Intro

For duplication, we look at places in code where there are six 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.

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Duplication Overall

25% duplication:

5,175 cleaned lines of cleaned code (without empty lines, comments, and frequently duplicated constructs such as imports)
1,323 duplicated lines

59 duplicates

Duplication per Extension

Duplication per Component (primary)

Longest Duplicates

The list of 20 longest duplicates.

Size	#	Folders	Files	Lines	Code
46	x 2	causalml/inference/meta causalml/inference/meta	tlearner.py slearner.py	245:394 (19%) 257:407 (20%)	view
41	x 2	causalml/inference/meta causalml/inference/meta	xlearner.py xlearner.py	85:141 (10%) 611:667 (10%)	view
38	x 4	causalml/inference/meta causalml/inference/meta causalml/inference/meta causalml/inference/meta	rlearner.py slearner.py tlearner.py xlearner.py	302:441 (9%) 268:407 (16%) 255:394 (16%) 382:521 (9%)	view
35	x 2	causalml/inference/meta causalml/inference/meta	xlearner.py xlearner.py	152:208 (8%) 678:735 (8%)	view
34	x 2	causalml/inference/meta causalml/inference/meta	rlearner.py rlearner.py	73:122 (8%) 640:688 (8%)	view
26	x 2	causalml/inference/meta causalml/inference/meta	rlearner.py xlearner.py	85:113 (6%) 96:124 (6%)	view
25	x 2	causalml/inference/meta causalml/inference/meta	tlearner.py slearner.py	188:219 (10%) 200:231 (10%)	view
21	x 2	causalml/metrics causalml/metrics	visualize.py visualize.py	501:526 (5%) 549:574 (5%)	view
17	x 2	causalml/inference/tree causalml/inference/tree	models.py models.py	458:478 (1%) 1290:1310 (1%)	view
17	x 2	causalml/inference/tree causalml/inference/tree	utils.py utils.py	39:61 (9%) 75:97 (9%)	view
15	x 2	causalml/inference/meta causalml/inference/meta	rlearner.py rlearner.py	122:139 (3%) 563:580 (3%)	view
14	x 2	causalml/inference/meta causalml/inference/meta	tlearner.py slearner.py	112:129 (5%) 126:143 (6%)	view
14	x 2	causalml/dataset causalml/dataset	regression.py regression.py	117:132 (8%) 183:198 (8%)	view
13	x 2	causalml/inference/meta causalml/inference/meta	rlearner.py xlearner.py	235:250 (3%) 304:318 (3%)	view
12	x 2	causalml/inference/meta causalml/inference/meta	tlearner.py tlearner.py	402:422 (5%) 430:450 (5%)	view
12	x 2	causalml/inference/meta causalml/inference/meta	tlearner.py slearner.py	478:492 (5%) 476:490 (5%)	view
12	x 2	causalml/dataset causalml/dataset	regression.py regression.py	87:102 (7%) 120:134 (7%)	view
11	x 2	causalml/dataset causalml/dataset	regression.py regression.py	53:65 (6%) 152:164 (6%)	view
11	x 2	causalml/inference/tree causalml/inference/tree	models.py models.py	1091:1101 (1%) 1138:1148 (1%)	view
11	x 2	causalml/metrics causalml/metrics	visualize.py visualize.py	77:89 (2%) 185:197 (2%)	view

Most Frequent Duplicates

The list of 9 most frequently found duplicates.

Size	#	Folders	Files	Lines	Code
7	x 4	causalml/inference/meta causalml/inference/meta causalml/inference/meta causalml/inference/meta	tlearner.py tlearner.py slearner.py slearner.py	119:126 (2%) 485:492 (2%) 133:140 (3%) 483:490 (3%)	view
38	x 4	causalml/inference/meta causalml/inference/meta causalml/inference/meta causalml/inference/meta	rlearner.py slearner.py tlearner.py xlearner.py	302:441 (9%) 268:407 (16%) 255:394 (16%) 382:521 (9%)	view
6	x 3	causalml/inference/meta causalml/inference/meta causalml/inference/meta	xlearner.py slearner.py tlearner.py	132:137 (1%) 84:90 (2%) 74:79 (2%)	view
10	x 3	causalml/inference/meta causalml/inference/meta causalml/inference/meta	tlearner.py rlearner.py xlearner.py	214:225 (4%) 260:271 (2%) 337:348 (2%)	view
7	x 3	causalml/inference/tree causalml/inference/tree causalml/inference/tree	models.py models.py models.py	605:611 (<1%) 632:638 (<1%) 658:664 (<1%)	view
7	x 3	causalml/inference/meta causalml/inference/meta causalml/inference/meta	xlearner.py slearner.py tlearner.py	314:322 (1%) 202:210 (3%) 190:198 (2%)	view
6	x 3	causalml/inference/meta causalml/inference/meta causalml/inference/meta	rlearner.py tmle.py xlearner.py	105:111 (1%) 116:121 (6%) 116:122 (1%)	view
6	x 3	causalml/feature_selection causalml/feature_selection causalml/feature_selection	filters.py filters.py filters.py	235:240 (3%) 254:259 (3%) 274:279 (3%)	view
6	x 3	causalml/inference/meta causalml/inference/meta causalml/inference/meta	rlearner.py xlearner.py xlearner.py	238:244 (1%) 247:252 (1%) 307:312 (1%)	view

CasualMLDuplication

CasualML
Duplication