Source code for yggdrasil.metaschema.datatypes.SchemaMetaschemaType

import copy
import jsonschema
from yggdrasil.metaschema.datatypes import get_type_class, _type_registry
from import get_metaschema_property
from yggdrasil.metaschema.datatypes.JSONObjectMetaschemaType import (

def _specificity_sort_key(item):
    return item.specificity

def _normalize_schema(validator, ref, instance, schema):
    r"""Normalize a schema at the root to handle case where only type
    string specified."""
    # if isinstance(instance, str):
    #     instance = dict(type=instance)
    # return instance
    if isinstance(instance, str) and (instance in _type_registry):
        instance = {'type': instance}
    elif isinstance(instance, dict):
        if len(instance) == 0:
        elif 'type' not in instance:
            valid_types = None
            for k in instance.keys():
                prop_class = get_metaschema_property(k, skip_generic=True)
                if prop_class is None:
                if valid_types is None:
                    valid_types = set(prop_class.types)
                    valid_types = (valid_types & set(prop_class.types))
            if (valid_types is None) or (len(valid_types) == 0):
                # There were not any recorded properties so this must be a
                # dictionary of properties
                instance = {'type': 'object', 'properties': instance}
                if len(valid_types) > 1:
                    valid_type_classes = sorted([_type_registry[t] for t in valid_types],
                    s_max = valid_type_classes[0].specificity
                    valid_types = []
                    for tcls in valid_type_classes:
                        if tcls.specificity > s_max:
                    if 'scalar' in valid_types:
                        for t in ['1darray', 'ndarray']:
                            if t in valid_types:
                    if len(valid_types) > 1:
                        raise Exception("Multiple possible classes: %s" % valid_types)
                instance['type'] = valid_types[0]
    elif isinstance(instance, (list, tuple)):
        # If inside validation of items as a schema, don't assume a
        # list is a malformed schema. Doing so results in infinite
        # recursion.
        if not ((len(validator._schema_path_stack) >= 2)
                and (validator._schema_path_stack[-2:] == ['items', 0])):
            instance = {'type': 'array', 'items': instance}
    if isinstance(instance, dict) and ('type' in instance):
        typecls = get_type_class(instance['type'])
        instance = typecls.normalize_definition(instance)
    return instance

def _validate_schema(validator, ref, instance, schema):
    r"""Validate a schema at the root to handle case where only type
    string specified."""
    if validator._normalizing and (ref == '#'):
        validator._normalized = _normalize_schema(validator, ref, instance, schema)
    errors = validator._base_validator.VALIDATORS['$ref'](
        validator, ref, instance, schema) or ()
    for e in errors:
        yield e
    if validator._normalizing and (ref == '#'):
        instance = validator._normalizing

[docs]class SchemaMetaschemaType(JSONObjectMetaschemaType): r"""Schema type.""" name = 'schema' description = 'A schema type for evaluating subschema.' properties = ['type'] definition_properties = ['type'] metadata_properties = ['type'] specificity = JSONObjectMetaschemaType.specificity + 1 inherit_properties = ['extract_properties'] _replaces_existing = False example_data = {'type': 'boolean'}
[docs] @classmethod def encode_data(cls, obj, typedef): r"""Encode an object's data. Args: obj (object): Object to encode. typedef (dict): Type definition that should be used to encode the object. Returns: string: Encoded object. """ # Schemas should already be in JSON serializable format return cls.normalize(obj)
[docs] @classmethod def decode_data(cls, obj, typedef): r"""Decode an object. Args: obj (string): Encoded object to decode. typedef (dict): Type definition that should be used to decode the object. Returns: object: Decoded object. """ return obj
[docs] @classmethod def validate(cls, obj, raise_errors=False): r"""Validate an object to check if it could be of this type. Args: obj (object): Object to validate. raise_errors (bool, optional): If True, errors will be raised when the object fails to be validated. Defaults to False. Returns: bool: True if the object could be of this type, False otherwise. """ if not super(SchemaMetaschemaType, cls).validate(obj, raise_errors=raise_errors): return False try: x = copy.deepcopy(cls.metaschema()) x.setdefault('required', []) if 'type' not in x['required']: x['required'].append('type') x['additionalProperties'] = False jsonschema.validate(obj, x, cls=cls.validator()) except jsonschema.exceptions.ValidationError: if raise_errors: raise return False return True
[docs] @classmethod def normalize(cls, obj): r"""Normalize an object, if possible, to conform to this type. Args: obj (object): Object to normalize. Returns: object: Normalized object. """ if isinstance(obj, str): obj = {'type': obj} x = cls.metaschema() validators = {u'$ref': _validate_schema} normalizers = {tuple(): [_normalize_schema]} validator_class = copy.deepcopy(cls.validator()) obj = validator_class(x).normalize(obj, no_defaults=True, normalizers=normalizers, validators=validators) return obj