skelebot

Machine Learning Project Development Tool

Sean Shookman	Joao Moreira	Sherry Wang	Cody Hutchins	Kazi Tanzim Islam	Samuel Gaist
SanthoshBala18

About

Skelebot is a command-line tool for developing machine learning projects and executing them in Docker. The purpose of Skelebot is to simply make the life of a Data Scientist easier by doing a lot of the legwork for mundane tasks automatically through a unified, consistent interface.

[/code/my-iris-model] > skelebot -h
usage: skelebot [-h] [-v] [-e ENV] [-d HOST] [-s] [-n] [-c] [-V]
                {loadData,train,score,push,pull,jupyter,plugin,bump,prime,exec,publish,envs}
                ...

Iris Example
Example Skelebot Project
-----------------------------------
Version: 1.1.0
Environment: None
Skelebot Version: 2.0.0
-----------------------------------

positional arguments:
  {loadData,train,score,push,pull,jupyter,plugin,bump,prime,exec,publish,envs}
    loadData            Load the Iris Dataset and save it into the data folder for the train job to access (src/loadData.py)
    train               Use the data loaded in the loadData job to train the iris model (src/train.py)
    score               Use the model that was built in the train job to score new data against the iris model (src/score.py)
    push                Push an artifact to Artifactory
    pull                Pull an artifact from Artifactory
    jupyter             Spin up Jupyter in a Docker Container (port=8888, folder=.)
    plugin              Install a plugin for skelebot from a local zip file
    bump                Bump the skelebot.yaml project version
    prime               Generate Dockerfile and .dockerignore and build the docker image
    exec                Exec into the running Docker container
    publish             Publish your versioned Docker Image to the registry
    envs                Display the available environments for the project

optional arguments:
  -h, --help            show this help message and exit
  -v, --version         Display the version number of Skelebot
  -e ENV, --env ENV     Specify the runtime environment configurations
  -d HOST, --docker-host HOST
                        Set the Docker Host on which the command will be executed
  -s, --skip-build      Skip the build process and attempt to use previous docker build
  -n, --native          Run natively instead of through Docker
  -c, --contact         Display the contact email of the Skelebot project
  -V, --verbose         Print all job commands to the screen just before execution

Install

Install Skelebot with Pip:

pip install skelebot

Getting Started

To get started using Skelebot you can follow the Documentation.

Contributing

Anyone is welcome to make contributions to the project. If you would like to make a contribution, please read our Contributor Guide.

Versioning

This project adheres to Semantic Versioning. Please refer to the Changelog for information regarding the differences between versions of the project.