A software that offers parallel looping constructs to writing better-performing, scalable and efficient Perl programs.
Proc::ParallelLoop is a useful Perl module for those looking to easily write parallel for and foreach loops. The module allows for a controlled degree of parallelism that buffers output when necessary. The result is output from STDERR and STDOUT that looks as if it was produced through a plain sequential fashion.
One of the best features of Proc::ParallelLoop is that the return status from each loop iteration is preserved. This means that programmers can easily track how their subroutine is performing during the iteration process.
The SYNOPSIS for this module demonstrates how to use it in a code example. This includes utilizing the pardo and pareach methods to write subroutines for testing loops, updating already existing loops, and writing the body of the loop itself. Additionally, programmers can use array references to write the loop_body subroutine.
Overall, Proc::ParallelLoop is a useful tool for those looking to write parallel for and foreach loops that save time and provide a streamlined process. Its numerous features ensure that programmers can see output as if it was produced in a sequential fashion while still maintaining the return status of each iteration.
One of the best features of Proc::ParallelLoop is that the return status from each loop iteration is preserved. This means that programmers can easily track how their subroutine is performing during the iteration process.
The SYNOPSIS for this module demonstrates how to use it in a code example. This includes utilizing the pardo and pareach methods to write subroutines for testing loops, updating already existing loops, and writing the body of the loop itself. Additionally, programmers can use array references to write the loop_body subroutine.
Overall, Proc::ParallelLoop is a useful tool for those looking to write parallel for and foreach loops that save time and provide a streamlined process. Its numerous features ensure that programmers can see output as if it was produced in a sequential fashion while still maintaining the return status of each iteration.
What's New
Version 0.5: N/A