Threads for justinhj
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Okay, so what programming language is category theory? Is there a language where you can define algebraic laws and enforce them?
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Suppose you define a typeclass that represents an algebraic structure (like Monoid for example). This structure has some associated algebraic laws. I understand that in Haskell, you can’t enforce that instances of your typeclass obey these algebraic laws. Are there any programming languages that do a better job than Haskell at enforcing algebraic laws in typeclass instances?
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Pretty much “any” dependently typed language should allow formulating those laws I presume: Coq, Agda, Idris, Lean, …
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you can write proofs in agda about your code in relation to laws and then generate haskell from it. see https://github.com/agda/agda2hs that’s the ideal, but it has a lot of restrictions
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In general, there is a precise correspondence between variants of typed lambda calcului and what is known as the “internal logic” of categories which obey certain extra properties.
Here are some words:
Simply typed lambda calculus is the internal logic of Cartesian closed categories.
Linear typed lambda calculus is the internal logic of symmetric monoidal categories.
The “reason” for these correspondences is that one can use a category as an “abstract machine” to compile these lambda calculi into. For worked out examples, see the paper “compiling to categories” by conal Ellott. Finally, I apologise for not linking to anything, as I’m typing on my phone :)
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I studied AI back when Prolog was predominantly used in European AI research and I still have a soft spot for the language, even if I immediately stopped using it on graduation and wrote video games in C
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justinhj
2 years ago
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Do you know of resources like rubykoans or ziglings for other languages?
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nooga
2 years ago
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Do you know of resources like rubykoans or ziglings for other languages?
I see Clojure in that repo but I have two other links: http://clojurekoans.com/ and http://clojurescriptkoans.com/
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There’s also https://www.4clojure.com/
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spacejam
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2 years ago
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Why I rewrote my Rust keyboard firmware in Zig: consistency, mastery, and fun
FWIW, this is how you express conditional arguments / struct fields in Rust. The condition has to encompass the name as well as the type, not just the type as was first attempted.
I feel like Rust has definitely obliterated its complexity budget in unfortunate ways. Every day somebody comes to the sled discord chat with confusion over some async interaction. The fixation on async-await, despite it slowing down almost every real-world workload it is applied to, and despite it adding additional bug classes and compiler errors that simply don’t exist unless you start using it, has been particularly detrimental to the ecosystem. Sure, the async ecosystem is a “thriving subcommunity” but it’s thriving in the Kuhnian sense where a field must be sufficiently problematic to warrant collaboration. There’s no if-statement community anymore because they tend to work and be reasonably well understood. With async-await, I observed that the problematic space of the overall community shifted a bit from addressing external issues through memory safety bug class mitigation to generally coping with internal issues encountered due to some future not executing as assumed.
The problematic space of a community is a nice lens to think about in general. It is always in-flux with the shifting userbase and their goals. What do people talk about? What are people using it for? As the problematic space shifts, at best it can introduce the community to new ideas, but there’s also always an aspect of it that causes mourning over what it once represented. Most of my friends who I’ve met through Rust have taken steps to cut interactions with “the Rust community” down to an absolute minimum due to it tending to produce a feeling of alienation over time. I think this is pretty normal.
I’m going to keep using Rust to build my database in and other things that need to go very fast, but I see communities like Zig’s as being in some ways more aligned with the problematic spaces I enjoy geeking out with in conversations. I’m also thinking about getting a lot more involved in Erlang since I realized I haven’t felt that kind of problem space overlap in any language community since I stopped using it.
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I was surprised to see the Rust community jump on the async-await bandwagon, because it was clear from the beginning it’s a bandwagon. When building a stable platform (e.g. a language) you wait for the current fashion to crest and fall, so you can hear the other side of the story – the people who used it in anger, and discovered what the strengths and weaknesses really are. Rust unwisely didn’t do that.
I will note though that the weaknesses of the async-await model were apparent right from the beginning, and yet here we are. A lesson for future languages.
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This hits me particularly hard because I had experienced a lot of nearly-identical pain around async when using various flavors of Scala futures for a few years before picking up Rust in 2014. I went to the very first Rust conference, Rust Camp in 2015 at Berkeley, and described a lot of the pain points that had caused significant issues in the Scala community to several of the people directly working on the core async functionality in Rust. Over the years I’ve had lots of personal conversations with many of the people involved, hoping that sharing my experiences would somehow encourage others to avoid well-known painful paths. This overall experience has caused me to learn a lot about human psychology - especially our inability to avoid problems when there are positive social feedback loops that lead to those problems. It makes me really pessimistic about climate apocalypse and rising authoritarianism leading us to war and genocides, and the importance of taking months and years away from work to enjoy life for as long as it is possible to do so.
The content of ideas does not matter very much compared to the incredibly powerful drive to exist in a tribe. Later on when I read Kuhn’s Structure of Scientific Revolutions, Feyerabend’s Against Method, and Ian Hacking’s Representing and Intervening, which are ostensibly about the social aspects of science, I was blown away by how strongly their explanations of how science often moves in strange directions that may not actually cause “progress” mapped directly to the experiences I’ve had while watching Rust grow and fail to avoid obvious traps due to the naysayers being drowned out by eager participants in the social process of Making Rust.
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I think that Kuhn’s Structure of Scientific Revolutions has the broadest appeal and I think that nearly anyone who has any interaction with open source software will find a tremendous number of connections to their own work. Science’s progressions are described in a way that applies equally to social-technical communities of all kinds. Kuhn is also the most heavily cited thinker in later books on the subject, so by reading his book, you gain deeper access to much of the content of the others, as it is often assumed that you have some familiarity with Kuhn.
You can more or less replace any mention of “paper citation” with “software dependency” without much loss in generality while reading Kuhn. Hacking and Feyerabend are more challenging, but I would recommend them both highly. Feyerabend is a bit more radical and critical, and Hacking zooms out a bit more and talks about a variety of viewpoints, including many perspectives on Kuhn and Feyerabend. Hacking’s writing style is really worth experiencing, even by just skimming something random by him, by anyone who writes about deep subjects. I find his writing to be enviably clear, although sometimes he leans a bit into sarcasm in a way that I’ve been put off by.
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If you don’t mind, what’s an example of async/await pain that’s common among languages and not to do with how Rust uniquely works? I ask because I’ve had a good time with async/await, but in plainer, application-level languages.
(Ed: thanks for the thoughtful replies)
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I read that one, and I took their point. All this tends to make me wonder if Swift (roughly, Rust minus borrow checker plus Apple backing) is doing the right thing by working on async/await now.
But so far I don’t mind function coloring as I use it daily in TypeScript. In my experience, functions that need to be async tend to be the most major steps of work. The incoming network request is async, the API call it makes is async, and then all subsequent parsing and page rendering aren’t async, but can be if I like.
Maybe, like another commenter said, whether async/await is a net positive has more to do with adapting the language to a domain that isn’t otherwise its strong suit.
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You might be interested in knowing that Zig has async/await but there is no function coloring problem.
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Indeed this is an interesting difference at least in presentation. Usually, async/await provides sugar for an existing concurrency type like Promise or Task. It doesn’t provide the concurrency in the first place. Function colors are then a tradeoff for hiding the type, letting you think about the task and read it just like plain synchronous code. You retain the option to call without await, such that colors are not totally restrictive, and sometimes you want to use the type by hand; think Promise.all([…]).
Zig seems like it might provide all these same benefits by another method, but it’s hard to tell without trying it. I also can’t tell yet if the async frame type is sugared in by the call, or by the function definition. It seems like it’s a sort of generic, where the nature of the call will specialize it all the way down. If so, neat!
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Well, I think that async/await was a great thing for javascript, and generally it seems to work well in languages that have poor threading support. But Rust has great threading support, and Rust’s future-based strategy aimed from the beginning at copying Scala’s approach. A few loud research-oriented voices in the Rust community said “we think Scala’s approach looks great” and it drowned out the chorus of non-academic users of Scala who had spent years of dealing with frustrating compilation issues and issues where different future implementations were incompatible with each other and overall lots of tribalism that ended up repeating in a similar way in the Rust async/await timeline.
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I am somewhat surprised that you say Rust’s futures are modeled after Scala’s. I assume the ones that ended up in the standard library. As for commonalities: They also offer combinators on top of a common futures trait and you need explicit support in libraries - that’s pretty much all that is similar to Rust’s.
In Scala, futures were annoying because exceptions and meaningless stacktraces. In Rust, you get the right stacktraces and error propagation.
In Rust, Futures sucked for me due to error conversions and borrowing being basically unsupported until async await. Now they are still annoying because of ecosystem split (sync vs various partially compatible async).
The mentioned problem of competing libraries is basically unpreventable in fields without wide consensus and would have happened with ANY future alternative. If you get humans to agree on sensible solutions and not fight about irrelevant details, you are a wizard.
Where I agree is that it was super risky to spend language complexity budget on async/await, even though solving the underlying generator/state machine problem felt like a good priority. While async await feels a bit to special-cased and hacky to be part of the language… It could be worse. If we find a better solution for async in Rust, we wouldn’t have to teach the current way anymore.
Other solutions would just have different pros and cons. E.g. go’s or zig’s approach seemed the solution even deeper into the language with the pro of setting a somewhat universal standard for the language.
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It was emulating Finagle from the beginning: https://medium.com/@carllerche/announcing-tokio-df6bb4ddb34 but then the decision to push so much additional complexity into the language itself so that people could have an easier time writing strictly worse systems was just baffling.
Having worked in Finagle for a few years before that, I tried to encourage some of the folks to aim for something lighter weight since the subset of Finagle users who felt happy about its high complexity seemed to be the ones who went to work at Twitter where the complexity was justified, but it seemed like most of the community was pretty relieved to switch to Akka which didn’t cause so much type noise once it was available.
I don’t expect humans not to fragment now, but over time I’ve learned that it’s a much more irrational process than I had maybe believed in 2014. Mostly I’ve been disappointed about being unable to communicate with what was a tiny community about something that I felt like I had a lot of experience with and could help other people avoid pain around, but nevertheless watch it bloom into a huge crappy thing that now comes back into my life every day even when I try to ignore it by just using a different feature set in my own stuff.
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I hope you will get a reply by someone with more Rust experience than me, but I imagine that the primary problem is that even if you don’t have to manually free memory in Rust, you still have to think about where the memory comes from, which tends to make lifetime management more complicated, requiring to occasionally forcefully move things unto the heap (Box) and also use identity semantics (Pin), and so all of this contributes to having to deal with a lot of additional complexity to bake into the application the extra dynamicism that async/await enables, while still maintaining the safety assurances of the borrow checker.
Normally, in higher level languages you don’t ever get to decide where the memory comes from, so this is a design dimension that you never get to explore.
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I’m curious if you stuck around in Scala or pay attention to what’s going on now because I think it has one of the best stories when it comes to managing concurrency. Zio, Cats Effect, Monix, fs2 and Akka all have different goals and trade offs but the old problem of Future is easily avoided
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I was surprised to see the Rust community jump on the async-await bandwagon, because it was clear from the beginning it’s a bandwagon.
I’m not surprised. I don’t know how async/await works exactly, but it definitely has a clear use case. I once implemented a 3-way handshake in C. There was some crypto underneath, but the idea was, from the server’s point of view was to receive a first message, respond, then wait for the reply. Once the reply comes and is validated the handshake is complete. (The crypto details were handled by a library.)
Even that simple handshake was a pain in the butt to handle in C. Every time the server gets a new message, it needs to either spawn a new state machine, or dispatch it to an existing one. Then the state machine can do something, suspend, and wait for a new message. Note that it can go on after the handshake, as part of normal network communication.
That state machine business is cumbersome and error prone, I don’t want to deal with it. The programming model I want is blocking I/O with threads. The efficiency model I want is async I/O. So having a language construct that easily lets me suspend & resume execution at will is very enticing, and I would jump to anything that gives me that —at least until I know better, which I currently don’t.
I’d even go further: given the performance of our machines (high latencies and high throughputs), I believe non-blocking I/O at every level is the only reasonable way forward. Not just for networking, but for disk I/O, filling graphics card buffers, everything. Language support for this is becoming as critical as generics themselves. We laughed “lol no generics” at Go, but now I do believe it is time to start laughing “lol no async I/O” as well. The problem now is to figure out how to do it. Current solutions don’t seem to be perfect (though there may be one I’m not aware of).
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The whole thing with async I/O is that process creation is too slow, and then thread creation was too slow, and some might even consider coroutine creation too slow [1]. It appears that concerns that formerly were of the kernel (managing I/O among tasks; scheduling tasks) are now being pushed out to userland. Is this the direction we really want to go?
[1] I use coroutines in Lua to manage async I/O and I think it’s fine. It makes the code look like non-blocking, but it’s not.
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I don’t think it’s unreasonable to think that the kernel should have as few concerns as possible. It’s a singleton, it doesn’t run with the benefit of memory protection, and its internal APIs aren’t as stable as the ones it provides to userland.
… and, yes, I think a lot of async/await work is LARPing. But that’s because a lot of benchmark-oriented development is LARPing, and probably isn’t special to async/await specifically.
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I’m not sure what you’re getting at. I want async I/O to avoid process creation and thread creation and context switches, and even scheduling to some extent. What I want is one thread per core, and short tasks being sent to them. No process creation, no thread creation, no context switching. Just jump the instruction pointer to the relevant task, and return to the caller when it’s done.
And when the task needs to, say, read from the disk, then it should do so asynchronously: suspend execution, return to the caller, wait for the response to come back, and when it does resume execution. It can be done explicitly with message passing, but that’s excruciating. A programming model where I can kinda pretend the call is blocking (but in fact we’re yielding to the caller) is much nicer, and I believe very fast.
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Thank you for sharing, Zig has been much more conservative than Rust in terms of complexity but we too have splurged a good chunk of the budget on async/await. Based on my experience producing introductory materials for Zig, async/await is by far the hardest thing to explain and probably is going to be my biggest challenge to tackle for 2021. (that said, it’s continuations, these things are confusing by nature)
On the upside
despite it slowing down almost every real-world workload it is applied to
This is hopefully not going to be a problem in our case. Part of the complexity of async/await in Zig is that a single library implementation can be used in both blocking and evented mode, so in the end it should never be the case that you can only find an async version of a client library, assuming authors are willing to do the work, but even if not, support can be added incrementally by contributors interested in having their use case supported.
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I feel like Rust has definitely obliterated its complexity budget in unfortunate ways.
I remember the time I asked one of the more well-known Rust proponents “so you think adding features improves a language” and he said “yes”. So it was pretty clear to me early on that Rust would join the feature death march of C++, C#, …
Rust has many language features and they’re all largely disjoint from each other, so knowing some doesn’t help me guess the others.
That’s so painfully true.
For instance, it has different syntax for struct creation and function calls, their poor syntax choices also mean that structs/functions won’t get default values any time soon.
;is mandatory (what is this, 1980?), but you can leave out,at the end.The severe design mistake of using
<>for generics also means you have to learn 4 different syntax variations, and when to use them.The whole module stuff is way too complex and only makes sense if you programmed in C before. I have basically given up on getting to know the intricacies, and just let IntelliJ handle
uses.Super weird that both
ifandswitchexist.Most of my friends who I’ve met through Rust have taken steps to cut interactions with “the Rust community” down to an absolute minimum due to it tending to produce a feeling of alienation over time.
Yes, that’s my experience too. I have some (rather popular) projects on GitHub that I archive from time to time to not having to deal with Rust people. There are some incredibly toxic ones, which seem to be – for whatever reason – close to some “core” Rust people, so they can do whatever the hell they like.
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For instance, it has different syntax for struct creation and function calls
Perhaps they are trying to avoid the C++ thing where you can’t tell whether
foo(bar)is struct creation or a function call without knowing whatfoois?The whole module stuff is way too complex and only makes sense if you programmed in C before. I have basically given up on getting to know the intricacies, and just let IntelliJ handle uses.
It only makes sense to someone who has programmed in C++. C’s “module” system is far simpler and easier to grok.
Super weird that both if and switch exist.
Would you have preferred
match condition() { true => { }, false => { }, }I think that syntax is clunky when you start needing
else if.-
Perhaps they are trying to avoid the C++ thing where you can’t tell whether foo(bar) is struct creation or a function call without knowing what foo is?
Why wouldn’t you be able to tell?
Even if that was the issue (it isn’t), that’s not the problem C++ has – it’s that
fooalso could be 3 dozen other things.Would you have preferred […]
No, I prefer having one unified construct that can deal with both usecases reasonably well.
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Why wouldn’t you be able to tell?
struct M { }; void L(M m); void f() { M(m); // e.g. M m; L(m); // function call }The only way to tell what is going on is if you already know the types of all the symbols.
No, I prefer having one unified construct that can deal with both usecases reasonably well.
Ok, do you have an example from another language which you think handles this reasonably well?
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The only way to tell what is going on is if you already know the types of all the symbols.
Let the IDE color things accordingly. Solved problem.
Ok, do you have an example from another language which you think handles this reasonably well?
I’m currently in the process of implementing it, but I think this is a good intro to my plans.
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Let the IDE color things accordingly. Solved problem.
The problem of course is for the writer of the IDE :)
Constructs like these in C++ make it not only harder for humans to parse the code, but for compilers as well. This turns into real-world performance decreases which are avoided in other languages.
I’m currently in the process of implementing it, but I think this is a good intro to my plans.
That’s interesting, but I think there’s a conflict with Rust’s goal of being a systems-level programming language. Part of that is having primitives which map reasonably well onto things that the compiler can translate into machine code. Part of the reason that languages like C have both
ifandswitchis because switch statements of the correct form may be translated into an indirect jump instead of repeated branches. Of course, a Sufficiently Smart Compiler could optimize this even in theifcase, but it is very easy to write code which is not optimizable in such a way. I think there is value to both humans and computers in having separate constructs for arbitrary conditionals and for equality. It helps separate intent and provides some good optimization hints.Another reason why this exists is for exhaustiveness checks. Languages with
switchcan check that you handle all cases of an enum.The other half of this is that Rust is the bastard child of ML and C++. ML and C++ both have
match/switch, so Rust has one too.
I think you will have a lot of trouble producing good error messages with such a syntax. For example, say someone forgets an
=or even both==s. If your language does false-y and truth-y coercion, then there may be no error at all here. And to the parser, it is not clear at all where the error is. Further, this sort of extension cannot be generalized to one-liners. That is, you cannot unambiguously parseif a == b then c == d then ewithout line-breaks.On the subject, in terms of prior-art, verilog allows expressions in its case labels. This allows for some similar syntax constructions (though more limited since functions are not as useful as in regular programming languages).
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For instance, it has different syntax for struct creation and function calls, their poor syntax choices also mean that structs/functions won’t get default values any time soon.
This is a good thing. Creating a struct is a meaningfully different operation from calling a function, and there’s no problem with having there be separate syntax for these two separate things.
The Rust standard library provides a Default trait, with examples of how to use it and customize it. I don’t find it at all difficult to work with structs with default values in Rust.
The whole module stuff is way too complex and only makes sense if you programmed in C before. I have basically given up on getting to know the intricacies, and just let IntelliJ handle uses.
I don’t understand this comment at all. Rust’s module system seems fairly similar to module systems in some other languages I’ve used, although I’m having trouble thinking of other languages that allow you to create a module hierarchy within a single file, like you can do with the
mod { }keyword (C++ allows nestednamespaces I think, but that’s it). I don’t see how knowing C has anything to do with understand Rust modules better. C has no module system at all.-
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This is a good thing.
I guess that’s why many Rust devs – immediately after writing a struct – also define a fun to wrap their struct creation? :-)
Creating a struct is a meaningfully different operation from calling a function
It really isn’t.
The Rust standard library provides a Default trait, with examples of how to use it and customize it. I don’t find it at all difficult to work with structs with default values in Rust.
That’s clearly not what I alluded to.
I don’t see how knowing C has anything to do with understand Rust modules better. C has no module system at all.
Rust’s module system only makes sense if you keep in mind that it’s main goal is to produce one big ball of compiled code in the end. In that sense, Rust’s module system is a round-about way to describe which parts of the code end up being part of that big ball.
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Putting a OCaml hat on:
- Struct creation and function calls are quite different. In particular it’s good to have structure syntax that can be mirrored in pattern matching, whereas function call has no equivalent in
match. - Multiple modules in one file is also possible in ML/OCaml. Maybe in some Wirth language, though I’m not sure on that one.
it’s main goal is to produce one big ball of compiled code in the end.
What other goal would there be? That’s what 100% of compiled languages aim at… Comparing rust to C which has 0 notion of module is just weird.
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Struct creation and function calls are quite different. In particular it’s good to have structure syntax that can be mirrored in pattern matching, whereas function call has no equivalent in match.
In what sense would this be an obstacle? I would expect that a modern language let’s you match on anything that provides the required method/has the right signature. “This is a struct, so you can match on it” feels rather antiquated.
What other goal would there be? That’s what 100% of compiled languages aim at… Comparing rust to C which has 0 notion of module is just weird.
It feels like it was built by someone who never used anything but C in his life, and then went “wouldn’t it be nice if it was clearer than in C which parts of the code contribute to the result?”.
The whole aliasing, reexporting etc. functionality feels like it exists as a replacement for some convenience C macros, and not something one actually would want. I prefer that there is a direct relationship between placing a file somewhere and it ending up in a specific place, without having to wire up everything again with the module system.
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There is documented inspiration from OCaml from the rust original creator. The first compiler was even in OCaml, and a lot of names stuck (like
Some/Nonerather than the HaskellJust/Nothing). It also has obvious C++ influences, notably the namespace syntax being::and<>for generics. The module system most closely reminds me of a mix of OCaml and… python, with special file names (mod.rs, like__init__.pyor something like that?), even though it’s much much simpler than OCaml. Again not just “auto wiring” files in is a net benefit (another lesson from OCaml I’d guess, where the build system has to clarify what’s in or out a specific library). It makes build more declarative.As for the matching: rust doesn’t have active patterns or the scala-style deconstruction. In this context (match against values you can pre-compile pattern-matching very efficiently to decision trees and constant time access to fields by offset. This would be harder to do efficiently with “just call this
deconstuctmethod”. This is more speculation on my side, but it squares with rust’s efficiency concerns. -
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- Struct creation and function calls are quite different. In particular it’s good to have structure syntax that can be mirrored in pattern matching, whereas function call has no equivalent in
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In almost all languages with mandatory semicolons, they exist to prevent multi-line syntax ambiguities. The designers of Go and Lua both went to great pains to avoid such problems in their language grammars. Unlike, for example, JavaScript. This article about semicolon insertion rules causing ambiguity and unexpected results should help illustrate some of these problems.
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Pointing out Javascript isn’t a valid excuse.
Javascript’s problems are solely Javascript’s. If we discarded every concept that was implemented poorly in Javascript, we wouldn’t have many concepts left to program with.
I want semicolon inference done right, simple as that.
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~_~
Semicolons are an easy way to eliminate grammar ambiguity for multi-line syntax. For any language. C++ for example would have numerous similar problems without semicolons.
Not needing
;doesn’t mean the grammar is ambiguous.Of course. Go and Lua are examples of languages designed specifically to avoid ambiguity without semicolons. JavaScript, C++, and Rust were not designed that way. JavaScript happens to be an easy way to illustrate possible problems because it has janky automatic semicolon insertion, whereas C++ and Rust do not.
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; is mandatory (what is this, 1980?), but you can leave out , at the end.
Same in Zig? Curious to know Zig rationale for this.
The rationale for semicolons. They make parsing simpler, particularly for multi-line syntax constructs. I have been extremely clear about this the entire time. I have rephrased my thesis multiple times:
In almost all languages with mandatory semicolons, they exist to prevent multi-line syntax ambiguities.
Semicolons are an easy way to eliminate grammar ambiguity for multi-line syntax.
Many underestimate the difficulty of creating a language without semicolons. Go has done so with substantial effort, and maintaining that property has by no means been effortless for them when adding new syntax to the language.
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Yeah, you know, maybe we should stop building languages that are so complex that they need explicitly inserted tokens to mark “previous thing ends here”? That’s the point I’m making.
when adding new syntax to the language
Cry me a river. Adding features does not improve a language.
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Having a clear syntax where errors don’t occur 15 lines below the missing
)or}(as would unavoidably happen without some separator — trust me, it’s one of OCaml’s big syntax problems for toplevel statements) is a net plus and not bloat.What language has no semicolon (or another separator, or parenthesis, like lisp) and still has a simple syntax? Even python has
;for same-line statements. Using vertical whitespace as a heuristic for automatic insertion isn’t a win in my book.-
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I didn’t know. That involves no whitespace/lexer trick at all? I mean, if you flatten a whole file into one line, does it still work? Is it still in LALR(1)/LR(1)/some nice fragment?
The typical problem in this kind of grammar is that, while binding constructs are easy to delimit (
var/val/let…), pure sequencing is not. If you havea = 1 b = 2 + 3 c = 4 d = f(a)semicolons make things just simpler for the parser. -
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Using vertical whitespace as a heuristic for automatic insertion isn’t a win in my book.
I agree completely. I love Lua in particular. You can have zero newlines yet it requires no semicolons, due to its extreme simplicity. Lua has only one ambiguous case: when a line begins with a
(and the previous line ends with a value.a = b (f or g)() -- call f, or g when f is nilSince Lua has no semantic newlines, this is exactly equivalent to:
a = b(f or g)()The Lua manual thus recommends inserting a
;before any line starting with(.a = b ;(f or g)()But I have never needed to do this. And if I did, I would probably write this instead:
a = b local helpful_explanatory_name = f or g helpful_explanatory_name()
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There’s a blog post by Graydon Hoare that I can’t find at the moment, where he enumerates features of Rust he thinks are clear improvements over C/C++ that have nothing to do with the borrow checker. Forcing if statements to always use braces is one of the items on his list; which I completely agree with. It’s annoying that in C/C++, if you want to add an additional line to a block of a brace-less if statement, you have to remember to go back and add the braces; and there have been major security vulnerabilities caused by people forgetting to do this.
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That was things Rust shipped without.
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The following would work just as well:
const foo = if bar { a } else { b };I’ve written an expression oriented language, where the parenthesis were optional, and the braces mandatory. I could use the exact same syntactic construct in regular code and in the ternary operator situation.
Another solution is inserting another keyword between the condition and the first branch, as many ML languages do:
const foo = if bar then a else b; -
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If
bis actually a parenthesised expression like(2+2), then the whole thing looks like a function call:const x = if a (2+2) else cParsing is no longer enough, you need to notice that
ais not a function. Lua has a similar problem with optional semicolon, and chose to interpret such situations as function calls. (Basically, a Lua instruction stops as soon as not doing so would cause a parse error).Your syntax would make sense in a world of optional semicolons, with a parser (and programmers) ready to handle this ambiguity. With mandatory semicolons however, I would tend to have mandatory curly braces as well:
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Thanks for the example!
I think this is another case where banning bad whitespace makes this unambiguous.
a - b => binary -a => unary a-b => binary a -b => error a- b => error - a => errorYou can summarise these rules as “infix operators must have balanced whitespace” and “unary operators must not be followed by whitespace”.
Following these rules, your expression is unambiguously a syntax error, but if you remove the whitespace between - and a it works.
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A minus sign before a number to indicate a negative number is probably recognizable as a negative number to most people in my country. I imagine most would recognise
-xas “negative x”, too. Generalising that to other identifiers is not difficult.An exclamation mark for boolean negation is less well known, but it’s not very difficult to learn. I don’t see why jump-to should fail if you’re using a language server, either.
More generally, people have been using specialist notations for centuries. Some mathematicians get a lot of credit for simply inventing a new way to write an older concept. Maybe we’d be better off with only named function calls, maybe our existing notations are made obsolete by auto-complete, but I am not convinced.
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My current feeling is that async/await is the worst way to express concurrency … except for all the other ways.
I have only minor experience with it (in Nim), but a good amount of experience with concurrency. Doing it with explicit threads sends you into a world of pain with mutexes everywhere and deadlocks and race conditions aplenty. For my current C++ project I built an Actor library atop thread pools (or dispatch queues), which works pretty well except that all calls to other actors are one-way so you now need callbacks, which become painful. I’m looking forward to C++ coroutines.
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This is amazing. I had similar feelings (looking previously at JS/Scala futures) when the the plans for async/await were floating around but decided to suspend my disbelief because of how good previous design decisions in the language were. Do you think there’s some other approach to concurrency fit for a runtime-less language that would have worked better?
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My belief is generally that threads as they exist today (not as they existed in 2001 when the C10K problem was written, but nevertheless keeps existing as zombie perf canon that no longer refers to living characteristics) are the nicest choice for the vast majority of use cases, and that Rust-style executor-backed tasks are inappropriate even in the rare cases where M:N pays off in languages like Go or Erlang (pretty much just a small subset of latency-bound load balancers that don’t perform very much CPU work per socket). When you start caring about millions of concurrent tasks, having all of the sources of accidental implicit state and interactions of async tasks is a massive liability.
I think The ADA Ravenscar profile (see chapter 2 for “motivation” which starts at pdf page 7 / marked page 3) and its successful application to safety critical hard real time systems is worth looking at for inspiration. It can be broken down to this set of specific features if you want to dig deeper. ADA has a runtime but I’m kind of ignoring that part of your question since it is suitable for hard real-time. In some ways it reminds me of an attempt to get the program to look like a pretty simple petri net.
I think that message passing and STM are not utilized enough, and when used judiciously they can reduce a lot of risk in concurrent systems. STM can additionally be made wait-free and thus suitable for use in some hard real-time systems.
I think that Send and Sync are amazing primitives, and I only wish I could prove more properties at compile time. The research on session types is cool to look at, and you can get a lot of inspiration about how to encode various interactions safely in the type system from the papers coming out around this. But it can get cumbersome and thus create more risks to the overall engineering effort than it solves if you’re not careful.
A lot of the hard parts of concurrency become a bit easier when we’re able to establish maximum bounds on how concurrent we’re going to be. Threads have a little bit more of a forcing function to keep this complexity minimized due to the fact that spawning is fallible due to often under-configured system thread limits. Having fixed concurrency avoids many sources of bugs and performance issues, and enables a lot of relatively unexplored wait-free algorithmic design space that gets bounded worst-case performance (while still usually being able to attempt a lock-free fast path and only falling back to wait-free when contention picks up). Structured concurrency often leans into this for getting more determinism, and I think this is an area with a lot of great techniques for containing risk.
In the end we just have code and data and risk. It’s best to have a language with forcing functions that pressure us to minimize all of these over time. Languages that let you forget about accruing data and code and risk tend to keep people very busy over time. Friction in some places can be a good thing if it encourages less code, less data, and less risk.
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I like rust and I like threads, and do indeed regret that most libraries have been switching to async-only. It’s a lot more complex and almost a new sub-language to learn.
That being said, I don’t see a better technical solution for rust (i.e. no mandatory runtime, no implicit allocations, no compromise on performance) for people who want to manage millions of connections. Sadly a lot of language design is driven by the use case of giant internet companies in the cloud and that’s a problem they have; not sure why anyone else cares. But if you want to do that, threads start getting in the way at 10k threads-ish? Maybe 100k if you tune linux well, but even then the memory overhead and latency are not insignificant, whereas a future can be very tiny.
Ada’s tasks seem awesome but to the best of my knowledge they’re for very limited concurrency (i.e the number of tasks is small, or even fixed beforehand), so it’s not a solution to this particular problem.
Of course async/await in other languages with runtimes is just a bad choice. Python in particular could have gone with “goroutines” (for lack of a better word) like stackless python already had, and avoid a lot of complexity. (How do people still say python is simple?!). At least java’s Loom project is heading in the right direction.
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Just like some teenagers enjoy making their slow cars super loud to emulate people who they look up to who drive fast cars, we all make similar aesthetic statements when we program. I think I may write on the internet in a way that attempts to emulate a grumpy grey-beard for similarly aesthetic socially motivated reasons. The actual effect of a program or its maintenance is only a part of our expression while coding. Without thinking about it, we also code as an expression of our social status among other coders. I find myself testing random things with quickcheck, even if they don’t actually matter for anything, because I think of myself as the kind of person who tests more than others. Maybe it’s kind of chicken-and-egg, but I think maybe we all do these things as statements of values - even to ourselves even when nobody else is looking.
Sometimes these costumes tend to work out in terms of the effects they grant us. But the overhead of Rust executors is just perf theater that comes with nasty correctness hazards, and it’s not a good choice beyond prototyping if you’re actually trying to build a system that handles millions of concurrent in-flight bits of work. It locks you into a bunch of default decisions around QoS, low level epoll behavior etc… that will always be suboptimal unless you rewrite a big chunk of the stack yourself, and at that point, the abstraction has lost its value and just adds cycles and cognitive complexity on top of the stack that you’ve already fully tweaked.
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Not who you’re asking, but the reason why rust can’t have green threads (as it used to have pre-1.0, and it was scraped), as far as I undertand:
Rust is shooting for C or C++-like levels of performance, with the ability to go pretty close to the metal (or close to whatever C does). This adds some constraints, such as the necessity to support some calling conventions (esp. for C interop), and precludes the use of a GC. I’m also pretty sure the overhead of the probes inserted in Erlang’s bytecode to check for reduction counts in recursive calls would contradict that (in rust they’d also have to be in loops, btw); afaik that’s how Erlang implements its preemptive scheduling of processes. I think Go has split stacks (so that each goroutine takes less stack space) and some probes for preemption, but the costs are real and in particular the C FFI is slower as a result. (saying that as a total non-expert on the topic).
I don’t see why async/await wouldn’t work… since it does; the biggest issues are additional complexity (a very real problem), fragmentation (the ecosystem hasn’t converged yet on a common event loop), and the lack of real preemption which can sometimes cause unfairness. I think Tokio hit some problems on the unfairness side.
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The biggest problem with green threads is literally C interop. If you have tiny call stacks, then whenever you call into C you have to make sure there’s enough stack space for it, because the C code you’re calling into doesn’t know how to grow your tiny stack. If you do a lot of C FFI, then you either lose the ability to use small stacks in practice (because every “green” thread winds up making an FFI call and growing its stack) or implementing some complex “stack switching” machinery (where you have a dedicated FFI stack that’s shared between multiple green threads).
Stack probes themselves aren’t that big of a deal. Rust already inserts them sometimes anyway, to avoid stack smashing attacks.
In both cases, you don’t really have zero-overhead C FFI any more, and Rust really wants zero-overhead FFI.
I think Go has split stacks (so that each goroutine takes less stack space)
No they don’t any more. Split Stacks have some really annoying performance cliffs. They instead use movable stacks: when they run out of stack space, they copy it to a larger allocation, a lot like how
Vecworks, with all the nice “amortized linear” performance patterns that result.
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Two huge differences:
- Erlang’s data structures are immutable (and it has much slower single threaded speed).
- Erlang doesn’t have threads like Rust does.
That changes everything with regard to concurrency, so you can’t really compare the two. A comparison to Python makes more sense, and Python async has many of the same problems (mutable state, and the need to compose with code and libraries written with other concurrency models)
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The fixation on async-await, despite it slowing down almost every real-world workload it is applied to, and despite it adding additional bug classes and compiler errors that simply don’t exist unless you start using it, has been particularly detrimental to the ecosystem.
I’m curious about this perspective. The number of individual threads available on most commodity machines even today is quite low, and if you’re doing anything involving external requests on an incoming-request basis (serializing external APIs, rewriting HTML served by another site, reading from slow disk, etc) and these external requests take anything longer than a few milliseconds (which is mostly anything assuming you have a commodity connection in most parts of the world, or on slower disks), then you are better off with a some form of “async” (or otherwise lightweight concurrent model of execution.) I understand that badly-used synchronization can absolutely tank performance with this many “tasks”, but in situations where synchronization is low (e.g. making remote calls, storing state in a db or separate in-memory cache), performance should be better than threaded execution.
Also, if I reach for Rust I’m deliberately avoiding GC. Go, Python, and Haskell are the languages I tend to reach for if I just want to write code and not think too hard about who owns which portion of data or how exactly the runtime schedules my code. With Rust I’m in it specifically to think about these details and think hard about them. That means I’m more prone to write complicated solutions in Rust, because I wouldn’t reach for Rust if I wanted to write something “simple and obvious”. I suspect a lot of other Rust authors are the same.
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The number of individual threads available on most commodity machines even today is quite low
I don’t agree with the premise here. It depends more on the kernel, not the “machine”, and Linux in particular has very good threading performance. You can have 10,000 simultaneous threads on vanilla Linux on a vanilla machine. async may be better for certain specific problems, but that’s not the claim.
Also a pure async model doesn’t let you use all your cores, whereas a pure threading model does. If you really care about performance and utilization, your system will need threads or process level concurrency in some form.
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I don’t agree with the premise here. It depends more on the kernel, not the “machine”, and Linux in particular has very good threading performance. You can have 10,000 simultaneous threads on vanilla Linux on a vanilla machine. async may be better for certain specific problems, but that’s not the claim.
I wasn’t rigorous enough in my reply, apologies.
What I meant to say was, the number of cores available on a commodity machine is quite low. Even if you spawn thousands of threads, your actual thread-level parallelism is limited to the # of cores available. If you’re at the point where you need to spawn more kernel threads than there are available cores, then you need to put engineering into determining how many threads to create and when. For IO bound workloads (which I described in my previous post), the typical strategy is to create a thread pool, and to allocate threads from this pool. Thread pools themselves are a solution so that applications don’t saturate available memory with threads and so you don’t overwhelm the kernel with time spent switching threads. At this point, your most granular “unit of concurrency” is each thread in this thread pool. If most of your workload is IO bound, you end up having to play around with your thread pool sizes to ensure that your workload is processed without thread contention on the one hand (too few threads) or up against resource limits (too many threads). You could of course build a more granular scheduler atop these threads, to put threads “to sleep” once they begin to wait on IO, but that is essentially what most async implementations are, just optimizations on “thread-grained” applications. Given that you’re already putting in the work to create thread pools and all of the fiddly logic with locking the pool, pulling out a thread, then locking and putting threads back, it’s not a huge lift to deal with async tasks. Of course if your workload is CPU bound, then these are all silly, as your main limiting resource is not IO but is CPU, so performing work beyond the amount of available CPU you have necessitates queuing.
Moreover the context with which I was saying this is that most Rust async libraries I’ve seen are async because they deal with IO and not CPU, which is what async models are good at.
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Various downsides are elaborated at length in this thread.
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Thanks for the listed points. What it’s made me realize is that there isn’t really a detailed model which allows us to demonstrate tradeoffs that come with selecting an async model vs a threaded model. Thanks for some food for thought.
My main concern with Rust async is mostly just its immaturity. Forget the code semantics; I have very little actual visibility into Tokio’s (for example) scheduler without reading the code. How does it treat many small jobs? Is starvation a problem, and under what conditions? If I wanted to write a high reliability web service with IO bound logic, I would not want my event loop to starve a long running request that may have to wait longer on IO than a short running request and cause long running requests to timeout and fail. With a threaded model and an understanding of my IO processing latency, I can ensure that I have the correct # of threads available with some simple math and not be afraid of things like starvation because I trust the Linux kernel thread scheduler much more than Tokio’s async scheduler.
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I hope I’m not opening any wounds or whacking a bee-hive for asking but… what sort of problematic interactions occur with the Rust community? I follow Rust mostly as an intellectual curiosity and therefor aren’t in deep enough to see the more annoying aspects. When I think of unprofessional language community behavior my mind mostly goes to Rails during the aughts when it was just straight-up hostile towards Java and PHP stuff. Is Rust doing a similar thing to C/C++?
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Definitely recommend SBCL unless you can afford a Lispworks license. CLISP is super slow. Lispworks is great but the free version is limited. SBCL is very fast and full featured.
Also good work on this guide, looks really good!
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I use SBCL and would recommend one using it after they have setup Emacs + Sly (or SLIME). But when trying out Lisp, it is likely that the person will try running things on a bare REPL from the terminal. In that scenario CLISP is a much better choice. It has the best out of the box REPL by far. History, auto-completion, colors, etc.
CLISP is super slow
We should learn from the Python and Ruby community on how to sell it. It ain’t slow, ‘fast enough’ 😉.
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For the record, this guide is not authored by me. Kudo to Prof. Sean Luke!
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Go’s treating of errors as first-class citizens is, by far, my favorite way of handling errors. Most of my other work is done in TypeScript, and it’s absolutely bonkers that we’re spending all this time typing functions and return types and the like, but when it comes to errors, we basically throw everything about type checking out the window. Obviously TypeScript can only handle so much given the choices in JavaScript, but it still feels like a huge missing opportunity for the language.
It’s actually gotten to the point where I’m considering making all my functions return tuple types, with a nullable error component just like Go:
type Err = Error | null; async function getUser(): Promise<[string, Err]> { try { const res = await fetch('/me'); const data = await res.json(); return [data, null]; } catch (err) { return ["", err]; } } (async () => { const [user, err] = await getUser(); if (err !== null) { console.error(err); return; } console.log(user); })();-
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The problem with Java isn’t checked exceptions, it’s that exceptions are used for stuff that’s not exceptional, like not finding a result. If exceptions weren’t being used where they shouldn’t, it’d annoy people far less than it does.
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I’m not aware of anything that Java-style checked exceptions can do that you can’t do with result types in a language with ML-style types.
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The only thing I can think of is that Java kinda let’s you combine unrelated exception types, while at least in Rust you would have to define an enum for it.
Plus, Rust is kinda bad with enums, because the individual enum members are not real types on their own, so you can’t say “only this specific error case of this enum can happen”.
But on the other hand, Java’s throws clause is basically a union, with exception supertypes mentioned in the throws clause subsuming subtypes, so they can accidentality be thrown away while coding.
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The only thing I can think of is that Java kinda let’s you combine unrelated exception types, while at least in Rust you would have to define an enum for it.
In OCaml you can combine
resulttypes with polymorphic variants which work like a set of constructors and are combined and type-inferred by the compiler. Here’s an explanation and so far it seems to work pretty well. Basically, composable checked exceptions in ML. -
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I totally feel your frustration with errors, but I think the tuple approach puts too much faith in the developer not making a mistake. Do you know if Go prevents returning both an error and value?
I would probably go with something like this:
type Result<T> = ({success: true} & T) | {success: false, err: Error} async function getUser(): Promise<Result<{user: string}>> { try { const res = await fetch('/me'); const user = await res.json() as string; return {success: true, user}; } catch (err) { return {success: false, err} } } (async () => { const result = await getUser(); // You can only access result.success here. if (!result.success) { // Since success === false in this block, err can be accessed console.error(result.err); return; } // Because we returned when success === false, TypeScript knows that this // has {success: true; user: string}. console.log(result.user); })();-
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Do you know if Go prevents returning both an error and value?
No, and that’s not really a bad thing IMHO. For example I wrote an email address parsing library which can return an error but also returns the list of email addresses it was able to parse, which is useful in various situations (e.g. “sent email to X, but wasn’t able to send to Y”).
In general, you probably shouldn’t return a value and an error in most cases though.
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That sounds like a problem waiting to happen. Like a C function that processes half your data and admittedly returns
-1but if you forget to check you might just go ahead and use the half-processed data thinking you’re done (e.g. who will ever notice that only 999 addresses were processed, not 1000 until 3 months later you’re wondering why there is a large discrepancy in what you excepted and what you got at which point it will be too late).-
Well the solution to that is to not forget to check it 🙃 But yeah, I get your point. Perhaps a better way would be to return an error with the mail addresses on the error struct, so you need to do something with the error, and if you’re sure you want to get the email addresses anyway you can still get them from the error 🤔 This way it’s at least explicit.
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Alternatively you can make that particular failure case (a partial success) not an error and return some kind of state struct where for each address it would state whether it was able to send it or not individually. Since there was some kind of success presumably. This is a discussion of API design, I am not particularly familiar with how that’s preferred to be done in Go, I just try to design APIs that prevent the user from shooting themselves in the foot.
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I just try to design APIs that prevent the user from shooting themselves in the foot.
Yeah, that’s a good attitude. In this particular case you really needed to ignore errors on multiple levels for things to really go wrong. I don’t remember the exact details off-hand as I wrote this over 4 years ago (and has been running pretty much bug-free in production ever since processing millions of emails daily, which is actually not a bad accomplishment considering there were many issues before) but I would perhaps do it different if I were to write it today, I was fairly new to Go at the time 😅
Generally speaking though the mantra of “check your errors!” in Go is strong enough that you can somewhat rely on it; you can run in to problems if you ignore errors and return empty data too.
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Not sure if you like it but you can use the io-ts-promise library to chain async operations together like this:
fetch('http://example.com/api/not-a-person') .then(response => response.json()) .then(tPromise.decode(Person)) .then(typeSafeData => console.log(`${typeSafeData.name} is ${typeSafeData.age} years old`), ) .catch(error => { if (tPromise.isDecodeError(error)) { console.error('Request failed due to invalid data.'); } else { console.error('Request failed due to network issues.'); } });
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When I went for my first programming job, it was at a games company, and I had a disk full of graphics demos and a completed game (just a simple sliding puzzle, but it was a full game). This really helped with the process as they could tell from looking at that, and talking with me about it, that I already knew 68000 code, how to put a working program together etc. When I went for my interview I was in the waiting area with a guy with a much better education (a masters degree from a better college), and yet I still got the job over him.
Side projects have helped since then. Maybe 15 years ago I was working on a Playstation game that wasn’t going anywhere and wanted to move to a better job. I spent some time on the side working on a Bezel surface renderer that used some advanced (at the time) surface subdivision techniques. Showing this to some guys at work I got a new and vastly better paid job without even applying for it! Some colleagues of mine one Friday afternoon said, hey congrats on the new job, and on Monday I got a call about it and started later that day. All from a side project.
These days I no longer work in gaming but I often do side projects in my spare time which sometimes don’t see the light of day and other times become conference talks or prototypes for new business systems.
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There’s a huge variation in people’s emacs configs. You can use those that people post publicly as a guide, but my advice is to start using Emacs and add to your configuration gradually.
Some public ones you may like: https://github.com/jwiegley/dot-emacs https://github.com/munen/emacs.d https://sites.google.com/site/steveyegge2/my-dot-emacs-file
One of the first things you’ll want to do is to be able to install manage packages from Melpa. Follow the instructions here: https://melpa.org/#/getting-started
Then just fix things that annoy you. For example, I like my buffer to fill the whole display, so I disable some things at startup:
(defun lose-superfluous-stuff() "remove stuff I don't like, like scroll bars and tool bars" (interactive) (if (fboundp 'scroll-bar-mode) (scroll-bar-mode -1)) (if (fboundp 'tool-bar-mode) (tool-bar-mode -1)) (if (fboundp 'menu-bar-mode) (menu-bar-mode -1)))I very rarely change default keys, but some people completely customize the layout. If you like Vim you may want to use Viper mode.
This one is a must if you don’t like beeping in the middle of the night:
; turn the annoying beep off (setq visible-bell t)If you’re on Mac this is a handy tip. You can use mdfind instead of the linux locate command. Makes it easy to search for things on your system…
;; set locate to use mdfind (when (eq system-type 'darwin) (setq locate-command "mdfind"))Most of the rest of my config file is decades old and commented out. Things like programming language configuration, binary paths, colour themes. Pretty much everything like that I don’t bother with anymore, I simply use Doom Emacs. I wouldn’t recommend it unless you’re already familiar with Emacs though.
Hopefully try to get out of this depressive state I’ve randomly entered this week. “Fuck it” seems to be the answer to resolving the feeling.
It’s been a rough mood week for me, too, here’s hoping we both feel better soon.
what are you using in the way of learning materials?