celery 4.2.1-2fakesync1 source package in Ubuntu

Changelog

celery (4.2.1-2fakesync1) cosmic; urgency=medium

  * Fake sync due to mismatching orig tarball.

 -- Mattia Rizzolo <email address hidden>  Thu, 27 Sep 2018 11:09:42 +0200

Upload details

Uploaded by:
Mattia Rizzolo on 2018-09-27
Uploaded to:
Cosmic
Original maintainer:
Ubuntu Developers
Architectures:
all
Section:
python
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Eoan release 19 hours ago universe python
Disco release on 2018-10-30 universe python
Cosmic release on 2018-09-27 universe python

Builds

Cosmic: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
celery_4.2.1.orig.tar.gz 1.3 MiB 1d13fbc6adf00ed0dc2a9eaeaf9637fa5551c86bef7019761c1e3cc9fedf70d1
celery_4.2.1-2fakesync1.debian.tar.xz 27.2 KiB cfb3dae1dae80c370d0f2dcd133ac0580b64dc485022ad1e8f8d6baae27d1384
celery_4.2.1-2fakesync1.dsc 3.1 KiB 723ab660d53da55bd9cdf3e71c0851030975143c3fd68d705d9380137ba56c70

View changes file

Binary packages built by this source

python-celery: async task/job queue based on message passing (Python2 version)

 Celery is 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. Tasks can execute asynchronously (in the
 background) or synchronously (wait until ready).
 .
 Celery is written in Python, but the protocol can be implemented
 in any language. It can also operate with other languages using
 webhooks.
 .
 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. Celery is easy to integrate with Django, using the
 python-django-celery package.
 .
 This package contains the Python 2 version of the library.

python-celery-common: async task/job queue based on message passing (common files)

 Celery is 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. Tasks can execute asynchronously (in the
 background) or synchronously (wait until ready).
 .
 Celery is written in Python, but the protocol can be implemented
 in any language. It can also operate with other languages using
 webhooks.
 .
 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. Celery is easy to integrate with Django, using the
 python-django-celery package.
 .
 This package contains the common files of the library.

python-celery-doc: async task/job queue based on message passing (Documentation)

 Celery is 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. Tasks can execute asynchronously (in the
 background) or synchronously (wait until ready).
 .
 Celery is written in Python, but the protocol can be implemented
 in any language. It can also operate with other languages using
 webhooks.
 .
 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. Celery is easy to integrate with Django, using the
 python-django-celery package.
 .
 This package contains the documentation.

python3-celery: async task/job queue based on message passing (Python3 version)

 Celery is 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. Tasks can execute asynchronously (in the
 background) or synchronously (wait until ready).
 .
 Celery is written in Python, but the protocol can be implemented
 in any language. It can also operate with other languages using
 webhooks.
 .
 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. Celery is easy to integrate with Django, using the
 python-django-celery package.
 .
 This package contains the Python 3 version of the library.