Result for 0347D6B6B88577065E1E43E4F6293A8AB3AE1BF6

Query result

Key Value
FileName./usr/lib/python2.7/site-packages/celery/backends/base.pyo
FileSize13675
MD55607DDD8280C07D17A2E47884AAB1270
SHA-10347D6B6B88577065E1E43E4F6293A8AB3AE1BF6
SHA-256C4798B0331F061C919BA42CA286764C6728575D080843BF41650C2B51AE1DE47
SSDEEP192:5i3htjmNahcRyE/KLOq+hMWz2rjrfFtC7cyzxKRgxDgOF1myhFc2o:5i3Lhcp/y3cMWz2Hz27b4RgxDgOFIysn
TLSHT162527F84F3B58E5BDB762676A0F0130AE5F9B13716067B51212C403A7A9C39EC53FB88
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
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