Welcome to SimLogger’s documentation!
Contents:
A simplified method for logging and saving information in scientific computing.
SimLogger seeks to simplify the process of saving and archiving data for scientific computing by handling all the file naming a storing for you.
Archive your python objects simply and easiy, and never worry about overwriting files. All data is defined with 3 key components
simTag - tag unique for each simulation (like naming the experiment)
objTag - tag unique for each object (like the variable within the experiments)
date-time - this is automatically added by SimLogger to help ensure unqiueness of files
With that you can save your data easily!
Installation
Install the python package
pip install SimLogger
To utilize the FigLogger you will need to register your machine ssh keys with kachery
Run the following command and follow the instructions
kachery-cloud-init
Then you can test it out!
from SimLogger import SimLogger
simTag = 'sampleSimulation'
objTag = 'sampleArray'
sampleArray = [1,2,3,4]
SimLogger.saveObj(simTag, objTag, sampleArray, makeNote=True)
# Outputs
# 2024-06-25 10:44:44,063 [INFO ] Logger Loaded
# 2024-06-25 10:44:44,064 [INFO ] OBJECT,sampleSimulation,sampleArray,data/obj/sampleSimulation_sampleArray_2024-06-25_10-44-44.pkl
#
# additionally a file is saved: data/obj/sampleSimulation_sampleArray_2024-06-25_10-44-44.pkl
And you can load your data later using a uniqueId
uniqueId - unique identifier that goes to the python pkl file (almost always is simTag_objTag)
from SimLogger import SimLogger
sampleArrayLoaded = SimLogger.getObjectFromuniqueId('sampleSimulation_sampleArray')
print(sampleArrayLoaded)
# Ouptuts
# [1, 2, 3, 4]
Development
install all dependencies (including linting and testing) with:
pip install -e '.[lint,test,doc]
run tests with:
pytest tests/
run linting + formatting + etc with:
pre-commit run --all-files