Result for 013793508EC6A61D7C79747AC594D1858FA1703B

Query result

Key Value
FileName./usr/lib/python2.7/site-packages/celery/canvas.pyo
FileSize26323
MD5109732E9EB217CE4E4D1410F30874A07
SHA-1013793508EC6A61D7C79747AC594D1858FA1703B
SHA-256B34CDB7E5AADD05A0D59D6452B59EB53DDC107C9BC2122E60433B0123C3D3F68
SSDEEP768:dJCm+GLN8eviGMQjUOsHZB9uVf3NIzNNMqnvV2kbkjykDXEwJta4InCpIWA2+GWK:dgm+GLN8kMQjUOmZPuVf3NIzNNMqnvVy
TLSHT19FC21044F3FA495BE661557190F0221BEAB5F07312013B4231AC55376DF8AAEC87EBC9
hashlookup:parent-total3
hashlookup:trust65

Network graph view

Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD53ADB92A768A8D5E030BF31F155B21B58
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
PackageRelease4.fc23
PackageVersion3.1.9
SHA-13C7FDFD4F67F27FD72F3DC4D9DAE6F3DF4A3F8B9
SHA-256E88D8FD0E7EA7D01436FD3A6A324515CFE654560CD0A393BDF154956E165E2EE
Key Value
MD55B80AD979CF836B674A7D6735C12BCAB
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
PackageRelease4.fc23
PackageVersion3.1.9
SHA-1C97185ACFD5327C8ECA353CA36D9B94B07E66670
SHA-2567B33BA996E10938E117A588924A9C1C70E947256022E179981FC2A1FE53E2799
Key Value
MD58BF659EC1BE47E624F476EE71B35173F
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
PackageRelease4.fc23
PackageVersion3.1.9
SHA-1AFA49ABA28324F8AE9E3DD82866C50DD3D0DF23A
SHA-25610D43CC290A443B2A116732B21180B1C7D83AB3281787AA34851BCBF121F0ABE