Joker is not a dialect of Clojure hosted on the Go runtime. Joker is a dialect of Clojure using its own interpreted runtime, that happens to be implemented in Go.

That means you cannot use Joker to build statically linked Go binaries and you cannot interop with Go from your own code.

And if you're interested in the idea of having an interpreted implementation of Clojure, for scripting use cases and fast startup, I would recommend you look into Babashka instead of Joker: https://babashka.org/

Joker was the best interpreted Clojure prior to Babashka, and nowadays, I would recommend Babashka over Joker all the time.

The reason Babashka is better than Joker for this is that it is implemented in Java, so it can directly reuse the existing Clojure implementation and libraries as-is as part of its interpreter. That allowed it to quickly surpass Joker in the amount of Clojure features it support and libraries it exposes, and continue to quickly keep up with Clojure. I'd also say the main developer behind Babashka is more active.

Even though Babashka is implemented in Java, it is still a single statically linked binary runtime that starts extremely fast and has a small memory footprint.

Kudos to Joker though for pioneering the idea and leading to Babashka.

Edit: And if you were excited because you thought this would let you write compiled statically linked binaries in Clojure, well for that you want to look at GraalVM native compilation which lets you compile real Clojure programs as low memory, fast startup, statically compiled single binaries: https://github.com/lread/clj-graal-docs

That, combined with how you'd lose access to a lot of the java library ecosystem, makes it less appealing to me to develop on.

Clojure cycle is even faster because you keep REPL open and evaluate code directly while application is running. After that, you build uberjar, then compile it with graal.

What you must understand though, is that you're asking for something contradictory. You cannot get runtime eval and code linking and also deliver a statically linked compiled machine code binary.

That's why statically linked to machine code binary languages don't offer dynamic code generation, linking and reflection that can't be declared or performed at compile time.

This is true for GraalVM. It means when you develop Clojure for GraalVM native compilation you can't leverage such dynamic behavior as well.

Though you can embed the SCI Clojure interpreter inside your application and do dynamic code evaluation with it at runtime.

The best way forward might be an option to compile some Joker code by generating Go code for it.

(This is based on writing an interpreter a few years ago. Perhaps Go’s compiler has improved?)

Just speculating on what GP specifically meant, but Go lacks the ability to pack structs, and probably lacks the equivalent of tricks like computed gotos [0] to increase bytecode interpreter speeds. In general, Go seems to (intentionally) lack a lot of low-level control of code generation, preferring a "there's one way to do things, and it either works, or it's a bug we'll fix" approach.

Which is probably for the best in "most" software, but interpreters typically use weird hacks to squeeze more performance out of the rock. Wren is a good example [1] of some of these optimizations, and has splendid comments/documentation.

[0] https://eli.thegreenplace.net/2012/07/12/computed-goto-for-e...

[1] https://github.com/wren-lang/wren/blob/main/src/vm/wren_vm.c

Also, there is the NaN boxing trick [1], which allows you to store a value that is essentially a tagged union that is either a double, a pointer, or an integer, in the same space as a double. To get these in a safe language, they essentially have to be built in already.

Go’s interface type is very high overhead compared to the union types used in other languages because it uses an entire pointer as a tag. Though, it only matters in special cases like interpreters. Most performance-intensive code isn’t nearly so dynamic.

[1] https://sean.cm/a/nan-boxing

I’ll try it out later

You could represent the heap as an array, use array offsets instead of pointers, and do your own garbage collection, but that’s pretty low level and you might as well compile to WebAssembly.

Let me know if you'd like to discuss this more.

[1] https://github.com/pflanze/lilyvm

- Clojure is kinda difficult to reason about performance wise. The lazyness.. some weird corner cases (like how `(first ..)` is slower than `(nth .. 0)`

- The STL is very strict on the "zero cost abstraction" front.

Maybe something like Immer but with some syntactic sugar to make it more light weight like Clojure?

With hooking into GDB you could probably make a REPL as well.. GDB has live code reload, introspection - you even get state of crash and sane stack traces :)

I would not consider this a corner case; it is stated in (first) docstring. (first) will create seq [1] object, then it will fetch the first element. (nth), on other hand, will not create seq object.

> The STL is very strict on the "zero cost abstraction" front.

Many edge cases which are lost in myriad of classes. For example, vector will allocate more memory than there are actually elements in it, and you never know when it will start resizing it (this is implementation detail). I would not call this as "zero cost abstraction".

[1] https://clojuredocs.org/clojure.core/seq

The Clojure `first` function on lists and vectors is O(1), not sure why you think it isn't. Are you thinking of `last` ?

https://tech.redplanetlabs.com/2020/09/02/clojure-faster/#fi...

I think I'm may have been wrong and it's not a complexity issue, but just incredibly slow.

The reason it is slower than `nth` is because `first` is a sequence function, so it first coerces the type into a sequence, and then it returns the first element of that sequence. The creation of the sequence object wrapping the vector is what slows it down compared to `nth`, but it is still O(1).

But the difference is more than 5x. That's kinda nuts.. In the context of C++ you don't just shrug your shoulders at 5x.

There is a really long discussion on GoogleGroups about why this was designed this way.. and I'm not sure I entirely understood the rational so I'm wary to say anyone is wrong. I definitely want to give them the benefit of the doubt and say it's probably like that for a good reason. But people were surprisingly very dismissive of this being a problem. To me it looks kinda obviously ugly (and maybe that's a tradeoff worth making). Furthermore, you have `peek` for the tail position, but no equivalent for the first position? To me it looks strange..

I actually don't mind that Clojure doesn't emphasis performance. To me it's just part of the tradeoff. But if you point this out then passionate people come out of the woodworks and get really defensive about it :S

I think this is the statement that people get defensive about. Clojure doesn't try to be the fastest language in the world, so beating Fortran is a non goal, hopefully that's obvious, but it takes performance very seriously, often at the detriment of usability in fact. Chunked sequence is one such example, it's purely done for performance reasons, but causes people a lot of headaches as it creates quite a few gotchas around lazy sequences.

First is another example, but I agree this one depends on your own philosophy and Clojure has an unconventional philosophy here.

The philosophy is that the choice of data-structure matters, and when performance is required, the programmer should make the right data-structure choices and use the appropriate data-structure optimized functions.

You could say that goes even further, that really the choice of constructs and the design of how to implement something matters if your use case is performance sensitive, and so small performance improvements like first having a special case on vectors don't matter for performance sensitive use cases anyways.

What that means is that, from my understanding, Clojure core devs aren't opposed to `first` and `last` having a faster path in some special cases, but they see that as an unimportant feature, that's way lower on the list of priorities, and they aren't convinced it's even worth the added complexity it would bring to the language implementation.

Effectively, where some languages say, this abstraction is so cool, because you can swap out the collection for a different one and get a free speed boost, Clojure says: this abstraction is so cool, because there is no collection you can switch too that would make the performance degrade.

So when it comes to performance trade offs, Clojure focuses on making the default and most straightforward way to implement something "fast enough" and scalable to larger inputs. You can think of this as for most use cases, the time it takes for a O(1) will be sufficient for the user, and your program won't choke if your input size grows larger.

And in the more exceptional cases where the O(1) isn't fast enough, or you have ridiculously large inputs beyond what even the common "at scale" use cases are. Well for those, Clojure wants to quickly make you realize you should not try to use the default and most straightforward way to implement this, but instead you need to immediately design for that performance.

And this isn't black or white either, there are cases where something was deemed worth having a faster internal implementation or special case, because it would have a substantial overall impact, for example with chunked sequence and transducers, or with how small maps are made into an array map, or with transients, etc.

> The philosophy is that the choice of data-structure matters, and when performance is required, the programmer should make the right data-structure choices and use the appropriate data-structure optimized functions.

Yeah, that's very sensible. When you know you're not just getting some seq, and you know you're going to get a vector - then you should use vector specific functionality. But I sort of don't get the impression the core library is compartmentalized this way. Maybe I've somehow overlooked it.. For instance I don't think there are a lot of function that take a vec on input, so in the vector case .. uhh what is the vector specific way to access the first element quickly? (not being snarky, genuinely asking)

> Clojure wants to quickly make you realize you should not try to use the default and most straightforward way to implement this, but instead you need to immediately design for that performance.

Yeah, things like VisualVM quickly make this apparent :) I guess my mild annoyance is at how ugly the code starts to get when it's optimized.

Tangentially, you might be a good person to ask: Do you happen to know why Java arrays aren't first class with their own syntax sugar like [],{},#{} etc ? Why are the docs discouraging their use? Is it because the other datatypes can't be coerced to a array? I often want to use them, but I feel I'm working against the grain of the language and doing something wrong. But I don't really appreciate the tradeoff involved

Clojure is really a functional language at heart, so when you need to go down to an imperative model for performance I agree that's when things start to feel not quite right, and you begin to fight the language a little, the lack of standard imperative loops become an obvious annoyance. But Clojure's stance is that it's hosted for a reason, and just write those imperative pieces in Java which is designed from the ground up for imperative programming, Clojure doesn't try to pretend like it can do imperative better than Java.

I'd say on the performance scale, Clojure tries to be a fast functional dynamic language. A lot of the dynamic behavior have a runtime cost, so there's a limit here in terms of raw performance, where the best it can hope to achieve is be as fast as statically typed Java.

I think as a fast functional dynamic language it succeeds, and this is where most of the effort has gone in terms of optimization.

> When you know you're not just getting some seq, and you know you're going to get a vector - then you should use vector specific functionality. But I sort of don't get the impression the core library is compartmentalized this way

The official cheatsheet is a good resource for this: https://clojure.org/api/cheatsheet you can look in it under Collections -> Vector

> For instance I don't think there are a lot of function that take a vec on input, so in the vector case .. uhh what is the vector specific way to access the first element quickly? (not being snarky, genuinely asking)

Like the cheatsheet shows, there's a few different vector functions for getting elements:

    ([1 2 3] 0) ;> 1
    (get [1 2 3] 0) ;> 1

For manipulating data in vectors, there's mapv and filterv and reduce, and you can leverage all of the transducer functions as well.

Basically the trick for performance with vectors is to use transient when creating them, use reduce to iterate over them (or a function based on reduce like mapv, filterv and all transducers), and use their index for getting elements from them.

> Tangentially, you might be a good person to ask: Do you happen to know why Java arrays aren't first class with their own syntax sugar like [],{},#{} etc ?

Clojure is very opinionated towards functional programming and immutability. Arrays are an imperative construct with mutation and specific memory address lookups as their basic premise. Clojure is also opinionated towards data driven/value driven modeling. Arrays aren't very good for that, they are homogeneous and they don't have value semantics.

Basically from the point of view of Clojure, arrays are a specialized tool that you should only need to use in special cases, because of some special non-functional requirement. And because they don't follow the standard Clojure data expectations: immutable and heterogeneous with value semantics, Clojure wants it that when an array is used, it is very explicit and obvious, so it uses different functions for them, that also happen to be better suited for arrays.

> I often want to use them, but I feel I'm working against the grain of the language and doing something wrong. But I don't really appreciate the tradeoff involved

I mean, you shouldn't use Clojure if you don't favour the functional programming style. One of the tradeoff is slightly worse performance, because computers are imperative machines. People who use Clojure are happy with it, because they believe they get better modularity, reuse, safety and productivity from functional programming, and lose very little efficiency and performance that it is a good trade off, where users won't notice the difference, but the programmer gains a lot of benefits.

Clojure cares about making sure that it delivers a fast and efficient implementation of a dynamic functional programming language. That's why it provides a good implementation of persistent collections, which are non-trivial to write, that's why it batches lazy-sequences, that's why it uses the JVM JIT runtime which does a great job at dealing with lots of small temporary objects and optimizing away extra indirections. That's why it goes out of its way to allow type hints for faster dispatch, of providing records over maps, array-maps for small maps, transients for local mutation over immutable collections, transducers and reducing fast iteration for data manipulation, primitive handling in loop/recur, etc.

I think you'd describe Clojure's performance target as: sufficiently performant. The claim is that it can give you dynamic and immutable data semantics that is sufficiently efficient to be used for practical applications, with paths towards selective optimizations where needed, like allowing full mutability in deftypes, and such.

The one thing it almost never does though is give you unmanaged mutability. It's pretty resilient to that, that's why you won't find anything faster than a volatile! (except for arrays). It doesn't want you to start having shared memory bugs in concurrent contexts. Though libraries exist for those.

Finally, I wouldn't say it discourages the use of arrays, when arrays is what you need it gives you the tools to do so. But when arrays is what you want because you have performance OCD, but don't actually need that level of performance, it would rather you used functional, immutable, heterogeneous with value semantics data-structures and functions instead, and will nudge you towards those.

Hope that answered your questions.

And yeah, your analysis of functional programming paradigms in Clojure mirrors how I think of it as well. I see that a lot, how the language is really pushing you to program functionally and almost intentionally making imperative/mutable programming painful so that you don't do it :)

Now that you've explained it it does seems obvious that arrays don't work too well with immutable structures. You're right about the OCD. C++ kinda instills that in you a bit. It feels "wrong" to have sequences of the same datatype (like pixels in an image) use the same container as sequences of varying data types (like a hiccup vector). For instance cache misses are something one is used to worrying about in C++ while in Clojure it's not even on the radar

I really appreciate you taking the time to explain things - especially so deep down in a thread

https://dragan.rocks/articles/18/Fluokitten-070-map-reduce-p...

Fluokitten and Neanderthal are great for high performance numerics. Can't really get any faster than Neanderthal (which uses MKL and the GPU for compute). And fluokitten can make working with arrays a bit nicer, in that it'll look a bit more like working with sequences, though you still need to be careful about the functions you use with it to avoid boxing.

https://clojure.org/reference/java_interop

Read the section about type hints and working with primitive types and the optimization tips section.

I've played with Neanderthal but the MKL dependency is a bit annoying (doesn't work on my Pinebook Pro and I can't ship binaries with it) - so I'd overlooked Fluokitten entirely. But this is very complementary to the Clojury way of doing stuff and has no dependencies. I'm def going to try to work this into my standard toolbox :)) I've only done the normal java-interop stuff in the past but this looks like a definite step up

Clojure is a hosted language, so hosting it on C++ (or Rust etc.) would be sweet for me personally. Also, I like compiler projects.

One thing I'd sorta fantasized about is (in a very hand wavey way) using Clojure + ClojureCL to run OpenCL kernels. In theory if you were to bundled your JAR with POCL.. you could selectively run your tight-loops/kernels on the CPU or GPU. So it'd be effectively like launching little C snippets. Furthermore, from what I remember, kernels are compiled and executed at run time - so it'd really fit with the whole REPL workflow and they would effectively simply be inline strings of C code that get executed

I think the main catch for the moment is that ClojureCL uses a MKL matrices to talk to the OpenCL driver (driver? dispatcher? I might be mixing up my terms) - but that could be modified to a JVM container

Probably my own bias - but the only time I've really been let down by Clojure and missed native was when I need to optimize a tight loop. Once you optimized Clojure past a certain point (to eliminate reflection, boxing issues, destructuring etc.) it starts to get ugly.

From the readme:

> The key features of Carp are the following:

> - Automatic and deterministic memory management (no garbage collector or VM)

> - Inferred static types for great speed and reliability

> - Ownership tracking enables a functional programming style while still using mutation of cache-friendly data structures under the hood

> - No hidden performance penalties – allocation and copying are explicit

> - Straightforward integration with existing C code

> - Lisp macros, compile time scripting and a helpful REPL

[0]: https://www.youtube.com/watch?v=sPhpelUfu8Q

[1]: https://sinusoid.es/immer/

1: https://hg.sr.ht/~vnorilo/pcoll/browse (not production quality)

Some of those are:

    - Default efficient immutable collections
    - Good support for safe concurrency and multi-core programming
    - Extended homoiconicity to include maps, vectors and sets as well as lists
    - Convenient short lambda syntax
    - Extensible data representation
    - Distinguishes between nil and empty list
    - Distinguishes between keywords and symbols
    - Real boolean types
    - Function arity overloading
    - Well thought out abstractions and set of standard functions: collections are abstractions, lazy sequences, transducers, relational set manipulation, etc.
    - Only two kinds of equality: by value or by reference, with the former being the default
    - Is a lisp-1 like Scheme, but also with more batteries included like Common Lisp
    - Slightly different visual appearance in its syntax, due to support for literal maps and vectors as well as lists, which can make things easier to visually parse.

If you want to produce native shippable statically linked binaries with Clojure look at GraalVM native compilation:

https://github.com/lread/clj-graal-docs

I've written a few things in it and found fewer footguns than React Native.

Granted, it comes with its own set of idiosyncracies, breaking version changes, half baked community libraries and developer ecosystem, but that's par for the course.

I've given up on Rust for me personally, but I think it is a great PL and effort. I am still playing with Zig, but I would love to just leverage my C background, and see if Cyclone eases me away from always coding in C.

So it's a Clojure REPL and linter/formatter? Why have REPL at all then?

To many, interactive development and debugging is the main point of the Clojure REPL. (Also true for many dynamic languages.) I take it you don't code and debug using such techniques. Some feel they are a revelation.