Result for 01F19BBACC69C0DD10541884DDAC73AA7C308479

Query result

Key Value
FileName./usr/share/doc/python-celery-doc/html/history/whatsnew-3.0.html
FileSize83682
MD5A695829ABB3FC087F487A395CE716EE9
SHA-101F19BBACC69C0DD10541884DDAC73AA7C308479
SHA-2562B92E227BF91A565DE37A46BBD30D89414B052933906DEA13A494ACC81298914
SSDEEP1536:ROuqxctpnVLayD8uhdUNOuW5Dv5lLlyu202X9sVS7PCGXAfr53:ROuUyo6
TLSHT19883BBA591B78633067781C7E7FA1B35B1EA4029E0920552E3FC93AC47CDC917A1BD2E
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize1723788
MD5974B37AC94001C859EF4FE941B68C7E6
PackageDescriptionasync 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.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-celery-doc
PackageSectiondoc
PackageVersion4.2.1-5ubuntu1
SHA-118DE35597542F766223AA62EA1ACEC390BFADBA6
SHA-256B51871DF83D473D5CF517AC68F30AEB98E640A5117BB27C3A4FB4A67AA0FF326