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
Release files for gin-config 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| gin-config-0.3.0.tar.gz | 38.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| gin_config-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 82.7 kB
Release files / gin-config-0.3.0.tar.gz
| Download URL | gin-config-0.3.0.tar.gz |
|---|---|
| Size | 38.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.41.0 CPython/3.7.5rc1
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Release files / gin_config-0.3.0-py3-none-any.whl
| Download URL | gin_config-0.3.0-py3-none-any.whl |
|---|---|
| Size | 44.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.41.0 CPython/3.7.5rc1
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