activeloopai / deeplake
Code health
This codebase scores 8.0 out of 10 for code health, which we rate good. It also scores maintainability 8.6 and static performance 9.9 out of 10. The three are scored separately and never blended into one number.
Do next
1 thing worth doing this quarter.
Worth planning
Delete 800 unused symbols and files (14,552 lines)
Nothing in the graph reaches them, across 102 files; every reader and agent pays to skip them.
- symbols
- 800
- lines
- 14,552
- safe to delete
- Yes(inferred)
Medium effort
Improve what Repowise can see
Add a test coverage report
Without one, Repowise cannot tell tested code from untested code, so every test-related action says “unknown”.
- line coverage
- Unknown, no report
Small effortReview the 24 proposed decisions
None is accepted yet, so nothing can drift from one and agents get no enforced guidance from them.
- proposed
- 24
- accepted
- 0
Medium effort
- Lines of code
- 192.9K
Recent activity
All commitsEverything we found
2,519 open
Every detector's open count by area, each with its worst example. An inventory, not a to-do list: the actions above are the part worth doing.
- worst item is critical severity. Code health828Untested hotspot · cpp/deeplake_pg/nd_utils.hpp23 findings · 9.2 deducted
- worst item is medium severity. Refactoring191sliced_array+1.5 health, S effort · cpp/nd/impl/sliced_array.hpp
- worst item is medium severity. Decisions24Avoid logs directory24 awaiting review
- worst item is medium severity. Ownership660cpp/3rd_party/boost_json_impl.cpp100% single-owner concentration, not touched in 90 days
- worst item is low severity. Dead code816python/deeplake/formats.pyiUnreachable symbol (40 lines)
Composition
Open the graphExplore this codebase
- Docs1,536 pages across 5 modules
- ChatAsk this codebase a question and get an answer with its sources.
- Files856 files with per-file docs, health and history
- ArchitectureDependency graph, layers, and 4 entry points
- Code healthPer-file scores, 1,147 open findings, coverage and refactoring targets
- Knowledge graphEntities, communities, and the paths between them
- Change couplingFiles that keep changing together, mined from commit history
- CommitsChange-risk ranked history with agent provenance
- ContributorsBus factor, per-file maintainers, and the human/agent split
- StatsSize class, origin, lifetime churn, rhythm and records
- CostsWhat indexing this snapshot cost, by model and by run.