Skip to main content

Celery Headless Connectors

Project description

Running headless Celery bootsteps to process json or pickled messages from Redis, RabbitMQ or AWS SQS. Also has a Kombu Publisher with docker RabbitMQ and Redis containers included as well. Headless means no task result backend (like mongo). I am planning to glue Django and Jupyter together with this connection framework, and allow workers to process messages from my windows laptop out of a shared broker.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

celery-connectors-1.0.5.tar.gz (25.8 kB view details)

Uploaded Source

Built Distribution

celery_connectors-1.0.5-py2.py3-none-any.whl (33.1 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file celery-connectors-1.0.5.tar.gz.

File metadata

File hashes

Hashes for celery-connectors-1.0.5.tar.gz
Algorithm Hash digest
SHA256 55b38742f38b94ac7764c3a108c8f4b78279d00d2d9ced04c1a7ac9058d836e4
MD5 08e273c1c6869fcb59921bed85888e47
BLAKE2b-256 03d1173fba919ccc239d6716986ce460adabfd32afc21e6b2718767787b1e49f

See more details on using hashes here.

File details

Details for the file celery_connectors-1.0.5-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for celery_connectors-1.0.5-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 4b6ae5da028304213004a6f8bb880b66259564986a36ae695173f6d1a317b64c
MD5 c8ca2bb0d2e5aef37e5bb507b9c62f4d
BLAKE2b-256 b3d8b705d6ee713d79b7d9281bb9f4c2c029d9b505cfbd5ba82f0bb37b36efa9

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page