elastic / faker-datasets

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.

Unit Size Overall

Legend:

101+

51-100

21-50

11-20

1-10

Unit Size per Extension

101+

51-100

21-50

11-20

1-10

Unit Size per Logical Component

primary logical decomposition

101+

51-100

21-50

11-20

1-10

Alternative Visuals

Longest Units

Top 12 longest units

Unit	# lines	McCabe index	# params
def __call__() in faker_datasets/__init__.py	14	4	2
def __call__() in faker_datasets/__init__.py	13	6	2
def chroot() in faker_datasets/__init__.py	12	5	3
def pick() in faker_datasets/__init__.py	10	4	5
def __call__() in faker_datasets/__init__.py	9	4	2
def dataset() in faker_datasets/__init__.py	8	9	2
def load_dataset() in faker_datasets/__init__.py	7	2	1
def __init__() in faker_datasets/__init__.py	7	6	3
def __init__() in faker_datasets/__init__.py	4	3	6
def load_json() in faker_datasets/__init__.py	3	1	1
def __init__() in faker_datasets/__init__.py	3	2	3
def __init__() in faker_datasets/__init__.py	2	1	2