ruby-in-parallel 0.1.17-1.3 source package in Ubuntu
Changelog
ruby-in-parallel (0.1.17-1.3) unstable; urgency=medium * Non-maintainer upload. * Add patch to skip random test failure. (Closes: #980585) -- Utkarsh Gupta <email address hidden> Thu, 21 Jan 2021 12:57:41 +0530
Upload details
- Uploaded by:
- Freexian Packaging Team
- Uploaded to:
- Sid
- Original maintainer:
- Freexian Packaging Team
- Architectures:
- all
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
Series | Published | Component | Section | |
---|---|---|---|---|
Mantic | release | universe | misc | |
Lunar | release | universe | misc | |
Jammy | release | universe | misc |
Downloads
File | Size | SHA-256 Checksum |
---|---|---|
ruby-in-parallel_0.1.17-1.3.dsc | 2.1 KiB | ac10f8e61960af1a820262b70247fd74e074fa2f272a0f72c52930f31cf90f3f |
ruby-in-parallel_0.1.17.orig.tar.xz | 15.8 KiB | de0d1d97fb355e063109eddcb62e2cd3bd1f13b2714e0bad0e3651cf65305d92 |
ruby-in-parallel_0.1.17-1.3.debian.tar.xz | 2.6 KiB | f993ebdcfcec07e9f24422601d173a888f12aa9cf83ece980a669a6fd3692bae |
Available diffs
- diff from 0.1.17-1.2 to 0.1.17-1.3 (835 bytes)
No changes file available.
Binary packages built by this source
- ruby-in-parallel: lightweight Ruby library with very simple syntax for parallelization
A lightweight Ruby library with very simple syntax, making use of
Process.fork to execute code in parallel.
.
Many other Ruby libraries that simplify parallel execution support
one primary use case - crunching through a large queue of small,
similar tasks as quickly and efficiently as possible. This library
primarily supports the use case of executing a few larger and
unrelated tasks in parallel, automatically managing the stdout and
passing return values back to the main process.
.
This library was created to be used by Puppet's Beaker test framework
to enable parallel execution of some of the framework's tasks, and
allow users to execute code in parallel within their tests.
.
If you are looking for something that excels at executing a large
queue of tasks in parallel as efficiently as possible, you should
take a look at the parallel project.