# pytorch/executorch SLOC report

> As of 2026-10-24 (commit ea5cd99bd4bb), pytorch/executorch contains 2,455,719 total lines: 2,177,800 code, 132,925 comments, 144,994 blank, across 6,512 files in 42 languages (top: JSON 57.1%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

pytorch/executorch has 2,177,800 source lines of code out of 2,455,719 total lines across 6,512 files, counted from the main ref at commit ea5cd99bd4bb by the OctoCounts tokei engine on 2026-10-24. 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 pytorch/executorch to commit ea5cd99bd4bb, 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 very large codebase by counted code lines. Code represents 88.7% of all lines, comments represent 5.4%, and the repository averages 334 code lines per file. JSON accounts for 57.1% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| JSON | 97 | 1,242,970 | 1,242,970 | 0 | 0 |
| Python | 2,637 | 534,883 | 425,715 | 35,928 | 73,240 |
| C++ | 1,124 | 280,505 | 224,776 | 26,355 | 29,374 |
| C Header | 1,024 | 146,084 | 98,389 | 31,379 | 16,316 |
| C | 67 | 57,006 | 55,019 | 1,267 | 720 |
| CMake | 175 | 24,526 | 17,544 | 4,476 | 2,506 |
| Bazel | 185 | 19,736 | 17,463 | 901 | 1,372 |
| Objective-C++ | 64 | 20,409 | 16,468 | 1,296 | 2,645 |
| YAML | 229 | 16,856 | 14,598 | 1,015 | 1,243 |
| GLSL | 180 | 21,756 | 13,616 | 3,951 | 4,189 |
| JavaScript | 66 | 11,717 | 10,484 | 494 | 739 |
| Shell | 128 | 14,311 | 10,430 | 1,992 | 1,889 |

Top language (JSON 57.1%). Generated at 2026-10-24T09:54:25.634455519+00:00. Canonical report: https://octocounts.com/github/pytorch/executorch

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/pytorch/executorch/commit/ea5cd99bd4bb2100b486fda30145b641abf95428?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&reportId=e9ccbd68f3535051e89aa44f135b2289d29a39f2887f6fcc041e567ec5e2d853).

## Report FAQ

### How many lines of code does pytorch/executorch have?

pytorch/executorch has 2,455,719 total lines, including 2,177,800 code lines, 132,925 comment lines, and 144,994 blank lines.

### How was the pytorch/executorch line count measured?

OctoCounts resolved the public GitHub repository to commit ea5cd99bd4bb, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for pytorch/executorch?

This OctoCounts report was generated from main at commit ea5cd99bd4bb on 2026-10-24T09:54:25.634455519+00:00.

## Similar repository reports

- [BAITC-Hacks/hack-96839d9e-hustlers](https://octocounts.com/github/BAITC-Hacks/hack-96839d9e-hustlers) — JSON, 2,167,611 code lines
- [cheaper-inference/OmniRoute](https://octocounts.com/github/cheaper-inference/OmniRoute) — JSON, 2,137,083 code lines
- [apify/crawlee](https://octocounts.com/github/apify/crawlee) — JSON, 2,283,279 code lines
- [dabiziluzhu55/citypulse-v2x-sim](https://octocounts.com/github/dabiziluzhu55/citypulse-v2x-sim) — JSON, 2,060,853 code lines
- [baserow/baserow](https://octocounts.com/github/baserow/baserow) — JSON, 1,983,405 code lines
- [wikimedia/mediawiki](https://octocounts.com/github/wikimedia/mediawiki) — JSON, 1,950,977 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)
- [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)
