# port-labs/ocean SLOC report

> port-labs/ocean: 148,802 code lines at commit b5ad6809a50e, counted with tokei-14.0.0 on 2026-10-22. Saved result 2249ac07014d8c81bad79c315b590dbdeb87360c25a8de653c5a65499c4f6e19.

port-labs/ocean has 148,802 source lines of code out of 328,197 total lines across 2,160 files, counted from the main ref at commit b5ad6809a50e by the OctoCounts tokei engine on 2026-10-22. 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 port-labs/ocean to commit b5ad6809a50e, 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 45.3% of all lines, comments represent 18.7%, and the repository averages 69 code lines per file. Python accounts for 85.9% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 1,676 | 151,273 | 127,772 | 1,577 | 21,924 |
| JSON | 143 | 10,875 | 10,875 | 0 | 0 |
| TOML | 104 | 6,342 | 5,179 | 211 | 952 |
| YAML | 52 | 2,423 | 2,351 | 33 | 39 |
| Shell | 16 | 1,534 | 1,161 | 116 | 257 |
| HCL | 10 | 822 | 685 | 10 | 127 |
| SVG | 5 | 394 | 394 | 0 | 0 |
| Makefile | 14 | 404 | 331 | 12 | 61 |
| Dockerfile | 1 | 94 | 54 | 20 | 20 |
| Markdown | 139 | 154,036 | 0 | 59,518 | 94,518 |

Top language (Python 85.9%). Generated at 2026-10-22T06:46:27.709870619Z. Canonical report: https://octocounts.com/github/port-labs/ocean/commit/b5ad6809a50ec6db89b3babd0c04aa0790993a94?reportId=2249ac07014d8c81bad79c315b590dbdeb87360c25a8de653c5a65499c4f6e19&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/port-labs/ocean/commit/b5ad6809a50ec6db89b3babd0c04aa0790993a94?reportId=2249ac07014d8c81bad79c315b590dbdeb87360c25a8de653c5a65499c4f6e19&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 port-labs/ocean have?

port-labs/ocean has 328,197 total lines, including 148,802 code lines, 61,497 comment lines, and 117,898 blank lines.

### How was the port-labs/ocean line count measured?

OctoCounts resolved the public GitHub repository to commit b5ad6809a50e, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for port-labs/ocean?

This OctoCounts report was generated from main at commit b5ad6809a50e on 2026-10-22T06:46:27.709870619Z.

## Similar repository reports

- [radixark/miles](https://octocounts.com/github/radixark/miles) — Python, 148,712 code lines
- [iws3/MarkGPT](https://octocounts.com/github/iws3/MarkGPT) — Python, 148,495 code lines
- [openai/openai-agents-python](https://octocounts.com/github/openai/openai-agents-python) — Python, 150,104 code lines
- [huggingface/text-generation-inference](https://octocounts.com/github/huggingface/text-generation-inference) — Python, 150,835 code lines
- [PoxenStudio/mybooks](https://octocounts.com/github/PoxenStudio/mybooks) — Python, 152,016 code lines
- [mesonbuild/meson](https://octocounts.com/github/mesonbuild/meson) — Python, 144,821 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)