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dask
distributed
Python2016–2021
dask / distributed

distributed

A distributed task scheduler for Dask

4Distinct people
4Mentions
0Explicit recommenders
1.7KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A distributed task scheduler for Dask

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 7:02:50 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year4 dated mentions

Observed mentions: 2016-04-12 17:21:53 UTC to 2021-11-18 12:42:30 UTC.

012016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20162017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC101
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101

What Hacker News says

1 sources
> I would suggest you don't make dramatic claims If you could point out some stuff from ZProc's page, that would be nice! > mpi is the grandfather of message passing libraries Never heard of it before, but just a simple google search reveals that it _might_ be more performant than zmq, but not as fault-tolerant and flexible. It really looks like a niche thing, from this comment by peter hintjens > Why smart cloud builders are betting everything on 0MQ. In detail, compare to the alternatives. Hand-rolling your own TCP stack is insane. Using any broker-based product won't scale. Buying licenses from IBM or TIBCO would eat up your capital. Supercomputing products like MPI aren't designed for this scale. There is literally no alternative. (http://zeromq.org/docs:the-ten-minute-talk) > Don't get me wrong, message-passing has some advantages, b
Read the rest
ut they certainly aren't that it 'solves' parallelism. Doesn't it? (For most people) --- I can't believe I'm hearing words against zmq on HN, its wierd. Even the guys over at Dask settled on ZMQ over anything - https://github.com/dask/distributed/issues/776 P.S. Seems like you know quite a lot about this topic. Do you have any projects of your own that I can see? Bottom line, I think most people would be happy doing message passing parallelism in the real world. Sure, it doesn't look that good in theory but works damn good in practicality.
In Parallel Programming with Python

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