No known security advisories.
The current version has no OSV.dev malware reports and no critical or high-severity vulnerabilities.
jupytext has 3.7M monthly downloads and 7K GitHub stars. Version 1.19.4 supports Python 3.9+, first published in 2018.
It is actively maintained under a permissive license, last released in Jun 2026.
It is built on top of markdown-it-py, mdit-py-plugins and nbformat. It is used by 118 tracked packages, including kaggle, mkdocs-jupyter and bddl.
GitHub topics include jupyter-notebook, jupyterlab-extension and version-control.
Package Insights
Score breakdown - each component scores 0-100, weighted by percentage
Maintenance
100
Popularity
80
Adoption
70
Community
70
Provenance
100
How the maintenance status was determined
Last commit
6 days ago
Monthly downloads
3,737,929
•
Active
Activity within 30 days
Stable
Activity within 31-180 days
Minimal
Activity within 181-365 days, or no activity data
At Risk
No activity for > 365 days, but > 10,000 monthly downloads
Archived
Repository flagged as archived on GitHub
How the popularity category was determined
Monthly downloads
3,737,929
Stars
7,211
Stars per 1k downloads
1.93
Industry Standard
> 10,000,000 monthly downloads
Hidden Gem
< 0.5 stars per 1k downloads and > 100,000 monthly downloads
Community Favorite
> 5 stars per 1k downloads
•
Rising Star
Balanced ratio of stars to downloads
Unknown
Fewer than 1,000 monthly downloads, or no star data
How download momentum is calculated
Week daily avg
123,732
Month daily avg
124,598
Momentum
-0.7%
((week_daily_avg - month_daily_avg) / month_daily_avg) * 100Python version support tiers
requires_python
>=3.9
Cutting Edge
Minimum supported version is 3.12 or newer
•
Modern
Minimum supported version is 3.9, 3.10, or 3.11
Legacy
Supports 3.8 or older (or Python 2)
Unknown
No requires_python specified or unparseable
License categories
License
MIT License
•
Permissive
MIT, Apache, BSD, ISC, Unlicense, CC0, etc.
Copyleft
GPL, LGPL, AGPL, MPL, EPL, etc.
Proprietary
Commercial, all rights reserved, custom EULAs
Unknown
No license specified, or none of the above match
How the release cadence was determined
Last release
16 days ago
Total releases
148
Releases/year
18.8
•
Rapid
Last release within 365 days and > 12 releases/year
Regular
Last release within 365 days
Slow
Last release 366-730 days ago
Stalled
Last release > 730 days ago, or no releases
Unknown
No usable release date available
How contributor risk was determined
Contributors
104
Monthly downloads
3,737,929
High Load
≤ 2 contributors and ≥ 50,000 monthly downloads
Moderate Load
< 10 contributors and ≥ 500,000 monthly downloads
Low Load
< 25 contributors and ≥ 5,000,000 monthly downloads, or sole maintainer with ≥ 10,000 monthly downloads
•
Balanced
Enough contributors for the package's popularity
Unknown
No contributor data available
Engagement
66
Issue Burden
19.8
per 1k stars
Discussions
0.4
per 1k stars
Fork Ratio
24.8%
contrib / forks
Stale Release
No
PR Velocity
Quiet
Weekly Downloads
GitHub Stars
Not all downloads include detailed metadata. Breakdowns reflect the subset that does.
Downloads by OS
Linux
52.3K
macOS
3.5K
Windows
2.7K
Python Versions
3.12
45.8%
24.5K
3.11
21.2%
11.4K
3.10
13.5%
7.2K
3.13
12.4%
6.6K
3.14
7.2%
3.9K
Top Countries
1.
US
47.7K
US
2.
IE
2.9K
IE
3.
SG
1.1K
SG
4.
IN
894
IN
5.
DE
707
DE
6.
NL
647
NL
7.
JP
575
JP
8.
FR
475
FR
9.
SE
362
SE
10.
CN
339
CN
Dependencies
6
66 optional dependencies
- autopep8[dev]
- autopep8[test-external]
- bash-kernel[test-ui]
- black[test-external]
- black[test-functional]
- black[test-integration]
- black[dev]
- black[test-cov]
- flake8[dev]
- flake8[test-external]
- gitpython[test-external]
- gitpython[dev]
- ipykernel[test-integration]
- ipykernel[test-external]
- ipykernel[test-cov]
- ipykernel[dev]
- isort[dev]
- isort[test-external]
- jupyter-fs[test-external]
- jupyter-fs[dev]
- jupyter-server[test-external]
- jupyter-server[test-integration]
- jupyter-server[dev]
- jupyter-server[test-cov]
- marimo[test-external]
- marimo[dev]
- myst-parser[docs]
- nbconvert[test-integration]
- nbconvert[test-cov]
- nbconvert[dev]
- nbconvert[test-external]
- pre-commit[test-external]
- pre-commit[dev]
- pytest[test-cov]
- pytest[test-external]
- pytest[test-functional]
- pytest[test-integration]
- pytest[test]
- pytest[dev]
- pytest-asyncio[test-cov]
- pytest-asyncio[test-external]
- pytest-asyncio[test-functional]
- pytest-asyncio[test-integration]
- pytest-asyncio[dev]
- pytest-asyncio[test]
- pytest-cov[test-cov]
- pytest-cov[dev]
- pytest-randomly[test-cov]
- pytest-randomly[test-external]
- pytest-randomly[test-functional]
- pytest-randomly[test-integration]
- pytest-randomly[dev]
- pytest-randomly[test]
- pytest-xdist[test-cov]
- pytest-xdist[test-external]
- pytest-xdist[test-functional]
- pytest-xdist[test-integration]
- pytest-xdist[test]
- pytest-xdist[dev]
- sphinx[test-external]
- sphinx[dev]
- sphinx[docs]
- sphinx-copybutton[docs]
- sphinx-gallery[dev]
- sphinx-gallery[test-external]
- sphinx-rtd-theme[docs]
Used By
118
- kaggle
- mkdocs-jupyter
- bddl
- absql
- gusty
- jupyterlite-sphinx
- otter-grader
- parody
- aizynthfinder
- pipulate
- euporie
- nodpy
- afterpython
- napari-assistant
- cdh-lava-core
- integrate-module
- leo
- juv
- lesia
- dlai-grader
- xarpes
- napari-pyclesperanto-assistant
- mtflib
- scdataloader
- jupyter-ascending
- datto
- contextmaker
- waldiez
- notebooker
- ogstools
- oasees-sdk
- logtalk-jupyter-kernel
- bioimage-embed
- dp-wizard-templates
- mkdocs-execute-plugin
- picaso
- dunderlab-docs
- engcom
- dstools
- headergen
- pytimings
- flowbook-python
- databricks-agent-notebooks
- qudi-core
- juplit
- sameproject
- pynb-dag-runner-snapshot
- mdformat-py-edu-fr
- jellycell
- pyfitit
GitHub Topics
Tags from the package's GitHub repository describing what it does.
Package Information
License
MIT License
First Release
August 31, 2018
Last Release
2 weeks ago
Last Commit
1 week ago
Latest Version
1.19.4
Total Releases
148
Contributors
104
Open PRs
21
Archived
No
Python Versions
3
3.9
3.10
3.11
3.12
3.13
3.14
Wheels
py3
Tracking Since
January 6, 2026
Data Updated
July 5, 2026
Data Freshness
Fresh