Result for 068087DFA0C4EF350937B06C6C804FA9DA14B86C

Query result

Key Value
FileName./usr/lib/python2.7/site-packages/celery/loaders/base.pyo
FileSize11114
MD54AA9370394E32F439C51FC10D4866C58
SHA-1068087DFA0C4EF350937B06C6C804FA9DA14B86C
SHA-2560CD988E7999EC2FE21318AEEF73B2DF4C3BA088E28E1CC0080F4185F4017A79C
SSDEEP192:8s8tCYuniJ+xhizElas5ltEnwcz7sE+utQnuBvivwvTDhqM:1YurMz6l8/spu2uBhTDhqM
TLSHT1703240C0A3F98D57D2B555B2D4F0131B99A4F07396013B82323C607E6EDD6A9C4BB78A
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
MD5D5A8BC3900068FD517AB157AF5CBEA98
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 web hooks. 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
PackageNamepython2-celery
PackageRelease2.fc24
PackageVersion3.1.20
SHA-1F65D060B30D33945DEDEB3386622B94C60810367
SHA-256D87DF7BE17D4F53B2DE87546C7A839A856DCDB5DB130C2DE081EF7FB120A74CF
Key Value
MD54B446B573EA850D5B36850AA7FD94A69
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 web hooks. 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
PackageNamepython2-celery
PackageRelease2.fc24
PackageVersion3.1.20
SHA-1CCF599967E71BDB38AA2BD1B3B6691D046D685B5
SHA-2568AA0CECEEEA9F691DABF1C21EA22C575FE69EE3027C1FEAC3D068583E17AA794