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Intro

For duplication, we look at places in code where there are 6 or more lines of code that are exactly the same.
Before duplication is calculated, the code is cleaned to remove empty lines, comments, and frequently duplicated constructs such as imports.
You should aim at having as little as possible (<5%) of duplicated code as high-level of duplication can lead to maintenance difficulties, poor factoring, and logical contradictions.

Learn more...

Duplication Overall

13% duplication:

2,454 cleaned lines of cleaned code (without empty lines, comments, and frequently duplicated constructs such as imports)
323 duplicated lines

42 duplicates

Duplication per Extension

Duplication per Component (primary)

Duplication Between Components (50+ lines)

Download: SVG DOT (open online Graphviz editor)

From Component --> To Component	Duplicated Lines	File Pairs	Details
pplbench/ppls/numpyro (41%) --> pplbench/ppls/pymc3 (19%)	68	3 file pairs	details...
pplbench/ppls/jags (13%) --> pplbench/ppls/stan (9%)	50	2 file pairs	details...

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Longest Duplicates

The list of 20 longest duplicates.

See data for all 42 duplicates...

Size	#	Folders	Files	Lines	Code
10	x 2	pplbench/ppls/numpyro pplbench/ppls/pymc3	logistic_regression.py logistic_regression.py	37:46 (32%) 36:45 (33%)	view
10	x 2	pplbench/ppls/jags pplbench/ppls/jags	logistic_regression.py robust_regression.py	17:31 (41%) 17:31 (38%)	view
9	x 2	pplbench/ppls/jags pplbench/ppls/stan	n_schools.py n_schools.py	15:23 (20%) 70:78 (20%)	view
9	x 2	pplbench/ppls/pymc3 pplbench/ppls/stan	inference.py inference.py	26:34 (18%) 31:39 (9%)	view
9	x 2	pplbench/ppls/jags pplbench/ppls/jags	logistic_regression.py robust_regression.py	33:42 (37%) 35:44 (34%)	view
8	x 2	pplbench/models pplbench/models	logistic_regression.py robust_regression.py	99:112 (15%) 104:117 (15%)	view
8	x 2	pplbench/ppls/jags pplbench/ppls/numpyro	inference.py inference.py	21:32 (26%) 24:34 (21%)	view
8	x 2	pplbench/ppls/stan pplbench/ppls/stan	logistic_regression.py robust_regression.py	28:43 (33%) 28:43 (30%)	view
8	x 2	pplbench/ppls/numpyro pplbench/ppls/pymc3	logistic_regression.py logistic_regression.py	15:22 (25%) 11:18 (26%)	view
8	x 2	website/src/pages website/src/pages	index.js index.js	53:60 (3%) 101:108 (3%)	view
8	x 2	pplbench/models pplbench/models	logistic_regression.py robust_regression.py	57:64 (15%) 61:68 (15%)	view
8	x 2	website/src/pages website/src/pages	index.js index.js	62:69 (3%) 110:117 (3%)	view
7	x 2	pplbench/models pplbench/models	crowd_sourced_annotation.py logistic_regression.py	133:141 (11%) 95:102 (13%)	view
7	x 2	pplbench/ppls/numpyro pplbench/ppls/pymc3	inference.py inference.py	29:35 (18%) 26:32 (14%)	view
7	x 2	pplbench/ppls/pymc3 pplbench/ppls/pymc3	logistic_regression.py robust_regression.py	20:29 (23%) 27:36 (17%)	view
7	x 2	pplbench/ppls/pymc3 pplbench/ppls/stan	inference.py inference.py	55:62 (14%) 62:69 (7%)	view
7	x 2	pplbench/ppls/jags pplbench/ppls/stan	n_schools.py n_schools.py	29:38 (15%) 27:36 (15%)	view
7	x 2	pplbench/ppls/numpyro pplbench/ppls/stan	inference.py inference.py	29:35 (18%) 31:37 (7%)	view
7	x 2	pplbench/ppls/stan pplbench/ppls/stan	logistic_regression.py robust_regression.py	44:51 (29%) 46:53 (26%)	view
6	x 2	pplbench/ppls pplbench/ppls/jags	base_ppl_inference.py inference.py	39:44 (27%) 27:32 (20%)	view

Duplicated Units

The list of top 2 duplicated units.

See data for all 2 unit duplicates...

Size	#	Folders	Files	Lines	Code
7	x 2	pplbench/ppls/stan pplbench/ppls/pymc3	inference.py inference.py	0:0 0:0	view
7	x 2	pplbench/ppls/jags pplbench/ppls/jags	robust_regression.py logistic_regression.py	0:0 0:0	view