## Memory management in [NumPy](https://numpy.org)*
[](https://mybinder.org/v2/gh/inaccel/numpy-allocator/master?labpath=NumPy-Allocator.ipynb)
[](https://badge.fury.io/py/numpy-allocator)
**NumPy is a trademark owned by [NumFOCUS](https://numfocus.org).*
#### Customize Memory Allocators
Α metaclass is used to override the internal data memory routines. The metaclass has four optional fields:
```python
>>> 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
```python
>>> import numpy as np
>>> with my_allocator:
... a = np.array([1, 2, 3])
...
>>> my_allocator.handles(a)
True
```
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