Why don't we see more adoption of alternative runtimes? Why doest the community push for the adoption of higher performing implementations as the standard? Does anyone run a more esoteric interpreter for one of these languages in production?
Implementing a sane subset of Python is not so difficult, because, well, d'uh, it's sane. Implementing all the leaky details, the insane data model (slightly less insane in Python 3), all the invasive interpreter APIs which are frequently used by frameworks and extensions, is a whole different story. More importantly, if you implement all those, there's not much to gain in performance any more. Pypy has made tremendous progress there, but I'd expect that it still suffers from this — bottom line is, there is no way to efficiently implement what CPython does, and I'd be surprised if Pypy is significantly faster than CPython in code that uses all this shit. I expect Pypy produces a lot of gain as soon as code doesn't use that.
We are running production systems in pypy and performance improvement is significant. Average 40percent faster than node in many areas.
Some of that has been fixed / got make up applied to play pretend.
PyPy has a glue layer to implement the C API. The C API is designed around reference counting, which PyPy doesn't do. This also shows up in Python code assuming files will be immediatly closed in lines like 'x = open(fname).read()'
Method resolution order. __slots__. globals(). id
> They're moving towards standardizing the ordered dict layout
Can you elaborate? Not sure what you mean.
> inspect library
Yes, a fair few functions in that module are CPython specific (or assume a CPython-ish runtime).
> C API
Isn't the C API CPython specific? It is not a Python-language feature. PyPy implemented it to drive up adoption. How would the C API be expected to work with Jython, or IronPython, or a JS implementation?
> Method resolution order
This is not a CPython leaking, it's a specified thing. Python uses the C3 algorithm.
Again, this is a language (or object model) feature?
Again, specified by the language? Not a CPython specific thing?
ID returns a unique identifier per object. That's all, in CPython it returns the memory address. Is that what you mean?
There are also only 5 'CPython implementation detail' warnings in the language data model docs
But the Python ecosystem depends on extensions written using the C API. If you are trying to write a new Python implementation and they tell you they need to be able to run some C extension you can tell them 'actually that's a CPython feature' all you want, but they'll go away and not use your implementation.
> How would the C API be expected to work with Jython, or IronPython, or a JS implementation?
Well you'd implement the same API using JNI, PlatformInvoke, or the V8 C extension API, or whatever else the platform you are building on has, respectively. But it's hard!
Ordered dict layout: https://mail.python.org/pipermail/python-dev/2016-September/...
Well I think those are the only ones actively maintained, aren't they? As a language community we're pretty lucky to have even two production-ready implementations.
Rubinius seems to lost all their contributors and to have deleted their JIT and ground to a halt. Topaz was just an experiment. I don't think Maglev or IronRuby have been maintained for a few years. Opal is still going but it's not quite what you mean when you talk about Ruby implementations.
> Why don't we see more adoption of alternative runtimes?
Because it's a huge volume of work that needs very specialised skills that few people have, so they often aren't maintained very long. Starting one is fun, finishing and maintaining is more of a slog.
Theres a good list of problems making a proper ruby implementation here http://blog.headius.com/2012/10/so-you-want-to-optimize-ruby...
And a list of what remains different in jruby here (mostly c extensions and threads) https://github.com/jruby/jruby/wiki/DifferencesBetweenMriAnd...
Nobody is going to use a new Ruby or Python unless it brings something new to the table. Pypy has it with speed. JRuby has Java compability. Without an X factor it's hard to get people excited to try it, let alone contribute.
The guy who was doing on the spare time spec for ruby got frustrated and believe the official ruby team were trying to kill competition and left iirc. Rubinius or whatever was built to that spec and engineyard was funding them iirc.
Drama. There was drama between Jruby and Ruby for awhile. And then it was og ruby vs jruby dev.
If you have a language spec then it's easier to implement kinda like java and tcl (tck?). But at the same time Oracle and Sun system was really really into the fact that only they can control that language.
Otherwise the edge cases will beat you nasty.
R have an alternative because RRevolution made money and now Microsoft bought them and there's a huge company backing. I don't think the people behind R really care if there's a competitor. They just do their thang.
What exactly would you like to see? For python:
- PyPy is seeing a lot of use,
- Cython is seeing a lot of use, mostly as a way to implement C glue, but also on its own
- MicroPython is seeing a lot of use on limited environments
- Nuitka is a "secret sauce" for people who want to compile their Python to an .exe without leaving any easily-decompilable .py files. (And they get a speedup as a bonus)
Even TinyPy had gotten some use in its day (before it was abandoned - nowadays, MicroPython fills the same niche).
Except for older languages (C++, C, Pascal, Basic, COBOL, Fortran, LISP, APL), it is actually rare to have more than two mature implementations of a language see e.g. (D, Go have their own and a GCC backend; C# has its own and Mono).
This is the ultimate truth.
The only way for an alternative implementation to compete is for someone to pay for its creation, documentation, maintenance, etc.
That's how we got all these great JS JITs and stuff: with Apple, Google, and co paying the bills, and pushing for them to succeed.
PyPy managed to get close to something working, but it lacks lots of the polish and resources available for CPython.
I am rooting for Crystal, but without massive backing like Go and Rust enjoy, it is difficult.
People keep complaining about the small community. Please join and help.
> lacks corporate [...] backing
Is that a bug or a feature? ...
I will when I find the chance to start working with it! I'm currently using Scala.
> Is that a bug or a feature? ...
It seems like a bug to me. Yes, corporate backing has its downsides, but it's a great way to ensure that a language will have long-term support. Look at React and TypeScript, for example. If Facebook and Microsoft didn't push them down our throats at the start, do you think their use would end up being so widespread?
If anything, community-driven projects can keep on track longer: Linux, Python, non-commercial distributions, while corporate-driven one can change direction or be dropped: Java, Visual Basic, MySQL, Solaris, a lot of Google projects.
It's much more difficult to steer a whole community in wrong direction or convince most contributors to drop a project.
Always take advice from people of failed products with a grain of salt.
No the point isn't that the VM is broken. The point is that the Ruby language has semantics and is used in idioms that nobody knows how to optimise well yet.
> tinyrb based on potion based on lua with classes is ~200x faster in method calls
tinyrb is interesting, but it just isn't the same semantics as Ruby:
tinyrb doesn't have a better VM - they're implementing a different programming language with all the hard bits left out!
In my project we've been having to do new original research into how to optimise Ruby - introducing concepts such as dispatch chains which haven't been needed more because people don't try to push metaprogramming in most language like they do in Ruby.
The simple potion/IO mop and ABI layout is far superior to matz ruby, just the method cache and thread support is missing. And this compiler has no optimizations at all yet, not even trivial constant folding. Still 200x faster.
This lua with mop VM can be used for every dynamic language, like ruby, perl, python, PHP, ... and will beat rpython or truffle/graal by lengths. The other VM based on this tvmjit ditto. This uses even luajit with s-expressions.
> Register-transfer level ... Not to be confused with Register transfer language.
What is the causes of this?