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I don't see JS as less powerful than Python for data science, it's faster than Python, or can use bindings just like Python. JS is maybe less commonly used than

I don't see JS as less powerful than Python for data science, it's faster than Python, or can use bindings just like Python. JS is maybe less commonly used than Python in data science nowadays, but I wouldn't be surprised if this changes in next years. There are equivalent libs like tensorflow-core, there are native features like BigInt, and there are libs for 64bits floats (decimal.js, big.js). I'd be glad to spend some time converting Scikit-learn into JS and also show you how expressive JS actually is, if you show me some Python code, I'll translate it

uryga 6y ago
> libs for 64bits floats (decimal.js, big.js) both of those libraries are for arbitrary precision decimals, not floats.
- __jem 6y ago
  If it's arbitrary precision, what's the difference, besides slightly more bookkeeping on your end?
danpalmer 6y ago
The fact that the number support isn’t part of the language is Linda the problem though. When you’re writing data science code, the value is in the answer more than the process of getting to that answer. Anything that complicates that gets in the way. This is why things like Pandas are so popular despite having some questionable engineering. Using a library for big number support, having to get that to play nicely with other libraries, it all goes against the aims. Now for data engineering it’s very different. I wouldn’t choose JS myself, but it’s a much more reasonable choice. For engineering the process by which you get the answer matters far more - is it scalable, testable, repeatable, etc. Having to use a library for big number support is fine. It’s two very different ways of working and I’m still fairly convinced that JS is not conducive to the former.
tyingq 6y ago
>it's faster than Python Is that generally true for data science type tasks, though, where the "fast" in python is really numpy, pandas, etc? >or can use bindings just like Python But there's not really anything like numpy/pandas for it to bind to at the moment, is there? Meaning anything as broad in functionality, fast, mature, etc.

uryga 6y ago

> libs for 64bits floats (decimal.js, big.js) both of those libraries are for arbitrary precision decimals, not floats.

__jem 6y ago
If it's arbitrary precision, what's the difference, besides slightly more bookkeeping on your end?

danpalmer 6y ago

The fact that the number support isn’t part of the language is Linda the problem though. When you’re writing data science code, the value is in the answer more than the process of getting to that answer. Anything that complicates that gets in the way. This is why things like Pandas are so popular despite having some questionable engineering. Using a library for big number support, having to get that to play nicely with other libraries, it all goes against the aims. Now for data engineering it’s very different. I wouldn’t choose JS myself, but it’s a much more reasonable choice. For engineering the process by which you get the answer matters far more - is it scalable, testable, repeatable, etc. Having to use a library for big number support is fine. It’s two very different ways of working and I’m still fairly convinced that JS is not conducive to the former.

tyingq 6y ago

>it's faster than Python Is that generally true for data science type tasks, though, where the "fast" in python is really numpy, pandas, etc? >or can use bindings just like Python But there's not really anything like numpy/pandas for it to bind to at the moment, is there? Meaning anything as broad in functionality, fast, mature, etc.