Intelligent checkpointing framework for Python-based machine learning and scientific computing.
Under development as part of a research project at the University of Illinois at Urbana-Champaign.
# Installation
Run the following command in a [virtual environment](https://docs.python.org/3/library/venv.html).
```
python setup.py install
```
# Jupyter Integration
Run Jupyter after installing kishu. In your notebook, you can enable kishu with the following command.
## Basic Usage
```
from kishu import init_kishu
init_kishu()
```
Then, all the cell executions are recorded, and the result of each cell execution is checkpointed.
## Working with Kishu
`init_kishu()` adds a new variable `_kishu` (of type KishuJupyterExecHistory) to Jupyter's namespace.
The special variable can be used for kishu-related operations, as follows.
Browse the execution log.
```
_kishu.log()
```
See the database file.
```
_kishu.checkpoint_file()
```
Restore a state.
```
_kishu.checkout(commit_id)
```
## Checkpoint Backend
Deploy a restful server.
```
flask --app kishu/backend run
```
# Deployment
The following command will upload this project to pypi (https://pypi.org/project/kishu/).
```
bash upload2pypi.sh
```
Raw data
{
"_id": null,
"home_page": "",
"name": "kishu",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": "",
"keywords": "kishu,elastic,dart,python,jupyter,notebook,server,lab,cli,web,gui,extension",
"author": "",
"author_email": "Yongjoo Park <yongjoo@g.illinois.edu>, Supawit Chockchowwat <supawit2@illinois.edu>, Zhaoheng Li <zl20@illinois.edu>",
"download_url": "https://files.pythonhosted.org/packages/d9/35/a37c57aa00bb997eb7efdd737c2001f82916a06d61e1696f4cee67d940aa/kishu-0.2.0.tar.gz",
"platform": null,
"description": "Intelligent checkpointing framework for Python-based machine learning and scientific computing. \nUnder development as part of a research project at the University of Illinois at Urbana-Champaign.\n\n\n# Installation\n\nRun the following command in a [virtual environment](https://docs.python.org/3/library/venv.html).\n```\npython setup.py install\n```\n\n\n# Jupyter Integration\n\nRun Jupyter after installing kishu. In your notebook, you can enable kishu with the following command.\n\n## Basic Usage\n\n```\nfrom kishu import init_kishu\ninit_kishu()\n```\nThen, all the cell executions are recorded, and the result of each cell execution is checkpointed.\n\n\n## Working with Kishu\n\n`init_kishu()` adds a new variable `_kishu` (of type KishuJupyterExecHistory) to Jupyter's namespace.\nThe special variable can be used for kishu-related operations, as follows.\n\nBrowse the execution log.\n```\n_kishu.log()\n```\n\nSee the database file.\n```\n_kishu.checkpoint_file()\n```\n\n\nRestore a state.\n```\n_kishu.checkout(commit_id)\n```\n\n## Checkpoint Backend\n\nDeploy a restful server.\n```\nflask --app kishu/backend run\n```\n\n# Deployment\n\nThe following command will upload this project to pypi (https://pypi.org/project/kishu/).\n\n```\nbash upload2pypi.sh\n```\n",
"bugtrack_url": null,
"license": "License not determined",
"summary": "Intelligent Python Checkpointing",
"version": "0.2.0",
"project_urls": {
"repository": "https://github.com/illinoisdata/kishu"
},
"split_keywords": [
"kishu",
"elastic",
"dart",
"python",
"jupyter",
"notebook",
"server",
"lab",
"cli",
"web",
"gui",
"extension"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "448061909ad62599b7b1b9941476c4ce17909807682817bd60ff1c8ad25be13c",
"md5": "ee28a815ec086490f19335c423b4d0bc",
"sha256": "deccf865fd2810e3da35ff438e760ef95c6b6b9d30f968eadf0bfd1128ad1793"
},
"downloads": -1,
"filename": "kishu-0.2.0-cp38-cp38-macosx_12_0_arm64.whl",
"has_sig": false,
"md5_digest": "ee28a815ec086490f19335c423b4d0bc",
"packagetype": "bdist_wheel",
"python_version": "cp38",
"requires_python": ">=3.8",
"size": 80677,
"upload_time": "2024-02-11T21:32:16",
"upload_time_iso_8601": "2024-02-11T21:32:16.440791Z",
"url": "https://files.pythonhosted.org/packages/44/80/61909ad62599b7b1b9941476c4ce17909807682817bd60ff1c8ad25be13c/kishu-0.2.0-cp38-cp38-macosx_12_0_arm64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "d935a37c57aa00bb997eb7efdd737c2001f82916a06d61e1696f4cee67d940aa",
"md5": "1c6bd9537185301c770e2c7e5809e509",
"sha256": "451a5f515174bbe34f86c9439e233702eb7dabea7e07bdc578f5fe68df16d29f"
},
"downloads": -1,
"filename": "kishu-0.2.0.tar.gz",
"has_sig": false,
"md5_digest": "1c6bd9537185301c770e2c7e5809e509",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 2538429,
"upload_time": "2024-02-11T21:32:17",
"upload_time_iso_8601": "2024-02-11T21:32:17.990619Z",
"url": "https://files.pythonhosted.org/packages/d9/35/a37c57aa00bb997eb7efdd737c2001f82916a06d61e1696f4cee67d940aa/kishu-0.2.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-02-11 21:32:17",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "illinoisdata",
"github_project": "kishu",
"github_not_found": true,
"lcname": "kishu"
}
JSON
