BaseSchema

BaseSchema(*, only=None, exclude=(), many=False, context=None, load_only=(), dump_only=(), partial=False, unknown=None)

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Base class for Schemas for validated Qiskit classes.

Provides convenience functionality for the Qiskit common use case:

deserialization into class instances instead of dicts.
handling of unknown attributes not defined in the schema.

model_cls

class used to instantiate the instance. The

Type

type

constructor is passed all named parameters from deserialization.

Attributes

TYPE_MAPPING

= {: , : , : , : , : , : , : , : , : , : , : , : , : , : }

dict_class

type

Return type

type

error_messages

= {}

Overrides for default schema-level error messages

opts

=

set_class

type

Return type

type

Methods

dump

BaseSchema.dump(obj, *, many=None)

Serialize an object to native Python data types according to this Schema’s fields.

Parameters

obj (Any) – The object to serialize.
many (Optional[bool]) – Whether to serialize obj as a collection. If None, the value for self.many is used.

Returns

Serialized data

New in version 1.0.0.

Changed in version 3.0.0b7: This method returns the serialized data rather than a (data, errors) duple. A ValidationError is raised if obj is invalid.

Changed in version 3.0.0rc9: Validation no longer occurs upon serialization.

dump_additional_data

BaseSchema.dump_additional_data(valid_data, original_data, **kwargs)

Include unknown fields after dumping.

Unknown fields are added with no processing at all.

Parameters

valid_data (dict or list) – data collected and returned by dump().
original_data (object or list) – object passed to dump() in the first place.
**kwargs – extra arguments from the decorators.

Returns

the same valid_data extended with the unknown attributes.

Return type

dict

Inspired by https://github.com/marshmallow-code/marshmallow/pull/595(opens in a new tab).

dumps

BaseSchema.dumps(obj, *args, many=None, **kwargs)

Same as dump(), except return a JSON-encoded string.

Parameters

obj (Any) – The object to serialize.
many (Optional[bool]) – Whether to serialize obj as a collection. If None, the value for self.many is used.

Returns

A json string

New in version 1.0.0.

Changed in version 3.0.0b7: This method returns the serialized data rather than a (data, errors) duple. A ValidationError is raised if obj is invalid.

from_dict

classmethod BaseSchema.from_dict(fields, *, name='GeneratedSchema')

Generate a Schema class given a dictionary of fields.

from marshmallow import Schema, fields
 
PersonSchema = Schema.from_dict({"name": fields.Str()})
print(PersonSchema().load({"name": "David"}))  # => {'name': 'David'}

Generated schemas are not added to the class registry and therefore cannot be referred to by name in Nested fields.

Parameters

fields (dict) – Dictionary mapping field names to field instances.
name (str) – Optional name for the class, which will appear in the repr for the class.

New in version 3.0.0.

Return type

type

get_attribute

BaseSchema.get_attribute(obj, attr, default)

Defines how to pull values from an object to serialize.

New in version 2.0.0.

Changed in version 3.0.0a1: Changed position of obj and attr.

handle_error

BaseSchema.handle_error(error, data, *, many, **kwargs)

Custom error handler function for the schema.

Parameters

error (ValidationError) – The ValidationError raised during (de)serialization.
data (Any) – The original input data.
many (bool) – Value of many on dump or load.
partial – Value of partial on load.

New in version 2.0.0.

Changed in version 3.0.0rc9: Receives many and partial (on deserialization) as keyword arguments.

load

BaseSchema.load(data, *, many=None, partial=None, unknown=None)

Deserialize a data structure to an object defined by this Schema’s fields.

Parameters

data (Union[Mapping[str, Any], Iterable[Mapping[str, Any]]]) – The data to deserialize.
many (Optional[bool]) – Whether to deserialize data as a collection. If None, the value for self.many is used.
partial (Union[bool, Sequence[str], Set[str], None]) – Whether to ignore missing fields and not require any fields declared. Propagates down to Nested fields as well. If its value is an iterable, only missing fields listed in that iterable will be ignored. Use dot delimiters to specify nested fields.
unknown (Optional[str]) – Whether to exclude, include, or raise an error for unknown fields in the data. Use EXCLUDE, INCLUDE or RAISE. If None, the value for self.unknown is used.

Returns

Deserialized data

New in version 1.0.0.

Changed in version 3.0.0b7: This method returns the deserialized data rather than a (data, errors) duple. A ValidationError is raised if invalid data are passed.

loads

BaseSchema.loads(json_data, *, many=None, partial=None, unknown=None, **kwargs)

Same as load(), except it takes a JSON string as input.

Parameters

json_data (str) – A JSON string of the data to deserialize.
many (Optional[bool]) – Whether to deserialize obj as a collection. If None, the value for self.many is used.
partial (Union[bool, Sequence[str], Set[str], None]) – Whether to ignore missing fields and not require any fields declared. Propagates down to Nested fields as well. If its value is an iterable, only missing fields listed in that iterable will be ignored. Use dot delimiters to specify nested fields.
unknown (Optional[str]) – Whether to exclude, include, or raise an error for unknown fields in the data. Use EXCLUDE, INCLUDE or RAISE. If None, the value for self.unknown is used.

Returns

Deserialized data

New in version 1.0.0.

Changed in version 3.0.0b7: This method returns the deserialized data rather than a (data, errors) duple. A ValidationError is raised if invalid data are passed.

make_model

BaseSchema.make_model(data, **_)

Make load return a model_cls instance instead of a dict.

on_bind_field

BaseSchema.on_bind_field(field_name, field_obj)

Hook to modify a field when it is bound to the Schema.

No-op by default.

Return type

None

validate

BaseSchema.validate(data, *, many=None, partial=None)

Validate data against the schema, returning a dictionary of validation errors.

Parameters

data (Mapping) – The data to validate.
many (Optional[bool]) – Whether to validate data as a collection. If None, the value for self.many is used.
partial (Union[bool, Sequence[str], Set[str], None]) – Whether to ignore missing fields and not require any fields declared. Propagates down to Nested fields as well. If its value is an iterable, only missing fields listed in that iterable will be ignored. Use dot delimiters to specify nested fields.

Return type

Dict[str, List[str]]

Returns

A dictionary of validation errors.

New in version 1.1.0.

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