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GNU Parallel 20190422 ('Invitation') released [stable]

Item posted by Ole Tange <tange> on Sun 21 Apr 2019 06:20:53 PM UTC.

GNU Parallel 20190422 ('Invitation') [stable] has been released. It is available for download at: http://ftpmirror.gnu.org/parallel/

No new functionality was introduced so this is a good candidate for a stable release.

Invitation to 10 year reception


GNU Parallel is 10 years old in a year on 2020-04-22. You are here by invited to a reception on Friday 2020-04-17.

The primary reception will be held in Copenhagen, DK. Please reserve the date and email happybirthdaygnuparallel@tange.dk if you want to join.

If you cannot make it, you are encouraged to host a parallel party.

So far we hope to have parallel parties at:


  PROSA
  Vester Farimagsgade 37A
  DK-1606 København V
  RSVP: happybirthdaygnuparallel@tange.dk

  PROSA
  Søren Frichs Vej 38 K th
  DK-8230 Åbyhøj
  RSVP: To be determined

  PROSA
  Overgade 54
  DK-5000 Odense C
  RSVP: To be determined


If you want to host a party held in parallel (either in this or in a parallel universe), please let me know, so it can be announced.

If you have parallel ideas for how to celebrate GNU Parallel, please post on the email list parallel@gnu.org. So far we have the following ideas:


If you have interesting stories about or uses of GNU Parallel, please post them, so can be part of the anniversary update.


Quote of the month:

  Y'all need some GNU parallel in your lives
    -- ChaKu @ChaiLovesChai@twitter


New in this release:




Get the book: GNU Parallel 2018 http://www.lulu.com/shop/ole-tange/gnu-parallel-2018/paperback/product-23558902.html

GNU Parallel - For people who live life in the parallel lane.


About GNU Parallel


GNU Parallel is a shell tool for executing jobs in parallel using one or more computers. A job can be a single command or a small script that has to be run for each of the lines in the input. The typical input is a list of files, a list of hosts, a list of users, a list of URLs, or a list of tables. A job can also be a command that reads from a pipe. GNU Parallel can then split the input and pipe it into commands in parallel.

If you use xargs and tee today you will find GNU Parallel very easy to use as GNU Parallel is written to have the same options as xargs. If you write loops in shell, you will find GNU Parallel may be able to replace most of the loops and make them run faster by running several jobs in parallel. GNU Parallel can even replace nested loops.

GNU Parallel makes sure output from the commands is the same output as you would get had you run the commands sequentially. This makes it possible to use output from GNU Parallel as input for other programs.

You can find more about GNU Parallel at: http://www.gnu.org/s/parallel/

You can install GNU Parallel in just 10 seconds with:
(wget -O - pi.dk/3 || curl pi.dk/3/ || fetch -o - http://pi.dk/3) | bash

Watch the intro video on http://www.youtube.com/playlist?list=PL284C9FF2488BC6D1

Walk through the tutorial (man parallel_tutorial). Your command line will love you for it.

When using programs that use GNU Parallel to process data for publication please cite:

O. Tange (2018): GNU Parallel 2018, March 2018, https://doi.org/10.5281/zenodo.1146014.

If you like GNU Parallel:


If you use programs that use GNU Parallel for research:


If GNU Parallel saves you money:



About GNU SQL


GNU sql aims to give a simple, unified interface for accessing databases through all the different databases' command line clients. So far the focus has been on giving a common way to specify login information (protocol, username, password, hostname, and port number), size (database and table size), and running queries.

The database is addressed using a DBURL. If commands are left out you will get that database's interactive shell.

When using GNU SQL for a publication please cite:

O. Tange (2011): GNU SQL - A Command Line Tool for Accessing Different Databases Using DBURLs, ;login: The USENIX Magazine, April 2011:29-32.


About GNU Niceload


GNU niceload slows down a program when the computer load average (or other system activity) is above a certain limit. When the limit is reached the program will be suspended for some time. If the limit is a soft limit the program will be allowed to run for short amounts of time before being suspended again. If the limit is a hard limit the program will only be allowed to run when the system is below the limit.

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