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activeloopai / deeplake

cppmainf432041192.9K linessynced 4h ago

Code health

8.1out of 10Excellent

This codebase scores 8.1 out of 10 on defect risk, which we rate excellent. It also scores maintainability 8.7 and static performance risk 9.9 out of 10. The three are scored separately and never blended into one number.

Full health report →
Documentation1,536pages0 with model-written prose, 1,536 built from the indexDead code802exportsUnused exports that nothing in the graph reaches
Lines of code
192.9K
Files
856
Symbols
13,494
Modules
7
Languages
12

Recent activity

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Commits

No commits indexed yet.

Decisions

  • Avoid logs directoryproposed · 4h ago
  • Enable and then remove TMATEproposed · 4h ago
  • Fix environment variablesproposed · 4h ago
  • Avoid running as rootproposed · 4h ago
  • Debug initdb stepproposed · 4h ago
  • Add numpy dependencyproposed · 4h ago

Needs attention

44 open
  • medium severity. ProposedAvoid logs directoryAuto-proposed decision awaiting review
  • medium severity. ProposedEnable and then remove TMATEAuto-proposed decision awaiting review
  • medium severity. ProposedFix environment variablesAuto-proposed decision awaiting review
  • medium severity. ProposedAvoid running as rootAuto-proposed decision awaiting review
  • medium severity. ProposedDebug initdb stepAuto-proposed decision awaiting review

Composition

Open the graph →
cpp 56%python 14%sql 10%c 8%markdown 6%Other 6%

Explore this codebase

  • Docs1,536 pages across 7 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 11 entry points→
  • Code healthPer-file scores, 1,412 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→