aws-samples / amazon-sagemaker-to-aws-lambda-pipeline-blogpost
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 85 lines of code in units (10.9% of code).
    • 0 very long units (0 lines of code)
    • 0 long units (0 lines of code)
    • 1 medium size units (21 lines of code)
    • 3 small units (44 lines of code)
    • 3 very small units (20 lines of code)
0% | 0% | 24% | 51% | 23%
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% | 24% | 51% | 23%
Unit Size per Logical Component
primary logical decomposition
101+
51-100
21-50
11-20
1-10
lambdachecker0% | 0% | 24% | 51% | 23%
Alternative Visuals
Longest Units
Top 7 longest units
Unit# linesMcCabe index# params
def text_to_word_sequence()
in lambdachecker/sms_spam_classifier_utilities.py
 21 10 2
def handler()
in lambdachecker/lambda_function.py
 19 4 2
def hashing_trick()
in lambdachecker/sms_spam_classifier_utilities.py
 14 2 4
def response()
in lambdachecker/lambda_function.py
 11 1 2
def one_hot()
in lambdachecker/sms_spam_classifier_utilities.py
 9 1 3
def one_hot_encode()
in lambdachecker/sms_spam_classifier_utilities.py
 6 2 2
def vectorize_sequences()
in lambdachecker/sms_spam_classifier_utilities.py
 5 2 2