DescribeBatchPredictionsInput, func(*machinelearning.DescribeBatchPredictionsOutput, bool) bool) error

	DescribeDataSourcesRequest(*machinelearning.DescribeDataSourcesInput) (*request.Request, *machinelearning.DescribeDataSourcesOutput)

	DescribeDataSources(*machinelearning.DescribeDataSourcesInput) (*machinelearning.DescribeDataSourcesOutput, error)

	DescribeDataSourcesPages(*machinelearning.DescribeDataSourcesInput, func(*machinelearning.DescribeDataSourcesOutput, bool) bool) error

	DescribeEvaluationsRequest(*machinelearning.DescribeEvaluationsInput) (*request.Request, *machinelearning.DescribeEvaluationsOutput)

	DescribeEvaluations(*machinelearning.DescribeEvaluationsInput) (*machinelearning.DescribeEvaluationsOutput, error)

	DescribeEvaluationsPages(*machinelearning.DescribeEvaluationsInput, func(*machinelearning.DescribeEvaluationsOutput, bool) bool) error

	DescribeMLModelsRequest(*machinelearning.DescribeMLModelsInput) (*request.Request, *machinelearning.DescribeMLModelsOutput)

	DescribeMLModels(*machinelearning.DescribeMLModelsInput) (*machinelearning.DescribeMLModelsOutput, error)

	DescribeMLModelsPages(*machinelearning.DescribeMLModelsInput, func(*machinelearning.DescribeMLModelsOutput, bool) bool) error

	DescribeTagsRequest(*machinelearning.DescribeTagsInput) (*request.Request, *machinelearning.DescribeTagsOutput)

	DescribeTags(*machinelearning.DescribeTagsInput) (*machinelearning.DescribeTagsOutput, error)

	GetBatchPredictionRequest(*machinelearning.GetBatchPredictionInput) (*request.Request, *machinelearning.GetBatchPredictionOutput)

	GetBatchPrediction(*machinelearning.GetBatchPredictionInput) (*machinelearning.GetBatchPredictionOutput, error)

	GetDataSourceRequest(*machinelearning.GetDataSourceInput) (*request.Request, *machinelearning.GetDataSourceOutput)

	GetDataSource(*machinelearning.GetDataSourceInput) (*machinelearning.GetDataSourceOutput, error)

	GetEvaluationRequest(*machinelearning.GetEvaluationInput) (*request.Request, *machinelearning.GetEvaluationOutput)

	GetEvaluation(*machinelearning.GetEvaluationInput) (*machinelearning.GetEvaluationOutput, error)

	GetMLModelRequest(*machinelearning.GetMLModelInput) (*request.Request, *machinelearning.GetMLModelOutput)

	GetMLModel(*machinelearning.GetMLModelInput) (*machinelearning.GetMLModelOutput, error)

	PredictRequest(*machinelearning.PredictInput) (*request.Request, *machinelearning.PredictOutput)

	Predict(*machinelearning.PredictInput) (*machinelearning.PredictOutput, error)

	UpdateBatchPredictionRequest(*machinelearning.UpdateBatchPredictionInput) (*request.Request, *machinelearning.UpdateBatchPredictionOutput)

	UpdateBatchPrediction(*machinelearning.UpdateBatchPredictionInput) (*machinelearning.UpdateBatchPredictionOutput, error)

	UpdateDataSourceRequest(*machinelearning.UpdateDataSourceInput) (*request.Request, *machinelearning.UpdateDataSourceOutput)

	UpdateDataSource(*machinelearning.UpdateDataSourceInput) (*machinelearning.UpdateDataSourceOutput, error)

	UpdateEvaluationRequest(*machinelearning.UpdateEvaluationInput) (*request.Request, *machinelearning.UpdateEvaluationOutput)

	UpdateEvaluation(*machinelearning.UpdateEvaluationInput) (*machinelearning.UpdateEvaluationOutput, error)

	UpdateMLModelRequest(*machinelearning.UpdateMLModelInput) (*request.Request, *machinelearning.UpdateMLModelOutput)

	UpdateMLModel(*machinelearning.UpdateMLModelInput) (*machinelearning.UpdateMLModelOutput, error)

	WaitUntilBatchPredictionAvailable(*machinelearning.DescribeBatchPredictionsInput) error

	WaitUntilDataSourceAvailable(*machinelearning.DescribeDataSourcesInput) error

	WaitUntilEvaluationAvailable(*machinelearning.DescribeEvaluationsInput) error

	WaitUntilMLModelAvailable(*machinelearning.DescribeMLModelsInput) 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 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
}

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.