Result for 02DC3B54334E2ED2A73FAD9D8F60C4CB987012BC

Query result

Key Value
FileName./usr/lib/python2.7/site-packages/celery/tests/test_task/test_context.pyo
FileSize6174
MD571DAC1061EC723CC0B4C623D404F8F46
SHA-102DC3B54334E2ED2A73FAD9D8F60C4CB987012BC
SHA-256EE6262D0AEF85FAEBB4290276FA60BFEA6C28A6B57835F1ED19815E12B856A1E
SSDEEP96:FLEjxG6HMJIhmsvCPyZ/zLUakwAACyMvF+hggDHnWDwdKUPoun/l:VEjxGWCKZ//HkwAwMvF+hg50h//l
TLSHT1AFD1BD90A3FA495BD5600436A2F04327EE75F0B7D900AB62123CE47C2DD8799C4AEB87
hashlookup:parent-total4
hashlookup:trust70

Network graph view

Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5434D72E7EA8C13F12D4EA12B8D63B4C9
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
PackageRelease1.fc17
PackageVersion2.2.8
SHA-1A4E3712A6ECFA3D0F193A02D55F10A5CD745488F
SHA-25647899557DB6061E5AD57ACB474C4841A7250607D847F55A14027D108CF9F9AAA
Key Value
MD547EAC1D28C12C4C6EF705FEB38656A78
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
PackageRelease1.fc17
PackageVersion2.2.8
SHA-11A157F9E0698A4A23B30951EF8D4E20DFBC42B7C
SHA-256C2CC3C8454FE469AB40E88105E826B9E234BD53EC4F09186834608050934F926
Key Value
MD5F017C46A709760F22613F55D93EF2773
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
PackageRelease1.fc17
PackageVersion2.2.8
SHA-163ECA3432BD716A289076D1FA27C9ECF6C60105F
SHA-2569198247CEE6E2EEF029180A97A66E388AA4C39385A7E985D44D98EA80BDE52D2
Key Value
MD532EB721A870A79C7CA3FB16D3B54B994
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
PackageRelease1.fc15
PackageVersion2.2.8
SHA-103FAD039308C15D07F0CD599CB26D530B1E97FC8
SHA-2569C0C47818FBB1FCADDD45A4E51FC7A2BFF006B2608A815F508DF49AA27EBDF4F