aws / graph-notebook - Conditional Complexity

Intro

Conditional complexity (also called cyclomatic complexity) is a term used to measure the complexity of software. The term refers to the number of possible paths through a program function. A higher value ofter means higher maintenance and testing costs (infosecinstitute.com).
Conditional complexity is calculated by counting all conditions in the program that can affect the execution path (e.g. if statement, loops, switches, and/or operators, try and catch blocks...).
Conditional complexity is measured at the unit level (methods, functions...).
Units are classified in four categories based on the measured McCabe index: 1-5 (simple units), 6-10 (medium complex units), 11-25 (complex units), 26+ (very complex units).

Learn more...

Conditional Complexity Overall

There are 473 units with 9,509 lines of code in units (40.4% of code).

3 very complex units (1,333 lines of code)
8 complex units (890 lines of code)
30 medium complex units (1,483 lines of code)
49 simple units (1,349 lines of code)
383 very simple units (4,454 lines of code)

Legend:

51+

26-50

11-25

6-10

1-5

Alternative Visuals

3D view of all units

Conditional Complexity per Extension

51+

26-50

11-25

6-10

1-5

Conditional Complexity per Logical Component

primary logical decomposition

51+

26-50

11-25

6-10

1-5

Most Complex Units

Top 50 most complex units

Unit	# lines	McCabe index	# params
def seed() in src/graph_notebook/magics/graph_magic.py	546	103	3
def load() in src/graph_notebook/magics/graph_magic.py	518	65	3
def sparql() in src/graph_notebook/magics/graph_magic.py	269	53	4
def add_results_with_pattern() in src/graph_notebook/network/gremlin/GremlinNetwork.py	69	46	3
def reset() in src/graph_notebook/magics/graph_magic.py	276	40	4
def add_path_edge() in src/graph_notebook/network/gremlin/GremlinNetwork.py	97	36	5
def setup_pretrained_endpoints() in src/graph_notebook/notebooks/03-Neptune-ML/03-Sample-Applications/04-Telco-Networks/neptune_ml_utils.py	111	31	7
def setup_pretrained_endpoints() in src/graph_notebook/notebooks/03-Neptune-ML/neptune_ml_utils.py	111	31	7
def add_results() in src/graph_notebook/network/sparql/SPARQLNetwork.py	106	31	2
def __init__() in src/graph_notebook/configuration/generate_config.py	67	27	8
def add_results() in src/graph_notebook/network/gremlin/GremlinNetwork.py	53	26	3
def parse_node() in src/graph_notebook/network/opencypher/OCNetwork.py	60	25	3
def parse_node() in src/graph_notebook/network/sparql/SPARQLNetwork.py	53	25	4
def neptune_ml_endpoint() in src/graph_notebook/magics/ml.py	73	24	4
def get_config_from_dict() in src/graph_notebook/configuration/get_config.py	59	24	2
def neptune_ml_training() in src/graph_notebook/magics/ml.py	77	23	4
def neptune_ml_dataprocessing() in src/graph_notebook/magics/ml.py	65	22	4
def handle_opencypher_status() in src/graph_notebook/magics/graph_magic.py	71	20	3
def setup_pretrained_endpoints_rdf() in src/graph_notebook/notebooks/03-Neptune-ML/02-SPARQL/neptune_ml_sparql_utils.py	70	19	5
def modeltransform_start() in src/graph_notebook/magics/ml.py	63	19	3
def get_node_property_value() in src/graph_notebook/network/opencypher/OCNetwork.py	35	17	5
def set_gremlin_profile_metrics() in src/graph_notebook/magics/metadata.py	54	15	2
def get_dict_element_property_value() in src/graph_notebook/network/gremlin/GremlinNetwork.py	29	14	5
def opencypher_http() in src/graph_notebook/neptune/client.py	58	13	8
def statistics() in src/graph_notebook/magics/graph_magic.py	37	13	3
def download_and_extract_archive_from_s3() in src/graph_notebook/seed/load_query.py	43	12	2
def normalize_notebook() in src/graph_notebook/notebooks/install.py	27	12	1
def delete_pretrained_endpoints() in src/graph_notebook/notebooks/03-Neptune-ML/03-Sample-Applications/04-Telco-Networks/neptune_ml_utils.py	21	12	1
def __process_ratings_users() in src/graph_notebook/notebooks/03-Neptune-ML/03-Sample-Applications/04-Telco-Networks/neptune_ml_utils.py	46	12	1
def delete_pretrained_endpoints() in src/graph_notebook/notebooks/03-Neptune-ML/neptune_ml_utils.py	21	12	1
def __process_ratings_users() in src/graph_notebook/notebooks/03-Neptune-ML/neptune_ml_utils.py	46	12	1
def insert_path_element() in src/graph_notebook/network/gremlin/GremlinNetwork.py	31	12	3
def graph_notebook_vis_options() in src/graph_notebook/magics/graph_magic.py	42	12	4
def get_queries() in src/graph_notebook/seed/load_query.py	31	11	3
def sparql_get_rows_and_columns() in src/graph_notebook/visualization/rows_and_columns.py	23	11	1
def delete_pretrained_data() in src/graph_notebook/notebooks/03-Neptune-ML/03-Sample-Applications/04-Telco-Networks/neptune_ml_utils.py	43	11	5
def delete_pretrained_data() in src/graph_notebook/notebooks/03-Neptune-ML/neptune_ml_utils.py	43	11	5
def add_vertex() in src/graph_notebook/network/gremlin/GremlinNetwork.py	169	11	3
def get_node_property_value() in src/graph_notebook/network/sparql/SPARQLNetwork.py	28	11	4
def add_security_params() in src/graph_notebook/magics/ml.py	20	11	2
def __init__() in src/graph_notebook/configuration/generate_config.py	45	11	15
def display_exceptions() in src/graph_notebook/decorators/decorators.py	41	10	1
def get_node_to_idx_mapping() in src/graph_notebook/notebooks/03-Neptune-ML/02-SPARQL/neptune_ml_sparql_utils.py	25	10	4
def get_node_to_idx_mapping() in src/graph_notebook/notebooks/03-Neptune-ML/03-Sample-Applications/04-Telco-Networks/neptune_ml_utils.py	25	10	4
def get_node_to_idx_mapping() in src/graph_notebook/notebooks/03-Neptune-ML/neptune_ml_utils.py	25	10	4
def insert_elementmap() in src/graph_notebook/network/gremlin/GremlinNetwork.py	17	10	5
def get_edge_property_value() in src/graph_notebook/network/opencypher/OCNetwork.py	26	10	4
def extract_prefix() in src/graph_notebook/network/sparql/SPARQLNetwork.py	27	10	2
def neptune_config_allowlist() in src/graph_notebook/magics/graph_magic.py	37	10	3
def load_ids() in src/graph_notebook/magics/graph_magic.py	92	10	3