# meta-recsys/generative-recommenders SLOC report

> As of 2026-10-22 (commit f88532f2eea5), meta-recsys/generative-recommenders contains 87,524 total lines: 70,425 code, 9,132 comments, 7,967 blank, across 363 files in 13 languages (top: Python 69.9%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

meta-recsys/generative-recommenders has 70,425 source lines of code out of 87,524 total lines across 363 files, counted from the main ref at commit f88532f2eea5 by the OctoCounts tokei engine on 2026-10-22. 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 meta-recsys/generative-recommenders to commit f88532f2eea5, 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 80.5% of all lines, comments represent 10.4%, and the repository averages 194 code lines per file. Python accounts for 69.9% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 197 | 58,704 | 49,237 | 4,037 | 5,430 |
| C Header | 41 | 14,872 | 11,754 | 1,980 | 1,138 |
| C++ | 27 | 9,483 | 7,706 | 964 | 813 |
| CUDA | 73 | 2,974 | 1,445 | 1,262 | 267 |
| Jupyter Notebooks | 1 | 98 | 78 | 7 | 13 |
| CMake | 1 | 113 | 70 | 20 | 23 |
| SVG | 1 | 85 | 57 | 28 | 0 |
| TOML | 2 | 60 | 53 | 0 | 7 |
| Shell | 2 | 42 | 14 | 28 | 0 |
| Dockerfile | 1 | 9 | 9 | 0 | 0 |
| Autoconf | 1 | 2 | 2 | 0 | 0 |
| Markdown | 12 | 1,072 | 0 | 796 | 276 |

Top language (Python 69.9%). Generated at 2026-10-22T06:07:59.868384393+00:00. Canonical report: https://octocounts.com/github/meta-recsys/generative-recommenders

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/meta-recsys/generative-recommenders/commit/f88532f2eea591361dd8796444971f66df82fe5d?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=f39d2561ab0cf299b4b473205151defdd6ff420c4b6bdea2205bb9cddf367b40).

## Report FAQ

### How many lines of code does meta-recsys/generative-recommenders have?

meta-recsys/generative-recommenders has 87,524 total lines, including 70,425 code lines, 9,132 comment lines, and 7,967 blank lines.

### How was the meta-recsys/generative-recommenders line count measured?

OctoCounts resolved the public GitHub repository to commit f88532f2eea5, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for meta-recsys/generative-recommenders?

This OctoCounts report was generated from main at commit f88532f2eea5 on 2026-10-22T06:07:59.868384393+00:00.

## Similar repository reports

- [henriquesebastiao/downtify](https://octocounts.com/github/henriquesebastiao/downtify) — Python, 70,854 code lines
- [ManimCommunity/manim](https://octocounts.com/github/ManimCommunity/manim) — Python, 71,118 code lines
- [verl-project/verl-recipe](https://octocounts.com/github/verl-project/verl-recipe) — Python, 71,152 code lines
- [cathrynlavery/diagram-design](https://octocounts.com/github/cathrynlavery/diagram-design) — Python, 71,290 code lines
- [Lightricks/LTX-2](https://octocounts.com/github/Lightricks/LTX-2) — Python, 71,741 code lines
- [LeonChaoX/qinyan-academic-skills](https://octocounts.com/github/LeonChaoX/qinyan-academic-skills) — Python, 71,845 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)
