diff --git a/outrank/__main__.py b/outrank/__main__.py index 33abfeb..4363c9b 100644 --- a/outrank/__main__.py +++ b/outrank/__main__.py @@ -183,13 +183,6 @@ def main(): help="Which ';'-separated features should be one-hot encoded into n new features (coverage analysis)", ) - parser.add_argument( - '--silent', - type=str, - default='False', - help='Suppress the logo and tips.', - ) - parser.add_argument( '--subfeature_mapping', type=str, @@ -225,6 +218,14 @@ def main(): help='Relevant for task data_generator -- name of the folder that contains generated data.', ) + parser.add_argument( + '--disable_tqdm', + default='False', + choices=['False', 'True'], + help='Either True or False.', + ) + + args = parser.parse_args() if args.task == 'selftest': diff --git a/outrank/core_ranking.py b/outrank/core_ranking.py index 31cc17e..93672f9 100644 --- a/outrank/core_ranking.py +++ b/outrank/core_ranking.py @@ -432,6 +432,7 @@ def compute_cardinalities(input_dataframe: pd.DataFrame, pbar: Any) -> None: GLOBAL_CARDINALITY_STORAGE[column].add( internal_hash(unique_value), ) + pbar.set_description( f'Computing cardinality (Hyperloglog update) {enx}/{input_dataframe.shape[1]}', ) @@ -498,6 +499,7 @@ def compute_batch_ranking( input_dataframe = input_dataframe[list(focus_set)] if args.transformers != 'none': + pbar.set_description('Adding transformations') input_dataframe = enrich_with_transformations( input_dataframe, numeric_column_types, logger, args, @@ -628,7 +630,7 @@ def estimate_importances_minibatches( local_coverage_object = defaultdict(list) local_pbar = tqdm.tqdm( - total=get_num_of_instances(input_file) - 1, position=0, + total=get_num_of_instances(input_file) - 1, position=0, disable=args.disable_tqdm == 'True', ) file_name, file_extension = os.path.splitext(input_file) diff --git a/outrank/task_ranking.py b/outrank/task_ranking.py index 1840bce..1ab28c8 100644 --- a/outrank/task_ranking.py +++ b/outrank/task_ranking.py @@ -32,14 +32,12 @@ ) -def outrank_task_conduct_ranking(args: Any): +def outrank_task_conduct_ranking(args: Any) -> None: # Data source = folder structure + relevant file specifications - - # No need for full-blown ranking in this case if args.task in ['identify_rare_values', 'feature_summary_transformers']: args.heuristic = 'Constant' - if args.silent != 'True': + if args.disable_tqdm == 'False': display_tool_name() display_random_tip() diff --git a/setup.py b/setup.py index 5d148e0..012d397 100644 --- a/setup.py +++ b/setup.py @@ -23,7 +23,7 @@ def _read_description(): packages = [x for x in setuptools.find_packages() if x != 'test'] setuptools.setup( name='outrank', - version='0.95.3', + version='0.95.4', description='OutRank: Feature ranking for massive sparse data sets.', long_description=_read_description(), long_description_content_type='text/markdown', diff --git a/tests/ranking_module_test.py b/tests/ranking_module_test.py index 5e96fbf..c7cf1d4 100644 --- a/tests/ranking_module_test.py +++ b/tests/ranking_module_test.py @@ -33,6 +33,7 @@ class args: target_ranking_only: str = 'True' interaction_order: int = 3 combination_number_upper_bound: int = 1024 + disable_tqdm: bool = False class CompareStrategiesTest(unittest.TestCase):