Result for 038F30F40DAECA223842843AE0ACC45278F07592

Query result

Key Value
FileName./usr/share/doc/python-celery-doc/html/history/whatsnew-3.0.html
FileSize82642
MD51A1B236E202DC35D75B04CEE14F67064
SHA-1038F30F40DAECA223842843AE0ACC45278F07592
SHA-2562FE382FC44C2E64A0C5AEEF29F23035B76F6FD031DAB0F94503B66FF87F4AB44
SSDEEP1536:3d6qTuUHnsQWyl89Wdt1Vum5IBTlmJYuT98c4YkKcsLej6klm4v:3d6pyRez
TLSHT16083BAA581B78237067781C7D7FE0B38B1EA802AE0960551E2FC936C47CDC917A1BD6E
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
FileSize1667148
MD5B0E65E85E0E2FC5E270B3CC370DF4545
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.
PackageMaintainerDebian Python Team <team+python@tracker.debian.org>
PackageNamepython-celery-doc
PackageSectiondoc
PackageVersion5.2.1-1
SHA-1F771CF3D911B991BDE70219696B22DD0A94656BA
SHA-25675914A2B0E58761102F44299A3927479DE4BA99532C20837EBDAC4D566C37A37