Result for 028933A68126DD5A6D7BECB3A38FD90BC93EA176

Query result

Key Value
FileName./usr/lib/python2.7/site-packages/celery/app/annotations.py
FileSize1434
MD5C4F531AFFD4D13E5E630BC70A8F023B3
SHA-1028933A68126DD5A6D7BECB3A38FD90BC93EA176
SHA-256AB573432A34461CB5F8AA616C0BC55D907CEDC3AF6D4F9A0B2DC6D8C3F6B45AF
SSDEEP24:lShx20O2FPd96RYGgCJ8paopzi/umclB2iBM5BgNg+E:0x2f+ELg4Oaq+umipOOal
TLSHT1A2219BCD27929595CF4FD22A79B6C105E23A788725051B7874AD03201F73070B3EEC8B
hashlookup:parent-total2
hashlookup:trust60

Network graph view

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
MD5313F408CD4E48C5C99F5B530BE6F459E
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
PackageRelease4.fc20
PackageVersion3.0.19
SHA-196BD5146AFE8100BDFD8DD807103D06AD6D7F9D3
SHA-25667E91DDD4DEA28FF16A5734389815FA748A0E2BB5B440305848A794EA2FB0C52
Key Value
MD57BAC8D3EB153BF7CF0F6BBB2FC1345BE
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
PackageRelease4.fc20
PackageVersion3.0.19
SHA-121AECBF834F753AAD30F68CDCBE8E0A7D70FF8C6
SHA-256F1BC6BDEB4B1C93A31F03C5A7064B5B64BA6924930705B7E222277D8BEED58D6