This page compares the source lines of code (SLOC) of pandas-dev/pandas and pola-rs/polars 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, pandas-dev/pandas contains 344,747 total lines (291,433 code) across 460 files, while pola-rs/polars contains 559,144 total lines (487,184 code) across 2,251 files as of 2026-08-26. pola-rs/polars is about 1.7x the size of pandas-dev/pandas by code lines. Code size is not code quality: a larger count only means more source material, not a better or worse project.
| Metric | pandas-dev/pandas | pola-rs/polars |
|---|---|---|
| Files | 460 | 2,251 |
| Total lines | 344,747 | 559,144 |
| Code lines | 291,433 | 487,184 |
| Comment lines | 19,915 | 15,988 |
| Blank lines | 33,399 | 55,972 |
| Languages counted | 11 | 9 |
Top languages in pandas-dev/pandas: Python (79.6% of code), Cython (15.1% of code), C (2.2% of code). Top languages in pola-rs/polars: Rust (76.4% of code), Python (22.4% of code), TOML (0.9% of code). Python appears in both top language lists; Cython, C, Autoconf, C++ appear only in pandas-dev/pandas's top languages; Rust, TOML, Makefile, Nix appear only in pola-rs/polars's top languages.
Methodology: both counts come from cached OctoCounts reports generated with tokei. pandas-dev/pandas was counted at ref main (commit 361e0a865121) on 2026-08-26; pola-rs/polars was counted at ref main (commit eeabf772341d) 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.
pola-rs/polars has more code: 487,184 code lines versus 291,433 for pandas-dev/pandas, about 1.7x 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 pandas-dev/pandas, pola-rs/polars, or any repository.
Methodology: both counts come from cached OctoCounts reports generated with tokei. pandas-dev/pandas was counted at ref main (commit 361e0a865121) on 2026-08-26; pola-rs/polars was counted at ref main (commit eeabf772341d) 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.