Parents (Total: 44)

The searched file hash is included in 44 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	32EB721A870A79C7CA3FB16D3B54B994
PackageArch	noarch
PackageDescription	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 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.
PackageMaintainer	Fedora Project
PackageName	python-celery
PackageRelease	1.fc15
PackageVersion	2.2.8
SHA-1	03FAD039308C15D07F0CD599CB26D530B1E97FC8
SHA-256	9C0C47818FBB1FCADDD45A4E51FC7A2BFF006B2608A815F508DF49AA27EBDF4F

Key	Value
MD5	4030529C23093D95AD94ECDA8DE54937
PackageArch	noarch
PackageDescription	This package contains extensions to the multiprocessing Pool.
PackageMaintainer	Fedora Project
PackageName	python-billiard
PackageRelease	2.fc14
PackageVersion	0.3.1
SHA-1	0E36CB96D4541D38B7EF963E0BC751FC5F3A33E2
SHA-256	B28465D0EA467E13C320A30B2FF37252B5577ACE92576F9BDB8255320C50C041

Key	Value
MD5	C95F7969409247FD0604AFDE60E2283E
PackageArch	noarch
PackageDescription	This package contains extensions to the multiprocessing Pool.
PackageMaintainer	Fedora Project
PackageName	python-billiard
PackageRelease	3.fc15
PackageVersion	0.3.1
SHA-1	1699CB957CF473395998A180AB29423052F38382
SHA-256	18F43733EE9D20CFA9414F6C4041F0E78E9678E109004E9ADC14CF19F88D97FF

Key	Value
MD5	47EAC1D28C12C4C6EF705FEB38656A78
PackageArch	noarch
PackageDescription	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 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.
PackageMaintainer	Fedora Project
PackageName	python-celery
PackageRelease	1.fc17
PackageVersion	2.2.8
SHA-1	1A157F9E0698A4A23B30951EF8D4E20DFBC42B7C
SHA-256	C2CC3C8454FE469AB40E88105E826B9E234BD53EC4F09186834608050934F926

Key	Value
MD5	48F7EB981582AE4D02DF110C2EDA1C3A
PackageArch	noarch
PackageDescription	django-celery provides Celery integration for Django; Using the Django ORM and cache backend for storing results, autodiscovery of task modules for applications listed in INSTALLED_APPS, and more. Celery is a 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 a single or more worker servers. Tasks can execute asynchronously (in the background) or synchronously (wait until ready).
PackageMaintainer	Fedora Project
PackageName	django-celery
PackageRelease	2.fc17
PackageVersion	2.2.7
SHA-1	1A9C41F1B18A9D02EACA483274AFAF387E5F4BC1
SHA-256	FB81D98B16FC46509032961B2AAC08CE644B7F5A1423BFB0023474A95A0D05A8

Key	Value
MD5	7BAC8D3EB153BF7CF0F6BBB2FC1345BE
PackageArch	noarch
PackageDescription	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 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.
PackageMaintainer	Fedora Project
PackageName	python-celery
PackageRelease	4.fc20
PackageVersion	3.0.19
SHA-1	21AECBF834F753AAD30F68CDCBE8E0A7D70FF8C6
SHA-256	F1BC6BDEB4B1C93A31F03C5A7064B5B64BA6924930705B7E222277D8BEED58D6

Key	Value
MD5	C8502AA284D8A08B7F9D5199F54F998D
PackageArch	noarch
PackageDescription	This package contains extensions to the multiprocessing Pool.
PackageMaintainer	Fedora Project
PackageName	python-billiard
PackageRelease	3.fc15
PackageVersion	0.3.1
SHA-1	2564FFEAB25D40B4BD47BB32FD310CC370BE4DA2
SHA-256	6990D402B21A549F06ED6B66B7E6A1D66728264D736890CF2DA27128C4F3F181

Key	Value
MD5	72C521863B1706EC25A92444C511D458
PackageArch	noarch
PackageDescription	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 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.
PackageMaintainer	Fedora Project
PackageName	python3-celery
PackageRelease	4.fc20
PackageVersion	3.0.19
SHA-1	2D1FD3DF14359932CDB295F4168C44F86C6013D5
SHA-256	1C5DF61FB93AA545A60EBA2CEF77880256C119AA8AE0263BC54F3BCF3519B9A7

Key	Value
MD5	DEEEC67F673E352BB995819A36083892
PackageArch	noarch
PackageDescription	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 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.
PackageMaintainer	Fedora Project
PackageName	python-celery
PackageRelease	1.fc18
PackageVersion	3.0.11
SHA-1	3FED1509C4B55AB136830B187E7EECD867F796DD
SHA-256	CBF2B52A72FD20986D3B7A06D5C226ED00D008838850EDC1F1F2DDA4D56ED610

Key	Value
MD5	11EC66F13E3CEB650FBD20E6215784F0
PackageArch	noarch
PackageDescription	django-celery provides Celery integration for Django; Using the Django ORM and cache backend for storing results, autodiscovery of task modules for applications listed in INSTALLED_APPS, and more. Celery is a 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 a single or more worker servers. Tasks can execute asynchronously (in the background) or synchronously (wait until ready).
PackageMaintainer	Fedora Project
PackageName	python-django-celery
PackageRelease	1.fc18
PackageVersion	3.0.11
SHA-1	42115C011EA5F0A921CEF024E48E19F0BAD4D7A1
SHA-256	FC7B9C9E3A79B0FB96F4885FA669EAFDDDD33A147065C9311E8DC0B405C0CE3D