# Qalculate/libqalculate SLOC report

> As of 2026-10-22 (commit 132d7b2f150d), Qalculate/libqalculate contains 339,023 total lines: 237,639 code, 57,843 comments, 43,541 blank, across 114 files in 10 languages (top: C++ 48.9%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

Qalculate/libqalculate has 237,639 source lines of code out of 339,023 total lines across 114 files, counted from the master ref at commit 132d7b2f150d by the OctoCounts tokei engine on 2026-10-22. 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 Qalculate/libqalculate to commit 132d7b2f150d, 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 70.1% of all lines, comments represent 17.1%, and the repository averages 2,085 code lines per file. C++ accounts for 48.9% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| C++ | 48 | 122,121 | 116,094 | 3,027 | 3,000 |
| PO File | 20 | 181,464 | 89,781 | 52,092 | 39,591 |
| C Header | 22 | 20,270 | 17,005 | 2,487 | 778 |
| Autoconf | 11 | 14,011 | 13,974 | 2 | 35 |
| JSON | 1 | 345 | 345 | 0 | 0 |
| M4 | 2 | 269 | 159 | 88 | 22 |
| Automake | 7 | 192 | 129 | 18 | 45 |
| Shell | 1 | 133 | 112 | 3 | 18 |
| XML | 1 | 40 | 40 | 0 | 0 |
| Markdown | 1 | 178 | 0 | 126 | 52 |

Top language (C++ 48.9%). Generated at 2026-10-22T06:42:31.988958206+00:00. Canonical report: https://octocounts.com/github/Qalculate/libqalculate

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/Qalculate/libqalculate/commit/132d7b2f150de1ace81c02a93701a012e10fb97c?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=d312e8c70fb97d31a0294a925645ba0ca794da949a2fa273fd38c9a09f706f9d).

## Report FAQ

### How many lines of code does Qalculate/libqalculate have?

Qalculate/libqalculate has 339,023 total lines, including 237,639 code lines, 57,843 comment lines, and 43,541 blank lines.

### How was the Qalculate/libqalculate line count measured?

OctoCounts resolved the public GitHub repository to commit 132d7b2f150d, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for Qalculate/libqalculate?

This OctoCounts report was generated from master at commit 132d7b2f150d on 2026-10-22T06:42:31.988958206+00:00.

## Similar repository reports

- [centreon/centreon-collect](https://octocounts.com/github/centreon/centreon-collect) — C++, 233,522 code lines
- [vicinaehq/vicinae](https://octocounts.com/github/vicinaehq/vicinae) — C++, 229,993 code lines
- [gscept/nebula](https://octocounts.com/github/gscept/nebula) — C++, 254,159 code lines
- [abseil/abseil-cpp](https://octocounts.com/github/abseil/abseil-cpp) — C++, 220,547 code lines
- [Mrsuss60/bloodborne_pc_windows_port](https://octocounts.com/github/Mrsuss60/bloodborne_pc_windows_port) — C++, 219,789 code lines
- [metasequoiaime/msime-windows](https://octocounts.com/github/metasequoiaime/msime-windows) — C++, 260,053 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)
- [Electron vs Tauri](https://octocounts.com/compare/electron-vs-tauri)
- [Godot vs Bevy](https://octocounts.com/compare/godot-vs-bevy)
- [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)