Metadata-Version: 2.1
Name: logrun
Version: 0.1.1
Summary: A convenient experiment logging package for Python
Home-page: https://github.com/dccsillag/logrun
Author: Daniel Csillag
Author-email: dccsillag@gmail.com
License: MIT
Description: # logrun
        
        A package for experiment logging in Python.
        
        Features include:
        
        - Stores relevant source code (only what is necessary) with the experiments automatically;
        - Easily fetch the experiments that generated a given file;
        - Easily fetch the experiments that were generated by a given script;
        - Shouldn't use tons of storage;
        - Everything runs locally -- no possibly-sketchy third-party will be getting aceess to your code and experiments.
        
        ## Example usage
        
        The following example trains a model and registers an experiment that outputed the file `trained_model.pth`:
        
        ```python
        from logrun.utils.general import outpath
        import pickle
        
        
        ...  # your experiment, yada yada yada
        model = ...
        ...  # your experiment, yada yada yada
        
        model.save(outpath("trained_model.pth"))
        ```
        
        Note that you only needed to import the module and use the `outpath` function here. Everything else is neatly encapsulated in the `logrun.internals` module.
        
        ## Documentation
        
        The documentation is available at [https://dccsillag.github.io/logrun/logrun/](https://dccsillag.github.io/logrun/logrun/).
        
        To generate it manually, use [`pdoc3`](https://pdoc3.github.io/pdoc/):
        
        ```sh
        pdoc --html logrun -o docs
        ```
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
Provides-Extra: utils-media
Provides-Extra: utils-data
Provides-Extra: utils-ml-cpu
Provides-Extra: utils-ml-gpu
