aws / sagemaker-scikit-learn-container
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 42 units with 249 lines of code in units (54.8% of code).
    • 0 very complex units (0 lines of code)
    • 0 complex units (0 lines of code)
    • 0 medium complex units (0 lines of code)
    • 2 simple units (41 lines of code)
    • 40 very simple units (208 lines of code)
0% | 0% | 0% | 16% | 83%
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% | 0% | 19% | 80%
java0% | 0% | 0% | 0% | 100%
Conditional Complexity per Logical Component
primary logical decomposition
51+
26-50
11-25
6-10
1-5
src/sagemaker_sklearn_container0% | 0% | 0% | 34% | 65%
src/sagemaker_sklearn_container/mms_patch0% | 0% | 0% | 0% | 100%
docker/0.23-1/resources/mms0% | 0% | 0% | 0% | 100%
ROOT0% | 0% | 0% | 0% | 100%
Most Complex Units
Top 20 most complex units
Unit# linesMcCabe index# params
def _set_mms_configs()
in src/sagemaker_sklearn_container/serving_mms.py
 30 7 2
def import_module()
in src/sagemaker_sklearn_container/serving.py
 11 6 2
def _retrieve_mms_server_process()
in src/sagemaker_sklearn_container/mms_patch/model_server.py
 10 5 0
def start_model_server()
in src/sagemaker_sklearn_container/mms_patch/model_server.py
 21 4 3
def _generate_mms_config_properties()
in src/sagemaker_sklearn_container/mms_patch/model_server.py
 14 3 0
def _reap_children()
in src/sagemaker_sklearn_container/mms_patch/model_server.py
 7 3 2
def default_input_fn()
in src/sagemaker_sklearn_container/handler_service.py
 5 3 2
def _retry_if_error()
in src/sagemaker_sklearn_container/serving_mms.py
 2 2 1
def _set_default_if_not_exist()
in src/sagemaker_sklearn_container/serving_mms.py
 3 2 2
def _adapt_to_mms_format()
in src/sagemaker_sklearn_container/mms_patch/model_server.py
 12 2 1
def _set_python_path()
in src/sagemaker_sklearn_container/mms_patch/model_server.py
 6 2 0
def _add_sigterm_handler()
in src/sagemaker_sklearn_container/mms_patch/model_server.py
 7 2 1
def _install_requirements()
in src/sagemaker_sklearn_container/mms_patch/model_server.py
 8 2 0
def default_input_fn()
in src/sagemaker_sklearn_container/serving.py
 3 2 2
def main()
in src/sagemaker_sklearn_container/serving.py
 10 2 2
def serving_entrypoint()
in src/sagemaker_sklearn_container/serving.py
 5 2 0
def get_mms_config_file_path()
in src/sagemaker_sklearn_container/serving_mms.py
 2 1 0
def _start_model_server()
in src/sagemaker_sklearn_container/serving_mms.py
 6 1 2
def start_model_server()
in src/sagemaker_sklearn_container/serving_mms.py
 5 1 0
def _create_model_server_config_file()
in src/sagemaker_sklearn_container/mms_patch/model_server.py
 3 1 0