Use case: dask + redis + progress reporting
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- python, redis
Research direction
Start with distributed/diagnostics/progress.py, especially MultiProgress, and compare the cited rq, arq, and huey queue models. Define an approach for submitting Dask workflows through a web API, running workers, and storing workflow status and progress in Redis; the issue is done when that approach is agreed and documented.
Written by the indexing model from the issue text.
Description
I have a couple of DAG workflows in dask. These workflows are triggered via user interfactions through a web API. I'd like to achieve the followings:
- The web API puts the workflow to a redis queue (RabbitMQ would be nice too, but redis is easier to start with).
- Run workers like the majority of job queue frameworks do (rq, arq, huey)
- Store the progress and current status of the workflows (with MultiProgress I guess) as key/values in redis
What would be the correct approach to implement it?
- Dominant language
- Python
- Stars
- 1.3k
- Forks
- 149
- PR merge metrics
- No merged PRs in 30d
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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