h2o-py/h2o/automl/autoh2o.py
def get_automl(project_name):
    """
    Retrieve information about an AutoML instance.

    :param str project_name:  A string indicating the project_name of the automl instance to retrieve.
    :returns: A dictionary containing the project_name, leader model, and leaderboard.
    """
    automl_json = h2o.api("GET /99/AutoML/%s" % project_name)
    project_name = automl_json["project_name"]
    leaderboard_list = [key["name"] for key in automl_json['leaderboard']['models']]

    if leaderboard_list is not None and len(leaderboard_list) > 0:
        leader_id = leaderboard_list[0]
    else:
        leader_id = None

    leader = h2o.get_model(leader_id)
    # Intentionally mask the progress bar here since showing multiple progress bars is confusing to users.
    # If any failure happens, revert back to user's original setting for progress and display the error message.
    is_progress = H2OJob.__PROGRESS_BAR__
    h2o.no_progress()
    try:
        # Parse leaderboard H2OTwoDimTable & return as an H2OFrame
        leaderboard = h2o.H2OFrame(
            automl_json["leaderboard_table"].cell_values,
            column_names=automl_json["leaderboard_table"].col_header)
    except Exception as ex:
        raise ex
    finally:
        if is_progress is True:
            h2o.show_progress()

    leaderboard = leaderboard[1:]
    automl_dict = {'project_name': project_name, "leader": leader, "leaderboard": leaderboard}
    return automl_dict
def get_automl(project_name):
    automl_json = h2o.api("GET /99/AutoML/%s" % project_name)
    project_name = automl_json["project_name"]
    leaderboard_list = [key["name"] for key in automl_json['leaderboard']['models']]

    if leaderboard_list is not None and len(leaderboard_list) > 0:
        leader_id = leaderboard_list[0]
    else:
        leader_id = None

    leader = h2o.get_model(leader_id)
    # Intentionally mask the progress bar here since showing multiple progress bars is confusing to users.
    # If any failure happens, revert back to user's original setting for progress and display the error message.
    is_progress = H2OJob.__PROGRESS_BAR__
    h2o.no_progress()
    try:
        # Parse leaderboard H2OTwoDimTable & return as an H2OFrame
        leaderboard = h2o.H2OFrame(
            automl_json["leaderboard_table"].cell_values,
            column_names=automl_json["leaderboard_table"].col_header)
    except Exception as ex:
        raise ex
    finally:
        if is_progress is True:
            h2o.show_progress()

    leaderboard = leaderboard[1:]
    automl_dict = {'project_name': project_name, "leader": leader, "leaderboard": leaderboard}
    return automl_dict
def get_automl ( project_name ) : automl_json = h2o . api ( "GET /99/AutoML/%s" % project_name ) project_name = automl_json [ "project_name" ] leaderboard_list = [ key [ "name" ] for key in automl_json [ 'leaderboard' ] [ 'models' ] ] if leaderboard_list is not None and len ( leaderboard_list ) > 0 : leader_id = leaderboard_list [ 0 ] else : leader_id = None leader = h2o . get_model ( leader_id ) # Intentionally mask the progress bar here since showing multiple progress bars is confusing to users. # If any failure happens, revert back to user's original setting for progress and display the error message. is_progress = H2OJob . __PROGRESS_BAR__ h2o . no_progress ( ) try : # Parse leaderboard H2OTwoDimTable & return as an H2OFrame leaderboard = h2o . H2OFrame ( automl_json [ "leaderboard_table" ] . cell_values , column_names = automl_json [ "leaderboard_table" ] . col_header ) except Exception as ex : raise ex finally : if is_progress is True : h2o . show_progress ( ) leaderboard = leaderboard [ 1 : ] automl_dict = { 'project_name' : project_name , "leader" : leader , "leaderboard" : leaderboard } return automl_dict
Retrieve information about an AutoML instance.

    :param str project_name:  A string indicating the project_name of the automl instance to retrieve.
    :returns: A dictionary containing the project_name, leader model, and leaderboard.
Retrieve information about an AutoML instance .