3 ms·

> but with FANTASTIC libraries written in C _and FORTRAN_ ftfy - it's the only way a tragically slow language like Python can keep up. Edit: didn't forget FOR

> but with FANTASTIC libraries written in C _and FORTRAN_ ftfy - it's the only way a tragically slow language like Python can keep up. Edit: didn't forget FORTRAN

dagw 4y ago
libraries written in C That is simply not true. Even libraries like numpy, scipy and scikit-learn are majority python code.
- deafpolygon 4y ago
  Majority python code, being ~60% is mostly wrapper code, with the slowest parts (the parts that matter) written in C. https://stackoverflow.com/questions/1825857/how-much-of-numpy-and-scipy-is-in-c https://stackoverflow.com/questions/1825857/how-much-of-nump...
ihatepython 4y ago
Don't forget about FORTRAN
grog_tremor 4y ago
Eh, you massively overestimate the importance of performance. For the vast majority of use cases, performance just isn't a priority. Doubly so for Python, that shines for simple automation, command line applications, and perhaps some serveless computing. Being easy to write, having a good ecosystem of libraries, and being widely known is typically good enough. I wouldn't use Python to write a robust backend server side application, mostly because the language doesn't lend itself well for it.
- deafpolygon 4y ago
  Eh, you make incorrect assumptions about me. I'm stating a fact why Python is used - the data science ecosystem in Python thrives because of well-written libraries _written in C_ under the hood AND an easy-to-use language that writes like pseudocode. If it was too slow, we'd be doing all of this in Java, the C# or maybe doing it in C/Fortran. But because of some early design decisions (Guido being on the matrix-sig helped), the history behind Numeric/Numarray and finally NumPy and SciPy being based on those efforts allowed it to thrive.
  - grog_tremor 4y ago
    > it's the only way a tragically slow language like Python can keep up. Those were your words, not mine. I need not make any assumptions. I just replied listing use cases where Python shine due to its strengths, performance being mostly irrelevant. I didn't even mention data science. And although it's beyond the point, if I was to use Python, why should I care in which language a library was written? If the language allows libraries written in other languages, this is actually a nice feature.
    - UncleEntity 4y ago
      > If the language allows libraries written in other languages, this is actually a nice feature. That’s actually my primary use case for python, playing with C/C++ libraries in a repl because they don’t natively have one. Sure, it takes work to wrap a library but that’s something I enjoy doing.
mort96 4y ago
Does it matter?
- UncleEntity 4y ago
  Because it’s proof, PROOF!!!, that python is inferior to their favorite language. Just wait until they learn the python interpreter is written in C… <grabs popcorn>

> but with FANTASTIC libraries written in C _and FORTRAN_ ftfy - it's the only way a tragically slow language like Python can keep up. Edit: didn't forget FORTRAN

dagw 4y ago

libraries written in C That is simply not true. Even libraries like numpy, scipy and scikit-learn are majority python code.

deafpolygon 4y ago
Majority python code, being ~60% is mostly wrapper code, with the slowest parts (the parts that matter) written in C. https://stackoverflow.com/questions/1825857/how-much-of-numpy-and-scipy-is-in-c https://stackoverflow.com/questions/1825857/how-much-of-nump...

ihatepython 4y ago

Don't forget about FORTRAN

grog_tremor 4y ago

Eh, you massively overestimate the importance of performance. For the vast majority of use cases, performance just isn't a priority. Doubly so for Python, that shines for simple automation, command line applications, and perhaps some serveless computing. Being easy to write, having a good ecosystem of libraries, and being widely known is typically good enough. I wouldn't use Python to write a robust backend server side application, mostly because the language doesn't lend itself well for it.

deafpolygon 4y ago
Eh, you make incorrect assumptions about me. I'm stating a fact why Python is used - the data science ecosystem in Python thrives because of well-written libraries _written in C_ under the hood AND an easy-to-use language that writes like pseudocode. If it was too slow, we'd be doing all of this in Java, the C# or maybe doing it in C/Fortran. But because of some early design decisions (Guido being on the matrix-sig helped), the history behind Numeric/Numarray and finally NumPy and SciPy being based on those efforts allowed it to thrive.
- grog_tremor 4y ago
  > it's the only way a tragically slow language like Python can keep up. Those were your words, not mine. I need not make any assumptions. I just replied listing use cases where Python shine due to its strengths, performance being mostly irrelevant. I didn't even mention data science. And although it's beyond the point, if I was to use Python, why should I care in which language a library was written? If the language allows libraries written in other languages, this is actually a nice feature.
  - UncleEntity 4y ago
    > If the language allows libraries written in other languages, this is actually a nice feature. That’s actually my primary use case for python, playing with C/C++ libraries in a repl because they don’t natively have one. Sure, it takes work to wrap a library but that’s something I enjoy doing.

mort96 4y ago

Does it matter?

UncleEntity 4y ago
Because it’s proof, PROOF!!!, that python is inferior to their favorite language. Just wait until they learn the python interpreter is written in C… <grabs popcorn>