.. SimLogger documentation master file, created by
   sphinx-quickstart on Wed Jun 26 10:13:25 2024.
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Welcome to SimLogger's documentation!
=====================================

.. toctree::
   :maxdepth: 2
   :caption: Contents:
   
   SimLogger
   FigLogger
   SimNotify

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!

.. code-block:: python

    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``)  

.. code-block:: python

    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``


Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`