aws-samples / amazon-sagemaker-feature-store-end-to-end-workshop
Conditional Complexity

The distribution of complexity of units (measured with McCabe index).

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 139 units with 2,382 lines of code in units (89.5% of code).
    • 0 very complex units (0 lines of code)
    • 0 complex units (0 lines of code)
    • 3 medium complex units (136 lines of code)
    • 17 simple units (573 lines of code)
    • 119 very simple units (1,673 lines of code)
0% | 0% | 5% | 24% | 70%
Legend:
51+
26-50
11-25
6-10
1-5
Alternative Visuals
Conditional Complexity per Extension
51+
26-50
11-25
6-10
1-5
py0% | 0% | 5% | 24% | 70%
Conditional Complexity per Logical Component
primary logical decomposition
51+
26-50
11-25
6-10
1-5
utilities0% | 0% | 5% | 24% | 69%
04-module-working-with-online-store/custom_library0% | 0% | 48% | 0% | 51%
07-module-feature-monitoring0% | 0% | 0% | 35% | 64%
06-module-automated-pipeline0% | 0% | 0% | 15% | 84%
05-module-scalable-batch-ingestion/scripts0% | 0% | 0% | 0% | 100%
Most Complex Units
Top 20 most complex units
Unit# linesMcCabe index# params
def get_latest_featureset_values()
in 04-module-working-with-online-store/custom_library/helper.py
 48 15 3
def get_latest_featureset_values()
in utilities/feature_store_helper.py
 44 14 6
def _run_query()
in utilities/feature_store_helper.py
 44 11 5
def run_crawler()
in 07-module-feature-monitoring/feature_monitoring_utils.py
 35 9 5
def create_fg_from_df()
in utilities/Utils.py
 29 9 7
def list_feature_groups()
in utilities/feature_store_helper.py
 31 9 2
def create_fg_from_df()
in utilities/feature_store_helper.py
 32 8 9
def wait_until_job_ready()
in 07-module-feature-monitoring/feature_monitoring_utils.py
 27 7 4
def download_json_profiling()
in 07-module-feature-monitoring/feature_monitoring_utils.py
 18 7 3
def _run_query()
in 06-module-automated-pipeline/pipeline_utils.py
 32 7 4
def _run_query()
in utilities/Utils.py
 30 7 4
def _get_athena_col_defs()
in utilities/feature_store_helper.py
 19 7 2
def feature_databrew_profile()
in 07-module-feature-monitoring/feature_monitoring_utils.py
 45 6 4
def feature_monitoring_run()
in 07-module-feature-monitoring/feature_monitoring_utils.py
 34 6 2
28 6 5
def ingest_with_dw()
in utilities/Utils.py
 49 6 8
def _id_list_as_string()
in utilities/feature_store_helper.py
 11 6 4
def _get_other_cols()
in utilities/feature_store_helper.py
 15 6 5
def get_features()
in utilities/feature_store_helper.py
 91 6 6
def ingest_with_dw()
in utilities/feature_store_helper.py
 47 6 9