# matplotlib/matplotlib SLOC report

> As of 2026-09-17 (commit cfa473e42fa4), matplotlib/matplotlib contains 332,379 total lines: 256,762 code, 33,390 comments, 42,227 blank, across 1,232 files in 21 languages (top: Python 69.7%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

matplotlib/matplotlib has 256,762 source lines of code out of 332,379 total lines across 1,232 files, counted from the cfa473e42fa41572d9acbd8d6b7be6f1489dee46 ref at commit cfa473e42fa4 by the OctoCounts tokei engine on 2026-09-17. 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 matplotlib/matplotlib to commit cfa473e42fa4, 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 77.2% of all lines, comments represent 10.0%, and the repository averages 208 code lines per file. Python accounts for 69.7% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 870 | 227,462 | 178,941 | 22,574 | 25,947 |
| C Header | 156 | 55,832 | 40,134 | 7,718 | 7,980 |
| C++ | 55 | 33,003 | 24,518 | 2,103 | 6,382 |
| JSON | 9 | 4,428 | 4,428 | 0 | 0 |
| ReStructuredText | 54 | 4,654 | 3,472 | 0 | 1,182 |
| Objective-C | 1 | 2,026 | 1,675 | 124 | 227 |
| SVG | 16 | 1,085 | 1,045 | 3 | 37 |
| JavaScript | 3 | 1,001 | 767 | 104 | 130 |
| Meson | 23 | 811 | 715 | 36 | 60 |
| TOML | 1 | 497 | 388 | 80 | 29 |
| CSS | 5 | 356 | 244 | 49 | 63 |
| YAML | 2 | 233 | 200 | 16 | 17 |

Top language (Python 69.7%). Generated at 2026-09-17T20:06:27.671685583+00:00. Canonical report: https://octocounts.com/github/matplotlib/matplotlib

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/matplotlib/matplotlib/commit/cfa473e42fa41572d9acbd8d6b7be6f1489dee46?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 matplotlib/matplotlib have?

matplotlib/matplotlib has 332,379 total lines, including 256,762 code lines, 33,390 comment lines, and 42,227 blank lines.

### How was the matplotlib/matplotlib line count measured?

OctoCounts resolved the public GitHub repository to commit cfa473e42fa4, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for matplotlib/matplotlib?

This OctoCounts report was generated from cfa473e42fa41572d9acbd8d6b7be6f1489dee46 at commit cfa473e42fa4 on 2026-09-17T20:06:27.671685583+00:00.

## Similar repository reports

- [experientiallabs/experiential](https://octocounts.com/github/experientiallabs/experiential) — Python, 255,796 code lines
- [ZhuLinsen/daily_stock_analysis](https://octocounts.com/github/ZhuLinsen/daily_stock_analysis) — Python, 255,502 code lines
- [bytedance/deer-flow](https://octocounts.com/github/bytedance/deer-flow) — Python, 260,633 code lines
- [openai/openai-python](https://octocounts.com/github/openai/openai-python) — Python, 263,522 code lines
- [langchain-ai/deepagents](https://octocounts.com/github/langchain-ai/deepagents) — Python, 244,556 code lines
- [topoteretes/cognee](https://octocounts.com/github/topoteretes/cognee) — Python, 244,313 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)
