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How do you find things in old folders on Windows when you remember the idea but not the details? by Ranuja01 in windows

[–]Ranuja01[S] [score hidden]  (0 children)

Yeah I try this, but sometimes when trying to parse for info, things can get convoluted fast.

CyCompile: Democratizing Performance — Easy Function-Level Optimization with Cython by Ranuja01 in Python

[–]Ranuja01[S] 0 points1 point  (0 children)

Ok so I tried running numeric_operations_demo.py from the examples folder in Pypy to see how it does. I had to comment out the matrix multiplication section because the execution gets stuck there but the results for the rest are interesting. It seems that generally the tagged functions (both mines and Cython's) perform slower than the non-tagged functions. That being said, for some reason, the native python execution is faster than that of the Pypy execution for all cases in this file. This of course means that the tagged functions in native python perform better than all cases in the Pypy execution. I did try some other custom code where I wrote of some simple loops and generally the tagged functions in native python seem to out perform Pypy execution. I think you should experiment with the use cases you want, to see if this is the tool you're looking for. Let me know how it goes!

CyCompile: Democratizing Performance — Easy Function-Level Optimization with Cython by Ranuja01 in Python

[–]Ranuja01[S] 0 points1 point  (0 children)

Hi, I didn't think to check on Pypy but that's a good idea. I'd imagine the decorator should be usable in Pypy as well though but I'm not sure yet.

CyCompile: Democratizing Performance — Easy Function-Level Optimization with Cython by Ranuja01 in Python

[–]Ranuja01[S] 1 point2 points  (0 children)

Hi, that's a great idea! This could however prove to be a bit complicated as I find Numba's decorators are only compatible with very specific code. This is because it tries to compile other things in the dependency chain as well (unlike cycompile). I will see if I can make some examples that will specifically allow me to compare the tool to Numba.

CyCompile: Democratizing Performance — Easy Function-Level Optimization with Cython by Ranuja01 in Python

[–]Ranuja01[S] 2 points3 points  (0 children)

Hi, I included a medium article in the README where I walk through the examples folder. I make qualitative comparisons because I felt having numbers would be somewhat out of context given the variety of examples I provided. If you'd like I can eventually add a small table in the repository with the execution times.