5 ms·

Ah, just the right time to publish about numpy - right when everyone is moving over to Julia because of numpy's warts.

microcow 6y ago
I don't think that's accurate: https://trends.google.com/trends/explore?date=today%205-y&geo=US&q=%2Fm%2F0j3djl7,%2Fm%2F021plb https://trends.google.com/trends/explore?date=today%205-y&ge...
- throrthaway 6y ago
  Relieved to know I can still trust HNers to always take hyperbolic statements literally
  - ALittleLight 6y ago
    Not always.
hyperbovine 6y ago
*For certain definitions of everyone.
- konjin 6y ago
  Me on a Thursday afternoon when I'm bored.
alanbernstein 6y ago
I'm interested in Julia, but if numpy has warts, I suppose Julia has not yet had time to even grow its skin.
- Fishysoup 6y ago
  Theoretically Julia is better for scientific computing, the only issue is its package ecosystem isn't as mature as Python's. But it's growing incredibly fast and there have already been libraries available for a few years that would be really impractical to write and maintain at such a level in C++ for Python. I assume that for science at least Julia will catch on a lot.
  - BeetleB 6y ago
    > Theoretically Julia is better for scientific computing, the only issue is its package ecosystem isn't as mature as Python's. That's not a small issue. The ecosystem is probably the reason people choose NumPy over MATLAB, for example. NumPy is not inherently superior to MATLAB, and most academicians that adopted NumPy in the 2000's already had a MATLAB license, so cost was not a concern either.
    - srean 6y ago
      Well that could have been said (and was said) about Numpy/Scipy when it started, "oh R has so many more packages, what numpy can do I can do in MATLAB ...", yet here we are.
      - BeetleB 6y ago
        You probably don't realize it, you are agreeing with me :-)
        srean 6y ago
        It depends on the definition of 'people'. There were many who adopted numpy much before the ecosystem had had time to catchup. But I would readily concede that Dr. Jones @national_lab didnt at that time, in fact he probably hasnt even now. I do disagree strongly with the opinion that Numpy is no better than MATLAB :). MATLAB has adopted some Numpy features after Numpy came out (broadcasting for example) but Numpy offered some genuine and unique advantages, both technical (broadcasting, no need for a MEX compiler that I have to pay through my nose for, not restricted to weird naming conventions, nature of parameter passing, ...) and legal.
      - edgyquant 6y ago
        I just don't like the BASIC derived syntax of Julia (and Ruby.) I wish there was a language that was typed, had python like classes, subroutines and lambdas but JS like anonymous functions that was fast like Julia or at least close to numpy in number crunching without needing a module written in C.
sndean 6y ago
Interestingly, one of the Julia creators is one of the named reviewers.
- BeetleB 6y ago
  Julia and the NumPy/SciPy community get along pretty well (or at least they did while I was still doing this stuff). In fact, I may have first heard of Julia when someone presented it at PyCon.
  - mumblemumble 6y ago
    You can roughly divide people with strong opinions on Julia vis-a-vis Python into two groups: People who earnestly want them both to win, and people who are largely just watching from the sidelines.
sradman 6y ago
Julia is a fine platform for data science but so are Python/NumPY, R, and Matlab. Few of us have the luxury of building greenfield projects that are independent of our previous choices and real-world constraints. Understanding NumPY within this larger context is important, even if you are committed to the Julia ecosystem.

I don't think that's accurate: https://trends.google.com/trends/explore?date=today%205-y&geo=US&q=%2Fm%2F0j3djl7,%2Fm%2F021plb https://trends.google.com/trends/explore?date=today%205-y&ge...

throrthaway 6y ago
Relieved to know I can still trust HNers to always take hyperbolic statements literally
- ALittleLight 6y ago
  Not always.

hyperbovine 6y ago

*For certain definitions of everyone.

konjin 6y ago
Me on a Thursday afternoon when I'm bored.

alanbernstein 6y ago

I'm interested in Julia, but if numpy has warts, I suppose Julia has not yet had time to even grow its skin.

Fishysoup 6y ago
Theoretically Julia is better for scientific computing, the only issue is its package ecosystem isn't as mature as Python's. But it's growing incredibly fast and there have already been libraries available for a few years that would be really impractical to write and maintain at such a level in C++ for Python. I assume that for science at least Julia will catch on a lot.
- BeetleB 6y ago
  > Theoretically Julia is better for scientific computing, the only issue is its package ecosystem isn't as mature as Python's. That's not a small issue. The ecosystem is probably the reason people choose NumPy over MATLAB, for example. NumPy is not inherently superior to MATLAB, and most academicians that adopted NumPy in the 2000's already had a MATLAB license, so cost was not a concern either.
  - srean 6y ago
    Well that could have been said (and was said) about Numpy/Scipy when it started, "oh R has so many more packages, what numpy can do I can do in MATLAB ...", yet here we are.
    - BeetleB 6y ago
      You probably don't realize it, you are agreeing with me :-)
      - srean 6y ago
        It depends on the definition of 'people'. There were many who adopted numpy much before the ecosystem had had time to catchup. But I would readily concede that Dr. Jones @national_lab didnt at that time, in fact he probably hasnt even now. I do disagree strongly with the opinion that Numpy is no better than MATLAB :). MATLAB has adopted some Numpy features after Numpy came out (broadcasting for example) but Numpy offered some genuine and unique advantages, both technical (broadcasting, no need for a MEX compiler that I have to pay through my nose for, not restricted to weird naming conventions, nature of parameter passing, ...) and legal.
    - edgyquant 6y ago
      I just don't like the BASIC derived syntax of Julia (and Ruby.) I wish there was a language that was typed, had python like classes, subroutines and lambdas but JS like anonymous functions that was fast like Julia or at least close to numpy in number crunching without needing a module written in C.

sndean 6y ago

Interestingly, one of the Julia creators is one of the named reviewers.

BeetleB 6y ago
Julia and the NumPy/SciPy community get along pretty well (or at least they did while I was still doing this stuff). In fact, I may have first heard of Julia when someone presented it at PyCon.
- mumblemumble 6y ago
  You can roughly divide people with strong opinions on Julia vis-a-vis Python into two groups: People who earnestly want them both to win, and people who are largely just watching from the sidelines.

sradman 6y ago

Julia is a fine platform for data science but so are Python/NumPY, R, and Matlab. Few of us have the luxury of building greenfield projects that are independent of our previous choices and real-world constraints. Understanding NumPY within this larger context is important, even if you are committed to the Julia ecosystem.