aws / sagemaker-scikit-learn-container

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 47 units with 282 lines of code in units (64.2% 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)
3 simple units (58 lines of code)
44 very simple units (224 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 47 most complex units

Unit	# lines	McCabe index	# params
def _user_module_transformer() in src/sagemaker_sklearn_container/serving.py	17	9	1
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 _format_exception_message() in src/sagemaker_sklearn_container/exceptions.py	12	4	2
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 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 _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 _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 is_multi_model() in src/sagemaker_sklearn_container/serving.py	2	1	0
def default_model_fn() in src/sagemaker_sklearn_container/serving.py	2	1	1
def default_predict_fn() in src/sagemaker_sklearn_container/serving.py	3	1	2
def default_output_fn() in src/sagemaker_sklearn_container/serving.py	2	1	2
def _user_module_execution_parameters_fn() in src/sagemaker_sklearn_container/serving.py	2	1	1
def train() in src/sagemaker_sklearn_container/training.py	7	1	1
def main() in src/sagemaker_sklearn_container/training.py	2	1	0
def _create_model_server_config_file() in src/sagemaker_sklearn_container/mms_patch/model_server.py	3	1	0
def _add_sigchild_handler() in src/sagemaker_sklearn_container/mms_patch/model_server.py	2	1	0
def __init__() in src/sagemaker_sklearn_container/exceptions.py	5	1	3
def __init__() in src/sagemaker_sklearn_container/exceptions.py	2	1	3
def __init__() in src/sagemaker_sklearn_container/exceptions.py	2	1	3
def __init__() in src/sagemaker_sklearn_container/exceptions.py	2	1	3
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 default_model_fn() in src/sagemaker_sklearn_container/handler_service.py	2	1	1
def default_predict_fn() in src/sagemaker_sklearn_container/handler_service.py	3	1	2
def default_output_fn() in src/sagemaker_sklearn_container/handler_service.py	2	1	2
def __init__() in src/sagemaker_sklearn_container/handler_service.py	3	1	1
def read() in setup.py	2	1	1
public void doGet() in docker/1.2-1/resources/mms/ExecutionParameters.java	15	1	3
public SagemakerXgboostResponse() in docker/1.2-1/resources/mms/ExecutionParameters.java	5	1	0
public int getMaxConcurrentTransforms() in docker/1.2-1/resources/mms/ExecutionParameters.java	3	1	0
public String getBatchStrategy() in docker/1.2-1/resources/mms/ExecutionParameters.java	3	1	0
public int getMaxPayloadInMB() in docker/1.2-1/resources/mms/ExecutionParameters.java	3	1	0
public void setMaxConcurrentTransforms() in docker/1.2-1/resources/mms/ExecutionParameters.java	3	1	1
public void setBatchStrategy() in docker/1.2-1/resources/mms/ExecutionParameters.java	3	1	1
public void setMaxPayloadInMB() in docker/1.2-1/resources/mms/ExecutionParameters.java	3	1	1