{"id":13634080,"url":"https://github.com/xiaohk/stickyland","last_synced_at":"2025-05-16T07:05:26.506Z","repository":{"id":40638315,"uuid":"423897163","full_name":"xiaohk/stickyland","owner":"xiaohk","description":"Break the linear presentation of Jupyter Notebooks with sticky 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Extensions"],"sub_categories":[],"readme":"# StickyLand\n\n\u003c!-- [![Lite](https://gist.githubusercontent.com/xiaohk/9b9f7c8fa162b2c3bc3251a5c9a799b2/raw/c3438b4c49d89e4c367f581520ddd4cf8dac0f41/lite-badge-launch-small.svg)](https://xiaohk.github.io/stickyland/) --\u003e\n\n[![Github Actions Status](https://github.com/xiaohk/stickyland/workflows/Build/badge.svg)](https://github.com/xiaohk/stickyland/actions/workflows/build.yml)\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/xiaohk/stickyland/master?urlpath=lab/tree/examples/example-adult.ipynb)\n[![Lite](https://gist.githubusercontent.com/xiaohk/9b9f7c8fa162b2c3bc3251a5c9a799b2/raw/a7fca1d0a2d62c2b49f60c0217dffbd0fe404471/lite-badge-launch-small.svg)](https://xiaohk.github.io/stickyland/)\n[![pypi](https://img.shields.io/pypi/v/jupyterlab-stickyland?color=blue)](https://pypi.python.org/pypi/jupyterlab-stickyland)\n[![license](https://img.shields.io/badge/License-BSD--3-orange)](https://github.com/xiaohk/stickyland/blob/master/LICENSE)\n[![arxiv badge](https://img.shields.io/badge/arXiv-2202.11086-red)](https://arxiv.org/abs/2202.11086)\n[![DOI:10.1145/3491101.3519653](https://img.shields.io/badge/DOI-10.1145/3491101.3519653-blue)](https://doi.org/10.1145/3491101.3519653)\n\nBreak the linear presentation of Jupyter Notebooks with sticky cells!\n\n\u003ctable\u003e\n  \u003ctr\u003e\n    \u003ctd colspan=\"3\"\u003e\u003cimg src='https://i.imgur.com/FtmHafo.png'\u003e\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003e\u003ca href=\"https://youtu.be/eMlTtloGyho\"\u003e👨🏻‍🏫 Talk\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://youtu.be/OKaPmEBzEX0\"\u003e📺 Video\u003c/a\u003e\u003c/td\u003e\n    \u003ctd\u003e\u003ca href=\"https://arxiv.org/abs/2202.11086\"\u003e📖 \"StickyLand: breaking the linear presentation of computational Notebooks\"\u003c/a\u003e\u003c/td\u003e\n  \u003c/tr\u003e\n\u003c/table\u003e\n\n## Live Demo\n\nYou can try StickyLand directly in your browser without installing anything:\n\n|                                                                                             Fast loading                                                                                             |                                                                 Full functionality                                                                  |\n| :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------: |\n| [![Lite](https://gist.githubusercontent.com/xiaohk/9b9f7c8fa162b2c3bc3251a5c9a799b2/raw/a7fca1d0a2d62c2b49f60c0217dffbd0fe404471/lite-badge-launch-small.svg)](https://xiaohk.github.io/stickyland/) | [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/xiaohk/stickyland/master?urlpath=lab/tree/examples/example-adult.ipynb) |\n\n## Install\n\nFirst, you need to install JupyterLab. Then you can install StickyLand with `pip`:\n\n```bash\npip install stickyland\n```\n\n\u003e **Note**\n\u003e StickyLand only supports `JupyterLab \u003c 4`. In June 2023, `JupyterLab 4.0` was released with a lot of breaking changes. I will update StickyLand to support `JupyterLab 4.0` when the official extension documentation is more polished. Any contribution to the [`lab4`](https://github.com/xiaohk/stickyland/tree/lab4) branch is greatly appreciated!\n\n## Features\n\n![feature-gif](https://user-images.githubusercontent.com/15007159/155863418-c4e616fa-a003-4d6c-ba12-74cdb22d9bf4.gif)\n\n\u003cdetails\u003e\n  \u003csummary\u003eShow details\u003c/summary\u003e\n  \u003ctable\u003e\n    \u003ctr\u003e\u003c/tr\u003e\n    \u003ctr\u003e\u003c/tr\u003e\n    \u003ctr\u003e\u003ctd style=\"text-align:center\"\u003e\u003cb\u003eDrag and drop to create sticky cells\u003c/b\u003e\u003c/td\u003e\u003ctd\u003e\u003cb\u003eCreate sticky code and markdown from scratch\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\n    \u003ctr\u003e\u003c/tr\u003e\n    \u003ctr\u003e\u003cth\u003e\u003cvideo src='https://user-images.githubusercontent.com/15007159/155241848-298e593e-de7b-4d6e-be48-fd738c2586e6.mp4' width=180\u003e\u003c/video\u003e\u003c/th\u003e\u003cth\u003e\u003cvideo src='https://user-images.githubusercontent.com/15007159/155241844-4a5a910d-3cdf-48d2-9c6d-acb9e23fe6a4.mp4' width=180\u003e\u003c/video\u003e\u003c/th\u003e\u003c/tr\u003e\n    \u003ctr\u003e\u003c/tr\u003e\n    \u003ctr\u003e\u003ctd\u003e\u003cb\u003eAutomatically execute sticky cells\u003c/b\u003e\u003c/td\u003e\u003ctd\u003e\u003cb\u003eUse floating cells to create interactive dashboards\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\n    \u003ctr\u003e\u003c/tr\u003e\n    \u003ctr\u003e\u003ctd style=\"width:20px\"\u003e\u003cvideo src='https://user-images.githubusercontent.com/15007159/155242259-925ca910-f1d4-4b8d-b085-5120f1a21da6.mp4' width=180\u003e\u003c/video\u003e\u003c/td\u003e\u003ctd\u003e\u003cvideo src='https://user-images.githubusercontent.com/15007159/155243403-30625bd4-611c-4096-934d-7219fd6be8cb.mp4' width=180\u003e\u003c/video\u003e\u003c/td\u003e\u003c/tr\u003e\n  \u003c/table\u003e\n\n\u003c/details\u003e\n\n---\n\nWith multiple floating cells, users can create a full-fledged interactive dashboard. For example, a machine learning engineer can build an ML Error Analysis Dashboard (shown below) through simple drag-and-drop.\n\n\u003ctable\u003e\n  \u003ctr\u003e\u003ctd\u003e\u003cimg src=\"https://i.imgur.com/KN51RQV.png\"\u003e\u003c/td\u003e\u003c/tr\u003e\n  \u003ctr\u003e\u003c/tr\u003e\n  \u003ctr\u003e\u003ctd\u003eThe \u003cb\u003eML Error Analysis Dashboard\u003c/b\u003e consists of: \u003cb\u003e(A)\u003c/b\u003e markdown text describing the dashboard, \u003cb\u003e(B)\u003c/b\u003e\ninput field to specify a feature to diagnose, \u003cb\u003e(C)\u003c/b\u003e auto-run chart showing the distribution of the specified feature, \u003cb\u003e(D)\u003c/b\u003e second\ninput field to further specify the range within the feature to diagnose, \u003cb\u003e(E)\u003c/b\u003e auto-run table displaying all samples that meet the\ncriteria, \u003cb\u003e(F)\u003c/b\u003e auto-run \u003ca href=\"https://github.com/interpretml/interpret/\"\u003evisualization\u003c/a\u003e explaining how the ML model makes decision on these samples, \u003cb\u003e(G)\u003c/b\u003e \u003ca href=\"https://github.com/interpretml/gam-changer/\"\u003einteractive tool\u003c/a\u003e allowing\nthe ML engineer to fix the ML model by editing its parameters based on their error analysis.\u003c/td\u003e\u003c/tr\u003e\n\u003c/table\u003e\n\n## Development\n\nYou will need NodeJS to build the extension package.\nThe `jlpm` command is JupyterLab's pinned version of\n[yarn](https://yarnpkg.com/) that is installed with JupyterLab. You may use\n`yarn` or `npm` in lieu of `jlpm` below.\n\n```bash\n# Clone the repo to your local environment\n# Change directory to the jupyterlab_stickyland directory\n# Install package in development mode\npip install -e .\n# Link your development version of the extension with JupyterLab\njupyter labextension develop . --overwrite\n# Rebuild extension Typescript source after making changes\njlpm run build\n```\n\nYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.\n\n```bash\n# Watch the source directory in one terminal, automatically rebuilding when needed\njlpm run watch\n# Run JupyterLab in another terminal\njupyter lab\n```\n\nWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).\n\nBy default, the `jlpm run build` command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:\n\n```bash\njupyter lab build --minimize=False\n```\n\n## Citation\n\n```bibTeX\n@inproceedings{wangStickyLandBreakingLinear2022,\n  title = {{{StickyLand}}: {{Breaking}} the {{Linear Presentation}} of {{Computational Notebooks}}},\n  shorttitle = {{{StickyLand}}},\n  booktitle = {Extended {{Abstracts}} of the 2022 {{CHI Conference}} on {{Human Factors}} in {{Computing Systems}}},\n  author = {Wang, Zijie J. and Dai, Katie and Edwards, W. Keith},\n  year = {2022},\n  publisher = {{ACM}}\n}\n```\n\n## License\n\nThe software is available under the [BSD-3-Clause License](https://github.com/xiaohk/stickyland/blob/master/LICENSE).\n\n## Contact\n\nIf you have any questions, feel free to [open an issue](https://github.com/xiaohk/stickyland/issues/new) or contact [Jay Wang](https://zijie.wang).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxiaohk%2Fstickyland","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fxiaohk%2Fstickyland","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxiaohk%2Fstickyland/lists"}