SimpleJSON and NumPy array

Question

What is the most efficient way of serializing a numpy array using simplejson?

Answer 1

I just discovered tlausch's answer to this Question and realized it gives the almost correct answer for my problem, but at least for me it does not work in Python 3.5, because of several errors: 1 - infinite recursion 2 - the data was saved as None

since i can not directly comment on the original answer yet, here is my version:

import base64
import json
import numpy as np

    class NumpyEncoder(json.JSONEncoder):
        def default(self, obj):
            """If input object is an ndarray it will be converted into a dict
            holding dtype, shape and the data, base64 encoded.
            """
            if isinstance(obj, np.ndarray):
                if obj.flags['C_CONTIGUOUS']:
                    obj_data = obj.data
                else:
                    cont_obj = np.ascontiguousarray(obj)
                    assert(cont_obj.flags['C_CONTIGUOUS'])
                    obj_data = cont_obj.data
                data_b64 = base64.b64encode(obj_data)
                return dict(__ndarray__= data_b64.decode('utf-8'),
                            dtype=str(obj.dtype),
                            shape=obj.shape)


    def json_numpy_obj_hook(dct):
        """Decodes a previously encoded numpy ndarray with proper shape and dtype.

        :param dct: (dict) json encoded ndarray
        :return: (ndarray) if input was an encoded ndarray
        """
        if isinstance(dct, dict) and '__ndarray__' in dct:
            data = base64.b64decode(dct['__ndarray__'])
            return np.frombuffer(data, dct['dtype']).reshape(dct['shape'])
        return dct

expected = np.arange(100, dtype=np.float)
dumped = json.dumps(expected, cls=NumpyEncoder)
result = json.loads(dumped, object_hook=json_numpy_obj_hook)


# None of the following assertions will be broken.
assert result.dtype == expected.dtype, "Wrong Type"
assert result.shape == expected.shape, "Wrong Shape"
assert np.allclose(expected, result), "Wrong Values"