How to Install and Uninstall python3-celery.noarch Package on AlmaLinux 8
Last updated: November 28,2024
1. Install "python3-celery.noarch" package
Please follow the guidance below to install python3-celery.noarch on AlmaLinux 8
$
sudo dnf update
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$
sudo dnf install
python3-celery.noarch
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2. Uninstall "python3-celery.noarch" package
Please follow the guidance below to uninstall python3-celery.noarch on AlmaLinux 8:
$
sudo dnf remove
python3-celery.noarch
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$
sudo dnf autoremove
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3. Information about the python3-celery.noarch package on AlmaLinux 8
Last metadata expiration check: 2:21:22 ago on Mon Sep 5 03:22:42 2022.
Available Packages
Name : python3-celery
Version : 4.3.0
Release : 5.el8
Architecture : noarch
Size : 736 k
Source : python-celery-4.3.0-5.el8.src.rpm
Repository : epel
Summary : Distributed Task Queue
URL : http://celeryproject.org
License : BSD
Description : An open source asynchronous task queue/job queue based on
: distributed message passing. It is focused on real-time
: operation, but supports scheduling as well.
:
: The execution units, called tasks, are executed concurrently
: on one or more worker nodes using multiprocessing, Eventlet
: or gevent. Tasks can execute asynchronously (in the background)
: or synchronously (wait until ready).
:
: Celery is used in production systems to process millions of
: tasks a day.
:
: Celery is written in Python, but the protocol can be implemented
: in any language. It can also operate with other languages using
: web hooks.
:
: The recommended message broker is RabbitMQ, but limited support
: for Redis, Beanstalk, MongoDB, CouchDB and databases
: (using SQLAlchemy or the Django ORM) is also available.
Available Packages
Name : python3-celery
Version : 4.3.0
Release : 5.el8
Architecture : noarch
Size : 736 k
Source : python-celery-4.3.0-5.el8.src.rpm
Repository : epel
Summary : Distributed Task Queue
URL : http://celeryproject.org
License : BSD
Description : An open source asynchronous task queue/job queue based on
: distributed message passing. It is focused on real-time
: operation, but supports scheduling as well.
:
: The execution units, called tasks, are executed concurrently
: on one or more worker nodes using multiprocessing, Eventlet
: or gevent. Tasks can execute asynchronously (in the background)
: or synchronously (wait until ready).
:
: Celery is used in production systems to process millions of
: tasks a day.
:
: Celery is written in Python, but the protocol can be implemented
: in any language. It can also operate with other languages using
: web hooks.
:
: The recommended message broker is RabbitMQ, but limited support
: for Redis, Beanstalk, MongoDB, CouchDB and databases
: (using SQLAlchemy or the Django ORM) is also available.