Result for 02E86D8113A1B154B4FE8E9BFF7B89AA25E376F5

Query result

Key Value
FileName./usr/lib/python2.7/site-packages/celery/task/control.pyo
FileSize10452
MD526A0EEDC529CB405571A2B81145D4153
SHA-102E86D8113A1B154B4FE8E9BFF7B89AA25E376F5
SHA-2561938D1726DBB5AF1713ED223FDD398A9E9BF511A067BD523DB72E057A43C1F1E
SSDEEP192:1Nih4YraWTNnoA0RYBNvmRgOEKg44aetJeS+8e6CeGQd:yaWxnoA0RoOiI41tMSuiGC
TLSHT1FE221F80E37A8A33D7724575E2F152276634F13B62022B81316C68367FE93A5C5BBBC5
hashlookup:parent-total2
hashlookup:trust60

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Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD57E990ED79AB6AE0EF0DBB2E0817F1075
PackageArchnoarch
PackageDescriptionAn 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.
PackageMaintainerFedora Project
PackageNamepython-celery
PackageRelease3.fc16
PackageVersion2.2.7
SHA-18EAD785607459CB782C4FBBBF029B4E794D54957
SHA-256797FB737F208174287EB994114A77A8573EDF93E96BC94B85034EA8C39F180C0
Key Value
MD5A186BC055B222865B3D865840152E0D9
PackageArchnoarch
PackageDescriptionAn 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.
PackageMaintainerFedora Project
PackageNamepython-celery
PackageRelease3.fc16
PackageVersion2.2.7
SHA-1D31E39124A780FA4B5C19FAFCA3025AA00D34BD4
SHA-2563D03AF5AD0C60D5DAA8F7E0FEA1E693F2CC8A103A226E8205FD7B35CEF5C4C2D