celery 4.1.0-2 source package in Ubuntu

Changelog

celery (4.1.0-2) unstable; urgency=low

  * Add python(3)-ephem to Depends to allow for solar based schedules.
  * Pick upstream patch to fix solar based scheduler.
  * Refresh patches.

 -- Michael Fladischer <email address hidden>  Wed, 15 Nov 2017 14:58:01 +0100

Upload details

Uploaded by:
Debian Python Modules Team on 2017-11-16
Uploaded to:
Sid
Original maintainer:
Debian Python Modules Team
Architectures:
all
Section:
python
Urgency:
Low Urgency

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Builds

Bionic: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
celery_4.1.0-2.dsc 2.7 KiB 71f934cca6c5b3164f6db6ed9373c0cacaf5ddae305ac8df3fd4b19a5fc3033a
celery_4.1.0.orig.tar.gz 1.3 MiB 77ff3730198d6a17b3c1f05579ebe570b579efb35f6d7e13dba3b1368d068b35
celery_4.1.0-2.debian.tar.xz 22.3 KiB dc89301b8a1e7c56dce6908da5a6364d0e93a0113f746c1fc0a84a5b372eaae0

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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.