mozilla / mozilla-datahub-ingestion - 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 41 units with 478 lines of code in units (64.8% of code).

0 very complex units (0 lines of code)
0 complex units (0 lines of code)
1 medium complex units (46 lines of code)
4 simple units (103 lines of code)
36 very simple units (329 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 41 most complex units

Unit	# lines	McCabe index	# params
def get_metric_definitions() in sync/metrichub.py	46	13	0
def _build_metric_dict() in sync/datahub/metrichub_glossary.py	30	8	1
def _extract_table_references() in sync/metrichub.py	40	8	1
def get_bigquery_etl_table_references() in sync/bigquery_etl.py	21	7	0
def display_name() in sync/metrichub.py	12	6	1
def get_workunits_internal() in sync/datahub/bigquery_etl_source.py	33	5	1
def get_workunits_internal() in sync/datahub/glean_source.py	53	4	1
def _get_metric_level_link_text() in sync/datahub/metrichub_glossary.py	14	4	1
def get_workunits_internal() in sync/datahub/legacy_source.py	41	4	1
def _get_ping_schemas() in sync/legacy.py	13	4	0
def get_glean_pings() in sync/glean.py	19	4	0
def _get_looker_statistics_links() in sync/datahub/metrichub_glossary.py	17	3	1
def get_legacy_pings() in sync/legacy.py	8	3	0
def _get_looker_explore_link() in sync/datahub/metrichub_glossary.py	12	2	1
def _build_product_dict() in sync/datahub/metrichub_glossary.py	6	2	2
def main() in sync/datahub/metrichub_glossary.py	26	2	0
def bigquery_fully_qualified_names() in sync/legacy.py	6	2	1
def bigquery_dataset_names() in sync/glean.py	5	2	1
def bigquery_fully_qualified_names() in sync/glean.py	5	2	1
def __init__() in sync/datahub/glean_source.py	4	1	3
def get_platform_instance_id() in sync/datahub/glean_source.py	2	1	1
def create() in sync/datahub/glean_source.py	3	1	3
def get_workunit_processors() in sync/datahub/glean_source.py	7	1	1
def get_report() in sync/datahub/glean_source.py	2	1	1
def _generate_table_to_term_data() in sync/datahub/metrichub_glossary.py	2	1	0
def get_current_timestamp() in sync/datahub/utils.py	3	1	0
def __init__() in sync/datahub/bigquery_etl_source.py	5	1	3
def create() in sync/datahub/bigquery_etl_source.py	3	1	3
def get_report() in sync/datahub/bigquery_etl_source.py	2	1	1
def __init__() in sync/datahub/legacy_source.py	4	1	3
def get_platform_instance_id() in sync/datahub/legacy_source.py	2	1	1
def create() in sync/datahub/legacy_source.py	3	1	3
def get_workunit_processors() in sync/datahub/legacy_source.py	7	1	1
def get_report() in sync/datahub/legacy_source.py	2	1	1
def glean_dictionary_url() in sync/glean.py	2	1	1
def qualified_name() in sync/glean.py	2	1	1
def bigquery_table_name() in sync/glean.py	4	1	1
def title_cased_name() in sync/metrichub.py	2	1	1
def urn() in sync/metrichub.py	2	1	1
def title_cased_name() in sync/metrichub.py	2	1	1
def _raw_table_name() in sync/metrichub.py	6	1	1