and that is why the share of households with AC is increasing rapidly in places that didn't use to have them, as one would expect.
3,729 karma · joined September 16, 2008
Its funny how its mostly US-based libertarian types concerned about AC in Europe. There are plenty of things Europe over-regulates, but this is not it.
> What makes the “simulate inputs” approach work is that the engine takes utmost care to keep calculations identical on each client. This is not trivial because you still have to work with things that naturally differ on each client, such as mouse position or which units are selected - this is called the unsynced state. On top of that, there can be hardware differences that have to be worked around to get identical results - the huge effort involved is one of the reasons why Recoil is not available outside x86-64.
And also it has inspired a few other clojure datalog databases, so there is much more choice: * https://github.com/datalevin/datalevin * https://github.com/replikativ/datahike * https://github.com/threatgrid/asami
There is also xtdb, but it abandoned datalog and is going in another (albeit interesting direction) https://xtdb.com/
here is a comparison website, but it is somewhat out of date: https://clojurelog.github.io/
So it must have tools save, manipulate and visualize conveniently (pretty printing, folding etc) the values of vars that contain nested maps, sequences, sets, etc.
Existing clojure IDEs like CIDER for emacs or Calva for VSCode do that too, and it is a must have to have a nice experience with the language
For me the best textual interface I've ever used remains Magit in Emacs: https://magit.vc/ I wish more of Emacs was like it.
I actually use emacs as my git clients even when I'm using a different IDE for whatever reason.
For our team, it is very simple:
* we use a library send traces and traces only[0]. They bring the most value for observing applications and can contain all the data the other types can contain. Basically hash-maps vs strings and floats.
* we use manual instrumentation as opposed to automatic - we are deliberate in what we observe and have great understand of what emits the spans. We have naming conventions that match our code organization.
* we use two different backends - an affordable 3rd party service and an all-on-one Jaeger install (just run 1 executable or docker container) that doesn't save the spans on disk for local development. The second is mostly for piece of mind of team members that they are not going to flood the third party service.
[0] We have a previous setup to monitor infrastructure and in our case we don't see a lot of value of ingesting all the infrastructure logs and metrics. I think it is early days for OTEL metrics and logs, but the vendors don't tell you this.
* I can comfortably read any PDF; I don't think the font is too tiny. This is the main reason I bought it for.
* Android means great data support, I can open any format and I can even install the kindle app and read the books I purchased there.
* Using the pen seems nice enough, I started doing some annotations although I didn't buy this device for that.
* Nice way to sort of "airdrop" files from devices on the same network
The bad:
* I am a bit unhappy with the battery life; I hope I will tune it at some point.
* the screen is a little dark, so the "frontlight" needs to be on more often than a black and white e-ink device
The weird:
* the built-in AI assistant is trained in the PRC and has quite interesting opinions on current events and recent history.
So clothing can be more fun, if people want to of course - look at how music subcultures have incredibly varied ways of expression through clothing - metalheads, hiphopheads, punks etc.
It might be slightly harder to get started with, but then the simplicity comes in when it is time to solve common business problems. A trivial example would be - we have this nice db, now our clients want reports. You run your reporting as a separate clojure process, it doesn't impact production at all, without needing to setup reporting databases and log-shipping.
Rachel is spot on about what is often wrong with IT culture; "typecasting" people for someone's convenience or to get a fancy title leads to learned helplessness and dissmissing other people's expertise and interests. I rather we all try to keep things simple and encourage people to be well-rounded engineers.
* The cond macro which works similarly to C switch
* Hashmap functions like merge and merge-with
* Destructuring
* The for macro which is similar to the "for each in" statements
None of these are something unfamiliar to common programming languages so that code will not be hard understand once you go over the initial syntax and idiom hump. The syntax makes things much easier once you get to used to it, I think all Clojure programmers like it.
Casablanca
The first Sean Connery James Bond films, Casino Royale with Daniel Craig
The Matrix
Django Unchained
The Wolf of Wall street
Easiest way to do it any language is to shell out to gum: https://github.com/charmbracelet/gum
There are no production dbs in k8s, no service meshes, monitoring is only side-cars that send data to an off-cluster backend,
The automatic deployment with flux seems pretty nice!