aws / aws-jupyter-proxy
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 19 units with 168 lines of code in units (50.8% 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)
    • 1 simple units (20 lines of code)
    • 18 very simple units (148 lines of code)
0% | 0% | 0% | 11% | 88%
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% | 11% | 88%
Conditional Complexity per Logical Component
primary logical decomposition
51+
26-50
11-25
6-10
1-5
aws_jupyter_proxy0% | 0% | 0% | 11% | 88%
Most Complex Units
Top 19 most complex units
Unit# linesMcCabe index# params
def _get_canonical_querystring()
in aws_jupyter_proxy/awsproxy.py
 20 6 1
def _is_blacklisted_response_header()
in aws_jupyter_proxy/awsproxy.py
 7 5 2
def _finish_response()
in aws_jupyter_proxy/awsproxy.py
 6 4 2
def _compute_downstream_headers()
in aws_jupyter_proxy/awsproxy.py
 15 4 2
def _get_signed_canonical_headers()
in aws_jupyter_proxy/awsproxy.py
 19 4 1
def _get_downstream_signing_region()
in aws_jupyter_proxy/awsproxy.py
 7 3 1
def setup_handlers()
in aws_jupyter_proxy/handlers.py
 9 2 1
def _get_aws_region()
in aws_jupyter_proxy/awsconfig.py
 3 2 1
def _jupyter_server_extension_paths()
in aws_jupyter_proxy/__init__.py
 2 1 0
def load_jupyter_server_extension()
in aws_jupyter_proxy/__init__.py
 2 1 1
def get_service_info()
in aws_jupyter_proxy/awsproxy.py
 2 1 0
def create_endpoint_resolver()
in aws_jupyter_proxy/awsproxy.py
 2 1 0
def initialize()
in aws_jupyter_proxy/awsproxy.py
 3 1 3
def __init__()
in aws_jupyter_proxy/awsproxy.py
 5 1 0
def _compute_downstream_url()
in aws_jupyter_proxy/awsproxy.py
 12 1 2
def _sigv4_auth_header()
in aws_jupyter_proxy/awsproxy.py
 41 1 2
def _build_upstream_auth_info()
in aws_jupyter_proxy/awsproxy.py
 5 1 1
def sign()
in aws_jupyter_proxy/awsproxy.py
 2 1 2
def get_signature_key()
in aws_jupyter_proxy/awsproxy.py
 6 1 4