Result for 059215B81051A2AA5D3B58917B3048138D182D64

Query result

Key Value
FileName./usr/share/doc/python3-celery/examples/app/myapp.py
FileSize479
MD5E55760BEED9904C1EBF39C3465F0EBAA
SHA-1059215B81051A2AA5D3B58917B3048138D182D64
SHA-2568B862CF277D0BE4C265E3E9D62CB55F419F088DB101F091FFE1BE8C77A692DEB
SSDEEP12:odBJsJsYBJg/1LrGkQ0wCb3IwlxxJsVDB9OmgsE2aRLC:WBJDYBJgprWCzIzVbOmgs5aRLC
TLSHT137F0971788B7C2B0D7B985DFD28BE1A064652F2B56A0B315143485202E69A014EE50DC
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
MD572C521863B1706EC25A92444C511D458
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
PackageNamepython3-celery
PackageRelease4.fc20
PackageVersion3.0.19
SHA-12D1FD3DF14359932CDB295F4168C44F86C6013D5
SHA-2561C5DF61FB93AA545A60EBA2CEF77880256C119AA8AE0263BC54F3BCF3519B9A7
Key Value
MD55F1C1177B7FC41870EA7D7B25B9E5B05
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
PackageNamepython3-celery
PackageRelease4.fc20
PackageVersion3.0.19
SHA-1D1AB5F53BBB23332BA675E08671B9BA7796645D8
SHA-256B96C248FD620BD1A7B02999F3A0AC37FEDCCF518F9BF0DA831D30774F9F0B290
Key Value
MD5313F408CD4E48C5C99F5B530BE6F459E
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.fc20
PackageVersion3.0.19
SHA-196BD5146AFE8100BDFD8DD807103D06AD6D7F9D3
SHA-25667E91DDD4DEA28FF16A5734389815FA748A0E2BB5B440305848A794EA2FB0C52
Key Value
MD57BAC8D3EB153BF7CF0F6BBB2FC1345BE
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.fc20
PackageVersion3.0.19
SHA-121AECBF834F753AAD30F68CDCBE8E0A7D70FF8C6
SHA-256F1BC6BDEB4B1C93A31F03C5A7064B5B64BA6924930705B7E222277D8BEED58D6