multiprocess-shared-numpy-arrays

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multiprocess-shared-numpy-arrays

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Easily share numpy arrays between processes

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## multiprocess-shared-numpy-arrays

### Easily share numpy arrays between processes
Convenience functions for sharing
[numpy arrays](https://docs.scipy.org/doc/numpy/) 
between multiple processes using 
[multiprocessing.Array](https://docs.python.org/3.4/library/multiprocessing.html?highlight=process#multiprocessing.Array)
as process safe shared memory arrays.

#### Usage
```python
# Create shared array from numpy array:
make_shared_array(np_array, name='my_shared_array')

# Access shared array as numpy array:
array = get_shared_array('my_shared_array')
```

### Installation

```bash
pip install git+https://github.com/widmi/multiprocess-shared-numpy-arrays
```

### Full example:

```python
import numpy as np
from multiprocessing import Pool
from share_array.share_array import get_shared_array, make_shared_array

def worker_function(i):
    """Function that uses the shared array"""
    array = get_shared_array('my_shared_array')  # get shared memory array as numpy array
    array[:] += i  # modify the shared memory array as numpy array

if __name__ == '__main__':
    np_array = np.arange(3*5).reshape((3, 5))  # make a numpy array
    make_shared_array(np_array, name='my_shared_array')  # create shared memory array from numpy array
    shared_array = get_shared_array('my_shared_array')  # get shared memory array as numpy array
    
    print("Shared array before multiprocessing:")
    print(shared_array)  # Print array
    
    with Pool(processes=2) as pool:
        _ = pool.map(worker_function, range(15))  # use a multiprocessing.Pool to distribute work to worker processes
    
    print("Shared array after multiprocessing:")
    print(shared_array)  # Content of array was changed in worker processes
```

multiprocess-shared-numpy-arrays

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