numpy-allocator

Configurable memory allocations

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Project description

Memory management in NumPy*

*NumPy is a trademark owned by NumFOCUS.

Customize Memory Allocators

Α metaclass is used to override the internal data memory routines. The metaclass has four optional fields:

>>> import ctypes
>>> import ctypes.util
>>> import numpy_allocator
>>> my = ctypes.CDLL(ctypes.util.find_library('my'))
>>> class my_allocator(metaclass=numpy_allocator.type):
...     _calloc_ = ctypes.addressof(my.calloc_func)
...     _free_ = ctypes.addressof(my.free_func)
...     _malloc_ = ctypes.addressof(my.malloc_func)
...     _realloc_ = ctypes.addressof(my.realloc_func)
...

An example using the allocator

>>> import numpy as np
>>> with my_allocator:
...     a = np.array([1, 2, 3])
...
>>> my_allocator.handles(a)
True

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Release history Release notifications | RSS feed

This version

1.2.0

Nov 25, 2022

1.1.3

Nov 22, 2022

1.1.2

Nov 21, 2022

1.1.1

Nov 10, 2022

1.1.0

Jan 7, 2022

1.0.0

Jan 2, 2022

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