# Kuaishou-OneRec/OneReason_Eval_Benchmark SLOC report

> As of 2026-10-05 (commit 89e09b0b8e4c), Kuaishou-OneRec/OneReason_Eval_Benchmark contains 52,649 total lines: 42,636 code, 3,766 comments, 6,247 blank, across 216 files in 7 languages (top: Python 95.3%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

Kuaishou-OneRec/OneReason_Eval_Benchmark has 42,636 source lines of code out of 52,649 total lines across 216 files, counted from the main ref at commit 89e09b0b8e4c by the OctoCounts tokei engine on 2026-10-05. 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 Kuaishou-OneRec/OneReason_Eval_Benchmark to commit 89e09b0b8e4c, 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 81.0% of all lines, comments represent 7.2%, and the repository averages 197 code lines per file. Python accounts for 95.3% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 171 | 48,155 | 40,635 | 2,179 | 5,341 |
| Shell | 17 | 2,861 | 1,935 | 467 | 459 |
| JSON | 2 | 26 | 26 | 0 | 0 |
| TOML | 1 | 29 | 25 | 0 | 4 |
| SVG | 15 | 15 | 15 | 0 | 0 |
| Markdown | 9 | 1,547 | 0 | 1,105 | 442 |
| Plain Text | 1 | 16 | 0 | 15 | 1 |

Top language (Python 95.3%). Generated at 2026-10-05T06:08:41.304450721+00:00. Canonical report: https://octocounts.com/github/Kuaishou-OneRec/OneReason_Eval_Benchmark

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/Kuaishou-OneRec/OneReason_Eval_Benchmark/commit/89e09b0b8e4cd3e584ba70c2f46728e250e705b7?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&reportId=3b4ce431b86b5efcf5cb8c00dfa234481efde6a95c8e8f3eff1c4d15a15e04b3).

## Report FAQ

### How many lines of code does Kuaishou-OneRec/OneReason_Eval_Benchmark have?

Kuaishou-OneRec/OneReason_Eval_Benchmark has 52,649 total lines, including 42,636 code lines, 3,766 comment lines, and 6,247 blank lines.

### How was the Kuaishou-OneRec/OneReason_Eval_Benchmark line count measured?

OctoCounts resolved the public GitHub repository to commit 89e09b0b8e4c, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for Kuaishou-OneRec/OneReason_Eval_Benchmark?

This OctoCounts report was generated from main at commit 89e09b0b8e4c on 2026-10-05T06:08:41.304450721+00:00.

## Similar repository reports

- [bkerler/mtkclient](https://octocounts.com/github/bkerler/mtkclient) — Python, 42,933 code lines
- [jhljx/RecSys-Industrial-Book](https://octocounts.com/github/jhljx/RecSys-Industrial-Book) — Python, 43,080 code lines
- [GodmanAutomations/Kira](https://octocounts.com/github/GodmanAutomations/Kira) — Python, 41,962 code lines
- [shareAI-lab/learn-claude-code](https://octocounts.com/github/shareAI-lab/learn-claude-code) — Python, 41,934 code lines
- [Yuan1z0825/nature-skills](https://octocounts.com/github/Yuan1z0825/nature-skills) — Python, 41,921 code lines
- [markqvist/Reticulum](https://octocounts.com/github/markqvist/Reticulum) — Python, 43,746 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)