Convert String of an int array to a Numpy array of ints

[mdsousa]

In sending a message (Numpy int array) using RabbitMQ, this is how it is setup and sent

testImage = np.random.randint(0, 255, 10*1000)  # grey scale images
strImage = np.array_str(testImage)
message = <string of meta data> + strImage
channel.basic_publish(exchange='', routing_key='task_queue', body=message, properties=pika.BasicProperties(delivery_mode=2,  # make message persistent
    ))

This is the output of the message sent:

Output:
[x] Message params '0,1617801844,1617801844400951300,10000,[113  75  36 ... 167 157 131]'

In modifying the received message (from rabbitMQ) to get a Numpy int array I've tried:

    message = body.decode()
    parts = message.split(',')
    print("[x] message      %r" % message)
    print("[x] message type %s" % type(message))
    print("[x] parts        %s" % parts)
    print("[x] parts len    %s" % len(parts))
    

This is the output for the above code:

Output:
[x] message      '0,1617801844,1617801844400951300,10000,[113  75  36 ... 167 157 131]'
[x] message type <class 'str'>
[x] parts        ['0', '1617801844', '1617801844400951300', '10000', '[113  75  36 ... 167 157 131]']
[x] parts len    5

I then start working of the message part that is the Numpy array:

    imagePart = parts[4]
    print()
    print("[x] imagePart ", imagePart)
    print(repr(imagePart))
    print(re.sub("\s+", ",", imagePart.strip()))
    print(type(re.sub("\s+", ",", imagePart.strip())))
    print(np.array(re.sub("\s+", ",", imagePart.strip())))
    print(np.array(re.sub("\s+", ",", imagePart.strip())).size)
    print(type(np.array(re.sub("\s+", ",", imagePart.strip()))))
    print(repr(np.array(re.sub("\s+", ",", imagePart.strip()))))
    print()
    

The output for the above code block is (I'm not sure why it thinks it's of dtype 'U27'):

Output:
[x] imagePart  [113  75  36 ... 167 157 131]
'[113  75  36 ... 167 157 131]'
[113,75,36,...,167,157,131]
<class 'str'>
[113,75,36,...,167,157,131]
1
<class 'numpy.ndarray'>
array('[113,75,36,...,167,157,131]', dtype='<U27')

I then try a different approach:

    npPart = np.asarray(imagePart, dtype=np.str)
    npSplit = np.char.split(npPart)
    npSplitPart = np.array(npSplit, dtype=object)
    print(npSplitPart)
    print(npSplitPart.dtype)
    print("[x] npSplitPart type ", type(npSplitPart))
    print("[x] npSplitPart shape ", npSplitPart.shape)
    print("[x] npSplitPart size ", npSplitPart.size)
    print(repr(npSplitPart))
    print(np.array(npSplitPart))

This is the output for the above code block:

Output:
['[113', '75', '36', '...', '167', '157', '131]']
object
[x] npSplitPart type  <class 'numpy.ndarray'>
[x] npSplitPart shape  ()
[x] npSplitPart size  1
array(list(['[113', '75', '36', '...', '167', '157', '131]']),
      dtype=object)
['[113', '75', '36', '...', '167', '157', '131]']

What I would like is to get back to the original Numpy int array. Any idea what I am doing wrong or missing?

Thanks...