# zilliztech/memsearch SLOC report

> As of 2026-09-06 (commit 6f86211d4145), zilliztech/memsearch contains 27,723 total lines: 17,053 code, 6,326 comments, 4,344 blank, across 190 files in 9 languages (top: Python 60.3%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

zilliztech/memsearch has 17,053 source lines of code out of 27,723 total lines across 190 files, counted from the 6f86211d4145fd534c2f76425f033faf313ea331 ref at commit 6f86211d4145 by the OctoCounts tokei engine on 2026-09-06. The report is cached by commit, tokei version, and analysis options, so recounting the same revision returns exactly these numbers.

OctoCounts produced this report by resolving zilliztech/memsearch to commit 6f86211d4145, downloading the repository source archive, and counting every source file with tokei, the open-source line counter written in Rust. The table below breaks the count down by programming language into files, total lines, code lines, comment lines, and blank lines, so the figures can be compared across languages and projects. Results are cached by commit, tokei version, and analysis options, so counting the same revision again reproduces exactly these numbers.

## Repository size insights

This is a medium-sized codebase by counted code lines. Code represents 61.5% of all lines, comments represent 22.8%, and the repository averages 90 code lines per file. Python accounts for 60.3% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 40 | 12,352 | 10,277 | 301 | 1,774 |
| JavaScript | 3 | 2,727 | 2,604 | 84 | 39 |
| Shell | 22 | 3,238 | 2,356 | 527 | 355 |
| TypeScript | 7 | 1,701 | 1,402 | 152 | 147 |
| JSON | 5 | 222 | 222 | 0 | 0 |
| YAML | 2 | 134 | 97 | 31 | 6 |
| TOML | 1 | 107 | 95 | 0 | 12 |
| Markdown | 86 | 6,144 | 0 | 4,289 | 1,855 |
| Plain Text | 24 | 1,098 | 0 | 942 | 156 |

Top language (Python 60.3%). Generated at 2026-09-06T07:59:47.688979057+00:00. Canonical report: https://octocounts.com/github/zilliztech/memsearch

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/zilliztech/memsearch/commit/6f86211d4145fd534c2f76425f033faf313ea331?analysis=%7B%22ignoredDirs%22%3A%5B%5D%2C%22ignoredLanguages%22%3A%5B%5D%2C%22profile%22%3A%22default%22%2C%22includeDocs%22%3Afalse%2C%22includeTests%22%3Afalse%2C%22includeGenerated%22%3Afalse%7D).

## Report FAQ

### How many lines of code does zilliztech/memsearch have?

zilliztech/memsearch has 27,723 total lines, including 17,053 code lines, 6,326 comment lines, and 4,344 blank lines.

### How was the zilliztech/memsearch line count measured?

OctoCounts resolved the public GitHub repository to commit 6f86211d4145, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for zilliztech/memsearch?

This OctoCounts report was generated from 6f86211d4145fd534c2f76425f033faf313ea331 at commit 6f86211d4145 on 2026-09-06T07:59:47.688979057+00:00.

## Similar repository reports

- [DeepBlueDynamics/grubcrawler](https://octocounts.com/github/DeepBlueDynamics/grubcrawler) — Python, 17,046 code lines
- [zhinkgit/embeddedskills](https://octocounts.com/github/zhinkgit/embeddedskills) — Python, 17,227 code lines
- [fsspec/filesystem_spec](https://octocounts.com/github/fsspec/filesystem_spec) — Python, 16,869 code lines
- [FalkorDB/code-graph](https://octocounts.com/github/FalkorDB/code-graph) — Python, 17,420 code lines
- [Tencent/WeMM-Embedding](https://octocounts.com/github/Tencent/WeMM-Embedding) — Python, 16,606 code lines
- [ReturnFI/Blitz](https://octocounts.com/github/ReturnFI/Blitz) — Python, 16,590 code lines

## Related OctoCounts pages

- [Recently analyzed repositories](https://octocounts.com/recent)
- [Popular SLOC reports](https://octocounts.com/popular)
- [Trending GitHub repositories](https://octocounts.com/trending)
- [Hall of Monoliths](https://octocounts.com/hall-of-monoliths)
- [TensorFlow vs PyTorch](https://octocounts.com/compare/tensorflow-vs-pytorch)
- [Django vs Ruby on Rails](https://octocounts.com/compare/django-vs-rails)
- [Laravel vs Django](https://octocounts.com/compare/laravel-vs-django)
- [GitHub SLOC counter guide](https://octocounts.com/docs/github-sloc-counter)
- [Counting methodology](https://octocounts.com/docs/methodology)
- [SLOC and code metrics glossary](https://octocounts.com/docs/glossary)
- [Original research: how filtering changes SLOC counts](https://octocounts.com/research)
- [OctoCounts API docs](https://octocounts.com/docs/api)
