Intelligent Python Checkpointing
Project description
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.
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
Project details
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