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Doesn't numpy use a natively compiled Fortran or c library for that? https://github.com/numpy/numpy/blob/main/numpy/core/src/multiarray/arraytypes.c.src https:

Doesn't numpy use a natively compiled Fortran or c library for that? https://github.com/numpy/numpy/blob/main/numpy/core/src/multiarray/arraytypes.c.src https://github.com/numpy/numpy/blob/main/numpy/core/src/mult...

p1esk 4y ago
Why should I care what Numpy is written in? All I see is Python.
- easytiger 4y ago
  Because it is like saying you use a bash script to configure and launch a c++ application and saying it is a bash script. Python is not a high performance language, it isn't meant to be and it's strengths lie elsewhere. One of it's great strengths is interop with c libs. Your assertion was that numpy etc will be faster than something else despite being python: > Try writing a matmul operation in C++ and profile it against the same thing done in Numpy/Pytorch/TensorFlow/Jax. You’ll be surprised. I mean TensorFlow is c++/cuda!
  - p1esk 4y ago
    I mean TensorFlow is c++/cuda! No. When I write Tensorflow code I write Python. I don’t care what TF does under the hood just like I don’t care that Python itself might be implemented in C. Though I got to say TF is quite ugly and not a good example of Python’s user friendliness. But that’s another topic.
    - easytiger 4y ago
      As long as you know python is doing little to no computational work.
      - necovek 4y ago
        That's a known and widely publicised trait of Python. In the early days, Python tutorial warned against adding to strings by doing "+" even though it works because that performed a new allocation and string copy. What you were asked to do was use fast, optimized C-based primitives like "\n".join(list_of_strings) etc. Basically, Python is an "ergonomic" language built in C. Saying how something is implemented in C at the lower level is pointless, because all of Python is. Yes, doing loops over large data sets in Python is slow. Which is why it provides itertools (again, C-based functions) in stdlib.
    - gpderetta 4y ago
      But as soon as you step out of the optimized path, the performance cliff is huge. Also you are forced to work in non idiomatic awkward meta-languages.

p1esk 4y ago

Why should I care what Numpy is written in? All I see is Python.

easytiger 4y ago
Because it is like saying you use a bash script to configure and launch a c++ application and saying it is a bash script. Python is not a high performance language, it isn't meant to be and it's strengths lie elsewhere. One of it's great strengths is interop with c libs. Your assertion was that numpy etc will be faster than something else despite being python: > Try writing a matmul operation in C++ and profile it against the same thing done in Numpy/Pytorch/TensorFlow/Jax. You’ll be surprised. I mean TensorFlow is c++/cuda!
- p1esk 4y ago
  I mean TensorFlow is c++/cuda! No. When I write Tensorflow code I write Python. I don’t care what TF does under the hood just like I don’t care that Python itself might be implemented in C. Though I got to say TF is quite ugly and not a good example of Python’s user friendliness. But that’s another topic.
  - easytiger 4y ago
    As long as you know python is doing little to no computational work.
    - necovek 4y ago
      That's a known and widely publicised trait of Python. In the early days, Python tutorial warned against adding to strings by doing "+" even though it works because that performed a new allocation and string copy. What you were asked to do was use fast, optimized C-based primitives like "\n".join(list_of_strings) etc. Basically, Python is an "ergonomic" language built in C. Saying how something is implemented in C at the lower level is pointless, because all of Python is. Yes, doing loops over large data sets in Python is slow. Which is why it provides itertools (again, C-based functions) in stdlib.
  - gpderetta 4y ago
    But as soon as you step out of the optimized path, the performance cliff is huge. Also you are forced to work in non idiomatic awkward meta-languages.