I found it crazy useful to study old, established, mature technologies, like relational databases, storage, low-level networking stack, optimizing compilers, etc. Much more valuable than learning the fad of the year. For example, consider studying internals of Postgresql if you're using it.

This plea for help is specifically for non-coding, but still deeply technical work.

He likely couldn't "just" do it. The synchronization overhead for federation is large, and with the amount of data Reddit has, you'd have to put a lot of effort into writing efficient code to handle that. Or pay for a lot of servers doing it.

BTW, it would be interesting to see whether current lemmy codebase could handle it as well…

I'm not a person who'd be loyal to a brand. Yet Motorola consistently produces devices that turn out to be the best trade-offs (price to functionality) for me. And, so far, all these devices were pretty durable as well, though it's not that I really put smartphones into lots of use. That's all I can say.

So far I've been following recommendations from this person: https://old.reddit.com/...

I guess the best start would be to have a person to organize volunteers.

At such scale, a scraper wouldn't be necessary, that's easily doable by humans involved in these communities—with a human touch as well.

Yes, many times. And I recall using the technique manually back when I was working with Subversion many, many years ago. No fun stories though, sorry, it's just another tool in a toolbox.

As of May 2023, 65% of the Ukrainian refugees that left Ukraine starting February 2022 and decided to stay in Poland found a job—so, within around a year, as opposed to 5-6 years as in the article. Cultural similarity here is likely making it much, much simpler. For those who want to read more about the situation of Ukrainian refugees in Poland, this report by Polish National Bank (Narodowy Bank Polski, NBP) might be useful: https://nbp.pl/... (in English!), there is a lot of interesting details.

From my experience, despite all the citogenesis described in other comments here, Wikipedia citations are still better vetted than in many, many scientific papers, let alone regular journalism :/ I recall spending days following citation links in already well-cited papers to basically debunk basic statements in the field.

Given these criteria, ggplot2 wins by a landslide. The API, thanks to R's nonstandard evaluation feature, is crazy good compared to whatever is available in Python. Not having to use numpy/pandas as inputs is a bonus as well, somehow pandas managed to duplicate many bad features of R's data frame and introduce its own inconsistences, without providing many of the good features¹. Styling defaults are decent, definitely much better than matplotlib's, and it's much easier to consistently apply custom styling. Future of ggplot2 is defined by downstream libraries, ggplot2 is just the core of the ecosystem, which, at this point, is mature and stable. Matplotlib's activity is mostly because that lack of nonstandard evaluation makes it more cumbersome to implement flexible APIs, and so it just takes more work. Both have very minimal support for interactive and web, it's easier to just use shiny/dask to wrap them than to force them alone to do web/interactive stuff. Which, btw, again I'd say shiny » dask if nothing but for R's nonstandard evaluation feature.

Note though that learning proper R takes time, and if you don't know it yet, you will underestimate time necessary to get friendly. Nonstandard evaluation alone is so nonstandard that it gives headaches to people who'd otherwise be skilled programmers already. matplotlib would hugely win by flexibility, which you apparently don't need—but there's always that one tiny tweak you would wish to be able to do. Also, it's usually much easier to use the platform's default, whatever publishing platform you're going to use.

As for me, if I have choice, I'm picking ggplot2 as a default. So far it was good enough for significant majority of my academic and professional work.

¹ Admitably numpy was not designed for data analysis directly, and pandas has some nice features missing from R's data frames.

Another idea that just occurred to me. Maybe position: absolute; both the real content and the gibberish content with the same top, left, width, and height attributes so that the real content and the gibberish overlap and occupy the same location on the page. Make sure both the real and gibberish content elements have no background so that remains clear. Put the gibberish content in the DOM before the real content. (I think that will ensure that the gibberish appears behind the real content even without setting the z-index.) And then make JS set the color of the text in the gibberish element the same color as the background so humans can’t see it.

Be aware that these techniques can affect accessibility for people using screen readers.

Last job, we started writing mixing bits of Kotlin in an otherwise mostly-Java in a monolithic Spring-based service. Good experience.

Yep, thank you, that's pretty close to what I imagined!

Mosh is not more secure than SSH: it uses SSH to initiate connections, so this is the upper bound.¹ Mosh's UDP protocol has not been given the same security attention as SSH's, though. As such, I'm willing to use it over the open internet for private stuff, but not for business use cases.

¹ I know mosh authors write «In one concrete respect, the Mosh protocol is more secure than SSH's: SSH relies on unauthenticated TCP to carry the contents of the secure stream.», but this refers to the UDP stream after the connection is initiated. If there is a security hole in SSH, it's pretty likely the attacker could take advantage of it during the connection initiation process. Mosh authors do acknowledge this in the subsequent paragraph: «However, in typical usage, Mosh relies on SSH to exchange keys at the beginning of a session, so Mosh will inherit the weaknesses of SSH—at least insofar as they affect the brief SSH session that is used to set up a long-running Mosh session.»

Kernel is not a monolithic application, and you cannot develop it like one. There are tons of actors: independent developers, small support companies (like Collabora), corporations, all with different priorities. There is a large number of independent forks (e.g. for obscure devices), that will never be merged, but need to merge e.g. security patches from the mainline. A single project management tool won't do, not your typical business grade tracking&reporting tool.

CI is already there. Not a central one—again, distributed across different organizations. Different organizations have different needs for CI, e.g. supporting weird architectures that they need to develop against.

There is a reason Torvalds created git—existing tools just wouldn't work. There might be a place for a similar revolution regarding a bugtracker…

Storj does it at 7 USD/TB. And there are providers that technically provide unlimited bandwidth, like Hetzner's dedicated servers; they still have some abuse limits, but even working within the limits should make it much cheaper. This means custom engineering though.

It is cumbersome to discover all these places on lemmy :/ Honestly, by the list of communities my instance shows, this one looks the most active. Thank you!

I've seen this text when it was published, and it was pretty eye-opening at the time. I liked it so much I've set a quarterly reminder to go back to it and review where did I manage to improve.

lemmy.ml is hosted in EU, and lemmynsfw.com uses CloudFlare, which operates in EU. Worst case, issue a GDPR request to both.