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Turns DLHub metadata into functional Python objects

Project description

# DLHub home_run

[![Build Status](https://travis-ci.org/DLHub-Argonne/home_run.svg?branch=master)](https://travis-ci.org/DLHub-Argonne/home_run) [![Coverage Status](https://coveralls.io/repos/github/DLHub-Argonne/home_run/badge.svg?branch=master)](https://coveralls.io/github/DLHub-Argonne/home_run?branch=master) [![PyPI version](https://badge.fury.io/py/home-run.svg)](https://badge.fury.io/py/home-run)

home_run is a tool used by [the Data and Learning Hub for Science](https://www.dlhub.org) internally to turn a bunch of files and a recipe into an functional Python object.

## Installation

home_run is on PyPi. Install it by calling

`bash pip install home_run `

home_run is designed to be as light-weight as possible, and has only requests as a dependency.

## Technical Details

The key ingredients for using home_run are files describing a function that will be served by DLHub. These include a metadata file describing the servable (see [dlhub_sdk](http://github.com/dlhub-argonne/dlhub_sdk) for tools for creating these files, and [dlhub_schemas](http://github.com/dlhub-argonne/dlhub_schemas) for the schemas), and the actual files that make up the servable (e.g., a Keras hdf5 file).

Each particular type of servable has its own recipe for going from these files to a Python object. All recipes are a subclass of BaseServable, which provides the general framework for defining a servable object. Each subclass has a matching BaseMetadataModel class in dlhub_sdk. For example, the type of servable that can be described by the PythonStaticMethodModel can be run by the PythonStaticMethodServable.

## Project Support This material is based upon work supported by Laboratory Directed Research and Development (LDRD) funding from Argonne National Laboratory, provided by the Director, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357.

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