The Wrapped Exchange Array is a convenient way in order to exchange array data easily via processes or remote nodes
Project description
wea.py
The Wrapped Exchange Array is a convenient way in order to exchange array data easily via processes or remote nodes. Inspired and adopted partly from Julia’s InterProcessCommunication WrappedArray.
The wrapped exchange array can be accessed like a numpy array because under the hood, numpy is applied.
Getting started
Install the package from Pypi
pip install wea
Shared memory
import wea
import numpy as np
...
wa = wea.shared_memory.create_shared_array('/awesome-1', np.dtype('float64'), (10, 2))
wa[:] = my_new_data[:]
...
Creating a shared memory segment
In order to create a new shared memory segment, use the following snippet
import wea
import numpy as np
type = np.dtype('float64')
dims = (10, 2)
wa = wea.shared_memory.create_shared_array('/awesome-1', type, dims)
wa[:] = np.random.randn(dims[0], dims[1])
If creating was not possible because the segment already exists , a FileExistsError
exception will be thrown.
Attaching to an existing shared memory array
If a wrapped exchange array was already created, you can attach to it simply by
import wea
import numpy as np
wa = wea.shared_memory.attach_shared_array('/awesome-1')
wa[:] = np.random.randn(dims[0], dims[1])
The metadata of the array are stored in the shared memory header segment and will be retrieved for the numpy array creation.
If attaching was not possible because the segment does not exist so far, a FileNotFoundError
exception will be thrown.
Bytearray buffer memory
import wea
import numpy as np
...
wa = wea.buffered_memory.create_buffered_array(np.dtype('float64'), (10, 2))
wa[:] = my_new_data[:]
buf = wa.exchange buffer
share(buf) # where share calls your prefered communication protocol
...
Creating a buffered memory segment
In order to create a new buffered memory segment, use the following snippet
import wea
import numpy as np
type = np.dtype('float64')
dims = (10, 2)
wa = wea.buffered_memory.create_buffered_array(type, dims)
wa[:] = np.random.randn(dims[0], dims[1])
buf: bytearray = wa.exchange_buffer
Actually it copies the content from the numpy array into the buffer. Thus, the current behavior is like a deep copy.
Loading from an existing buffered memory segment
If a wrapped exchange array was already created, you can load from it simply by
import wea
import numpy as np
buf: bytearray = receive() # where receive via your prefered communication protocol
wa = wea.buffered_memory.load_buffered_array(buf)
The metadata of the array are stored in the buffered memory header segment and will be retrieved for the numpy array creation.
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