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Python will still be used 20 years from now. The clear advantage of Python is the enormous ecosystem that is available, the millions of questions on SO giving s

Python will still be used 20 years from now. The clear advantage of Python is the enormous ecosystem that is available, the millions of questions on SO giving solutions to every problem you can run into, the books and learning materials etc, programmers and corporations having invested loads of time and effort in building, maintaining and battle-testing libraries. Don't get me wrong, i think Julia is an amazing language, but being an amazing language is neither necessary or sufficient to succeed. R shows how you can succeed just fine with a kinda weird language.

logicchains 7y ago
>The clear advantage of Python is the enormous ecosystem that is available, the millions of questions on SO giving solutions to every problem you can run into All of this is also available in Julia via its near-seamless Python interop. Its package manager even does a better job of managing Python packages than Python does.
ScottPJones 7y ago
Python's ecosystem is great - but Julia's is growing incredibly fast, and in some cases Julia has already surpassed what is available in other languages (for example, take a look at the whole differential equations ecosystem: https://github.com/JuliaDiffEq https://github.com/JuliaDiffEq). Also, Python's ecosystem is only a 'pyimport(name)' away (using the PyCall.jl package). Same thing is true for R and a number of other languages (RCall.jl, JavaCall.jl, etc.) I've been using SymPy, QisKit, matplotlib and other Python packages with no problem in Julia.
mumblemumble 7y ago
I would be careful treating this too much like a popularity contest. Python will still be used 20 years from now, but that doesn't necessarily mean that it's going to be dominant 20 years from now. Source: I used to do a lot of programming in various dialects of Basic, which, a bit over 20 years ago, was popular largely because of its own ubiquity and popularity. And, while I still maintain some Basic code, I was surprised how quickly it died. One day everything was being written in it. The next day, we were were writing new things in a fancy new language that everyone agreed was more productive, and talking to the existing stuff through an FFI. And, a day later, we were replacing modules in order to get them off of the "legacy" platform.
awb 7y ago
> Python will still be used 20 years from now So much technology has come and gone since 2000. If innovation continues to accelerate I'd be hesitant to predict what 2040 will look like. Programming might become so simple and automated that we won't need StackOverflow to the extent we do today. It's really hard to predict the next year or two let alone the next 20.
- earenndil 7y ago
  > If innovation continues to accelerate It won't; that is a naive view. Innovation can't keep accelerating forever, and I would be surprised if it even keeps up its current pace; far likelier it's a sigmoid curve - https://en.wikipedia.org/wiki/Sigmoid_function https://en.wikipedia.org/wiki/Sigmoid_function
  - gugagore 7y ago
    I don't know if you're talking about like the heat death of the universe, and so like nothing is "forever", but I don't see signs of programming language innovation slowing down at all.
- goatlover 7y ago
  Programming languages from 2000 remain, though. C, C++, Java, JS, Python, etc. Even Fortran, Cobol and Lisp remain in use. There’s been attempts since the 80s to popularize visual and and higher level approaches to programming, but the traditional languages still dominate. And the newer ones like Go, Elixir and Julia are like the traditional C, Lisp and Fortrans.
  - awb 7y ago
    Sure, some do, but past adoption is not a guarantee of future adoption. 20 years in the future is a long time. Just look at Flash. Who knows, maybe a Quantum OS will dominate that doesn't support Python. So yes, if someone will still be using Python in 20 years, I'm sure you're right. But Python just as easily could be relegated to a niche domain while other languages take over a broader range of applications. Especially if someone's able to build a programming translator where you can easily port your code base from one language to another.
baron_harkonnen 7y ago
I remember when Python was a new and exciting language and people said the exact same thing about Perl. "You'll never see Python replace Perl for string processing, Perl has such a huge ecosystem!". At the time Perl was the de facto interpreted/"scripting" language. Sure Perl is around still, but it has become a rather niche language used in a small number of specific communities. I use Python everyday, and still haven't had enough time to properly learn Julia, and I would certainly not be shocked to see Julia take over the lion's share of numeric computing from Python in 20 years.
- cwyers 7y ago
  Yes, some things succeed. Most things don't succeed. If you bet on failure 100% of the time, you'll have your misses, but you'll hit more than you miss.
- int_19h 7y ago
  Python replaced Perl in many niches, because Python was better suited to general tasks. For string processing, it wasn't as convenient, but there were so many other things where it was clearly a better choice. And being able to use a single "good enough" language for everything is itself a major convenience. Julia is the opposite - it's better than Python in one particular narrow niche, and cannot replace it broadly. So it has to offer enough to justify going from one language to two.
  - Recurecur 7y ago
    "Julia is the opposite - it's better than Python in one particular narrow niche, and cannot replace it broadly. So it has to offer enough to justify going from one language to two." How so? Julia is a fine general purpose language. I'd go so far as to say it's more appropriate than Python for a wide class of problems!
    - hpcjoe 7y ago
      In many ways, Julia is a better python than python, if only for the lack of the (quite insane in the 2000s) program structure by text formatting. That is a misfeature. Julia is fast out of the box. You don't need Julia + some-other-language to get performance. You can use your GPUs fairly trivially from within the language (though this is implemented as FFI, it still has an idiomatic feel to it). As for the previous comments on Perl, I am reminded of Mark Twain's famous retort. Rumors of its demise are greatly exaggerated.
dcolkitt 7y ago
> R shows how you can succeed just fine with a kinda weird language. One thing that most people don't appreciate about R is the subtle influence from lisp world. This makes it really feel like the language is optimized for data science down to the most basic syntax level.
- gugagore 7y ago
  I'd love an example of the subtle influence. In any case, the influence of lisp on julia is pretty obvious if you're familiar with lisp, I believe.
  - cwyers 7y ago
    I believe that R was originally an implementation of S in Scheme, because of the restrictive commercial licensing of S and the desire to have a free-as-in-beer alternative that was S-compatible. This comes through in things like R's metaprogramming: https://adv-r.hadley.nz/meta-big-picture.html#meta-big-picture https://adv-r.hadley.nz/meta-big-picture.html#meta-big-pictu...
gugagore 7y ago
> the millions of questions on SO giving solutions to every problem you can run into I definitely know what you mean. I too have the experience of typing in basically natural language queries into Google and have stack overflow turn it into copy-paste-able code for me. But what's also true is that in 20 years the problems being solved will likely be bigger, and more complicated, and in many cases we'll be solving them on platforms that require good abstractions over multiple cores. So none of that is really in Python's wheelhouse. (Complexity is an issue because abstrations in Python almost always come at a cost.)
dv_dt 7y ago
Perl used to be in somewhere similar to Pythons place 20 years ago...
socialdemocrat 7y ago
> The clear advantage of Python is the enormous ecosystem that is available Could have said that about Perl back in the day too, or a great number of languages. The key problem Python faces competing against Julia in the long run is that Julia runs faster with less resources. By that I mean that because packages in Julia combine easier and are written all in Julia, it is simply much faster to develop equivalent functionality in Julia compared to Python. Thus as Julia grows the speed of advancement will just keep growing. There is also a sort of asymptotic curve for most software. As you reach certain complexity advancing gets slower. Python due to its age has acquired a lot of cruft which will slow development down. I know exactly how this feels from having worked on very similar software products of different age. The older software really had problems keeping up speed. The younger software moved ahead faster due to cleaner design. We needed far less people to add more features than the competition. Python will struggle with old design decisions it can no longer undo. Look at e.g. the enormous amount of man hours required to get JIT compilation working in Python. It still does not work well. Meanwhile Julia has require less manpower making a whole language with better JIT compilation. Language design matters over time. I don't claim Julia will overtake Python any time soon. But over a long time frame I think it is inevitable, because legacy goes against Python in too many areas.

logicchains 7y ago

>The clear advantage of Python is the enormous ecosystem that is available, the millions of questions on SO giving solutions to every problem you can run into All of this is also available in Julia via its near-seamless Python interop. Its package manager even does a better job of managing Python packages than Python does.

ScottPJones 7y ago

Python's ecosystem is great - but Julia's is growing incredibly fast, and in some cases Julia has already surpassed what is available in other languages (for example, take a look at the whole differential equations ecosystem: https://github.com/JuliaDiffEq https://github.com/JuliaDiffEq). Also, Python's ecosystem is only a 'pyimport(name)' away (using the PyCall.jl package). Same thing is true for R and a number of other languages (RCall.jl, JavaCall.jl, etc.) I've been using SymPy, QisKit, matplotlib and other Python packages with no problem in Julia.

mumblemumble 7y ago

I would be careful treating this too much like a popularity contest. Python will still be used 20 years from now, but that doesn't necessarily mean that it's going to be dominant 20 years from now. Source: I used to do a lot of programming in various dialects of Basic, which, a bit over 20 years ago, was popular largely because of its own ubiquity and popularity. And, while I still maintain some Basic code, I was surprised how quickly it died. One day everything was being written in it. The next day, we were were writing new things in a fancy new language that everyone agreed was more productive, and talking to the existing stuff through an FFI. And, a day later, we were replacing modules in order to get them off of the "legacy" platform.

awb 7y ago

> Python will still be used 20 years from now So much technology has come and gone since 2000. If innovation continues to accelerate I'd be hesitant to predict what 2040 will look like. Programming might become so simple and automated that we won't need StackOverflow to the extent we do today. It's really hard to predict the next year or two let alone the next 20.

earenndil 7y ago
> If innovation continues to accelerate It won't; that is a naive view. Innovation can't keep accelerating forever, and I would be surprised if it even keeps up its current pace; far likelier it's a sigmoid curve - https://en.wikipedia.org/wiki/Sigmoid_function https://en.wikipedia.org/wiki/Sigmoid_function
- gugagore 7y ago
  I don't know if you're talking about like the heat death of the universe, and so like nothing is "forever", but I don't see signs of programming language innovation slowing down at all.
goatlover 7y ago
Programming languages from 2000 remain, though. C, C++, Java, JS, Python, etc. Even Fortran, Cobol and Lisp remain in use. There’s been attempts since the 80s to popularize visual and and higher level approaches to programming, but the traditional languages still dominate. And the newer ones like Go, Elixir and Julia are like the traditional C, Lisp and Fortrans.
- awb 7y ago
  Sure, some do, but past adoption is not a guarantee of future adoption. 20 years in the future is a long time. Just look at Flash. Who knows, maybe a Quantum OS will dominate that doesn't support Python. So yes, if someone will still be using Python in 20 years, I'm sure you're right. But Python just as easily could be relegated to a niche domain while other languages take over a broader range of applications. Especially if someone's able to build a programming translator where you can easily port your code base from one language to another.

baron_harkonnen 7y ago

I remember when Python was a new and exciting language and people said the exact same thing about Perl. "You'll never see Python replace Perl for string processing, Perl has such a huge ecosystem!". At the time Perl was the de facto interpreted/"scripting" language. Sure Perl is around still, but it has become a rather niche language used in a small number of specific communities. I use Python everyday, and still haven't had enough time to properly learn Julia, and I would certainly not be shocked to see Julia take over the lion's share of numeric computing from Python in 20 years.

cwyers 7y ago
Yes, some things succeed. Most things don't succeed. If you bet on failure 100% of the time, you'll have your misses, but you'll hit more than you miss.
int_19h 7y ago
Python replaced Perl in many niches, because Python was better suited to general tasks. For string processing, it wasn't as convenient, but there were so many other things where it was clearly a better choice. And being able to use a single "good enough" language for everything is itself a major convenience. Julia is the opposite - it's better than Python in one particular narrow niche, and cannot replace it broadly. So it has to offer enough to justify going from one language to two.
- Recurecur 7y ago
  "Julia is the opposite - it's better than Python in one particular narrow niche, and cannot replace it broadly. So it has to offer enough to justify going from one language to two." How so? Julia is a fine general purpose language. I'd go so far as to say it's more appropriate than Python for a wide class of problems!
  - hpcjoe 7y ago
    In many ways, Julia is a better python than python, if only for the lack of the (quite insane in the 2000s) program structure by text formatting. That is a misfeature. Julia is fast out of the box. You don't need Julia + some-other-language to get performance. You can use your GPUs fairly trivially from within the language (though this is implemented as FFI, it still has an idiomatic feel to it). As for the previous comments on Perl, I am reminded of Mark Twain's famous retort. Rumors of its demise are greatly exaggerated.

dcolkitt 7y ago

> R shows how you can succeed just fine with a kinda weird language. One thing that most people don't appreciate about R is the subtle influence from lisp world. This makes it really feel like the language is optimized for data science down to the most basic syntax level.

gugagore 7y ago
I'd love an example of the subtle influence. In any case, the influence of lisp on julia is pretty obvious if you're familiar with lisp, I believe.
- cwyers 7y ago
  I believe that R was originally an implementation of S in Scheme, because of the restrictive commercial licensing of S and the desire to have a free-as-in-beer alternative that was S-compatible. This comes through in things like R's metaprogramming: https://adv-r.hadley.nz/meta-big-picture.html#meta-big-picture https://adv-r.hadley.nz/meta-big-picture.html#meta-big-pictu...

gugagore 7y ago

> the millions of questions on SO giving solutions to every problem you can run into I definitely know what you mean. I too have the experience of typing in basically natural language queries into Google and have stack overflow turn it into copy-paste-able code for me. But what's also true is that in 20 years the problems being solved will likely be bigger, and more complicated, and in many cases we'll be solving them on platforms that require good abstractions over multiple cores. So none of that is really in Python's wheelhouse. (Complexity is an issue because abstrations in Python almost always come at a cost.)

dv_dt 7y ago

Perl used to be in somewhere similar to Pythons place 20 years ago...

socialdemocrat 7y ago

> The clear advantage of Python is the enormous ecosystem that is available Could have said that about Perl back in the day too, or a great number of languages. The key problem Python faces competing against Julia in the long run is that Julia runs faster with less resources. By that I mean that because packages in Julia combine easier and are written all in Julia, it is simply much faster to develop equivalent functionality in Julia compared to Python. Thus as Julia grows the speed of advancement will just keep growing. There is also a sort of asymptotic curve for most software. As you reach certain complexity advancing gets slower. Python due to its age has acquired a lot of cruft which will slow development down. I know exactly how this feels from having worked on very similar software products of different age. The older software really had problems keeping up speed. The younger software moved ahead faster due to cleaner design. We needed far less people to add more features than the competition. Python will struggle with old design decisions it can no longer undo. Look at e.g. the enormous amount of man hours required to get JIT compilation working in Python. It still does not work well. Meanwhile Julia has require less manpower making a whole language with better JIT compilation. Language design matters over time. I don't claim Julia will overtake Python any time soon. But over a long time frame I think it is inevitable, because legacy goes against Python in too many areas.