func ExampleMachineLearning_CreateMLModel() { sess, err := session.NewSession() if err != nil { fmt.Println("failed to create session,", err) return } svc := machinelearning.New(sess) params := &machinelearning.CreateMLModelInput{ MLModelId: aws.String("EntityId"), // Required MLModelType: aws.String("MLModelType"), // Required TrainingDataSourceId: aws.String("EntityId"), // Required MLModelName: aws.String("EntityName"), Parameters: map[string]*string{ "Key": aws.String("StringType"), // Required // More values... }, Recipe: aws.String("Recipe"), RecipeUri: aws.String("S3Url"), } resp, err := svc.CreateMLModel(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_UpdateMLModel() { svc := machinelearning.New(nil) params := &machinelearning.UpdateMLModelInput{ MLModelID: aws.String("EntityId"), // Required MLModelName: aws.String("EntityName"), ScoreThreshold: aws.Double(1.0), } resp, err := svc.UpdateMLModel(params) if err != nil { if awsErr, ok := err.(awserr.Error); ok { // Generic AWS error with Code, Message, and original error (if any) fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr()) if reqErr, ok := err.(awserr.RequestFailure); ok { // A service error occurred fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID()) } } else { // This case should never be hit, the SDK should always return an // error which satisfies the awserr.Error interface. fmt.Println(err.Error()) } } // Pretty-print the response data. fmt.Println(awsutil.StringValue(resp)) }
func ExampleMachineLearning_CreateBatchPrediction() { sess, err := session.NewSession() if err != nil { fmt.Println("failed to create session,", err) return } svc := machinelearning.New(sess) params := &machinelearning.CreateBatchPredictionInput{ BatchPredictionDataSourceId: aws.String("EntityId"), // Required BatchPredictionId: aws.String("EntityId"), // Required MLModelId: aws.String("EntityId"), // Required OutputUri: aws.String("S3Url"), // Required BatchPredictionName: aws.String("EntityName"), } resp, err := svc.CreateBatchPrediction(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_CreateBatchPrediction() { svc := machinelearning.New(nil) params := &machinelearning.CreateBatchPredictionInput{ BatchPredictionDataSourceID: aws.String("EntityId"), // Required BatchPredictionID: aws.String("EntityId"), // Required MLModelID: aws.String("EntityId"), // Required OutputURI: aws.String("S3Url"), // Required BatchPredictionName: aws.String("EntityName"), } resp, err := svc.CreateBatchPrediction(params) if err != nil { if awsErr, ok := err.(awserr.Error); ok { // Generic AWS Error with Code, Message, and original error (if any) fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr()) if reqErr, ok := err.(awserr.RequestFailure); ok { // A service error occurred fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID()) } } else { // This case should never be hit, the SDK should always return an // error which satisfies the awserr.Error interface. fmt.Println(err.Error()) } } // Pretty-print the response data. fmt.Println(awsutil.StringValue(resp)) }
func ExampleMachineLearning_Predict() { svc := machinelearning.New(nil) params := &machinelearning.PredictInput{ MLModelID: aws.String("EntityId"), // Required PredictEndpoint: aws.String("VipURL"), // Required Record: map[string]*string{ // Required "Key": aws.String("VariableValue"), // Required // More values... }, } resp, err := svc.Predict(params) if err != nil { if awsErr, ok := err.(awserr.Error); ok { // Generic AWS error with Code, Message, and original error (if any) fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr()) if reqErr, ok := err.(awserr.RequestFailure); ok { // A service error occurred fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID()) } } else { // This case should never be hit, the SDK should always return an // error which satisfies the awserr.Error interface. fmt.Println(err.Error()) } } // Pretty-print the response data. fmt.Println(awsutil.StringValue(resp)) }
func ExampleMachineLearning_CreateDataSourceFromS3() { svc := machinelearning.New(nil) params := &machinelearning.CreateDataSourceFromS3Input{ DataSourceID: aws.String("EntityId"), // Required DataSpec: &machinelearning.S3DataSpec{ // Required DataLocationS3: aws.String("S3Url"), // Required DataRearrangement: aws.String("DataRearrangement"), DataSchema: aws.String("DataSchema"), DataSchemaLocationS3: aws.String("S3Url"), }, ComputeStatistics: aws.Boolean(true), DataSourceName: aws.String("EntityName"), } resp, err := svc.CreateDataSourceFromS3(params) if err != nil { if awsErr, ok := err.(awserr.Error); ok { // Generic AWS error with Code, Message, and original error (if any) fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr()) if reqErr, ok := err.(awserr.RequestFailure); ok { // A service error occurred fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID()) } } else { // This case should never be hit, the SDK should always return an // error which satisfies the awserr.Error interface. fmt.Println(err.Error()) } } // Pretty-print the response data. fmt.Println(awsutil.StringValue(resp)) }
func ExampleMachineLearning_Predict() { sess, err := session.NewSession() if err != nil { fmt.Println("failed to create session,", err) return } svc := machinelearning.New(sess) params := &machinelearning.PredictInput{ MLModelId: aws.String("EntityId"), // Required PredictEndpoint: aws.String("VipURL"), // Required Record: map[string]*string{ // Required "Key": aws.String("VariableValue"), // Required // More values... }, } resp, err := svc.Predict(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_DescribeMLModels() { sess, err := session.NewSession() if err != nil { fmt.Println("failed to create session,", err) return } svc := machinelearning.New(sess) params := &machinelearning.DescribeMLModelsInput{ EQ: aws.String("ComparatorValue"), FilterVariable: aws.String("MLModelFilterVariable"), GE: aws.String("ComparatorValue"), GT: aws.String("ComparatorValue"), LE: aws.String("ComparatorValue"), LT: aws.String("ComparatorValue"), Limit: aws.Int64(1), NE: aws.String("ComparatorValue"), NextToken: aws.String("StringType"), Prefix: aws.String("ComparatorValue"), SortOrder: aws.String("SortOrder"), } resp, err := svc.DescribeMLModels(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_DescribeTags() { sess, err := session.NewSession() if err != nil { fmt.Println("failed to create session,", err) return } svc := machinelearning.New(sess) params := &machinelearning.DescribeTagsInput{ ResourceId: aws.String("EntityId"), // Required ResourceType: aws.String("TaggableResourceType"), // Required } resp, err := svc.DescribeTags(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_GetMLModel() { sess, err := session.NewSession() if err != nil { fmt.Println("failed to create session,", err) return } svc := machinelearning.New(sess) params := &machinelearning.GetMLModelInput{ MLModelId: aws.String("EntityId"), // Required Verbose: aws.Bool(true), } resp, err := svc.GetMLModel(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_DescribeDataSources() { svc := machinelearning.New(nil) params := &machinelearning.DescribeDataSourcesInput{ EQ: aws.String("ComparatorValue"), FilterVariable: aws.String("DataSourceFilterVariable"), GE: aws.String("ComparatorValue"), GT: aws.String("ComparatorValue"), LE: aws.String("ComparatorValue"), LT: aws.String("ComparatorValue"), Limit: aws.Int64(1), NE: aws.String("ComparatorValue"), NextToken: aws.String("StringType"), Prefix: aws.String("ComparatorValue"), SortOrder: aws.String("SortOrder"), } resp, err := svc.DescribeDataSources(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_GetEvaluation() { svc := machinelearning.New(nil) params := &machinelearning.GetEvaluationInput{ EvaluationId: aws.String("EntityId"), // Required } resp, err := svc.GetEvaluation(params) if err != nil { if awsErr, ok := err.(awserr.Error); ok { // Generic AWS error with Code, Message, and original error (if any) fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr()) if reqErr, ok := err.(awserr.RequestFailure); ok { // A service error occurred fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID()) } } else { // This case should never be hit, the SDK should always return an // error which satisfies the awserr.Error interface. fmt.Println(err.Error()) } } // Pretty-print the response data. fmt.Println(awsutil.Prettify(resp)) }
func ExampleMachineLearning_CreateDataSourceFromS3() { sess, err := session.NewSession() if err != nil { fmt.Println("failed to create session,", err) return } svc := machinelearning.New(sess) params := &machinelearning.CreateDataSourceFromS3Input{ DataSourceId: aws.String("EntityId"), // Required DataSpec: &machinelearning.S3DataSpec{ // Required DataLocationS3: aws.String("S3Url"), // Required DataRearrangement: aws.String("DataRearrangement"), DataSchema: aws.String("DataSchema"), DataSchemaLocationS3: aws.String("S3Url"), }, ComputeStatistics: aws.Bool(true), DataSourceName: aws.String("EntityName"), } resp, err := svc.CreateDataSourceFromS3(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_UpdateDataSource() { sess, err := session.NewSession() if err != nil { fmt.Println("failed to create session,", err) return } svc := machinelearning.New(sess) params := &machinelearning.UpdateDataSourceInput{ DataSourceId: aws.String("EntityId"), // Required DataSourceName: aws.String("EntityName"), // Required } resp, err := svc.UpdateDataSource(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_UpdateMLModel() { sess, err := session.NewSession() if err != nil { fmt.Println("failed to create session,", err) return } svc := machinelearning.New(sess) params := &machinelearning.UpdateMLModelInput{ MLModelId: aws.String("EntityId"), // Required MLModelName: aws.String("EntityName"), ScoreThreshold: aws.Float64(1.0), } resp, err := svc.UpdateMLModel(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_AddTags() { svc := machinelearning.New(session.New()) params := &machinelearning.AddTagsInput{ ResourceId: aws.String("EntityId"), // Required ResourceType: aws.String("TaggableResourceType"), // Required Tags: []*machinelearning.Tag{ // Required { // Required Key: aws.String("TagKey"), Value: aws.String("TagValue"), }, // More values... }, } resp, err := svc.AddTags(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_CreateMLModel() { svc := machinelearning.New(nil) params := &machinelearning.CreateMLModelInput{ MLModelID: aws.String("EntityId"), // Required MLModelType: aws.String("MLModelType"), // Required TrainingDataSourceID: aws.String("EntityId"), // Required MLModelName: aws.String("EntityName"), Parameters: map[string]*string{ "Key": aws.String("StringType"), // Required // More values... }, Recipe: aws.String("Recipe"), RecipeURI: aws.String("S3Url"), } resp, err := svc.CreateMLModel(params) if err != nil { if awsErr, ok := err.(awserr.Error); ok { // Generic AWS error with Code, Message, and original error (if any) fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr()) if reqErr, ok := err.(awserr.RequestFailure); ok { // A service error occurred fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID()) } } else { // This case should never be hit, the SDK should always return an // error which satisfies the awserr.Error interface. fmt.Println(err.Error()) } } // Pretty-print the response data. fmt.Println(awsutil.StringValue(resp)) }
func ExampleMachineLearning_CreateDataSourceFromRDS() { svc := machinelearning.New(nil) params := &machinelearning.CreateDataSourceFromRDSInput{ DataSourceID: aws.String("EntityId"), // Required RDSData: &machinelearning.RDSDataSpec{ // Required DatabaseCredentials: &machinelearning.RDSDatabaseCredentials{ // Required Password: aws.String("RDSDatabasePassword"), // Required Username: aws.String("RDSDatabaseUsername"), // Required }, DatabaseInformation: &machinelearning.RDSDatabase{ // Required DatabaseName: aws.String("RDSDatabaseName"), // Required InstanceIdentifier: aws.String("RDSInstanceIdentifier"), // Required }, ResourceRole: aws.String("EDPResourceRole"), // Required S3StagingLocation: aws.String("S3Url"), // Required SecurityGroupIDs: []*string{ // Required aws.String("EDPSecurityGroupId"), // Required // More values... }, SelectSQLQuery: aws.String("RDSSelectSqlQuery"), // Required ServiceRole: aws.String("EDPServiceRole"), // Required SubnetID: aws.String("EDPSubnetId"), // Required DataRearrangement: aws.String("DataRearrangement"), DataSchema: aws.String("DataSchema"), DataSchemaURI: aws.String("S3Url"), }, RoleARN: aws.String("RoleARN"), // Required ComputeStatistics: aws.Boolean(true), DataSourceName: aws.String("EntityName"), } resp, err := svc.CreateDataSourceFromRDS(params) if err != nil { if awsErr, ok := err.(awserr.Error); ok { // Generic AWS error with Code, Message, and original error (if any) fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr()) if reqErr, ok := err.(awserr.RequestFailure); ok { // A service error occurred fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID()) } } else { // This case should never be hit, the SDK should always return an // error which satisfies the awserr.Error interface. fmt.Println(err.Error()) } } // Pretty-print the response data. fmt.Println(awsutil.StringValue(resp)) }
func ExampleMachineLearning_CreateDataSourceFromRDS() { sess, err := session.NewSession() if err != nil { fmt.Println("failed to create session,", err) return } svc := machinelearning.New(sess) params := &machinelearning.CreateDataSourceFromRDSInput{ DataSourceId: aws.String("EntityId"), // Required RDSData: &machinelearning.RDSDataSpec{ // Required DatabaseCredentials: &machinelearning.RDSDatabaseCredentials{ // Required Password: aws.String("RDSDatabasePassword"), // Required Username: aws.String("RDSDatabaseUsername"), // Required }, DatabaseInformation: &machinelearning.RDSDatabase{ // Required DatabaseName: aws.String("RDSDatabaseName"), // Required InstanceIdentifier: aws.String("RDSInstanceIdentifier"), // Required }, ResourceRole: aws.String("EDPResourceRole"), // Required S3StagingLocation: aws.String("S3Url"), // Required SecurityGroupIds: []*string{ // Required aws.String("EDPSecurityGroupId"), // Required // More values... }, SelectSqlQuery: aws.String("RDSSelectSqlQuery"), // Required ServiceRole: aws.String("EDPServiceRole"), // Required SubnetId: aws.String("EDPSubnetId"), // Required DataRearrangement: aws.String("DataRearrangement"), DataSchema: aws.String("DataSchema"), DataSchemaUri: aws.String("S3Url"), }, RoleARN: aws.String("RoleARN"), // Required ComputeStatistics: aws.Bool(true), DataSourceName: aws.String("EntityName"), } resp, err := svc.CreateDataSourceFromRDS(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_GetEvaluation() { svc := machinelearning.New(session.New()) params := &machinelearning.GetEvaluationInput{ EvaluationId: aws.String("EntityId"), // Required } resp, err := svc.GetEvaluation(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_DeleteRealtimeEndpoint() { svc := machinelearning.New(session.New()) params := &machinelearning.DeleteRealtimeEndpointInput{ MLModelId: aws.String("EntityId"), // Required } resp, err := svc.DeleteRealtimeEndpoint(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_DeleteDataSource() { svc := machinelearning.New(nil) params := &machinelearning.DeleteDataSourceInput{ DataSourceId: aws.String("EntityId"), // Required } resp, err := svc.DeleteDataSource(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_UpdateBatchPrediction() { svc := machinelearning.New(nil) params := &machinelearning.UpdateBatchPredictionInput{ BatchPredictionId: aws.String("EntityId"), // Required BatchPredictionName: aws.String("EntityName"), // Required } resp, err := svc.UpdateBatchPrediction(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func init() { Before("@machinelearning", func() { World["client"] = machinelearning.New(nil) }) When(`^I attempt to call the "(.+?)" API without the "(.+?)" parameter$`, func(s1 string, s2 string) { // call(s1, nil, true) T.Skip() // pending }) When(`^I attempt to call the "(.+?)" API with "(.+?)" parameter$`, func(s1 string, s2 string) { // call(s1, nil, true) T.Skip() // pending }) Then(`^the hostname should equal the "(.+?)" parameter$`, func(s1 string) { T.Skip() // pending }) }
func ExampleMachineLearning_CreateDataSourceFromRedshift() { sess, err := session.NewSession() if err != nil { fmt.Println("failed to create session,", err) return } svc := machinelearning.New(sess) params := &machinelearning.CreateDataSourceFromRedshiftInput{ DataSourceId: aws.String("EntityId"), // Required DataSpec: &machinelearning.RedshiftDataSpec{ // Required DatabaseCredentials: &machinelearning.RedshiftDatabaseCredentials{ // Required Password: aws.String("RedshiftDatabasePassword"), // Required Username: aws.String("RedshiftDatabaseUsername"), // Required }, DatabaseInformation: &machinelearning.RedshiftDatabase{ // Required ClusterIdentifier: aws.String("RedshiftClusterIdentifier"), // Required DatabaseName: aws.String("RedshiftDatabaseName"), // Required }, S3StagingLocation: aws.String("S3Url"), // Required SelectSqlQuery: aws.String("RedshiftSelectSqlQuery"), // Required DataRearrangement: aws.String("DataRearrangement"), DataSchema: aws.String("DataSchema"), DataSchemaUri: aws.String("S3Url"), }, RoleARN: aws.String("RoleARN"), // Required ComputeStatistics: aws.Bool(true), DataSourceName: aws.String("EntityName"), } resp, err := svc.CreateDataSourceFromRedshift(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func TestPredictEndpoint(t *testing.T) { ml := machinelearning.New(nil) ml.Handlers.Send.Clear() ml.Handlers.Send.PushBack(func(r *service.Request) { r.HTTPResponse = &http.Response{ StatusCode: 200, Header: http.Header{}, Body: ioutil.NopCloser(bytes.NewReader([]byte("{}"))), } }) req, _ := ml.PredictRequest(&machinelearning.PredictInput{ PredictEndpoint: aws.String("https://localhost/endpoint"), MLModelID: aws.String("id"), Record: map[string]*string{}, }) err := req.Send() assert.Nil(t, err) assert.Equal(t, "https://localhost/endpoint", req.HTTPRequest.URL.String()) }
func ExampleMachineLearning_CreateEvaluation() { svc := machinelearning.New(nil) params := &machinelearning.CreateEvaluationInput{ EvaluationDataSourceId: aws.String("EntityId"), // Required EvaluationId: aws.String("EntityId"), // Required MLModelId: aws.String("EntityId"), // Required EvaluationName: aws.String("EntityName"), } resp, err := svc.CreateEvaluation(params) if err != nil { // Print the error, cast err to awserr.Error to get the Code and // Message from an error. fmt.Println(err.Error()) return } // Pretty-print the response data. fmt.Println(resp) }
func ExampleMachineLearning_DescribeMLModels() { svc := machinelearning.New(nil) params := &machinelearning.DescribeMLModelsInput{ EQ: aws.String("ComparatorValue"), FilterVariable: aws.String("MLModelFilterVariable"), GE: aws.String("ComparatorValue"), GT: aws.String("ComparatorValue"), LE: aws.String("ComparatorValue"), LT: aws.String("ComparatorValue"), Limit: aws.Long(1), NE: aws.String("ComparatorValue"), NextToken: aws.String("StringType"), Prefix: aws.String("ComparatorValue"), SortOrder: aws.String("SortOrder"), } resp, err := svc.DescribeMLModels(params) if err != nil { if awsErr, ok := err.(awserr.Error); ok { // Generic AWS error with Code, Message, and original error (if any) fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr()) if reqErr, ok := err.(awserr.RequestFailure); ok { // A service error occurred fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID()) } } else { // This case should never be hit, the SDK should always return an // error which satisfies the awserr.Error interface. fmt.Println(err.Error()) } } // Pretty-print the response data. fmt.Println(awsutil.StringValue(resp)) }
func init() { Before("@machinelearning", func() { World["client"] = machinelearning.New(smoke.Session) }) }
func init() { Before("@machinelearning", func() { World["client"] = machinelearning.New(nil) }) }