This page compares the source lines of code (SLOC) of pallets/flask and django/django 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, pallets/flask contains 12,777 total lines (10,176 code) across 61 files, while django/django contains 543,623 total lines (392,744 code) across 3,582 files as of 2026-09-08. django/django is about 39x the size of pallets/flask by code lines. Code size is not code quality: a larger count only means more source material, not a better or worse project.
| Metric | pallets/flask | django/django |
|---|---|---|
| Files | 61 | 3,582 |
| Total lines | 12,777 | 543,623 |
| Code lines | 10,176 | 392,744 |
| Comment lines | 793 | 44,971 |
| Blank lines | 1,808 | 105,908 |
| Languages counted | 8 | 12 |
Top languages in pallets/flask: Python (78.7% of code), ReStructuredText (14.5% of code), TOML (3.3% of code). Top languages in django/django: PO File (60.8% of code), Python (31.1% of code), Modelica (5.6% of code). Python, CSS appear in both top language lists; ReStructuredText, TOML, HTML appear only in pallets/flask's top languages; PO File, Modelica, JavaScript appear only in django/django's top languages.
Methodology: both counts come from cached OctoCounts reports generated with tokei. pallets/flask was counted at ref main (commit d318b6834711) on 2026-08-26; django/django was counted at ref 802baf5da5b8d8b44990a8214a43b951e7ab8b39 (commit 802baf5da5b8) on 2026-09-08. 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.
django/django has more code: 392,744 code lines versus 10,176 for pallets/flask, about 39x as much, based on cached OctoCounts reports as of 2026-09-08.
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 pallets/flask, django/django, or any repository.
Methodology: both counts come from cached OctoCounts reports generated with tokei. pallets/flask was counted at ref main (commit d318b6834711) on 2026-08-26; django/django was counted at ref 802baf5da5b8d8b44990a8214a43b951e7ab8b39 (commit 802baf5da5b8) on 2026-09-08. 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.