Result for 04B87C43D04C4941230011C6CD382C9B8347C38C

Query result

Key Value
FileName./usr/lib/python3.5/site-packages/celery/app/__pycache__/defaults.cpython-35.pyc
FileSize9035
MD567D26CBFC32D90850A89C7D266ADD557
SHA-104B87C43D04C4941230011C6CD382C9B8347C38C
SHA-256639ADAE807F87DAFE5F8BC74A92EBB653D03E19D34BB54F4B23EF92D466F5AF2
SSDEEP192:E/LxJCTnoaVmfVe+uCKK5Opyudrbyysf2VcR//:E3CTnfYuPgWdrbyyncF/
TLSHT1AD123C472BF5D2D9F562BEF6D07522CA1E72F2857E0C934510A4E0227BE6ACF90E4189
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
MD5F9DDF342AB0263BA6DFDFADB9C6C03EF
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
PackageNamepython3-celery
PackageRelease2.fc24
PackageVersion3.1.20
SHA-1A78E19022E3EF58DDA204528AB50F0A197B0DA4D
SHA-2560DA0579739C43E8D42685D20194FBB47C5CA625A9F5437A290F89C1A56F36854
Key Value
MD5042DAB88C79682672D90CEDA5EB6784B
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
PackageNamepython3-celery
PackageRelease2.fc24
PackageVersion3.1.20
SHA-196F891EAD23CD72E82D3ADF6AADC8C9C5D0A8924
SHA-2567C321A613B3E17047566AE0DBD9F3E853BD54112ACF5175721E61734FB6AA4BC