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Everytime Julia is mentioned on HN, I see a surprising amount of people who dislike the language for whatever reason. I understand a lot of their concerns (time

Everytime Julia is mentioned on HN, I see a surprising amount of people who dislike the language for whatever reason. I understand a lot of their concerns (time to first plot, debugging sucks, IDE support isn't amazing yet). However, I don't see a lot of alternatives for the niche that Julia occupies. If you want to do high performance scientific computing, there aren't a lot of options in terms of languages. Python is the de facto but it's so slow for anything that can't be well represented as vectorized NumPy operations. There are ways around that like Numba, Jax, Cython, etc. but their use cases are pretty limited, and they don't work well with other Python packages. There is, of course, C and C++ which are commonly used to speed up Python or as standalone packages. However, C++ is such a complicated beast that writing performant and correct code takes forever. C is much more manageable, but I find that there are not a lot of scientific packages written in pure C. This isn't even touching on the horrendous build system that is CMake. Fortran is a pretty simple looking language and would probably be the closest to Julia in terms of speed and expressiveness, but the writing is on the wall and Fortran's days are numbered. I am not aware of many new packages being developed using it. Other than that, there's languages like Rust and Go but those have ecosystems that are so small, they make Julia's ecosystem look like Python's. I really don't want to spend my time as a grad student writing basic numerical libraries from scratch.

ska 4y ago
> but the writing is on the wall and Fortran's days are numbered. They've been saying this since the late 1980s. Not that I think it's particularly lively, mind.
- eesmith 4y ago
  For fun, I looked for even earlier examples. Here's a couple: From "The Handbook of Computers and Computing", by Arthur H. Seidman and Ivan Flores, 1984, https://archive.org/details/handbookofcomput00seid/page/342/mode/2up?q=dead https://archive.org/details/handbookofcomput00seid/page/342/... : > For many years, it has been popular to predict that FORTRAN soon will be a dead language, to be replaced by a "better" language. Despite the undeniable fact that there are more eloquent, rich and powerful languages available, FORTRAN continues to be used widely and, indeed, is still the most popular programming language for scientific and engineering applications. From NASA Conference Publication 2055, Engineering and Scientific Data Management, 1978,https://archive.org/details/NASA_NTRS_Archive_19780025833/page/n175/mode/2up?q=dead https://archive.org/details/NASA_NTRS_Archive_19780025833/pa... > Margaret White: ... I know FORTRAN is essentially a dead language, but there is a lot of FORTRAN around. Would you care to respond? > Jim Browne: Is there anyone from IBM who would care to respond? The microphone is yours. Who is it? How many times has FORTRAN been buried?
QuadmasterXLII 4y ago
If Julia gets to where it wants to be, pretty soon there will be tasks for which there is no practical alternative to Julia. At this point, people will be in some sense forced to use it, and the floodgates of hate will open (see javascript, matlab, cmake, cpp). Maybe this is the warning trickle?
- culi 4y ago
  You're describing the current state of Python. Julia is kind of a response to Python. Python's become the de facto for ML and dataviz. Two things it's kind of a terrible tool for I'm sure people will become more critical of Julia if it successfully becomes the de facto for those things but there's a big difference in that Julia is very focused on those things whereas Python is trying to be as general purpose as possible
  - culi 4y ago
    Tangent, but tbh I really don't see what the future of Python is. I don't understand why we don't just teach JS or TS as a starting language. It has about as much baggage and is about as easy to understand as Python and is the only language with a comparable ecosystem. Plus you also get to learn the language of the web for free. And now that you have stuff like deno that can run typescript without any messy dependencies. You can just make a quick ts file and write your webscraper or proof of concept and run it in the terminal. At least personally, that replaces my primary use-case for Python and I get to take advantage of TS's amazing type system which really comes in handy when dealing with external APIs. I really don't see a place for Python ml --> Julia, C++, R dataviz --> R, JS/TS beginner-friendly --> JS web --> JS want a backend framework but wanna choose a language that's easy to hire for --> TS, Ruby huge, stable community --> JS/TS quick scripts --> Deno systems --> Rust, C++, Java, Go I'd say it still dominates in scripting/webscraping and creating shareable work (e.g. Jupyter), but I'm just pointing out that at this point it's replaceable in those areas
    - veqq 4y ago
      > I really don't see a place for Python I agree. Around 2008, I was drunk on "the zen of Python", considering myself a Pythonista, writing elegant solutions, making unmaintainable one liners etc. But really Lisp was so much better for that power/speed of development. Eventually (for me) go was so much more powerful, easy to maintain etc. with actual industry usage (seemingly instantly) without any loss in productivity. Python solutions seem no better than maligned JS solutions nowadays - but at least there's TS and efforts to improve it where they can. Indeed, most Python code doesn't seem to be in proper production, but just one of exploratory scripts and pieces strewn about in notebooks. It seems like it could easily lose market share quite quickly.
EFreethought 4y ago
> Fortran's days are numbered. I see what you did there.
quanto 4y ago
> Fortran is a pretty simple looking language and would probably be the closest to Julia in terms of speed and expressiveness, but the writing is on the wall and Fortran's days are numbered. I am not aware of many new packages being developed using it. Nothing could be further from the truth. Fortran, both the language itself and the packages in the ecosystem, is continually developed. There are a few peer-reviewed studies that quantitatively tracked Fortran usages and concluded that Fortran is not just for legacy code -- people actually continue to write new packages precisely for the reasons you mentioned (expressivity, performance)
- CoreyFieldens 4y ago
  Could you link to some of those papers? I would be interested in learning more about the frontier of Fortran development. I recently learned about the LFortran project and while I think it's an interesting project, I feared it would be too late for the language.
  - pjmlp 4y ago
    I guess one thing would be to catch up with all the ISO releases since late 90's. "Modern Fortran" book would be one way of doing it, https://www.manning.com/books/modern-fortran https://www.manning.com/books/modern-fortran
- zorked 4y ago
  Fortran is a case of a language that has grown below the trend of the industry. There are probably more active Fortran projects and developer now than at any point in history. But it became a smaller piece of the much larger pie so people think it's "dead". Same goes with Perl - probably more Perl developers than at its heyday in the 90s but a smaller chunk of the overall picture. Measure by noise levels and anything that doesn't explode seems to be dying.
canadianfella 4y ago
pavon 4y ago
I still prefer Matlab/Octave for numerical exploration, after initially being excited for Julia but later becoming disillusioned with it. I’ve always found Matlab the language to be small and simple, with just a few oddities. The library is where most of the warts accumulated, but I’ve used it long enough to learn them. Performance is much better than python - very fast matrix operations and Java-like speeds for everything else, with comparable startup times.
- enriquto 4y ago
  Octave is almost the perfect tool for numerical computing. Only problem is that loops are slow. Some millionaire out here should pay a "stallion" to write a good JIT octave interpreter and the world would be such a better place!
- martopix 4y ago
  I always hear this "fast matrix operations" argument from Matlab users, but don't they both use BLAS? The difference can only be marginal
stewbrew 4y ago
Java (or kotlin or scala) using arrow, spark, H2O etc.?
prometheon1 4y ago
What about R?
- kaines 4y ago
  And with that, what about data.table?
nigerianbrince 4y ago
It has one based indexing. That's because they're catering to matlab guys, not professional developers.
- trenchgun 4y ago
  That is a ridiculous argument.
  - martopix 4y ago
    It may be ridiculous, but I dislike it deeply and it's one of the reasons I don't want to switch.
    - zorked 4y ago
      I thought so too but it bothers a lot less now that the default style of iteration is "for x in y" instead of looping over indices. In fact I barely think about it. And, yes, for math-y stuff that you are going to be reading off a book, it helps keep things more compatible.
- syockit 4y ago
  It's catering to Fortran developers. Matlab was also catering to Fortran developers (you can read up the history of Matlab). And I wouldn't discount HPC guys as non-developers.
gjadi 4y ago
What about nim for an alternative to Julia? (disclaimer: I've used neither of them)
- deleted 4y ago
  [deleted]
- Moissanite 4y ago
  Nim is more of a Golang-Python hybrid; people like me who learned Python first find the Go syntax offensive and the focus on error handling to be very pessimistic and boring to write, but creating something with Python which you can just compile and distribute is a pain in the ass. Nim solves both problems nicely. Sadly it is too much of a minnow in terms of available packages, e.g. for things like mature cloud SDKs.
- planetis 4y ago
  Nim has a scientific community https://github.com/SciNim https://github.com/SciNim which host many science related packages like plotting and nd arrays.
JonChesterfield 4y ago
Re Fortran - it should be a really sensible choice for writing floating point themed python extensions. It has a usable standardised interface to C (as of... F2003? I think) so generating a stub that glues a fortran module onto python's C API would be straightforward. In ye olden days I wrote the numeric kernels and fortran and distributed them across machines in c++, wouldn't be averse to doing the same thing today. Main argument against that is probably that it's possible to get the same sort of codegen out of C++ and fortran native programmers are somewhat scarce, though I'd bet on it being easier to teach to domain people than julia or c++.
Moissanite 4y ago
I have confidence in Fortran continuing to exist in a useful state for my lifetime and beyond. If Julia had evolved into a community-managed language in the same way that Python has, I would have a positive outlook on it - but I am nervous about the efforts to commercialise it (which mostly just seems to be a case of skimming value off of financial institutions). It is totally understandable why the creators went down this route, but I just wish they had been more idealistic rather than getting on the "everything is a VC-backed company" bandwagon. While I hope Julia continues to grow, I don't trust its longevity enough to put serious effort into using it for myself.
- adgjlsfhk1 4y ago
  Julia is community managed. JuliaHub (previously known as JuliaComputing) does do a bunch of work on Julia, but doesn't "own" the language in the way Google does for Go. There are a number of Julia developers with exactly the same amount of control over Julia as anyone at JuliaHub has at a number of colleges and companies.
  - Moissanite 4y ago
    Sorry, not buying it. Entirely possible it is just a perception problem and not a real one, but the situation is just not comparable to a language like Fortran. Google owning Go is a big downside, but I think people know that going in - also, Google makes no attempt to monetize the language.
    - adgjlsfhk1 4y ago
      The situation is very different from Fortran, but mostly in good ways. The Fortran standards committee's meetings aren't open to the public, and they publish a new version of the standard every 5 years that takes another 5 years for the compilers to catch up to (if they ever support the new version). In the Julia world, you just make a pull request on github, and if it's something that needs a discussion, it gets discussed in a meeting that happens every other week and is open to and takes input from anyone.
Moissanite 4y ago
> Everytime Julia is mentioned on HN, I see a surprising amount of people who dislike the language for whatever reason. I am mostly indifferent to the language (love the Jupyter equivalent tool Pluto, dislike Pkg, love the simplicity of matrix operations, dislike being pushed towards the REPL...) - I am increasingly irked by the observation that in topics like this the Julia community comes out in force to downvote anyone who expresses a negative opinion.
rgavuliak 4y ago
For me it's the fact that it's probably for over 10 years that I've been reading on how amazing Julia is and how it's going to become much bigger than Python in Data Science yet I've never seen any evidence of that. It gets tiring after some time and yet the Julia community keeps making these claims.

ska 4y ago

> but the writing is on the wall and Fortran's days are numbered. They've been saying this since the late 1980s. Not that I think it's particularly lively, mind.

eesmith 4y ago
For fun, I looked for even earlier examples. Here's a couple: From "The Handbook of Computers and Computing", by Arthur H. Seidman and Ivan Flores, 1984, https://archive.org/details/handbookofcomput00seid/page/342/mode/2up?q=dead https://archive.org/details/handbookofcomput00seid/page/342/... : > For many years, it has been popular to predict that FORTRAN soon will be a dead language, to be replaced by a "better" language. Despite the undeniable fact that there are more eloquent, rich and powerful languages available, FORTRAN continues to be used widely and, indeed, is still the most popular programming language for scientific and engineering applications. From NASA Conference Publication 2055, Engineering and Scientific Data Management, 1978,https://archive.org/details/NASA_NTRS_Archive_19780025833/page/n175/mode/2up?q=dead https://archive.org/details/NASA_NTRS_Archive_19780025833/pa... > Margaret White: ... I know FORTRAN is essentially a dead language, but there is a lot of FORTRAN around. Would you care to respond? > Jim Browne: Is there anyone from IBM who would care to respond? The microphone is yours. Who is it? How many times has FORTRAN been buried?

QuadmasterXLII 4y ago

If Julia gets to where it wants to be, pretty soon there will be tasks for which there is no practical alternative to Julia. At this point, people will be in some sense forced to use it, and the floodgates of hate will open (see javascript, matlab, cmake, cpp). Maybe this is the warning trickle?

culi 4y ago
You're describing the current state of Python. Julia is kind of a response to Python. Python's become the de facto for ML and dataviz. Two things it's kind of a terrible tool for I'm sure people will become more critical of Julia if it successfully becomes the de facto for those things but there's a big difference in that Julia is very focused on those things whereas Python is trying to be as general purpose as possible
- culi 4y ago
  Tangent, but tbh I really don't see what the future of Python is. I don't understand why we don't just teach JS or TS as a starting language. It has about as much baggage and is about as easy to understand as Python and is the only language with a comparable ecosystem. Plus you also get to learn the language of the web for free. And now that you have stuff like deno that can run typescript without any messy dependencies. You can just make a quick ts file and write your webscraper or proof of concept and run it in the terminal. At least personally, that replaces my primary use-case for Python and I get to take advantage of TS's amazing type system which really comes in handy when dealing with external APIs. I really don't see a place for Python ml --> Julia, C++, R dataviz --> R, JS/TS beginner-friendly --> JS web --> JS want a backend framework but wanna choose a language that's easy to hire for --> TS, Ruby huge, stable community --> JS/TS quick scripts --> Deno systems --> Rust, C++, Java, Go I'd say it still dominates in scripting/webscraping and creating shareable work (e.g. Jupyter), but I'm just pointing out that at this point it's replaceable in those areas
  - veqq 4y ago
    > I really don't see a place for Python I agree. Around 2008, I was drunk on "the zen of Python", considering myself a Pythonista, writing elegant solutions, making unmaintainable one liners etc. But really Lisp was so much better for that power/speed of development. Eventually (for me) go was so much more powerful, easy to maintain etc. with actual industry usage (seemingly instantly) without any loss in productivity. Python solutions seem no better than maligned JS solutions nowadays - but at least there's TS and efforts to improve it where they can. Indeed, most Python code doesn't seem to be in proper production, but just one of exploratory scripts and pieces strewn about in notebooks. It seems like it could easily lose market share quite quickly.

EFreethought 4y ago

> Fortran's days are numbered. I see what you did there.

quanto 4y ago

> Fortran is a pretty simple looking language and would probably be the closest to Julia in terms of speed and expressiveness, but the writing is on the wall and Fortran's days are numbered. I am not aware of many new packages being developed using it. Nothing could be further from the truth. Fortran, both the language itself and the packages in the ecosystem, is continually developed. There are a few peer-reviewed studies that quantitatively tracked Fortran usages and concluded that Fortran is not just for legacy code -- people actually continue to write new packages precisely for the reasons you mentioned (expressivity, performance)

CoreyFieldens 4y ago
Could you link to some of those papers? I would be interested in learning more about the frontier of Fortran development. I recently learned about the LFortran project and while I think it's an interesting project, I feared it would be too late for the language.
- pjmlp 4y ago
  I guess one thing would be to catch up with all the ISO releases since late 90's. "Modern Fortran" book would be one way of doing it, https://www.manning.com/books/modern-fortran https://www.manning.com/books/modern-fortran
zorked 4y ago
Fortran is a case of a language that has grown below the trend of the industry. There are probably more active Fortran projects and developer now than at any point in history. But it became a smaller piece of the much larger pie so people think it's "dead". Same goes with Perl - probably more Perl developers than at its heyday in the 90s but a smaller chunk of the overall picture. Measure by noise levels and anything that doesn't explode seems to be dying.

canadianfella 4y ago

pavon 4y ago

I still prefer Matlab/Octave for numerical exploration, after initially being excited for Julia but later becoming disillusioned with it. I’ve always found Matlab the language to be small and simple, with just a few oddities. The library is where most of the warts accumulated, but I’ve used it long enough to learn them. Performance is much better than python - very fast matrix operations and Java-like speeds for everything else, with comparable startup times.

enriquto 4y ago
Octave is almost the perfect tool for numerical computing. Only problem is that loops are slow. Some millionaire out here should pay a "stallion" to write a good JIT octave interpreter and the world would be such a better place!
martopix 4y ago
I always hear this "fast matrix operations" argument from Matlab users, but don't they both use BLAS? The difference can only be marginal

stewbrew 4y ago

Java (or kotlin or scala) using arrow, spark, H2O etc.?

prometheon1 4y ago

What about R?

kaines 4y ago
And with that, what about data.table?

nigerianbrince 4y ago

It has one based indexing. That's because they're catering to matlab guys, not professional developers.

trenchgun 4y ago
That is a ridiculous argument.
- martopix 4y ago
  It may be ridiculous, but I dislike it deeply and it's one of the reasons I don't want to switch.
  - zorked 4y ago
    I thought so too but it bothers a lot less now that the default style of iteration is "for x in y" instead of looping over indices. In fact I barely think about it. And, yes, for math-y stuff that you are going to be reading off a book, it helps keep things more compatible.
syockit 4y ago
It's catering to Fortran developers. Matlab was also catering to Fortran developers (you can read up the history of Matlab). And I wouldn't discount HPC guys as non-developers.

gjadi 4y ago

What about nim for an alternative to Julia? (disclaimer: I've used neither of them)

deleted 4y ago
[deleted]
Moissanite 4y ago
Nim is more of a Golang-Python hybrid; people like me who learned Python first find the Go syntax offensive and the focus on error handling to be very pessimistic and boring to write, but creating something with Python which you can just compile and distribute is a pain in the ass. Nim solves both problems nicely. Sadly it is too much of a minnow in terms of available packages, e.g. for things like mature cloud SDKs.
planetis 4y ago
Nim has a scientific community https://github.com/SciNim https://github.com/SciNim which host many science related packages like plotting and nd arrays.

JonChesterfield 4y ago

Re Fortran - it should be a really sensible choice for writing floating point themed python extensions. It has a usable standardised interface to C (as of... F2003? I think) so generating a stub that glues a fortran module onto python's C API would be straightforward. In ye olden days I wrote the numeric kernels and fortran and distributed them across machines in c++, wouldn't be averse to doing the same thing today. Main argument against that is probably that it's possible to get the same sort of codegen out of C++ and fortran native programmers are somewhat scarce, though I'd bet on it being easier to teach to domain people than julia or c++.

Moissanite 4y ago

I have confidence in Fortran continuing to exist in a useful state for my lifetime and beyond. If Julia had evolved into a community-managed language in the same way that Python has, I would have a positive outlook on it - but I am nervous about the efforts to commercialise it (which mostly just seems to be a case of skimming value off of financial institutions). It is totally understandable why the creators went down this route, but I just wish they had been more idealistic rather than getting on the "everything is a VC-backed company" bandwagon. While I hope Julia continues to grow, I don't trust its longevity enough to put serious effort into using it for myself.

adgjlsfhk1 4y ago
Julia is community managed. JuliaHub (previously known as JuliaComputing) does do a bunch of work on Julia, but doesn't "own" the language in the way Google does for Go. There are a number of Julia developers with exactly the same amount of control over Julia as anyone at JuliaHub has at a number of colleges and companies.
- Moissanite 4y ago
  Sorry, not buying it. Entirely possible it is just a perception problem and not a real one, but the situation is just not comparable to a language like Fortran. Google owning Go is a big downside, but I think people know that going in - also, Google makes no attempt to monetize the language.
  - adgjlsfhk1 4y ago
    The situation is very different from Fortran, but mostly in good ways. The Fortran standards committee's meetings aren't open to the public, and they publish a new version of the standard every 5 years that takes another 5 years for the compilers to catch up to (if they ever support the new version). In the Julia world, you just make a pull request on github, and if it's something that needs a discussion, it gets discussed in a meeting that happens every other week and is open to and takes input from anyone.

Moissanite 4y ago

> Everytime Julia is mentioned on HN, I see a surprising amount of people who dislike the language for whatever reason. I am mostly indifferent to the language (love the Jupyter equivalent tool Pluto, dislike Pkg, love the simplicity of matrix operations, dislike being pushed towards the REPL...) - I am increasingly irked by the observation that in topics like this the Julia community comes out in force to downvote anyone who expresses a negative opinion.

rgavuliak 4y ago

For me it's the fact that it's probably for over 10 years that I've been reading on how amazing Julia is and how it's going to become much bigger than Python in Data Science yet I've never seen any evidence of that. It gets tiring after some time and yet the Julia community keeps making these claims.