Result for 0009D591B502F561282128C1573E3AF2CE4CC2F2

Query result

Key Value
FileName./usr/lib/python2.7/site-packages/celery/app/annotations.py
FileSize1416
MD5D95BB29B569CB76099222160AD61BFB3
SHA-10009D591B502F561282128C1573E3AF2CE4CC2F2
SHA-256B5CFB3025F37082EAA17C8D914E434EDE6C545A0BC7C56F4DBB68DA5825AD865
SSDEEP24:lShx20O2FPd96RYGgAaWfpaopzi/umclB2iBM5BgNgn:0x2f+ELgAzaq+umipOOan
TLSHT1B42136CD27919955CF5F962A79B6C105E235788729052B78B4AD03241F73071B3EE88B
hashlookup:parent-total6
hashlookup:trust80

Network graph view

Parents (Total: 6)

The searched file hash is included in 6 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD55AB278C7F16131BA3CBFA842FEB3499F
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.fc19
PackageVersion3.0.15
SHA-19C572C79C52E198FD8322A6AD9EC53219B3C3E24
SHA-256DDF2C87B7B410DE19FB8B740E40369AD56C1318A161523D6581CD5C757C06E1A
Key Value
MD5D30D8C0D4D15D4C380BFF7F5EC6DDF8F
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.fc19
PackageVersion3.0.15
SHA-1D69133618A2EA7CC422B2D4C80FF45A680B26428
SHA-256F731EC5E7740258A321B9B589E5C9439B532784EE8AFD8000F45158CEAFCDB03
Key Value
MD5C3499A46E5C284990141CFD2A5B5FEE8
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.fc19
PackageVersion3.0.15
SHA-16989EF6FA18A96A261A090488A2C57A248BB5E16
SHA-2562D09A0F5075E2A70CB66DE65AA7D81D5059BDBEF6C692B2D65518849E3B1D7F3
Key Value
MD553BC43842BF07CC5D56BBE87973D3A44
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.fc18
PackageVersion3.0.11
SHA-1A83C81BA99C37EDC964A0475026D8A1199D62E04
SHA-2563941E8B2087CC6CF472B55DBFC45A2D70FF4CF6947C0A751FAD1F8EC4E5D7FA8
Key Value
MD5827EA0FB5A89EEFB3635C5C018A2358F
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.fc18
PackageVersion3.0.11
SHA-15B7785EA3C6CC9724B3E27C64444971C5C9CD496
SHA-256AF01E550874C09C65DE0CBF4F9B940F6C7A2153746B1CB3D99E87A758A4F1B13
Key Value
MD5DEEEC67F673E352BB995819A36083892
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.fc18
PackageVersion3.0.11
SHA-13FED1509C4B55AB136830B187E7EECD867F796DD
SHA-256CBF2B52A72FD20986D3B7A06D5C226ED00D008838850EDC1F1F2DDA4D56ED610