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2017-12-08
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- # adventofcode (240)
- # beginners (87)
- # boot (4)
- # cider (27)
- # cljs-dev (20)
- # cljsrn (24)
- # clojure (365)
- # clojure-argentina (1)
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- # clojure-dev (12)
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- # portkey (5)
- # re-frame (4)
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- # shadow-cljs (17)
- # vim (1)
5 years remote. Agree on the importance of discipline. I work from a coffee shop once a week just to feed off the energy of people moving around me. On this remote job I’ve done, Clojure, Typescript, Kotlin, Groovy, Python & Go.
single laptop. External monitors are distracting. When I’m home I have an external monitor. I use it when I’m working indoors. When the weather is good, I work from the backyard only on the laptop.
Really? I need atleast: emacs + 3 terminals (cljs dev build, cljs prod build, clj build) + chrome (showing webpage) + chrome devtools for debugging + another chrome window [documentation / code I'm copying from]
I don’t use glasses yet, but I’m 40, and having lots of screens with small fonts give me a headache.
@qqq If you have Emacs, you shouldn't need additional terminals -- run it all inside Emacs! 🙂
I work with my editor full screen, dock/menu/task bar hidden. Single screen. Multiple desktops. Browser full screen on one, editor on another. A couple of terminal windows on another (for when I want to kick off full build/test processes -- and go read stuff elsewhere while that's running). Email full screen on another desktop. Slack on another. Helps keep the focus on just one thing at once.
Have anyone used Scala? I wrote a hello-world with a test and it takes 30 seconds to compile and run it with sbt
. It seems to be a pain to program with such slow compilation time.
we should move the conversation to ClojureVerse http://clojureverse.org for better readability. it would be available for more people searching.
Is ClojureVerse yet another StackOverflow clone (what are it's procs)?
A the same time, Clojure usually takes only 3 seconds to run tests via lein test
.
@ghsgd2 Usually you don’t run code in Clojure by starting a new JVM: the REPL is your main weapon there
@borkdude Yeah, repl reduces tests time even further. I worked on Java/Scala codebase and it seems that if code is simple enough and you could write it from 1st-2nd time that's fine otherwise it's just hard to use.
But there are people which used Scala for substantial time! I'm wondering how they managed to adapt to such a slow feedback loop.
Great cross-pollination example 🙂
@ghsgd2 yup, I’ve written Scala. It is super slow to compile and it is a well known fact
@niklas.collin Were you distracted from work by slow compilation?
Any tricks how to test some short Scala snippets?
What if I need to use my own class methods?
And it depends on class B and library C?
In Clojure I could re-evaluate defn
in REPL and start using updated version immediately. Is there something similar for Scala?
(`C-c C-e` and it's loaded)
I see. That's why Scala isn't for me. Thank you, @niklas.collin!
I try to stay away from Scala but unfortunately that’s the main language in my team currently 😞
it has some neat things like pattern matching and relatively good type system but in general it is overly complex and most scala code is near to being unreadable due to all libraries using implicit
keyword stuff and due to Scala’s obsession of trying to remove extra characters with syntatic sugar
Haha. It's yet another GWT. 🙂 May the force be with you and good luck maintaining it!
this destroys my mind since I’ve gotten used to instant feedback loop of Clojure development
it does get slightly better if you keep sbt running and let it auto compile stuff but still, it’s slow as hell
@ghsgd2 I think the fastest way is to make a file like this:
case class Foo(x: Int)
object Foo extends App {
println(Foo(1))
}
and then call scala file.scala
@borkdude Thanks, that's much better!
$ time scala file.scala
Foo(1)
real 0m1.440s
user 0m1.078s
sys 0m0.130s
which ML library (especially Deep Learning ones) offers the most power while requiring little to no ml/math/stats knowledge? (assuming there's such a thing) Personally atm I'm quite unwilling to learn ML - don't want to open the can of worms. I've heard there are some abstractions for non-ML-savvy devs, so I wonder - which is the best abstraction out there?
Re: Scala -- we tried Scala at work back in the 2.7/2.8 days. Slow compilation, impenetrable compiler errors relating to type conflicts, baroque code at times. We tried it because it had XML literal syntax and promised concurrency -- and we had a problem that involved producing a lot of XML exports. Back then the actor library had (known!) memory leaks so our app worked fine but had to be restarted via a cron job to avoid running out of heap(!).
The migration from 2.7 to 2.8 was incredibly painful -- with every milestone build introducing new binary compatibility problems and the entire tool chain needing to be updated (so you couldn't start using the new build of the compiler until all the libraries and tools you depended on had been rebuilt with that version).
yeah, scala never has compatibility between compilers, right?
It's better now but binary compatibility is still a bit of a problem.
That was 2009/2010. So I tried Clojure for the same problem and, although it initially ran slower, the code was even more concise than Scala, "compilation time" was effectively negligible due to the compile-on-demand nature of Cloure, and the syntax was way less confusing to read for newbies at the company. After some tweaks, the Clojure code ran faster than the Scala code (more concurrency was easier to write in Clojure). So we dropped Scala and started using Clojure for more things.
http://perun.io is also cool.
http://cryogenweb.org/ is great for that
Have you folks seen this? https://danluu.com/butler-lampson-1999/
It made me kinda angry but I think it’s ultimately sobering.
It was done in 1999. Maybe today it would be different.
hasn’t ARM become much more successful as a RISC since that was published?
Well and that everything is now RISC.
even Intel is RISC with with a wrapper now yeah
Intel-based processors have an internal instruction set that is RISC
it’s like a fugue in here
More of a crab-canon I’d say 😉
It'd be interesting to see a more up-to-date version of that @nickbauman
For example, parallel programming on GPUs has shared memory, but any sort of locks, or coordination between cores is extremely expensive.
and I mis-read some of the dates there, guess this is only 3 years old
The parallelism argument for being still a maybe is probably right.
Even with the superior way Clojure does it, allowing you to avoid the locking paradigm in nearly all situations.
But parallel programming problems are considered “solved” only to the degree that the problems can be expressed as “share-nothing” problems.
lotta interesting stuff isn’t “share nothing”
Thank you very much, @seancorfield! That's strange that Scala is popular in FinTech though.