Deleting Resources

Resources can be deleted individually using the corresponding method for each type of resource.

api.delete_source(source)
api.delete_dataset(dataset)
api.delete_model(model)
api.delete_prediction(prediction)
api.delete_evaluation(evaluation)
api.delete_ensemble(ensemble)
api.delete_batch_prediction(batch_prediction)
api.delete_cluster(cluster)
api.delete_centroid(centroid)
api.delete_batch_centroid(batch_centroid)
api.delete_anomaly(anomaly)
api.delete_anomaly_score(anomaly_score)
api.delete_batch_anomaly_score(batch_anomaly_score)
api.delete_sample(sample)
api.delete_correlation(correlation)
api.delete_statistical_test(statistical_test)
api.delete_logistic_regression(logistic_regression)
api.delete_linear_regression(linear_regression)
api.delete_association(association)
api.delete_association_set(association_set)
api.delete_topic_model(topic_model)
api.delete_topic_distribution(topic_distribution)
api.delete_batch_topic_distribution(batch_topic_distribution)
api.delete_time_series(time_series)
api.delete_forecast(forecast)
api.delete_fusion(fusion)
api.delete_pca(pca)
api.delete_deepnet(deepnet)
api.delete_projection(projection)
api.delete_batch_projection(batch_projection)
api.delete_project(project)
api.delete_script(script)
api.delete_library(library)
api.delete_execution(execution)
api.delete_external_connector(external_connector)

Each of the calls above will return a dictionary with the following keys:

• code If the request is successful, the code will be a bigml.api.HTTP_NO_CONTENT (204) status code. Otherwise, it wil be one of the standard HTTP error codes. See the documentation on status codes for more info.

• error If the request does not succeed, it will contain a dictionary with an error code and a message. It will be None otherwise.