Metadata-Version: 2.1
Name: ravenml
Version: 1.2
Summary: ML Training CLI Tool
Home-page: UNKNOWN
Author: Carson Schubert, Abhi Dhir, Pratyush Singh
Author-email: carson.schubert14@gmail.com
License: MIT
Download-URL: https://github.com/autognc/ravenML/archive/v1.2.tar.gz
Description: <!-- [![Build Status](https://travis-ci.com/autognc/ravenML.svg?branch=master)](https://travis-ci.com/autognc/ravenML) -->
        
        # ravenML
        CLI tool for machine learning model training.
        
        ## Installation 
        
        ### PyPI
        Install from pip via:
        ```bash
        pip install ravenml
        ```
        
        ### Conda Installation (development)
        Create the conda environment from the `environment.yml` file using:
        ```bash
        conda env create -f environment.yml
        ```
        
        Activate the conda environment with:
        ```bash
        conda activate ravenml      # may require source activate ravenml depending on system setup
        ```
        
        Install ravenML from the root of this repository using:
        ```bash
        pip install --editable .
        ```
        
        ## Configuration
        ravenML must be configured with the name of the S3 buckets you wish to pull [Jigsaw](https://github.com/autognc/jigsaw)-created
        datasets from and upload trained models to.
        
        After installation, set this configuration by running:
        ```bash
        ravenml config update
        ```
        
        You can check your configuration anytime by running `ravenml config show`, and update it anytime with `ravenml config update`.
        
        ### Training Plugins
        ravenML provides core functionality while unique model training pipelines are implemented
        via plugins dynamically loaded at runtime. A default set of plugins is located at
        [ravenML-plugins](https://github.com/autognc/ravenML-plugins). See the README there
        for more information about how plugins work and how to make your own.
        
        To install all default plugins for use with ravenML you just need to clone the repository
        and run a script.
        
        Clone the respository with:
        ```bash
        git clone https://github.com/autognc/ravenML-plugins
        ```
        
        Install default plugins by navigating to the downloaded `ravenML` directory and using:
        ```bash
        ./install_all.sh
        ```
        
        To test your installation run `ravenml train list` and verify that the training plugin names appear on your console.
        
        ## Contributing
        
        ### Commitizen
        We will use commitizen for all commit messages. The repository is set up to use
        commitizen via the `.czrc` file. If you have commitizen already installed globally,
        you can use it to commit for this repository.  
        
        If you do not have commitizen installed, follow the instructions on their 
        [GitHub](https://github.com/commitizen/cz-cli).  
        
        If you do not have npm installed, you will need to do that before installing commitizen.
        npm is distributed with Node.js. Install Node.js [here](https://nodejs.org/en/download/).
        
Keywords: machine learning,data science
Platform: UNKNOWN
Description-Content-Type: text/markdown
