# zxkmm/kicad-harness SLOC report

> zxkmm/kicad-harness: 24,115 code lines at commit db4bcdba4417, counted with tokei-14.0.0 on 2026-10-12. Saved result 4d1a53e98e528fe4a83e0de5df3a748e84d911bb661b58d9423d6c4dba145da4.

zxkmm/kicad-harness has 24,115 source lines of code out of 33,065 total lines across 39 files, counted from the main ref at commit db4bcdba4417 by the OctoCounts tokei engine on 2026-10-12. 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 zxkmm/kicad-harness to commit db4bcdba4417, 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 72.9% of all lines, comments represent 4.6%, and the repository averages 618 code lines per file. Python accounts for 99.8% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 33 | 32,185 | 24,057 | 891 | 7,237 |
| Shell | 1 | 57 | 44 | 4 | 9 |
| TOML | 1 | 17 | 14 | 0 | 3 |
| Markdown | 4 | 806 | 0 | 618 | 188 |

Top language (Python 99.8%). Generated at 2026-10-12T08:04:55.398778396Z. Canonical report: https://octocounts.com/github/zxkmm/kicad-harness/commit/db4bcdba4417343441a221b93f245808b77f3f28?reportId=4d1a53e98e528fe4a83e0de5df3a748e84d911bb661b58d9423d6c4dba145da4&analysis=%7B%22profile%22%3A%22default%22%2C%22ignoredDirs%22%3A%5B%5D%2C%22includeDocs%22%3Afalse%2C%22includeTests%22%3Afalse%2C%22ignoredLanguages%22%3A%5B%5D%2C%22includeGenerated%22%3Afalse%7D

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/zxkmm/kicad-harness/commit/db4bcdba4417343441a221b93f245808b77f3f28?reportId=4d1a53e98e528fe4a83e0de5df3a748e84d911bb661b58d9423d6c4dba145da4&analysis=%7B%22profile%22%3A%22default%22%2C%22ignoredDirs%22%3A%5B%5D%2C%22includeDocs%22%3Afalse%2C%22includeTests%22%3Afalse%2C%22ignoredLanguages%22%3A%5B%5D%2C%22includeGenerated%22%3Afalse%7D).

## Report FAQ

### How many lines of code does zxkmm/kicad-harness have?

zxkmm/kicad-harness has 33,065 total lines, including 24,115 code lines, 1,513 comment lines, and 7,437 blank lines.

### How was the zxkmm/kicad-harness line count measured?

OctoCounts resolved the public GitHub repository to commit db4bcdba4417, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for zxkmm/kicad-harness?

This OctoCounts report was generated from main at commit db4bcdba4417 on 2026-10-12T08:04:55.398778396Z.

## Similar repository reports

- [VoxHash/Telegram-Multi-Account-Message-Sender](https://octocounts.com/github/VoxHash/Telegram-Multi-Account-Message-Sender) — Python, 24,155 code lines
- [makeentropy/JMKstudio-Project-0-pool-0-DataSet-0](https://octocounts.com/github/makeentropy/JMKstudio-Project-0-pool-0-DataSet-0) — Python, 24,021 code lines
- [3b1b/manim](https://octocounts.com/github/3b1b/manim) — Python, 23,952 code lines
- [guillaumemeyer/watermarks-remover](https://octocounts.com/github/guillaumemeyer/watermarks-remover) — Python, 24,390 code lines
- [MG1937/ASC](https://octocounts.com/github/MG1937/ASC) — Python, 24,460 code lines
- [yutori-ai/yutori-sdk-python](https://octocounts.com/github/yutori-ai/yutori-sdk-python) — Python, 23,749 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)