activeloopai / deeplake
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.
github.com/activeloopai/deeplakeIndexed at f432041Up to date with upstream
About this codebase
856 files and 13,494 symbols in 5 modules, led by C++ (478 files) and Python (123).
Built from the index
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.
On the leaderboards:#1 of 5 C++ repos
Do next
4 things worth doing this quarter.
Worth planning
Break up duckdb_value_to_pg_datum (CCN 49, 418 lines)
cpp/deeplake_pg/duckdb_pg_convert.cpp:363
duckdb_value_to_pg_datum nests its control flow deeply, and part of it is duplicated, so splitting it also removes a copy; 1 file imports it.
- gain
- up to +1.6 health on this file(inferred)
- finding
- Nested complexity
- size
- CCN 49, 418 lines, nests 6 deep
- severity
- high
Medium effort, worth a checkBreak up datum_to_nd (CCN 51, 210 lines)
cpp/deeplake_pg/nd_utils.hpp:574
datum_to_nd nests its control flow deeply, and part of it is duplicated, so splitting it also removes a copy; 8 files import it.
- gain
- up to +0.7 health on this file(inferred)
- finding
- Nested complexity
- size
- CCN 51, 210 lines, nests 5 deep
- severity
- high
Medium effort, worth a checkDelete 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
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Go deeper
- OverviewEverything the index found, what changed this week, commits and decisions.
- DocumentationModule-by-module documentation, 1,536 pages, 0 written by a model.
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[](https://repowise.dev/repo/activeloopai/deeplake?src=badge_card)How activeloopai/deeplake works
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training. This page is a map of the activeloopai/deeplake repository, written primarily in C++, rebuilt from the source each time it is indexed. Repowise parses every symbol, computes a dependency graph, scores per-file code health from complexity, duplication, test coverage and churn, mines git history for hotspots and ownership, and lifts the architectural decisions into documentation you can read here or query through MCP.
The codebase has 856 files and 13,494 symbols in 5 modules, led by C++, Python and C. Code health is 8.0 out of 10, rated good.
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