celery 4.2.1-1fakesync1 source package in Ubuntu

Changelog

celery (4.2.1-1fakesync1) cosmic-proposed; urgency=medium

  * Fake sync due to mismatching orig tarball.

 -- Mattia Rizzolo <email address hidden>  Wed, 26 Sep 2018 23:40:53 +0200

Upload details

Uploaded by:
Mattia Rizzolo on 2018-09-26
Uploaded to:
Cosmic
Original maintainer:
Ubuntu Developers
Architectures:
all
Section:
python
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section

Builds

Cosmic: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
celery_4.2.1.orig.tar.gz 1.3 MiB 1d13fbc6adf00ed0dc2a9eaeaf9637fa5551c86bef7019761c1e3cc9fedf70d1
celery_4.2.1-1fakesync1.debian.tar.xz 27.1 KiB 7a53f8d14a57639e8fd2ef6cfcfab34b9918c17d0821b314ccd716f03116d7dd
celery_4.2.1-1fakesync1.dsc 3.1 KiB 215d0298df82eab2ca7f1d073ba8a88bcfd7b640a5deb371c6cb95c060d300bd

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.