arthurai.core.util.NumpyEncoder

class arthurai.core.util.NumpyEncoder(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None)

Bases: json.encoder.JSONEncoder

Special json encoder for numpy types

Methods

convert_value	Converts the given object from a numpy data type to a python data type, if the object is already a python data type it is returned
default	Implement this method in a subclass such that it returns a serializable object for o, or calls the base implementation (to raise a TypeError).
encode	Return a JSON string representation of a Python data structure.
iterencode	Encode the given object and yield each string representation as available.

Attributes

item_separator
key_separator

static convert_value(obj)

Converts the given object from a numpy data type to a python data type, if the object is already a python data type it is returned

Parameters

obj – object to convert

Returns

python data type version of the object

default(o)

Implement this method in a subclass such that it returns a serializable object for o, or calls the base implementation (to raise a TypeError).

For example, to support arbitrary iterators, you could implement default like this:

def default(self, o):
    try:
        iterable = iter(o)
    except TypeError:
        pass
    else:
        return list(iterable)
    # Let the base class default method raise the TypeError
    return JSONEncoder.default(self, o)

encode(o)

Return a JSON string representation of a Python data structure.

>>> from json.encoder import JSONEncoder
>>> JSONEncoder().encode({"foo": ["bar", "baz"]})
'{"foo": ["bar", "baz"]}'

iterencode(o, _one_shot=False)

Encode the given object and yield each string representation as available.

For example:

for chunk in JSONEncoder().iterencode(bigobject):
    mysocket.write(chunk)