# plastic-labs/honcho SLOC report

> As of 2026-09-16 (commit 210b56cf953f), plastic-labs/honcho contains 275,778 total lines: 197,322 code, 42,715 comments, 35,741 blank, across 972 files in 14 languages (top: Python 73.2%). Default configuration. Counted with tokei via OctoCounts.

plastic-labs/honcho has 197,322 source lines of code out of 275,778 total lines across 972 files, counted from the main ref at commit 210b56cf953f by the OctoCounts tokei engine on 2026-09-16. 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 plastic-labs/honcho to commit 210b56cf953f, 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 71.6% of all lines, comments represent 15.5%, and the repository averages 203 code lines per file. Python accounts for 73.2% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 517 | 177,703 | 144,384 | 9,232 | 24,087 |
| JSON | 58 | 38,013 | 38,008 | 0 | 5 |
| TypeScript | 60 | 18,505 | 13,187 | 3,054 | 2,264 |
| SVG | 11 | 556 | 551 | 0 | 5 |
| Shell | 2 | 453 | 435 | 8 | 10 |
| TOML | 10 | 444 | 380 | 16 | 48 |
| YAML | 6 | 324 | 228 | 74 | 22 |
| JavaScript | 1 | 69 | 60 | 5 | 4 |
| Dockerfile | 2 | 96 | 52 | 19 | 25 |
| INI | 1 | 117 | 32 | 61 | 24 |
| SQL | 3 | 11 | 5 | 5 | 1 |
| MDX | 262 | 33,935 | 0 | 26,445 | 7,490 |

Top language (Python 73.2%). Generated at 2026-09-16T16:32:40.878378708+00:00. Canonical report: https://octocounts.com/github/plastic-labs/honcho

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/plastic-labs/honcho/commit/210b56cf953fcf447ffafcb428d4b4f1823b83fd?analysis=%7B%22ignoredDirs%22%3A%5B%5D%2C%22ignoredLanguages%22%3A%5B%5D%2C%22profile%22%3A%22default%22%2C%22includeDocs%22%3Atrue%2C%22includeTests%22%3Atrue%2C%22includeGenerated%22%3Atrue%7D).

## Report FAQ

### How many lines of code does plastic-labs/honcho have?

plastic-labs/honcho has 275,778 total lines, including 197,322 code lines, 42,715 comment lines, and 35,741 blank lines.

### How was the plastic-labs/honcho line count measured?

OctoCounts resolved the public GitHub repository to commit 210b56cf953f, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for plastic-labs/honcho?

This OctoCounts report was generated from main at commit 210b56cf953f on 2026-09-16T16:32:40.878378708+00:00.

## Similar repository reports

- [PrefectHQ/fastmcp](https://octocounts.com/github/PrefectHQ/fastmcp) — Python, 196,705 code lines
- [AstrBotDevs/AstrBot](https://octocounts.com/github/AstrBotDevs/AstrBot) — Python, 196,166 code lines
- [crewaiinc/crewai](https://octocounts.com/github/crewaiinc/crewai) — Python, 198,571 code lines
- [dograh-hq/dograh](https://octocounts.com/github/dograh-hq/dograh) — Python, 199,995 code lines
- [gptme/gptme](https://octocounts.com/github/gptme/gptme) — Python, 200,777 code lines
- [langchain-ai/langchain](https://octocounts.com/github/langchain-ai/langchain) — Python, 201,005 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)
