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Fast Numpy I/O : Fast replacement for numpy.load and numpy.save

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In the tests, performing an operation on the array `test_fastnumpyio_save` after it has been loaded gives an `output array is read-only` error: ``` start = timer() for i in range(iterations):...

![image](https://github.com/user-attachments/assets/65628229-2bfb-468f-a7c0-2f302a208ed1) It is caused by the `OWNDATA` and `WRITEABLE ` flags ``` C_CONTIGUOUS : True F_CONTIGUOUS : False OWNDATA : False WRITEABLE : False ALIGNED : True WRITEBACKIFCOPY : False...

fix https://github.com/divideconcept/fastnumpyio/issues/8 ### test Windows 11 WSL, Python 3.10.15 x64, Numpy 1.26.4, 12th Gen Intel(R) Core(TM) i7-12700KF 3.60 GHz: ``` numpy.save: 0:00:00.657019 fastnumpyio.save: 0:00:00.185535 fastnumpyio.pack: 0:00:00.157975 numpy.load: 0:00:01.783694 fastnumpyio.load: 0:00:00.257334...

I would we very helpful, if structured arrays are supported by this module.

Hi, I wanted to try out your save and load functions, but got this error with your load function: ``` save("/media/w/numpy_array_fast.npy", numpy_array) load("/media/w/numpy_array_fast.npy") ``` ``` Exception has occurred: ValueError invalid...

Hey, I really like your package here. Would you mind publishing this to pypi? For my projects, this would make it way easier to install it, and colleagues to install...