Skip to main content

Gin-Config: A lightweight configuration library for Python

Project description

Gin

Gin provides a lightweight configuration framework for Python, based on dependency injection. Functions or classes can be decorated with @gin.configurable, allowing default parameter values to be supplied from a config file (or passed via the command line) using a simple but powerful syntax. This removes the need to define and maintain configuration objects (e.g. protos), or write boilerplate parameter plumbing and factory code, while often dramatically expanding a project's flexibility and configurability.

Gin is particularly well suited for machine learning experiments (e.g. using TensorFlow), which tend to have many parameters, often nested in complex ways.

Authors: Dan Holtmann-Rice, Sergio Guadarrama, Nathan Silberman Contributors: Oscar Ramirez, Marek Fiser

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gin-config-0.4.0.tar.gz (42.9 kB view hashes)

Uploaded Source

Built Distributions

gin_config-0.4.0-py2.py3-none-any.whl (46.2 kB view hashes)

Uploaded Python 2 Python 3

gin_config-0.4.0-py2-none-any.whl (46.2 kB view hashes)

Uploaded Python 2

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page