dunk
huey
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.
dunk
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Wilfred/difftastic: a structural diff that understands syntax
Here’s another one. Output is a little more colorful and resembles GitHub.
https://github.com/darrenburns/dunk
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A Guide to Overengineering a Windows Terminal
dunk - You can use this to get prettier git diffs.
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This Week in Python
dunk – Prettier git diffs
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Dunk is my new diff pager
# Dunk - prettier git diffs # https://github.com/darrenburns/dunk - name: check is dunk installed shell: command -v black register: dunk_exists ignore_errors: yes - name: install dunk when: dunk_exists is failed shell: pipx install dunk
huey
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Nextflow: Data-Driven Computational Pipelines
I've considered using Nextflow for bioinformatics pipelines but have yet to take the plunge. At work, I develop a proteomics pipeline that is composed of huey¹ tasks (Python library; simple alternative to Celery) which either use subprocess to call out to some external tool, or are just pure python. It runs in a worker container which is created by docker swarm, and all containers pull jobs from redis. For our scale, it works great. However, I don't have control over the resource utilization of individual steps, and in the past I've had issues with the pipeline blocking as a result of how I was chaining tasks together. I think something like Nextflow would remove these limitations, but one thing I think I would miss is the ability to debug individual pipeline steps locally with an interactive debugger. As far as I can tell, Nextflow has logging/tracing facilities but nothing quite like an interactive debugger. I'd be happy to be told I'm wrong, or even that I'm doing it wrong.
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¹ https://github.com/coleifer/huey/
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Background jobs with Django
Other options are DjangoQ and Huey, which tend to work ok. Of the two I prefer DjangoQ. Database backed, don't require the Redis/Celery rigmarole.
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What's the best thing you've learned about Django this year?
Funny, just this moment i finally switched from Celery to huey. And so far I don't regret. huey looks very promising, has good documentation and is well integrated into DJango. You should give it a try: https://github.com/coleifer/huey
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This Week in Python
huey – a little task queue for python
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What is your favourite task queuing framework?
Huey -> Same again?
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5 background scheduling libraries in Python you must know
Huey: https://github.com/coleifer/huey
- Celery in production: Three more years of fixing bugs
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Not sure if I should use celery or asyncio
I just want to add that a couple celery alternatives worth looking at include huey and dramatiq.
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What is the best option for a (Python 3) task queue on Windows now that Celery 4 has dropped Windows support?
huey
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Django 4.0 released
same, I ran into an issue cos of django-background-tasks. I am thinking to replace it with huey
What are some alternatives?
themes - Themes for Windows Terminal
celery - Distributed Task Queue (development branch)
DeepFaceLive - Real-time face swap for PC streaming or video calls
rq - Simple job queues for Python
geodiff - Library for handling diffs for geospatial data
dramatiq - A fast and reliable background task processing library for Python 3.
z - Save time typing out directory paths in PowerShell by jumping around instead.
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
gh-dash - A beautiful CLI dashboard for GitHub 🚀
mrq - Mr. Queue - A distributed worker task queue in Python using Redis & gevent
Pipe - A Python library to use infix notation in Python
KQ - Kafka-based Job Queue for Python