# k2-fsa/sherpa-onnx SLOC report

> As of 2026-09-07 (commit df3a2636074a), k2-fsa/sherpa-onnx contains 448,266 total lines: 328,396 code, 44,150 comments, 75,720 blank, across 4,498 files in 37 languages (top: C++ 26.9%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

k2-fsa/sherpa-onnx has 328,396 source lines of code out of 448,266 total lines across 4,498 files, counted from the df3a2636074ae9bbf84c03f66b9d8a66290af077 ref at commit df3a2636074a by the OctoCounts tokei engine on 2026-09-07. 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 k2-fsa/sherpa-onnx to commit df3a2636074a, 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 large codebase by counted code lines. Code represents 73.3% of all lines, comments represent 9.8%, and the repository averages 73 code lines per file. C++ accounts for 26.9% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| C++ | 597 | 114,996 | 88,229 | 5,885 | 20,882 |
| Python | 352 | 68,911 | 55,888 | 2,207 | 10,816 |
| C Header | 527 | 46,353 | 27,672 | 9,822 | 8,859 |
| Dart | 255 | 32,497 | 25,755 | 2,081 | 4,661 |
| Shell | 565 | 24,800 | 17,658 | 2,475 | 4,667 |
| JavaScript | 194 | 22,982 | 16,515 | 2,808 | 3,659 |
| Rust | 90 | 15,338 | 12,716 | 581 | 2,041 |
| Kotlin | 197 | 15,172 | 12,131 | 1,038 | 2,003 |
| CMake | 134 | 12,829 | 9,384 | 1,542 | 1,903 |
| Java | 180 | 12,620 | 9,290 | 831 | 2,499 |
| Pascal | 64 | 11,466 | 7,698 | 1,762 | 2,006 |
| C# | 137 | 9,732 | 7,265 | 738 | 1,729 |

Top language (C++ 26.9%). Generated at 2026-09-07T19:55:12.838459576+00:00. Canonical report: https://octocounts.com/github/k2-fsa/sherpa-onnx

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/k2-fsa/sherpa-onnx/commit/df3a2636074ae9bbf84c03f66b9d8a66290af077?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 k2-fsa/sherpa-onnx have?

k2-fsa/sherpa-onnx has 448,266 total lines, including 328,396 code lines, 44,150 comment lines, and 75,720 blank lines.

### How was the k2-fsa/sherpa-onnx line count measured?

OctoCounts resolved the public GitHub repository to commit df3a2636074a, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for k2-fsa/sherpa-onnx?

This OctoCounts report was generated from df3a2636074ae9bbf84c03f66b9d8a66290af077 at commit df3a2636074a on 2026-09-07T19:55:12.838459576+00:00.

## Similar repository reports

- [gammasoft71/xtd](https://octocounts.com/github/gammasoft71/xtd) — C++, 304,708 code lines
- [memgraph/memgraph](https://octocounts.com/github/memgraph/memgraph) — C++, 299,153 code lines
- [YimMenu/YimMenuV2](https://octocounts.com/github/YimMenu/YimMenuV2) — C++, 357,897 code lines
- [electronicarts/CnC_Red_Alert](https://octocounts.com/github/electronicarts/CnC_Red_Alert) — C++, 368,288 code lines
- [Ominus-tch/Piano-Visualizer](https://octocounts.com/github/Ominus-tch/Piano-Visualizer) — C++, 277,221 code lines
- [ggml-org/ggml](https://octocounts.com/github/ggml-org/ggml) — C++, 269,756 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)
- [Electron vs Tauri](https://octocounts.com/compare/electron-vs-tauri)
- [Godot vs Bevy](https://octocounts.com/compare/godot-vs-bevy)
- [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)