create_connector |
Create a new connector of a supported type (among: "SQL", "FTP", "SFTP", "S3", "GCP"). If check_if_exist is enabled, the function will check if a connector with the same name already exists. If yes, it will return a message and the information of the existing connector instead of creating a new one. |
create_dataframe_from_dataset |
Create a dataframe from a dataset_id. |
create_dataset_embedding |
Create a dataset embedding from a dataset_id. |
create_dataset_from_dataframe |
Upload dataset from data frame. |
create_dataset_from_datasource |
Create a dataset from an existing datasource. |
create_dataset_from_file |
Upload dataset from file name. |
create_datasource |
Create a new datasource If check_if_exist is enabled, the function will check if a datasource with the same name already exists. If yes, it will return a message and the information of the existing datasource instead of creating a new one. |
create_deployment_api_key |
Create a new API key for a deployed model. |
create_deployment_model |
Create a new deployment for a model. |
create_deployment_predictions |
Create predictions on a deployed model using a dataset. |
create_experiment |
Create a new experiment. If check_if_exist is enabled, the function will check if an experiment with the same name already exists. If yes, it will return a message and the information of the existing experiment instead of creating a new one. |
create_experiment_version |
Create a new version of an existing experiment. |
create_export |
Export data using an existing exporter and the resource to export |
create_exporter |
Create a new exporter |
create_folder |
Upload folder from a local file. |
create_pipeline_trigger |
Trigger an existing pipeline run. |
create_prediction |
Create a prediction on a specified experiment_version |
create_project |
Create a new project. If check_if_exist is enabled, the function will check if a project with the same name already exists. If yes, it will return a message and the information of the existing project instead of creating a new one. |
create_project_user |
Add user in and existing project. |
delete_connector |
Delete an existing connector. |
delete_dataset |
Delete an existing dataset. |
delete_datasource |
Delete a datasource |
delete_deployment |
Delete an existing deployment. |
delete_experiment |
Delete a experiment on the platform. |
delete_exporter |
Delete an exporter |
delete_folder |
Delete an existing folder. |
delete_pipeline |
Delete an existing pipeline |
delete_prediction |
Delete a prediction. |
delete_project |
Delete an existing project. |
delete_project_user |
Delete user in and existing project. |
get_best_model_id |
Get the model_id that provide the best predictive performance given experiment_version_id. If include_blend is false, it will return the model_id from the best "non blended" model. |
get_connectors |
Get information of all connectors available for a given project_id. |
get_connector_id_from_name |
Get a connector_id from a connector_name for a given project_id. If duplicated name, the first connector_id that match it is retrieved. |
get_connector_info |
Get information about connector from its id. |
get_datasets |
Get information of all datasets available for a given project_id. |
get_dataset_embedding |
Get a dataset embedding from a dataset_id. |
get_dataset_head |
Show the head of a dataset from its id. |
get_dataset_id_from_name |
Get a dataset_id from a dataset_name. If duplicated name, the first dataset_id that match it is retrieved. |
get_dataset_info |
Get a dataset from its id. |
get_datasources |
Get information of all data sources available for a given project_id. |
get_datasource_id_from_name |
Get a datasource_id from a datasource_name If duplicated name, the first datasource_id that match it is retrieved |
get_datasource_info |
Get a datasource from its id. |
get_deployments |
Get information of all deployments of a given type available for a given project_id. |
get_deployment_api_keys |
Get API keys for a deployed model. |
get_deployment_app_logs |
Get logs from a deployed app. |
get_deployment_id_from_name |
Get a deployment_id from a name and type for a given project_id. If duplicated name, the first deployment_id that match it is retrieved. |
get_deployment_info |
Get information about a deployment from its id. |
get_deployment_predictions |
Get listing of predictions related to a deployment_id. |
get_deployment_prediction_info |
Get information related to predictions of a prediction_id. |
get_deployment_usage |
Get usage (calls, errors and response time) of the last version of a deployed model. |
get_experiments |
Get information of all experiments available for a given project_id. |
get_experiment_id_from_name |
Get a experiment_id from a experiment_name If duplicated name, the first experiment_id that match it is retrieved. |
get_experiment_info |
Get a experiment from its experiment_id. |
get_experiment_version_features |
Get features information related to a experiment_version_id. |
get_experiment_version_id |
Get a experiment version id from a experiment_id and its version number. |
get_experiment_version_info |
Get a experiment_version info from its experiment_version_id |
get_experiment_version_models |
Get a model list related to a experiment_version_id. |
get_experiment_version_predictions |
Get a list of prediction from a experiment_version_id. |
get_exporters |
Get information of all exporters available for a given project_id. |
get_exporter_exports |
Get all exports done from an exporter_id |
get_exporter_id_from_name |
Get a exporter_id from a exporter_name. If duplicated name, the first exporter_id that match it is retrieved |
get_exporter_info |
Get an exporter from its id. |
get_features_infos |
Get information of a given feature related to a experiment_version_id. |
get_folder |
Get a folder from its id. |
get_folders |
Get information of all image folders available for a given project_id. |
get_folder_id_from_name |
Get a folder_id from a folder_name. If duplicated name, the first folder_id that match it is retrieved. |
get_model_cv |
Get the cross validation file from a specific model. |
get_model_feature_importance |
Get feature importance corresponding to a model_id. |
get_model_hyperparameters |
Get hyperparameters corresponding to a model_id. |
get_model_infos |
Get model information corresponding to a model_id. |
get_pipelines |
Get information of all pipelines of a given type available for a given project_id. |
get_pipeline_id_from_name |
Get a pipeline_id from a pipeline_name and type for a given project_id. If duplicated name, the first pipeline_id that match it is retrieved. |
get_pipeline_info |
Get information about a pipeline from its id and its type. |
get_prediction |
Get a specific prediction from a prediction_id. Wait up until time_out is reached and wait wait_time between each retry. |
get_prediction_infos |
Get a information about a prediction_id. |
get_projects |
Retrieves all projects. |
get_project_id_from_name |
Get a project_id from a project_name If duplicated name, the first project_id that match it is retrieved. |
get_project_info |
Get a project from its project_id. |
get_project_users |
Get users from a project. |
helper_cv_classif_analysis |
Get metrics on a CV file retrieved by Prevision.io for a binary classification use case |
helper_drift_analysis |
[BETA] Return a data.frame that contains features, a boolean indicating if the feature may have a different distribution between the submitted datasets (if p-value < threshold), their exact p-value and the test used to compute it. |
helper_optimal_prediction |
[BETA] Compute the optimal prediction for each rows in a data frame, for a given model, a list of actionable features and a number of samples for each features to be tested. |
helper_plot_classif_analysis |
Plot RECALL, PRECISION & F1 SCORE versus top n predictions for a binary classification use case |
pause_experiment_version |
Pause a running experiment_version on the platform. |
pio_download |
Download resources according specific parameters. |
pio_init |
Initialization of the connection to your instance Prevision.io. |
pio_list_to_df |
Convert a list returned from APIs to a dataframe. Only working for consistent list (same naming and number of columns). |
pio_request |
Request the platform. Thanks to an endpoint, the url and the API, you can create request. |
resume_experiment_version |
Resume a paused experiment_version on the platform. |
stop_experiment_version |
Stop a running or paused experiment_version on the platform. |
test_connector |
Test an existing connector. |
test_datasource |
Test a datasource |
test_deployment_type |
Check if a type of a deployment is supported |
test_pipeline_type |
Check if a type of a pipeline is supported |
update_experiment_version_description |
Update the description of a given experiment_version_id. |
update_project_user_role |
Update user role in and existing project. |