I’ve never used Haskell. I won’t claim I’m good at Rust. I mostly work with Ruby and Clojure, both dynamic languages where you don’t really need to worry about types. But then of course that’s not true. Even if you put Rails’s magic aside, it’s way too easy to write code that accidentally works (in an absolutely unintended fashion).
What’s the deal with types?
What’s an ideal database?
I’ve been reading about and considering language design choices (for my new pet project), and one thing I really like (though I rarely actually use in action) is Clojure’s transducers. I couldn’t find it in the talk introducing them, but I vaguely recall someone vaguely recalling that Rich Hickey said Clojure’d have much less laziness if he’d found the idea of transducers sooner.
Then in a completely different thought process (maybe there could be transducers, process transformations for thought processes as well?) about databases. I was considering databases I used so far, things I tried to achieve with them, the difficulties and nice things.
Writing a lisp-ish compiler in Rust
It was a while back that I got a notice from Shibuya lisp that the 100th event is coming up. It’s a (Common) Lisp/Clojure meetup in Tokyo (though since covid, online). I don’t know if it’s a common thing among lispers, but everyone there seems to at least try writing their own lisp (and talk about it) somewhere down the path.
Before I wasn’t that interested. I could do most of what I wanted to do in Clojure without too much pain. Then I tried writing a (performant) wrapper around Netty and it got a bit more painful. Things like
nth calls on function argument lists started showing up on my flame charts (testing with 100 million requests) and rough edges around interop cut my hands (hello
proxy and abstract classes).
ErlangはEricssonがはるか昔に開発した通信環境用の言語で、ものすごく頑丈で安定している環境として有名。実際に世界中のモバイル通信環境で用いられ99.9999999% (“nine nines”) の可用性を誇っている。最近ではRuby風でErlangのBEAMを実行環境とするElixirが流行っている印象がある。分散を前提にしている関数型言語としてClojureに近いと感じた。そして実際にBEAMの上でClojureを実装しているものがある。
Down the __extmap rabbit hole
Was trying to figure out whatzerusski on Clojurians Slack
defrecorddoes in the impl of ILookup it generates and I absolutely do not understand that magic. Essentially it amounts to
(get __extmap key)and I can’t even figure out how this magical
__extmapgets into scope (a global or some special runtime thing?) and
thisisn’t even used. Confused
This post on Clojurians sent me down the rabbit hole looking for where this “mysterious”
__extmap comes from. It really isn’t obvious at first, but when I found it, it was “wow” times “duh”.
Clojure and Java functional interfaces
functions all you want. Java’s had Runnable and Callable that are pretty similar in concept.
->. In Ruby it’s
(foo) -> foo, and surprisingly in Java it’s the same. Run a few rounds with futures and/or streaming stuff and you’ll definitely want to pass such a lambda to
forEach for example.
Next up in the series complaining about Clojure’s Java interop is proxy. While vararg method calls are inconvenient at worst, there are some (I’d say common) things that simply cannot be achieved with proxy.
Once again this is something I ran into while working with Netty. In one of the HTTP/2 examples, they have one implementation extending AbstractHttp2ConnectionHandlerBuilder<T, B> (have I mentioned I find these extremely long Java class names just hilarious?). The Java implementation is pretty straightforward: implement the abstract method of the class and be done with it.
Clojure vs Java varargs
Variable length argument lists (varargs) have been around since Java 5 (so quite a long while), yet I get the impression that many people either don’t know about this feature or their tools don’t support it. I ran into one of them working with Netty from Clojure and it wasn’t trivial at all how to use them through interop.
Partition of integer into exactly the given number of distinct parts
Ran into this issue in a programming challenge on HackerRank and I was surprised there weren’t any “simple” solutions online. The math related is mostly focused on finding the number of possible partitions of an integer, instead of generating even just one such partition.
A very naive approach might be to enumerate all partitions and then filter them down to those with exactly the wanted number of summands and then filter further to those with distinct parts and pick the first that fulfills the conditions.
But when the subject integer can be 1018 then that simply isn’t realistic. Insert sophisticated simile involving the heat death of the universe.
Counting the milliseconds
I’ve been building a Netty-based web server in Clojure. While I haven’t had the strength to do much with it these past few months because I prioritized the climbing season, now that Hacktoberfest is incoming I’m planning to go pedal to the metal with it (and with my git GUI work-in-progress).
I’m building iny (named after a fox from Fekete Istvan’s Vuk) with the clear goal to replace Aleph. While I’m a huge fan of Aleph and the libraries around it (like Manifold) it’s no longer maintained, which is simply not acceptable when we’re now looking at http/3 coming out sooner than later (support is already in browsers after all).
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