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Why isn't some big company putting its weight behind Julia considering what it has to offer in the field of data science? I just don't get why it's still playin

by cutler 7y ago

Why isn't some big company putting its weight behind Julia considering what it has to offer in the field of data science? I just don't get why it's still playing second fiddle to Python. Tech is full of inertia, paradoxically.

6thaccount2 7y ago
I think some finance groups are probably putting in some donations if I had to guess.
- cutler 7y ago
  That's not the same as Google's support for Python, Go and Kotlin or Microsoft's support for Typescript and maybe soon Rust. I would have thought the case for supporting Julia was very strong considering Python's performance and concurrency problems.
  - 6thaccount2 7y ago
    Python's performance is less of an issue when you use libraries like Numpy that are basically running optimized C code. Depending on what you're doing, Python is usually great at performance where the time it saves the user writing code is more valuable than the performance itself (a lot of exploratory scientific research).
    - DNF2 7y ago
      Numpy is great if you can vectorize your code in a straightforward manner. But when you start doing anything non-standard it becomes difficult. I can tell you that programmer productivity can plummet drastically when you need to get everything into vectorized form. Also, custom classes and types do not vectorize well at all.
      - 6thaccount2 7y ago
        Agreed.
tavert 7y ago
Since I stopped using Julia I've kept an eye on the HN Who's Hiring threads for mentions of it. I see one consistent listing from Gambit Research, and occasionally one or two others that come and go. Anecdotal to only sample from HN and not larger listing sites like Indeed etc, but it reinforces my skepticism about industry adoption.
- j88439h84 7y ago
  Why'd you stop using Julia?
  - tavert 7y ago
    1. Carelessness, lack of professionalism, and instability from many of the core language and package developers 2. Over concentration of the main contributors within the same startup that has a questionable business model and long-term prospects 3. Language issues that limit the desirability of Julia for use in larger projects
    - j88439h84 7y ago
      What language did you land on after leaving?
      - tavert 7y ago
        Mix of C++ and Python. They're both kind of awful in their own way, but well-supported and stable.
vmchale 7y ago
> Why isn't some big company putting its weight behind Julia considering what it has to offer in the field of data science? Same as J > Tech is full of inertia, paradoxically. I don't think it's paradoxical. Novelty is essential in academia, but that is not the case in industry.
- deleted 7y ago
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parsimo2010 7y ago
Julia has raised millions of dollars in funding, and includes some pretty big names- National Science Foundation, DARPA, and a pretty big chunk from venture capital as well. They don't have a benevolent sponsor like Python has enjoyed from Google, but they're doing alright. They aren't as big as Python because Python has been around for nearly 30 years. Julia is just a baby compared to that. As it grows it will increase it's share. It may not ever surpass Python in terms of raw users, because Julia is focused on numerical computing, but Python is more general purpose.
- Recurecur 7y ago
  > It may not ever surpass Python in terms of raw users, because Julia is focused on numerical computing, but Python is more general purpose. That isn't the case. Julia's primary focus is scientific/numeric, but it's also general purpose. Take a look at Julia Robotics, for instance: http://www.juliarobotics.org/ http://www.juliarobotics.org/
  - parsimo2010 7y ago
    Julia is focused on numerical computing, not exclusively for numerical computing. Note that Julia has built in n-D arrays and useful operations, while Python requires the numpy package (or other similar package) for them. Julia's Matlab-esque syntax makes it clear where its priorities lie. You could call any Turing-complete language with I/O a general purpose language, but some are clearly designed for certain tasks.
    - cutler 7y ago
      Julia will be general purpose when it has its own popular web framework. To be an all-round language it must not be second rate with text processing for the sake of being excellent with math.
      - byt143 7y ago
        http://genieframework.com/ http://genieframework.com/
StreamBright 7y ago
Because almost every business problem is already solved in Python (meaning in C++/C/Fortran with a Python interface) and most companies do not want to re-implement those libraries just for the sake of using a new language.

by cutler 7y ago

6thaccount2 7y ago

I think some finance groups are probably putting in some donations if I had to guess.

cutler 7y ago
That's not the same as Google's support for Python, Go and Kotlin or Microsoft's support for Typescript and maybe soon Rust. I would have thought the case for supporting Julia was very strong considering Python's performance and concurrency problems.
- 6thaccount2 7y ago
  Python's performance is less of an issue when you use libraries like Numpy that are basically running optimized C code. Depending on what you're doing, Python is usually great at performance where the time it saves the user writing code is more valuable than the performance itself (a lot of exploratory scientific research).
  - DNF2 7y ago
    Numpy is great if you can vectorize your code in a straightforward manner. But when you start doing anything non-standard it becomes difficult. I can tell you that programmer productivity can plummet drastically when you need to get everything into vectorized form. Also, custom classes and types do not vectorize well at all.
    - 6thaccount2 7y ago
      Agreed.

tavert 7y ago

Since I stopped using Julia I've kept an eye on the HN Who's Hiring threads for mentions of it. I see one consistent listing from Gambit Research, and occasionally one or two others that come and go. Anecdotal to only sample from HN and not larger listing sites like Indeed etc, but it reinforces my skepticism about industry adoption.

j88439h84 7y ago
Why'd you stop using Julia?
- tavert 7y ago
  1. Carelessness, lack of professionalism, and instability from many of the core language and package developers 2. Over concentration of the main contributors within the same startup that has a questionable business model and long-term prospects 3. Language issues that limit the desirability of Julia for use in larger projects
  - j88439h84 7y ago
    What language did you land on after leaving?
    - tavert 7y ago
      Mix of C++ and Python. They're both kind of awful in their own way, but well-supported and stable.

vmchale 7y ago

> Why isn't some big company putting its weight behind Julia considering what it has to offer in the field of data science? Same as J > Tech is full of inertia, paradoxically. I don't think it's paradoxical. Novelty is essential in academia, but that is not the case in industry.

deleted 7y ago
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deleted 7y ago

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parsimo2010 7y ago

Julia has raised millions of dollars in funding, and includes some pretty big names- National Science Foundation, DARPA, and a pretty big chunk from venture capital as well. They don't have a benevolent sponsor like Python has enjoyed from Google, but they're doing alright. They aren't as big as Python because Python has been around for nearly 30 years. Julia is just a baby compared to that. As it grows it will increase it's share. It may not ever surpass Python in terms of raw users, because Julia is focused on numerical computing, but Python is more general purpose.

Recurecur 7y ago
> It may not ever surpass Python in terms of raw users, because Julia is focused on numerical computing, but Python is more general purpose. That isn't the case. Julia's primary focus is scientific/numeric, but it's also general purpose. Take a look at Julia Robotics, for instance: http://www.juliarobotics.org/ http://www.juliarobotics.org/
- parsimo2010 7y ago
  Julia is focused on numerical computing, not exclusively for numerical computing. Note that Julia has built in n-D arrays and useful operations, while Python requires the numpy package (or other similar package) for them. Julia's Matlab-esque syntax makes it clear where its priorities lie. You could call any Turing-complete language with I/O a general purpose language, but some are clearly designed for certain tasks.
  - cutler 7y ago
    Julia will be general purpose when it has its own popular web framework. To be an all-round language it must not be second rate with text processing for the sake of being excellent with math.
    - byt143 7y ago
      http://genieframework.com/ http://genieframework.com/

StreamBright 7y ago

Because almost every business problem is already solved in Python (meaning in C++/C/Fortran with a Python interface) and most companies do not want to re-implement those libraries just for the sake of using a new language.