6 ms·

> S6 was aiming to do for Python what V8 did for Javascript > Python is slow, and a lot of researchers use Python as their primary interface to build models.

> S6 was aiming to do for Python what V8 did for Javascript > Python is slow, and a lot of researchers use Python as their primary interface to build models. Why not just build models in JS?

zem 4y ago
python has a large ecosystem of scientific, mathematical, and machine learning libraries. there is no real replacement for that in the js world.
- brrrrrm 4y ago
  Do you think this will start to change? I often see posts on this site bemoaning the performance of Python (often referencing the order of magnitude performance differences of similarly dynamic languages like JavaScript). I'm hopeful that honest efforts to port over useful bits of the scientific/mathematical ecosystem to JS will start to take off someday soon.
  - Terretta 4y ago
    Have you considered why CS101 and data scientists may be adopting Python over JS? And have a look at, say, Julia.
  - zem 4y ago
    I'm betting on julia as the replacement personally, it seems to be attracting a growing fraction of the scientific community.
    - deleted 4y ago
      [deleted]
- pjmlp 4y ago
  Other than the fact those libraries aren't written in Python, they are only bindings to native code libraries that can be used from any language with FFI.
  - qsort 4y ago
    It's massive work to reimplement say, Numpy and Pandas in javascript, in part because the language is different, and in part because the API is huge. It's technically possible, but not something that's available right now (nor there seems to be any real interest/serious effort going on). It's more likely that something like Julia ends up replacing Python, even though I still believe it's a low probability thing.
    - brrrrrm 4y ago
      More work than JIT compiling Python?
      - qsort 4y ago
        There's over 200k loc of Python in numpy alone, so yeah, it's the same order of magnitude of work to end up with a credible alternative.
        brrrrrm 4y ago
        hmm, there's 1.6M lines of C++ in V8. And that's not a collection of simple mathematical functions - it's an entire compiler with many interdependent components. I think there's this weird but popular idea that people think it's easier to build a fast language than port a couple hundred independent functions.
  - cdavid 4y ago
    This is a common trope that does not really match reality. Pytorch readme quote pytorch is not a Python binding into a monolithic C++ framework. It is built to be deeply integrated into Python. could be applied to many key libraries of this ecosystem. For sure, a lot of those libraries rely on tons of compiled code in C/C++/Fortran, but the python code is not mere wrapping on top of those libs. And most of the compiled code inside those repos has a lot of internal logic as well. Some examples (using cloc on git main branch, as tokei does not understand cython): * sklearn: 150 kloc python, ~10kloc cython, not much of other languages * NumPy: 200kloc python, 350kloc for C/C++ * scipy: 800 kloc C, 200 kloc python (the 800kloc surprised me and it looks like a lot of it is C generated code from cython)
ipsum2 4y ago
To those downvoting brrrrm, he's asking in earnest and is working on his own JS ML library that looks very promising.
yyyk 4y ago
>Why not just build models in JS? Because ML/Data source has particular numerical requirements. JavaScript has poor mathematical defaults and still misses useful datatypes like float16*. * Yes, this can emulated. Emulation is slow. You've gained some speed and then paid it back for emulation.
- yyyk 4y ago
  Correction: Data science.
- brrrrrm 4y ago
  Non-trivial numerics are done through FFI in python. Python doesn’t support fp16, but a native library behind it does. The exact same premise applies to JavaScript
  - yyyk 4y ago
    If you're doing all the interesting bits via FFI, Javascript JIT does not give you much aside from a lot of extra work. Why should we reimplement the glue code for marginal improvements? If you are doing stuff without FFI, than JS's inadequacies do matter. IMHO, you can't beat Python for ML by being just a slightly faster Python (there aren't enough newcomers for that, the Python ecosystem is enough to assimilate them before other languages can). You need to offer something more significant to make migration worthwhile. Julia tries to do that by allowing to implement the main stack in Julia, if it had JS speed and DX it would have eaten Python's lunch.
    - brrrrrm 4y ago
      err, how is JS inadequate for that stuff? Python does not have fp16 support natively, neither does JS. It also doesn't have fp32, int64, int8, int32, uint32 etc. JavaScript does? JavaScript is 43 times faster for this random workload: (env) bwasti@bwasti-mbp ~ % time python bleh.py python bleh.py 9.27s user 0.06s system 99% cpu 9.352 total (env) bwasti@bwasti-mbp ~ % time bun bleh.ts bun bleh.ts 0.16s user 0.02s system 83% cpu 0.216 total (env) bwasti@bwasti-mbp ~ % cat bleh.py import random v = [0 for i in range(1000000)] for i in range(int(1e8)): v[i % len(v)] += 1 (env) bwasti@bwasti-mbp ~ % cat bleh.ts const v = new Float32Array(1000000) for (let i = 0; i < 1e8; ++i) { v[i % v.length] += 1 } Try as many as you want and you'll see that it just blows python out of the water

> S6 was aiming to do for Python what V8 did for Javascript > Python is slow, and a lot of researchers use Python as their primary interface to build models. Why not just build models in JS?

zem 4y ago

python has a large ecosystem of scientific, mathematical, and machine learning libraries. there is no real replacement for that in the js world.

brrrrrm 4y ago
Do you think this will start to change? I often see posts on this site bemoaning the performance of Python (often referencing the order of magnitude performance differences of similarly dynamic languages like JavaScript). I'm hopeful that honest efforts to port over useful bits of the scientific/mathematical ecosystem to JS will start to take off someday soon.
- Terretta 4y ago
  Have you considered why CS101 and data scientists may be adopting Python over JS? And have a look at, say, Julia.
- zem 4y ago
  I'm betting on julia as the replacement personally, it seems to be attracting a growing fraction of the scientific community.
  - deleted 4y ago
    [deleted]
pjmlp 4y ago
Other than the fact those libraries aren't written in Python, they are only bindings to native code libraries that can be used from any language with FFI.
- qsort 4y ago
  It's massive work to reimplement say, Numpy and Pandas in javascript, in part because the language is different, and in part because the API is huge. It's technically possible, but not something that's available right now (nor there seems to be any real interest/serious effort going on). It's more likely that something like Julia ends up replacing Python, even though I still believe it's a low probability thing.
  - brrrrrm 4y ago
    More work than JIT compiling Python?
    - qsort 4y ago
      There's over 200k loc of Python in numpy alone, so yeah, it's the same order of magnitude of work to end up with a credible alternative.
      - brrrrrm 4y ago
        hmm, there's 1.6M lines of C++ in V8. And that's not a collection of simple mathematical functions - it's an entire compiler with many interdependent components. I think there's this weird but popular idea that people think it's easier to build a fast language than port a couple hundred independent functions.
- cdavid 4y ago
  This is a common trope that does not really match reality. Pytorch readme quote pytorch is not a Python binding into a monolithic C++ framework. It is built to be deeply integrated into Python. could be applied to many key libraries of this ecosystem. For sure, a lot of those libraries rely on tons of compiled code in C/C++/Fortran, but the python code is not mere wrapping on top of those libs. And most of the compiled code inside those repos has a lot of internal logic as well. Some examples (using cloc on git main branch, as tokei does not understand cython): * sklearn: 150 kloc python, ~10kloc cython, not much of other languages * NumPy: 200kloc python, 350kloc for C/C++ * scipy: 800 kloc C, 200 kloc python (the 800kloc surprised me and it looks like a lot of it is C generated code from cython)

ipsum2 4y ago

To those downvoting brrrrm, he's asking in earnest and is working on his own JS ML library that looks very promising.

yyyk 4y ago

>Why not just build models in JS? Because ML/Data source has particular numerical requirements. JavaScript has poor mathematical defaults and still misses useful datatypes like float16*. * Yes, this can emulated. Emulation is slow. You've gained some speed and then paid it back for emulation.

yyyk 4y ago
Correction: Data science.
brrrrrm 4y ago
Non-trivial numerics are done through FFI in python. Python doesn’t support fp16, but a native library behind it does. The exact same premise applies to JavaScript
- yyyk 4y ago
  If you're doing all the interesting bits via FFI, Javascript JIT does not give you much aside from a lot of extra work. Why should we reimplement the glue code for marginal improvements? If you are doing stuff without FFI, than JS's inadequacies do matter. IMHO, you can't beat Python for ML by being just a slightly faster Python (there aren't enough newcomers for that, the Python ecosystem is enough to assimilate them before other languages can). You need to offer something more significant to make migration worthwhile. Julia tries to do that by allowing to implement the main stack in Julia, if it had JS speed and DX it would have eaten Python's lunch.
  - brrrrrm 4y ago
    err, how is JS inadequate for that stuff? Python does not have fp16 support natively, neither does JS. It also doesn't have fp32, int64, int8, int32, uint32 etc. JavaScript does? JavaScript is 43 times faster for this random workload: (env) bwasti@bwasti-mbp ~ % time python bleh.py python bleh.py 9.27s user 0.06s system 99% cpu 9.352 total (env) bwasti@bwasti-mbp ~ % time bun bleh.ts bun bleh.ts 0.16s user 0.02s system 83% cpu 0.216 total (env) bwasti@bwasti-mbp ~ % cat bleh.py import random v = [0 for i in range(1000000)] for i in range(int(1e8)): v[i % len(v)] += 1 (env) bwasti@bwasti-mbp ~ % cat bleh.ts const v = new Float32Array(1000000) for (let i = 0; i < 1e8; ++i) { v[i % v.length] += 1 } Try as many as you want and you'll see that it just blows python out of the water