# kovidgoyal/kitty SLOC report

> As of 2026-09-17 (commit b079feaf43c1), kovidgoyal/kitty contains 375,185 total lines: 272,599 code, 72,261 comments, 30,325 blank, across 910 files in 21 languages (top: Python 27.1%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

kovidgoyal/kitty has 272,599 source lines of code out of 375,185 total lines across 910 files, counted from the b079feaf43c1fc79d616a2acc916856fbf09da1b ref at commit b079feaf43c1 by the OctoCounts tokei engine on 2026-09-17. 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 kovidgoyal/kitty to commit b079feaf43c1, 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 72.7% of all lines, comments represent 19.3%, and the repository averages 300 code lines per file. Python accounts for 27.1% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 250 | 88,144 | 73,756 | 2,899 | 11,489 |
| Go | 334 | 81,122 | 72,365 | 2,377 | 6,380 |
| C | 139 | 83,298 | 70,751 | 4,963 | 7,584 |
| C Header | 103 | 47,655 | 36,431 | 8,698 | 2,526 |
| Objective-C | 8 | 10,604 | 8,635 | 772 | 1,197 |
| JSON | 4 | 5,851 | 5,819 | 0 | 32 |
| Slang | 36 | 3,957 | 2,675 | 609 | 673 |
| XML | 4 | 645 | 577 | 3 | 65 |
| Shell | 9 | 709 | 546 | 80 | 83 |
| BASH | 1 | 414 | 332 | 50 | 32 |
| Zsh | 2 | 508 | 263 | 206 | 39 |
| Fish | 4 | 295 | 243 | 27 | 25 |

Top language (Python 27.1%). Generated at 2026-09-17T01:27:42.401014888+00:00. Canonical report: https://octocounts.com/github/kovidgoyal/kitty

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/kovidgoyal/kitty/commit/b079feaf43c1fc79d616a2acc916856fbf09da1b?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 kovidgoyal/kitty have?

kovidgoyal/kitty has 375,185 total lines, including 272,599 code lines, 72,261 comment lines, and 30,325 blank lines.

### How was the kovidgoyal/kitty line count measured?

OctoCounts resolved the public GitHub repository to commit b079feaf43c1, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for kovidgoyal/kitty?

This OctoCounts report was generated from b079feaf43c1fc79d616a2acc916856fbf09da1b at commit b079feaf43c1 on 2026-09-17T01:27:42.401014888+00:00.

## Similar repository reports

- [angr/angr](https://octocounts.com/github/angr/angr) — Python, 274,750 code lines
- [alirezarezvani/claude-skills](https://octocounts.com/github/alirezarezvani/claude-skills) — Python, 277,686 code lines
- [imbad0202/academic-research-skills](https://octocounts.com/github/imbad0202/academic-research-skills) — Python, 279,102 code lines
- [openai/openai-python](https://octocounts.com/github/openai/openai-python) — Python, 263,522 code lines
- [bytedance/deer-flow](https://octocounts.com/github/bytedance/deer-flow) — Python, 260,633 code lines
- [Imbad0202/academic-research-skills](https://octocounts.com/github/Imbad0202/academic-research-skills) — Python, 285,318 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)
