# HKUDS/DeepTutor SLOC report

> As of 2026-10-08 (commit 6cf793bd868b), HKUDS/DeepTutor contains 643,437 total lines: 548,824 code, 40,825 comments, 53,788 blank, across 2,391 files in 16 languages (top: Python 45.7%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

HKUDS/DeepTutor has 548,824 source lines of code out of 643,437 total lines across 2,391 files, counted from the main ref at commit 6cf793bd868b by the OctoCounts tokei engine on 2026-10-08. 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 HKUDS/DeepTutor to commit 6cf793bd868b, 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 85.3% of all lines, comments represent 6.3%, and the repository averages 230 code lines per file. Python accounts for 45.7% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 1,070 | 297,394 | 251,031 | 10,696 | 35,667 |
| TSX | 538 | 149,252 | 133,340 | 8,907 | 7,005 |
| JSON | 20 | 114,334 | 114,334 | 0 | 0 |
| TypeScript | 350 | 49,896 | 40,429 | 5,777 | 3,690 |
| YAML | 161 | 7,133 | 5,689 | 620 | 824 |
| CSS | 4 | 1,991 | 1,544 | 264 | 183 |
| JavaScript | 19 | 1,535 | 1,256 | 153 | 126 |
| TOML | 3 | 653 | 443 | 161 | 49 |
| SVG | 56 | 384 | 371 | 10 | 3 |
| Dockerfile | 1 | 614 | 343 | 194 | 77 |
| Batch | 2 | 36 | 24 | 7 | 5 |
| HTML | 1 | 15 | 15 | 0 | 0 |

Top language (Python 45.7%). Generated at 2026-10-08T23:30:59.826286189+00:00. Canonical report: https://octocounts.com/github/HKUDS/DeepTutor

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/HKUDS/DeepTutor/commit/6cf793bd868ba5ecbe64722936d4be8fab5a01df?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 HKUDS/DeepTutor have?

HKUDS/DeepTutor has 643,437 total lines, including 548,824 code lines, 40,825 comment lines, and 53,788 blank lines.

### How was the HKUDS/DeepTutor line count measured?

OctoCounts resolved the public GitHub repository to commit 6cf793bd868b, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for HKUDS/DeepTutor?

This OctoCounts report was generated from main at commit 6cf793bd868b on 2026-10-08T23:30:59.826286189+00:00.

## Similar repository reports

- [marketcalls/openalgo](https://octocounts.com/github/marketcalls/openalgo) — Python, 556,198 code lines
- [modelscope/FunASR](https://octocounts.com/github/modelscope/FunASR) — Python, 537,351 code lines
- [scipy/scipy](https://octocounts.com/github/scipy/scipy) — Python, 535,597 code lines
- [repowise-dev/repowise](https://octocounts.com/github/repowise-dev/repowise) — Python, 525,990 code lines
- [marin-community/marin](https://octocounts.com/github/marin-community/marin) — Python, 581,171 code lines
- [raullenchai/Rapid-MLX](https://octocounts.com/github/raullenchai/Rapid-MLX) — Python, 593,380 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)
