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Subject: [Python-ideas] Re: Multiple dispatch transpilation
From: Todd <toddrjen () gmail ! com>
Date: 2021-03-16 15:45:27
Message-ID: CAFpSVpJqmd58sX_77GOAWg6mK5ATa0cRn_kOV4qo78s7-RFSSA () mail ! gmail ! com
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Numba already provides as-needed JIT compilation and type annotations. I am
not sure it supports multiple dispatch but if that was useful it could be
added with decorators. I am not sure integrating this into the language
will help much.
On Tue, Mar 16, 2021, 10:07 Marvin van Aalst <marvin.van.aalst@hhu.de>
wrote:
> Hi fellow Pythonistas!
>
> A colleague of mine recently got me involved in the Julia language and
> while I was really impressed by the performance, the complete lack of OOP
> and thus bad discoverability (not to mention all their unicode function
> names) for me leaves a lot to be desired.
>
> TL;DR:
>
> Julia uses a type-based multi-method system (multiple dispatch), that
> because of type-stability allows JIT compilation of very efficient code.
> Since Pythons single-dispatch classes are a subset of that system, it
> should in principle be possible to transform the code from Class.method
> to method(class:type), *before compilation* essentially allowing the same
> optimizations. For the other arguments could utilize the existing type
> annotations. The idea would be to allow this via decorators etc for code
> where it makes sense (e.g. high volume number crunching), while keeping the
> rest of the language free from JIT compiler issues and other nuisances.
>
> Very long version:
>
> Julia is a high level dynamically typed language, that often approaches or
> matches C performance. This is due to type-based multiple dispatch and
> type-stability through specialization. However, the coolest part is that
> the type system is set-theoretic, which makes it unnecessary to repeat
> functions for related types. This page
> <https://ucidatascienceinitiative.github.io/IntroToJulia/Html/WhyJulia>
> and this blog post
> <http://www.stochasticlifestyle.com/like-julia-scales-productive-insights-julia-developer/>
> give a good explanations of how this works. *However*, since with their
> multiple dispatch system everything can be written without using classes,
> they have opted to not include any OOP. This leads to a very high amount of
> functions that are accessible in the global namespace and hinders one to
> explore the packages in the usual, playful way that probably all of us are
> used to. So the usual resort is to have to read documentation. What a shame
> ;)
>
> Since all of Julia needs to be JIT compiled, importing packages usually
> takes a lot of time (it does some pre-compilation on first import, which
> takes a lot longer, but depending on the system its still quite a while). A
> quick search for "time-to-first-plot" or "latency" will be plenty to show
> that this is quite a nuisance. I believe that its perfectly fine for some
> code to be interpreted, as the python community has frequently shown, so
> that might not be the best approach. Only performance-critical code needs
> to be fast. In our world this is usually done by offloading the quick stuff
> into C, but in that case it gets really hard to expand those libraries
> (e.g. numpy has its own dispatch system, so pypy cannot help it as much as
> it could). Also extending numerical types for arrays is basically
> impossible.
>
> So how can we try to retain usability and still gain the performance for
> the code that needs it? In general I'd argue that multiple dispatch and JIT
> compilation is fine, as our performance critical code usually runs for very
> long times, so the added overhead is minimal. If the code doesn't take a
> large amount of time, you probably don't need to optimize it anyway. I'd
> argue that one way to get there would be to "transpile" our Python code by
> inserting a step before compilation that utilizes the type annotations that
> already exist and then pulls typed versions out of the classes. So e.g.
> Class.method(x:int) would be transformed into the typed version method(class:type,
> x:int), from where on multiple dispatch could be run.
>
> This would have the further advantage, that in Julia it can be very hard
> to see, which attributes a type should have and which methods necessarily
> have to be defined in order to guarantee library compatibility. In OOP, we
> can easily achieve that by defining the type as an abstract base class.
>
> A lot of the statements about Julia here come from Jeff Bezansons (one of
> the Julia main devs PhD thesis)
> <https://dspace.mit.edu/handle/1721.1/99811>. It's a quick read and I
> would in general recommend reading it.
>
> On the one hand, in general I think that julia is more compiler-friendly
> than it is user or tooling-friendly (since methods for your type can be
> defined outside of the scope of the class, its very hard for your IDE to
> tell you if that function you just misspelled doesn't exist). On the other
> hand, its quite nice to be able to create a custom array and just push it
> through all the numerical libraries in a very efficient way, which works
> because you have defined all the required methods. I think this way of
> speeding up things would be cooler than enabling static typing which many
> people are asking for, as we still retain the flexibility (or might even
> increase it in the case of arrays), while greatly speeding up code.
>
> Since I only understand all these things at a high level, I'm sure that
> I've greatly simplified or misrepresented something. The real hope here is
> that someone smarter than me is inspired by that idea and manages to build
> something cool. I'd by happy to help in any way I can though.
>
> Thanks for reading this far, you are a good person :*
>
> Cheers,
>
> Marvin
> _______________________________________________
> Python-ideas mailing list -- python-ideas@python.org
> To unsubscribe send an email to python-ideas-leave@python.org
> https://mail.python.org/mailman3/lists/python-ideas.python.org/
> Message archived at
> https://mail.python.org/archives/list/python-ideas@python.org/message/Z26RADVHYNQBET3FHP47XFIJLEXPY3ND/
> Code of Conduct: http://python.org/psf/codeofconduct/
>
[Attachment #5 (text/html)]
<div dir="auto"><div>Numba already provides as-needed JIT compilation and type \
annotations. I am not sure it supports multiple dispatch but if that was useful it \
could be added with decorators. I am not sure integrating this into the language \
will help much.<br><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On \
Tue, Mar 16, 2021, 10:07 Marvin van Aalst <<a \
href="mailto:marvin.van.aalst@hhu.de">marvin.van.aalst@hhu.de</a>> \
wrote:<br></div><blockquote class="gmail_quote" style="margin:0 0 0 \
.8ex;border-left:1px #ccc solid;padding-left:1ex">
<div>
<p style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">Hi fellow Pythonistas!</span></p> <p \
style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">A colleague of mine recently got me involved in the \
Julia language and while I was really impressed by the performance, the complete lack \
of OOP and thus bad discoverability (not to mention all their unicode function names) \
for me leaves a lot to be desired. </span></p> <p \
style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">TL;DR: </span></p> <p \
style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">Julia uses a type-based multi-method system (multiple \
dispatch), that because of type-stability allows JIT compilation of very efficient \
code. Since Pythons single-dispatch classes are a subset of that system, it should in \
principle be possible to transform the code from </span><span \
style="box-sizing:border-box"><code \
style="box-sizing:border-box;font-family:var(--monospace);text-align:left;vertical-align:initial;border:1px \
solid rgb(231,234,237);background-color:rgb(243,244,244);border-radius:3px;padding:0px \
2px;font-size:0.9em">Class.method</code></span><span style="box-sizing:border-box"> \
to </span><span style="box-sizing:border-box"><code \
style="box-sizing:border-box;font-family:var(--monospace);text-align:left;vertical-align:initial;border:1px \
solid rgb(231,234,237);background-color:rgb(243,244,244);border-radius:3px;padding:0px \
2px;font-size:0.9em">method(class:type)</code></span><span \
style="box-sizing:border-box">, </span><span style="box-sizing:border-box"><strong \
style="box-sizing:border-box"><span style="box-sizing:border-box">before \
compilation</span></strong></span><span style="box-sizing:border-box"> essentially \
allowing the same optimizations. For the other arguments could utilize the existing \
type annotations. The idea would be to allow this via decorators etc for code where \
it makes sense (e.g. high volume number crunching), while keeping the rest of the \
language free from JIT compiler issues and other nuisances. </span></p> <p \
style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">Very long version:</span></p> <p \
style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">Julia is a high level dynamically typed language, that \
often approaches or matches C performance. This is due to type-based multiple \
dispatch and type-stability through specialization. However, the coolest part is that \
the type system is set-theoretic, which makes it unnecessary to repeat functions for \
related types. </span><span style="box-sizing:border-box"><a \
href="https://ucidatascienceinitiative.github.io/IntroToJulia/Html/WhyJulia" \
style="box-sizing:border-box;color:rgb(65,131,196)" target="_blank" \
rel="noreferrer"><span style="box-sizing:border-box">This page</span></a></span><span \
style="box-sizing:border-box"> and this </span><span style="box-sizing:border-box"><a \
href="http://www.stochasticlifestyle.com/like-julia-scales-productive-insights-julia-developer/" \
style="box-sizing:border-box;color:rgb(65,131,196)" target="_blank" \
rel="noreferrer"><span style="box-sizing:border-box">blog post</span></a></span><span \
style="box-sizing:border-box"> give a good explanations of how this works. \
</span><span style="box-sizing:border-box"><strong \
style="box-sizing:border-box"><span \
style="box-sizing:border-box">However</span></strong></span><span \
style="box-sizing:border-box">, since with their multiple dispatch system everything \
can be written without using classes, they have opted to not include any OOP. This \
leads to a very high amount of functions that are accessible in the global namespace \
and hinders one to explore the packages in the usual, playful way that probably all \
of us are used to. So the usual resort is to have to read documentation. What a shame \
;)</span></p> <p style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">Since all of Julia needs to be JIT compiled, importing \
packages usually takes a lot of time (it does some pre-compilation on first import, \
which takes a lot longer, but depending on the system its still quite a while). A \
quick search for "time-to-first-plot" or "latency" will be plenty \
to show that this is quite a nuisance. I believe that its perfectly fine for some \
code to be interpreted, as the python community has frequently shown, so that might \
not be the best approach. Only performance-critical code needs to be fast. In our \
world this is usually done by offloading the quick stuff into C, but in that case it \
gets really hard to expand those libraries (e.g. numpy has its own dispatch system, \
so pypy cannot help it as much as it could). Also extending numerical types for \
arrays is basically impossible.</span></p> <p \
style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">So how can we try to retain usability and still gain \
the performance for the code that needs it? In general I'd argue that multiple \
dispatch and JIT compilation is fine, as our performance critical code usually runs \
for very long times, so the added overhead is minimal. If the code doesn't take a \
large amount of time, you probably don't need to optimize it anyway. I'd \
argue that one way to get there would be to "transpile" our Python code by \
inserting a step before compilation that utilizes the type annotations that already \
exist and then pulls typed versions out of the classes. So e.g. </span><span \
style="box-sizing:border-box"><code \
style="box-sizing:border-box;font-family:var(--monospace);text-align:left;vertical-align:initial;border:1px \
solid rgb(231,234,237);background-color:rgb(243,244,244);border-radius:3px;padding:0px \
2px;font-size:0.9em">Class.method(x:int)</code></span><span \
style="box-sizing:border-box"> would be transformed into the typed version \
</span><span style="box-sizing:border-box"><code \
style="box-sizing:border-box;font-family:var(--monospace);text-align:left;vertical-align:initial;border:1px \
solid rgb(231,234,237);background-color:rgb(243,244,244);border-radius:3px;padding:0px \
2px;font-size:0.9em">method(class:type, x:int)</code></span><span \
style="box-sizing:border-box">, from where on multiple dispatch could be run. \
</span></p> <p style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">This would have the further advantage, that in Julia it \
can be very hard to see, which attributes a type should have and which methods \
necessarily have to be defined in order to guarantee library compatibility. In OOP, \
we can easily achieve that by defining the type as an abstract base class. \
</span></p> <p style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">A lot of the statements about Julia here come from \
</span><span style="box-sizing:border-box"><a \
href="https://dspace.mit.edu/handle/1721.1/99811" \
style="box-sizing:border-box;color:rgb(65,131,196)" target="_blank" \
rel="noreferrer"><span style="box-sizing:border-box">Jeff Bezansons (one of the Julia \
main devs PhD thesis)</span></a></span><span style="box-sizing:border-box">. It's \
a quick read and I would in general recommend reading it.</span></p> <p \
style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">On the one hand, in general I think that julia is more \
compiler-friendly than it is user or tooling-friendly (since methods for your type \
can be defined outside of the scope of the class, its very hard for your IDE to tell \
you if that function you just misspelled doesn't exist). On the other hand, its \
quite nice to be able to create a custom array and just push it through all the \
numerical libraries in a very efficient way, which works because you have defined all \
the required methods. I think this way of speeding up things would be cooler than \
enabling static typing which many people are asking for, as we still retain the \
flexibility (or might even increase it in the case of arrays), while greatly speeding \
up code.</span></p> <p style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">Since I only understand all these things at a high \
level, I'm sure that I've greatly simplified or misrepresented something. The \
real hope here is that someone smarter than me is inspired by that idea and manages \
to build something cool. I'd by happy to help in any way I can though. \
</span></p> <p style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">Thanks for reading this far, you are a good person \
:*</span></p> <p style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">Cheers,</span></p> <p \
style="box-sizing:border-box;line-height:inherit;margin:0.8em \
0px;white-space:pre-wrap;color:rgb(51,51,51);font-family:"Open \
Sans","Clear Sans","Helvetica \
Neue",Helvetica,Arial,sans-serif;font-size:16px;font-style:normal;font-variant-li \
gatures:normal;font-variant-caps:normal;font-weight:400;letter-spacing:normal;text-ali \
gn:start;text-indent:0px;text-transform:none;word-spacing:0px;text-decoration-style:initial;text-decoration-color:initial"><span \
style="box-sizing:border-box">Marvin </span></p>
</div>
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</blockquote></div></div></div>
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