Uber / causalml
Uplift modeling and causal inference with machine learning algorithms
GitHub Repo
14K
lines of main code
73 files
1.8K
lines of test code
20 files
378
lines of other code
11 files
89%
main code touched
1 year (12K LOC)
17%
new main code
1 year (2.5K LOC)
1
recent contributors
past 30 days
5y
age
1,730 days
8.1K
py
838
yml
PXD
212
pxd
64
toml
IN
6
in
CFG
4
cfg

github actions
make


Main Code: 13,745 LOC (73 files) = PY (58%) + PYX (33%) + YML (6%) + PXD (1%) + TOML (<1%) + IN (<1%) + CFG (<1%)
Secondary code: Test: 1,842 LOC (20); Generated: 0 LOC (0); Build & Deploy: 0 LOC (0); Other: 378 LOC (11);
Duplication: 34%
File Size: 20% long (>1000 LOC), 23% short (<= 200 LOC)
Unit Size: 13% long (>100 LOC), 45% short (<= 10 LOC)
Conditional Complexity: 10% complex (McCabe index > 50), 60% simple (McCabe index <= 5)
Logical Component Decomposition: primary (3 components)

4 years, 9 months old

  • 82% of code older than 365 days
  • 10% of code not updated in the past 365 days

3% of code updated more than 50 times

Also see temporal dependencies for files frequently changed in same commits.
Goals: Keep the system simple and easy to change (4)
Straight_Line
Features of interest:
TODOs
3 files

generated by sokrates.dev (configuration) on 2024-04-03