This page compares the source lines of code (SLOC) of astral-sh/uv and python-poetry/poetry using cached OctoCounts reports. Code size is not code quality: a larger count only means more source material, not a better or worse project.
As of 2026-08-26, astral-sh/uv contains 408,364 total lines (350,572 code) across 908 files, while python-poetry/poetry contains 30,220 total lines (20,949 code) across 197 files as of 2026-08-26. astral-sh/uv is about 17x the size of python-poetry/poetry by code lines. Code size is not code quality: a larger count only means more source material, not a better or worse project.
| Metric | astral-sh/uv | python-poetry/poetry |
|---|---|---|
| Files | 908 | 197 |
| Total lines | 408,364 | 30,220 |
| Code lines | 350,572 | 20,949 |
| Comment lines | 25,637 | 3,357 |
| Blank lines | 32,155 | 5,914 |
| Languages counted | 12 | 4 |
Top languages in astral-sh/uv: Rust (65.6% of code), JSON (27.8% of code), YAML (2.9% of code). Top languages in python-poetry/poetry: Python (97.2% of code), JSON (1.9% of code), TOML (0.9% of code). JSON, Python, TOML appear in both top language lists; Rust, YAML appear only in astral-sh/uv's top languages; Markdown appears only in python-poetry/poetry's top languages.
Methodology: both counts come from cached OctoCounts reports generated with tokei. astral-sh/uv was counted at ref main (commit 0697445cfef3) on 2026-08-26; python-poetry/poetry was counted at ref main (commit 5370f1397073) on 2026-08-26. See the counting methodology for ignored directories and analysis options.
Evidence and next steps:
Note: code size is not code quality. OctoCounts only reports reproducible line counts and makes no claim that either project is better.
astral-sh/uv has more code: 350,572 code lines versus 20,949 for python-poetry/poetry, about 17x as much, based on cached OctoCounts reports as of 2026-08-26.
Not necessarily. SLOC measures size, not complexity, quality, or maintainability. A larger codebase can mean more features, more generated or vendored code, more verbose language idioms, or more tests — none of which imply the code is harder to work with. Use SLOC to gauge the scale of what you'd be reading or maintaining, not as a quality signal for astral-sh/uv, python-poetry/poetry, or any repository.
Methodology: both counts come from cached OctoCounts reports generated with tokei. astral-sh/uv was counted at ref main (commit 0697445cfef3) on 2026-08-26; python-poetry/poetry was counted at ref main (commit 5370f1397073) on 2026-08-26. See the counting methodology for ignored directories and analysis options.
Yes. This page shows the default branch for each repository. Use the interactive comparison tool to pick any public GitHub repository, branch, tag, or commit SHA for both sides and get a fresh side-by-side report.