# opendatalab/MinerU SLOC report

> As of 2026-09-08 (commit 735db71ea6d1), opendatalab/MinerU contains 108,813 total lines: 60,584 code, 38,510 comments, 9,719 blank, across 257 files in 10 languages (top: Python 96.0%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

opendatalab/MinerU has 60,584 source lines of code out of 108,813 total lines across 257 files, counted from the 735db71ea6d17fad094f82655066b7c8b778d98d ref at commit 735db71ea6d1 by the OctoCounts tokei engine on 2026-09-08. 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 opendatalab/MinerU to commit 735db71ea6d1, 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 55.7% of all lines, comments represent 35.4%, and the repository averages 236 code lines per file. Python accounts for 96.0% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 218 | 69,750 | 58,178 | 2,232 | 9,340 |
| YAML | 5 | 979 | 920 | 19 | 40 |
| JavaScript | 1 | 578 | 494 | 33 | 51 |
| CSS | 1 | 455 | 455 | 0 | 0 |
| Dockerfile | 11 | 358 | 227 | 80 | 51 |
| TOML | 1 | 190 | 176 | 0 | 14 |
| HTML | 1 | 119 | 104 | 6 | 9 |
| JSON | 1 | 30 | 30 | 0 | 0 |
| Markdown | 7 | 935 | 0 | 722 | 213 |
| Plain Text | 11 | 35,419 | 0 | 35,418 | 1 |

Top language (Python 96.0%). Generated at 2026-09-08T15:11:45.357584271+00:00. Canonical report: https://octocounts.com/github/opendatalab/MinerU

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/opendatalab/MinerU/commit/735db71ea6d17fad094f82655066b7c8b778d98d?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 opendatalab/MinerU have?

opendatalab/MinerU has 108,813 total lines, including 60,584 code lines, 38,510 comment lines, and 9,719 blank lines.

### How was the opendatalab/MinerU line count measured?

OctoCounts resolved the public GitHub repository to commit 735db71ea6d1, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for opendatalab/MinerU?

This OctoCounts report was generated from 735db71ea6d17fad094f82655066b7c8b778d98d at commit 735db71ea6d1 on 2026-09-08T15:11:45.357584271+00:00.

## Similar repository reports

- [opendatalab/mineru](https://octocounts.com/github/opendatalab/mineru) — Python, 60,506 code lines
- [nvidia-cosmos/cosmos-transfer1](https://octocounts.com/github/nvidia-cosmos/cosmos-transfer1) — Python, 60,502 code lines
- [mnemosyne-oss/mnemosyne](https://octocounts.com/github/mnemosyne-oss/mnemosyne) — Python, 60,163 code lines
- [oraios/serena](https://octocounts.com/github/oraios/serena) — Python, 61,185 code lines
- [usestrix/strix](https://octocounts.com/github/usestrix/strix) — Python, 59,879 code lines
- [jianchang512/pyvideotrans](https://octocounts.com/github/jianchang512/pyvideotrans) — Python, 59,804 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)
