mpz | Music player for big local collections | Audio Utils library

The bottleneck of my code is the repeated calling of pow(base,exponent,modulus) for very large integers (numpy does not support such large integers, about 100 to 256 bits). However, my exponent and modulus is always the same. Could I somehow utilize this to speed the computation up with a custom function? I tried to define a function as seen below (function below is for general modulus and exponent).

However, even if I hardcode every operation without the while-loop and if-statements for a fixed exponent and modulus, it is slower than pow.

In the second line before the out statement the answer is -1, buy due to my print it should be the answer: 618970019642690137449562111, which is 2**89-1, instead i'm getting -1

I can't for the life of me figure out what the bug is, could someone enlighten me? Why am i getting -1 there instead of 618970019642690137449562111

Here is the code, the error with the "-1" is two lines right before the "[Out 778:]" statement ( you have to scroll right to see it). It should keep climbing the powers of 2 tree minus 1 but it gives the answer -1 which is incorrect:

I am porting my c++ code from Linux to Windows using MSYS2 (64 bit). The key library is GNU MP (gmplib). The following code gives wrong results in MSYS2/MinGW64 environment while in Ubuntu works fine. Apparantly there is an unwanted conversion from 64 bit integer to 32 bit unteger when using mpz_set_ui function.

This piece of code

I would like to use GMP on windows, and I need to build static programs. (which means that, if anyone can provide another solution to compile win32 x86_64 programs using libgmp, I will also appreciate it.)

Now I have msys2 installed, and in it I have executed

I'm developing a Python library for cryptography. I wanted to optimize my library by writing the main classes in C++ with GMP. I wrote my C++ classes and I wrote the extern methods to use the main arithmetic operations: addition, subtraction, etc... These methods returns the results as char* to avoid cast problems. I built the DLL of my library and I declared the methods in a Python wrapper with ctypes. I noticed that after each arithmetic operation with huge numbers the memory grew exponentially. I was looking for problems in my C++ implementation, but there were no problems thanks to the C++ garbage collector. I was looking for a possible solution, so I discovered that I had to implement a C++ method to free up memory of the string created by the DLL. So I wrote this simple method: