Project

Reverse Dependencies for rubocop-rspec

The projects listed here declare rubocop-rspec as a runtime or development dependency

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No release in over 3 years
A library to parse XML documents for SAML configuration
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Repository is archived
No commit activity in last 3 years
No release in over 3 years
Gem to encapsulate Monterail's company-wide rubocop setup.
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Repository is gone
No release in over 3 years
A Ruby gem to manipulate Bitcoin money without loss of precision.
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The project is in a healthy, maintained state
A service that uses a relational database inserts messages/events into an outbox table as part of the local transaction.
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Low commit activity in last 3 years
No release in over a year
A tool for generating CHANGELOGs and managing app versioning.
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Low commit activity in last 3 years
No release in over a year
RFC7644 SCIM (System for Cross-domain Identity Management) 2.0 filter parser. See https://tools.ietf.org/html/rfc7644#section-3.4.2.2 This gem implements a filter syntax parser as well as an optional integration for integrating the filter with an Arel table.
2019
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Low commit activity in last 3 years
No release in over a year
Provides a simple mapping between Active Record scopes and controller parameters for Ruby On Rails 4
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No release in over a year
Ruby translators to transform various metadata feeds into solr documents and a command-line utility to access/utilize the gem's translators to harvest metadata into a working solr instance.
2019
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0.0
Repository is archived
No commit activity in last 3 years
No release in over 3 years
Season automatically creates scopes for your models' datetime columns.
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No commit activity in last 3 years
No release in over 3 years
This gems aims to simplify the organization of support files when using the Selenium Webdriver gem directly
2019
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No release in over a year
An AI-powered pair programmer. Provides a user-friendly interface for using AI API's to automatically repair broken code and suggest improvements. Simply provide the faulty code as input, and the gem will generate a corrected version using advanced machine learning techniques.
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