Ruby code, perhaps more than most code, is written for readability and “beauty”. It’s a part of Ruby culture that I greatly appreciate. But if you care about performance, you will act differently, regardless of language. And the whole point of this code is to show that if you care about performance above all else, there’s of plenty of room to maneuver in interpreted Ruby.
It is, indeed, a fundamental goal of ruby that there are multiple ways to write the same thing, and that the programmer should not need to understand nuances of the compiler.
"I need to guess how the compiler works. If I'm right, and I'm smart enough, it's no problem. But if I'm not smart enough, and I'm really not, it causes confusion. The result will be unexpected for an ordinary person. This is an example of how orthogonality is bad." -matz 2003.
In this particular example, the fact that assignments return the value of the right-hand side is well-known and used frequently in Ruby code. The fact that arrays have to be allocated is obvious. The fact that allocations have a runtime cost is obvious. The only thing that isn't obvious is that the return value allocation of assignments whose value isn't used are optimized away. If you know that, you'll think of appending the nil to activate that optimization. Characterizing the lack of that step as a "mistake" only makes sense if the goal for your code is to maximize performance -- which in this case, most unusually for Ruby, it was.
~/scripts > ruby fib.rb
2.3346780000720173
~/scripts > ruby --yjit fib.rb
1.5913339999970049
So looks like YJIT doesn't "know" about this optimizationRunning the original fib benchmark (i.e., without the author's technique to eliminate the array allocation) on an M1 Pro, I see:
CRuby 3.3.1:
2.058589000022039
CRuby 3.3.1 w/ YJIT:
1.4314430000958964
TruffleRuby 24.0.1 (Native):
0.20155820800573565
TruffleRuby 24.0.1 (JVM):
0.1336908749944996
I took the best time out of three for each implementation, but there wasn't that much variance over all. Standard caveats about benchmarking on an actively used laptop apply.Running the new prime_counter benchmark that the crystalruby author mentions in another thread¹, I see:
Crystal 1.12.1 (LLVM 18.1.4) w/ crystalruby 0.2.0 in CRuby 3.3.1:
0.34096299996599555
CRuby 3.3.1:
2.9615250000497326
CRuby 3.3.1 w/ YJIT:
1.640430000028573
TruffleRuby 24.0.1 (Native):
0.2504862080095336
TruffleRuby 24.0.1 (JVM):
0.25282600001082756
YJIT and TruffleRuby make different trade-offs, so I'm not trying to say the latter is necessarily better. But, I think the TruffleRuby numbers show what are possible in terms of Ruby optimization. Unfortunately, there's currently an issue in TruffleRuby with one of the crystalruby gem's dependencies³, so I had to extract the Ruby benchmark out to a separate file. incompatibility.¹ -- https://news.ycombinator.com/item?id=40153218
² -- The method_source gem used by crystalruby catches exceptions and matches against the message² for some conditional handling. TruffleRuby 24.0 now uses to Prism as its parser and Prism has an exception message with slightly different wording from CRuby. Consequently, method_source's handling doesn't work with Prism. It's hard to say where the compatibility issue lies, since exception messages aren't stable APIs. We'll get it sorted out.
³ -- https://github.com/banister/method_source/blob/06f21c66380c6...
That's impressive numbers for running the unoptimized code. I might give TruffleRuby a shot!
Go is the opposite. It's great, as you say, because it's dirt simple. It's a brutalist get-the-job-done kind of language, and I think if I were to start a company working with other engineers, I'd absolutely choose Go for that reason. It's easy to read. It's easy to reason about. And there's very little implicitness in it.
Are you aware that you're referencing the Python mantra with that? Feel free to Google it, it's from 2004.
There should be one-- and preferably only one --obvious way to do it.
the Python mantra with that?
Offtopic but, I switched from Ruby to Python for a new job about six months ago.While I love Ruby, I was looking forward to some of that "one way to do things" simplicity I'd been promised by Python.
Boy... were my hopes crushed. There are a lot of possible ways to do any given thing, from iteration to package/import structures, etc.
For the most part it seems like the proliferation of options in Python is pretty sane; I can generally see why each choice was made to address existing pain points. So kudos to Python for that. But man, did they leave "one way to do it" behind a loooong time ago.
And they honestly never really adhered to it either. It was just a knee-jerk reaction to a (I believe Haskell) presentation that said something like "we got n ways to do x", where n was in the double digits and x was something extremely uninteresting like looping over an array.
Can't really recall details though, it was old knowledge by the time I Heard about it around 2010 and a quick Google didn't help me dig it up
with some being slower than others.
Do we all agree that in practice, these sort of micro-optimizations almost never matter?It's certainly easy to think of situations where they do matter, but unless your project is FaaS (Fibonacci As A Service) probably not.
All the inefficiencies add up, at scale. a 3% inefficiency means you're spending ~3% more on compute. CI takes longer. Dev velocity decreases.
It's idiomatic Ruby in a very particular case that likely was explicitly chosen to demonstrate such a dramatic effect.
You're _usually_ not returning implicit arrays from loops in production code. Parallel assignments, when they're used, are almost always in the first line of an initialize method, not the returned line of an enumerable block.
To be fair, I do not think that is a "mistake" as such. I have written Ruby professionally for 6 years or so and have committed to several Ruby open source projects and haven't seen an innocus `nil` sitting at the end of a loop, to prevent array allocation.
The argument would be fair, if it wasn't idiomatic Ruby.
More like - knowing internals of a language will allow one to gain more performance out of it. That has been true for almost every programming language, but general speaking the goal of a VM based language is to not require that _specialized_ knowledge.