Redis
celery
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Redis | celery | |
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237 | 36 | |
58,355 | 20,878 | |
0.6% | 0.8% | |
9.8 | 9.6 | |
4 days ago | 3 days ago | |
C | Python | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Redis
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When not to use Deno โ๏ธ
Database reads are expensive and slow. There's a multitude of other reasons why caching is essential, but for the project I'm working on I'm using supabase and their free tier supports only a limited amount of bandwidth. To avoid any rate-limiting I added a Redis layer in front of it to reduce the number of queries that hit the database directly.
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Lessons learned from picking a Java based driver for Amazon ElastiCache for Redis - Part 1
The AWS Lambda function had been written in Java and therefore the team looked at different Java-based Redis drivers and eventually decided to use Jedis, a Java client for Redis designed for performance and ease of use. One of the reasons they chose to use Jedis was that it proved to be a lightweight library. Instantiating the client connection takes somewhere between 200-600ms (depending on the lambda memory settings) which impacts the cold start of the lambda function.
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Scaling moderate sized websites
Caching - while it's not possible to cache everything, there's always a large percentage of your website / app that can be cached for an hour or ten minutes or 1 day etc... - all depends on the type of content but the longer you can cache for without negatively effecting content quality - the better. A good caching server example would be redis : https://redis.io/ or https://memcached.org/
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Unleashing the Power of GPT-3 with a Serverless Node.js REST API: A Step-by-Step Guide
The code uses the codehooks-js library to handle routing and middleware for the API, and the node-fetch library to make HTTP requests to the OpenAI API. The code also uses the built-in codehooks.io Key-Value store to cache the response from the OpenAI API for 60 seconds, in order to reduce the number of requests made to the OpenAI API (If you want to create your own Node.js Express backend, you just need to replace this cache with Redis for example).
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Using In-Memory Databases in Data Science
Redis is an in-memory database and an open-source streaming engine with an IMDB data structure server that supports multiple data sets and data streams. This open-source platform has high throughputs and lower bandwidth due to its in-memory features that lead to faster processing of big data in data science applications.
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Guaranteeing webhook delivery in NextJS Application
Quirrel is a popular open-source webhook framework that makes it easy to add webhook support to your app. It makes uses of redis under the hood.
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System Design: Caching, Content Delivery Networks (CDN) & Proxies.
Redis
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All you (probably) need to know about caching on the web ๐
Redis is an in-memory data store that you can use as a database โ or a cache in front of your regular database. The speed of Redis makes it ideal to cache database queries, complex computations, API calls, and session state.
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Database 101: Data Consistency for Beginners
I didn't finish college and I didn't see anything about Databases when I was there, so I don't have any theoretical background and on these 4 years coding at enterprise level my focus was totally in things like: Clean Code, SOLID, Design Patterns and other stuff code related and my only Database knowledge was about SQL/MySQL and Cache/Redis.
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Perl Weekly #597 - Happy New Year!
For the course I started to collect Open Source projects developed by corporations. There are a few where the product is open source such as Redis and Elastic. There are others where the company shares some of its code as open source such as Netflix, Facebook, or Booking.com.
celery
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Django Styleguide
I spent 3 years building a high scale crawler on top of Celery.
I can't recommend it. We found many bugs in the more advanced features of Celery (like Canvas) we also ran into some really weird issues like tasks getting duplicated for no reason [1].
The most concerning problem is that the project was abandoned. The original creator is not working on it anymore and all issues that we raised were ignored. We had to fork the project and apply our own fixes to it. This was 4 years ago so maybe things improved since them.
Celery is also extremely complex.
I would recommend https://dramatiq.io/ instead.
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Processing input and letting user download the result
You can use celery to process the file for extraction, saving and creating rar/zip.
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RQ-Scheduler for tasks in far future?
Celery not usefull for long term future tasks (far future) ยท Issue #4522 ยท celery/celery (github.com)
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Dedicated backend resources per client
A different approach would be to have a main web application which would communicate with worker processes for time intensive operations as you describe. The web app would communicate with workers via some form of MQ or even database. Many solutions exists for that in different languages, one such solution is [Celery](https://github.com/celery/celery) primarily developed for Python but these days it also supports Node, Go, PHP and Rust.
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Alternative for Django Celery.
Django-q2 only requires one dependency (except for Django itself). Celery, requires quite a few: https://github.com/celery/celery/blob/master/requirements/default.txt
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Deploying Django Application on AWS with Terraform. Setting up Celery and SQS
Add a Celery + SQS setup for local development.
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What is your favourite task queuing framework?
Celery -> What I'm currently considering using
same! the issue has been open with a lot of people experiencing it, but no resolution https://github.com/celery/celery/issues/4185
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What happened to the Celery project website?
It seems to be a preliminary home for the docs while the issues with the current domain are sorted out (see issue #7351).
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Boilerplates for integration services when you need to sync API resources or databases
Several years ago, finishing another such task at work and spending a lot of time integrating the Pytest with SQLAlchemy (I am loving TDD so much), I decided to create a boilerplate for such a service. At that time, I used Celery. So I stuffed my project with Celery, SQLAlchemy, Docker and Pytest.
What are some alternatives?
dramatiq - A fast and reliable background task processing library for Python 3.
Apache Kafka - Mirror of Apache Kafka
huey - a little task queue for python
rq - Simple job queues for Python
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
kombu - Messaging library for Python.
Redis - ๐ A robust, performance-focused, and full-featured Redis client for Node.js.
Sidekiq - Simple, efficient background processing for Ruby
mrq - Mr. Queue - A distributed worker task queue in Python using Redis & gevent
KQ - Kafka-based Job Queue for Python
arq - Fast job queuing and RPC in python with asyncio and redis.
Gearman