Auryn VS disco

Compare Auryn vs disco and see what are their differences.

Auryn

IoC Dependency Injector (by rdlowrey)

disco

Recommendations for Ruby and Rails using collaborative filtering (by ankane)
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Auryn disco
0 4
725 514
- -
0.0 5.9
10 months ago about 1 month ago
PHP Ruby
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Auryn

Posts with mentions or reviews of Auryn. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning Auryn yet.
Tracking mentions began in Dec 2020.

disco

Posts with mentions or reviews of disco. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-15.

What are some alternatives?

When comparing Auryn and disco you can also consider the following projects:

PHP-DI - The dependency injection container for humans

Pimple - A small PHP dependency injection container

Symfony DI - Allows you to standardize and centralize the way objects are constructed in your application

Container - Small but powerful dependency injection container

zend-servicemanager

Nette DI - 💎 Flexible, compiled and full-featured Dependency Injection Container with perfectly usable autowiring and support for all new PHP 7 features.

Acclimate - Adapters for PHP framework containers to an interoperable interface

Disco - PSR-11 compatible Dependency Injection Container for PHP.

ClanCats Container - 🚀 PHP Service Container with fast and cachable dependency injection.

Federated-Recommendation-Neural-Collaborative-Filtering - Federated Neural Collaborative Filtering (FedNCF). Neural Collaborative Filtering utilizes the flexibility, complexity, and non-linearity of Neural Network to build a recommender system. Aim to federate this recommendation system.

recommendify - Generate recommendations using collaborative filtering

predictor - Fast and efficient recommendations and predictions using Redis