awslabs / gluon-ts
Probabilistic time series modeling in Python
Summary
   |
|||
| Main Code: 53,539 LOC (454 files) = PY (99%) + R (<1%) + CFG (<1%) + PYI (<1%) + TOML (<1%) + IN (<1%) Secondary code: Test: 26,646 LOC (170); Generated: 0 LOC (0); Build & Deploy: 137 LOC (5); Other: 12,973 LOC (127); |
|||
| Duplication: 38% | |||
| File Size: 0% long (>1000 LOC), 44% short (<= 200 LOC) | |||
| Unit Size: 3% long (>100 LOC), 73% short (<= 10 LOC) | |||
| Conditional Complexity: 1% complex (McCabe index > 50), 85% simple (McCabe index <= 5) | |||
|
|
Logical Component Decomposition: primary (14 components) | ||
|
|
2 years, 8 months old
|
||
|
|
0% 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) | |||
|
Features of interest:
TODOs
64 files |
|||
Latest commit date: 2022-01-27
|
7
commits
(30 days)
4
contributors
(30 days) |
|