Note

This is the documentation for the current state of the development branch of Qiskit Experiments. The documentation or APIs here can change prior to being released.

ExperimentEncoder

class ExperimentEncoder(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None)

JSON Encoder for Qiskit Experiments.

This class extends the default Python JSONEncoder by including built-in support for

• complex numbers, inf and NaN floats, sets, and dataclasses.

• NumPy ndarrays and SciPy sparse matrices.

• Qiskit QuantumCircuit.

• Any class that implements a __json_encode__ method or a settings property.

Generic classes can be serialized by this encoder. This is done by attempting the following methods in order:

1. The object has a __json_encode__ method. This should have signature

   def __json_encode__(self) -> Any:
       # return a JSON serializable object value
   

   The value returned by __json_encode__ must be an object that can be serialized by the JSON encoder (for example a dict containing other JSON serializable objects).

   To deserialize this object using the ExperimentDecoder the class must also provide a __json_decode__ class method that can convert the value returned by __json_encode__ back to the object. This method should have signature

   @classmethod
   def __json_decode__(cls, value: Any) -> cls:
       # recover the object from the `value` returned by __json_encode__
   

2. The object has a settings property. This should have signature

   @property
   def settings(self) -> Dict[str, Any]:
       # Return settings value for reconstructing the instance
   

   Deserialization of objects from the value dictionary returned by settings is done by calling the class __init__ method cls(**settings).

3. In all other cases only the object class is saved. Deserialization will attempt to recover the object from default initialization of its class as cls().

Note

Serialization of custom classes works for user-defined classes in Python scripts, notebooks, or third party modules. Note however that these will only be able to be de-serialized if that class can be imported form the same scope at the time the ExperimentDecoder is invoked.

Constructor for JSONEncoder, with sensible defaults.

If skipkeys is false, then it is a TypeError to attempt encoding of keys that are not str, int, float or None. If skipkeys is True, such items are simply skipped.

If ensure_ascii is true, the output is guaranteed to be str objects with all incoming non-ASCII characters escaped. If ensure_ascii is false, the output can contain non-ASCII characters.

If check_circular is true, then lists, dicts, and custom encoded objects will be checked for circular references during encoding to prevent an infinite recursion (which would cause an RecursionError). Otherwise, no such check takes place.

If allow_nan is true, then NaN, Infinity, and -Infinity will be encoded as such. This behavior is not JSON specification compliant, but is consistent with most JavaScript based encoders and decoders. Otherwise, it will be a ValueError to encode such floats.

If sort_keys is true, then the output of dictionaries will be sorted by key; this is useful for regression tests to ensure that JSON serializations can be compared on a day-to-day basis.

If indent is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines. None is the most compact representation.

If specified, separators should be an (item_separator, key_separator) tuple. The default is (’, ‘, ‘: ‘) if indent is None and (‘,’, ‘: ‘) otherwise. To get the most compact JSON representation, you should specify (‘,’, ‘:’) to eliminate whitespace.

If specified, default is a function that gets called for objects that can’t otherwise be serialized. It should return a JSON encodable version of the object or raise a TypeError.

Attributes

item_separator = ', '

key_separator = ': '

Methods

default(obj)

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 super().default(o)

Return type:

Any

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)