Seamlessly prevent duplicate executions of celery tasks
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Updated
Jun 9, 2023 - Python
Seamlessly prevent duplicate executions of celery tasks
Celery Batches allows processing of multiple Celery task requests together
Train AI (Keras + Tensorflow) to defend apps with Django REST Framework + Celery + Swagger + JWT - deploys to Kubernetes and OpenShift Container Platform
Digital menu QR code generator app backend
E-commerce Web Application written in Django with Payment Integration, Asyncronous task processing using Celery, Flower etc..
A simple example of how to use Celery to schedule periodic tasks. It uses Redis as message broker.
Python factory for limiting Celery tasks by configuration
Integrating Flask API backend with Celery for long running tasks
A Platform designed to track different products on the biggest Ecommerce in MENA region
Dynamically update periodic tasks in Celery
一个来源于实际项目中的 celery-task-server 精简版
Helper to monitor jobs running Celery tasks in Django
background jobs in flask using celery, sqs and postgresql
Automated testing using pytest and performance testing using locust and django-silk .
My playground for Celery trials
An example of running multiple celery with each other consecutively
How To Mock Celery Tasks With Pytest (Step-by-Step Guide with Examples)
This is a flask application through which you can hit rest api's that allow you to create and add tasks in queue that executes and returns result asynhronously.The application is run on a uWSGI server and requests are routed through an nginx reverse-proxy. Docker is used to containerise each service and they are managed with docker compose
User can transfer balance now or later in bulk. After every successful transfer a transaction history will be created for both the accounts. Cash transaction(withdrawal or deposit) option is also available. In case of transfer failure no transaction history will be created and source account's balance will be adjusted.
It is kubernetes microservice that ingests Steam data, deployed as a service using sQLite for storing processes followed by an event driven message queue controlled by RabbitMQ. This message queue is also deployed as a service with an interconnection with celery workers integrated with Elasticsearch and Redis for caching and ingestion.
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