# alpacahq/example-scalping SLOC report

> As of 2026-09-16 (commit 4d0962785e27), alpacahq/example-scalping contains 423 total lines: 240 code, 113 comments, 70 blank, across 2 files in 2 languages (top: Python 100.0%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

alpacahq/example-scalping has 240 source lines of code out of 423 total lines across 2 files, counted from the 4d0962785e272a01fcb4c89f0e961264e9a91827 ref at commit 4d0962785e27 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 alpacahq/example-scalping to commit 4d0962785e27, 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 small codebase by counted code lines. Code represents 56.7% of all lines, comments represent 26.7%, and the repository averages 120 code lines per file. Python accounts for 100.0% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 1 | 281 | 240 | 4 | 37 |
| Markdown | 1 | 142 | 0 | 109 | 33 |

Top language (Python 100.0%). Generated at 2026-09-16T16:26:43.441443260+00:00. Canonical report: https://octocounts.com/github/alpacahq/example-scalping

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/alpacahq/example-scalping/commit/4d0962785e272a01fcb4c89f0e961264e9a91827?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 alpacahq/example-scalping have?

alpacahq/example-scalping has 423 total lines, including 240 code lines, 113 comment lines, and 70 blank lines.

### How was the alpacahq/example-scalping line count measured?

OctoCounts resolved the public GitHub repository to commit 4d0962785e27, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for alpacahq/example-scalping?

This OctoCounts report was generated from 4d0962785e272a01fcb4c89f0e961264e9a91827 at commit 4d0962785e27 on 2026-09-16T16:26:43.441443260+00:00.

## Similar repository reports

- [wanfangdata/wfdata-open-skills](https://octocounts.com/github/wanfangdata/wfdata-open-skills) — Python, 241 code lines
- [521xueweihan/HelloGitHub](https://octocounts.com/github/521xueweihan/HelloGitHub) — Python, 238 code lines
- [huysh3/sub2api-gpt-image-2](https://octocounts.com/github/huysh3/sub2api-gpt-image-2) — Python, 238 code lines
- [OBenner/data-engineering-interview-questions](https://octocounts.com/github/OBenner/data-engineering-interview-questions) — Python, 257 code lines
- [link89/dlna-cast](https://octocounts.com/github/link89/dlna-cast) — Python, 257 code lines
- [Yuqi-Zhou/Length_Collapse](https://octocounts.com/github/Yuqi-Zhou/Length_Collapse) — Python, 221 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)
