facebookresearch / nevergrad
A Python toolbox for performing gradient-free optimization
Summary
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| Main Code: 16,589 LOC (112 files) = PY (99%) + TOML (<1%) + IN (<1%) | |||
| Duplication: 6% | |||
| File Size: 21% long (>1000 LOC), 34% short (<= 200 LOC) | |||
| Unit Size: 2% long (>100 LOC), 69% short (<= 10 LOC) | |||
| Conditional Complexity: 4% complex (McCabe index > 50), 59% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (30 components) | ||
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3 years, 1 month old
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25% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
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Features of interest:
TODOs
30 files |
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Latest commit date: 2022-01-20
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3
commits
(30 days)
1
contributors
(30 days) |
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