# lycorp-jp/sim-use SLOC report

> As of 2026-10-06 (commit 3cd50704c292), lycorp-jp/sim-use contains 80,924 total lines: 58,358 code, 14,105 comments, 8,461 blank, across 490 files in 14 languages (top: Swift 80.4%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

lycorp-jp/sim-use has 58,358 source lines of code out of 80,924 total lines across 490 files, counted from the main ref at commit 3cd50704c292 by the OctoCounts tokei engine on 2026-10-06. 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 lycorp-jp/sim-use to commit 3cd50704c292, 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 72.1% of all lines, comments represent 17.4%, and the repository averages 119 code lines per file. Swift accounts for 80.4% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Swift | 374 | 64,577 | 46,913 | 10,948 | 6,716 |
| Shell | 21 | 5,216 | 3,596 | 1,027 | 593 |
| JSON | 21 | 3,081 | 3,081 | 0 | 0 |
| Kotlin | 21 | 2,641 | 1,791 | 623 | 227 |
| Python | 9 | 1,183 | 983 | 35 | 165 |
| TSX | 4 | 1,027 | 849 | 117 | 61 |
| XML | 16 | 578 | 485 | 54 | 39 |
| CSS | 1 | 438 | 375 | 1 | 62 |
| Batch | 2 | 164 | 128 | 0 | 36 |
| TypeScript | 2 | 111 | 76 | 25 | 10 |
| Makefile | 1 | 101 | 44 | 44 | 13 |
| YAML | 1 | 26 | 25 | 0 | 1 |

Top language (Swift 80.4%). Generated at 2026-10-06T18:53:50.119749773+00:00. Canonical report: https://octocounts.com/github/lycorp-jp/sim-use

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/lycorp-jp/sim-use/commit/3cd50704c292ab7502f73962d060960482e43f98?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 lycorp-jp/sim-use have?

lycorp-jp/sim-use has 80,924 total lines, including 58,358 code lines, 14,105 comment lines, and 8,461 blank lines.

### How was the lycorp-jp/sim-use line count measured?

OctoCounts resolved the public GitHub repository to commit 3cd50704c292, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for lycorp-jp/sim-use?

This OctoCounts report was generated from main at commit 3cd50704c292 on 2026-10-06T18:53:50.119749773+00:00.

## Similar repository reports

- [iina/iina](https://octocounts.com/github/iina/iina) — Swift, 59,957 code lines
- [noah-qin/Corta](https://octocounts.com/github/noah-qin/Corta) — Swift, 63,056 code lines
- [willfaust/Madeira](https://octocounts.com/github/willfaust/Madeira) — Swift, 64,250 code lines
- [cclank/tokei](https://octocounts.com/github/cclank/tokei) — Swift, 52,255 code lines
- [OpenEmu/OpenEmu](https://octocounts.com/github/OpenEmu/OpenEmu) — Swift, 51,887 code lines
- [apple/container](https://octocounts.com/github/apple/container) — Swift, 51,278 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)
- [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)
