grosser/parallel

Ruby: parallel processing made simple and fast

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Summary Information

Updated 1 hour ago
Type:Library / SDKCategory(s):Core & Utility LibrariesLanguages & Runtimes
Added to GitGenius on September 16th, 2026
Created on August 11th, 2009
Open Issues & Pull Requests: 37 (+0)
GitHub issues: Enabled
Number of forks: 267
Total Stargazers: 4,265 (+0)
Total Subscribers: 71 (+0)

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Median issue/PR response: 6.9 hours
Mean response time: 11.4 hours
90th percentile: 34.8 hours
Tracked items: 5

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Open issues: 2
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 663 days
Stale 30+ days: 2
Stale 90+ days: 2

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Comments in 7 days: 0
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Detailed Description

Parallel is a Ruby library that simplifies concurrent processing by distributing work across multiple processes or threads. It abstracts away the complexity of managing child processes, handling inter-process communication, and collecting results, allowing developers to parallelize existing code with minimal changes.

The library solves the problem of CPU-bound and I/O-bound workloads that would otherwise block execution in single-threaded Ruby. It works by spawning worker processes that execute tasks independently, then gathering their results back into the parent process. This approach bypasses Ruby's Global Interpreter Lock, making it suitable for computationally intensive operations. The tool handles the low-level details of process management so users can focus on what work needs parallelization rather than how to orchestrate it.

Developers should choose this tool when they have embarrassingly parallel problems—tasks that can be divided into independent units with minimal coordination overhead. It suits batch processing, data transformation pipelines, and any scenario where the same operation needs to run on many items. The library is particularly valuable in Rails applications where background job processing or data import tasks benefit from parallelization without introducing external dependencies like job queues.

The project maintains a steady stream of bug fixes and incremental improvements addressing edge cases in process management and result collection. Development shows responsiveness to user-reported issues with timely patches. The codebase receives occasional refactoring to improve maintainability and reduce technical debt. The project demonstrates consistent attention to compatibility across different Ruby versions and platforms. Updates occasionally introduce new convenience methods that reduce boilerplate for common parallelization patterns.