aws-samples / easy-amazon-sagemaker-deployments
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 49 units with 703 lines of code in units (63.5% of code).
    • 0 very complex units (0 lines of code)
    • 0 complex units (0 lines of code)
    • 2 medium complex units (207 lines of code)
    • 3 simple units (90 lines of code)
    • 44 very simple units (406 lines of code)
0% | 0% | 29% | 12% | 57%
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% | 29% | 12% | 57%
Conditional Complexity per Logical Component
primary logical decomposition
51+
26-50
11-25
6-10
1-5
ezsmdeploy0% | 0% | 46% | 15% | 38%
notebooks0% | 0% | 0% | 16% | 83%
ezsmdeploy/data0% | 0% | 0% | 0% | 100%
notebooks/src0% | 0% | 0% | 0% | 100%
ROOT0% | 0% | 0% | 0% | 100%
Most Complex Units
Top 20 most complex units
Unit# linesMcCabe index# params
def deploy()
in ezsmdeploy/__init__.py
 168 20 1
def choose_instance_type()
in ezsmdeploy/__init__.py
 39 15 1
def tar_model()
in ezsmdeploy/__init__.py
 29 8 1
def process_instance_type()
in ezsmdeploy/__init__.py
 39 7 1
def predict()
in notebooks/modelscript_mxnet.py
 22 6 2
def makedir_safe()
in ezsmdeploy/__init__.py
 12 4 2
def handle_requirements()
in ezsmdeploy/__init__.py
 16 4 1
def predict()
in notebooks/modelscript_ensemble_sklearn.py
 9 4 2
def predict()
in notebooks/src/transformscript.py
 9 4 2
def predict()
in notebooks/modelscript_pytorch.py
 14 4 2
def predict()
in notebooks/modelscript_sklearn.py
 9 4 2
def create_model()
in ezsmdeploy/__init__.py
 20 3 1
def deploy_model()
in ezsmdeploy/__init__.py
 28 3 1
def upload_model()
in ezsmdeploy/__init__.py
 16 3 1
def handle()
in ezsmdeploy/data/model_handler.py
 6 3 2
def predict()
in notebooks/modelscript_tensorflow.py
 10 3 2
def predict()
in notebooks/modelscript_tensorflow_lite.py
 19 3 2
def get_size()
in ezsmdeploy/__init__.py
 7 2 3
def build_docker()
in ezsmdeploy/__init__.py
 16 2 1
def get_model()
in ezsmdeploy/data/predictor.py
 4 2 1