aws / aws-deep-learning-containers-utils
Unit Size

The distribution of size of units (measured in lines of code).

Intro
  • Unit size measurements show the distribution of size of units of code (methods, functions...).
  • Units are classified in four categories based on their size (lines of code): 1-20 (small units), 20-50 (medium size units), 51-100 (long units), 101+ (very long units).
  • You should aim at keeping units small (< 20 lines). Long units may become "bloaters", code that have increased to such gargantuan proportions that they are hard to work with.
Learn more...
Unit Size Overall
  • There are 7 units with 88 lines of code in units (90.7% of code).
    • 0 very long units (0 lines of code)
    • 0 long units (0 lines of code)
    • 1 medium size units (27 lines of code)
    • 2 small units (36 lines of code)
    • 4 very small units (25 lines of code)
0% | 0% | 30% | 40% | 28%
Legend:
101+
51-100
21-50
11-20
1-10
Unit Size per Extension
101+
51-100
21-50
11-20
1-10
py0% | 0% | 30% | 40% | 28%
Unit Size per Logical Component
primary logical decomposition
101+
51-100
21-50
11-20
1-10
ROOT0% | 0% | 30% | 40% | 28%
Alternative Visuals
Longest Units
Top 7 longest units
Unit# linesMcCabe index# params
def _retrieve_instance_region()
in deep_learning_container.py
 27 4 0
def query_bucket()
in deep_learning_container.py
 20 4 0
def parse_args()
in deep_learning_container.py
 16 1 0
def _validate_instance_id()
in deep_learning_container.py
 7 2 1
def _retrieve_instance_id()
in deep_learning_container.py
 7 3 0
def requests_helper()
in deep_learning_container.py
 7 2 2
def main()
in deep_learning_container.py
 4 3 0