Result for 04E1D25B66C018B92EBB1C6354A5087C0BB39BC6

Query result

Key Value
FileName./usr/lib/python2.7/site-packages/celery/tests/test_events/test_events_state.pyo
FileSize14906
MD556405175D40CC60CE072B42BD6230DAD
SHA-104E1D25B66C018B92EBB1C6354A5087C0BB39BC6
SHA-2563E36E3F9143B76964B9A714ADBA297FDBA41670ABD35D56814905A0A2F1235DE
SSDEEP192:s/Z0ZtNm3eXaQ2PfjDRL14k6HR2j7rdEx22YCW:s2XguaQ2Pf//iRu/dEx2yW
TLSHT11B628CC0B3B68B1BD5B41136A3F41317FDB0F4F779016BA011A898792AD8359C5AE3DA
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