""" An implementation of JSON Schema for Python The main functionality is provided by the validator classes for each of the supported JSON Schema versions. Most commonly, the :function:`validate` function is the quickest way to simply validate a given instance under a schema, and will create a validator for you. """ from __future__ import division, unicode_literals import collections import itertools import operator import re import sys import warnings __version__ = "0.7" FLOAT_TOLERANCE = 10 ** -15 PY3 = sys.version_info[0] >= 3 if PY3: basestring = unicode = str iteritems = operator.methodcaller("items") from urllib.parse import unquote else: from itertools import izip as zip iteritems = operator.methodcaller("iteritems") from urllib import unquote class UnknownType(Exception): """ An unknown type was given. """ class InvalidRef(Exception): """ An invalid reference was given. """ class SchemaError(Exception): """ The provided schema is malformed. The same attributes exist for ``SchemaError``s as for ``ValidationError``s. """ validator = None def __init__(self, message): super(SchemaError, self).__init__(message) self.message = message self.path = [] class ValidationError(Exception): """ The instance didn't properly validate with the provided schema. Relevant attributes are: * ``message`` : a human readable message explaining the error * ``path`` : a list containing the path to the offending element (or [] if the error happened globally) in *reverse* order (i.e. deepest index first). """ # the failing validator will be set externally at whatever recursion level # is immediately above the validation failure validator = None def __init__(self, message): super(ValidationError, self).__init__(message) self.message = message # Any validator that recurses must append to the ValidationError's # path (e.g., properties and items) self.path = [] class Draft3Validator(object): """ A validator for JSON Schema draft 3. """ DEFAULT_TYPES = { "array" : list, "boolean" : bool, "integer" : int, "null" : type(None), "number" : (int, float), "object" : dict, "string" : basestring, } def __init__(self, schema, types=()): """ Initialize a validator. ``schema`` should be a *valid* JSON Schema object already converted to a native Python object (typically a dict via ``json.load``). ``types`` is a mapping (or iterable of 2-tuples) containing additional types or alternate types to verify via the 'type' property. For instance, the default types for the 'number' JSON Schema type are ``int`` and ``float``. To override this behavior (e.g. for also allowing ``decimal.Decimal``), pass ``types={"number" : (int, float, decimal.Decimal)} *including* the default types if so desired, which are fairly obvious but can be accessed via the ``DEFAULT_TYPES`` attribute on this class if necessary. """ self._types = dict(self.DEFAULT_TYPES) self._types.update(types) self._types["any"] = tuple(self._types.values()) self.schema = schema def is_type(self, instance, type): """ Check if an ``instance`` is of the provided (JSON Schema) ``type``. """ if type not in self._types: raise UnknownType(type) type = self._types[type] # bool inherits from int, so ensure bools aren't reported as integers if isinstance(instance, bool): type = _flatten(type) if int in type and bool not in type: return False return isinstance(instance, type) def is_valid(self, instance, _schema=None): """ Check if the ``instance`` is valid under the current schema. Returns a bool indicating whether validation succeeded. """ error = next(self.iter_errors(instance, _schema), None) return error is None @classmethod def check_schema(cls, schema): """ Validate a ``schema`` against the meta-schema to see if it is valid. """ for error in cls(cls.META_SCHEMA).iter_errors(schema): s = SchemaError(error.message) s.path = error.path s.validator = error.validator # I think we're safer raising these always, not yielding them raise s def iter_errors(self, instance, _schema=None): """ Lazily yield each of the errors in the given ``instance``. """ if _schema is None: _schema = self.schema for k, v in iteritems(_schema): validator = getattr(self, "validate_%s" % (k.lstrip("$"),), None) if validator is None: continue errors = validator(v, instance, _schema) or () for error in errors: # if the validator hasn't already been set (due to recursion) # make sure to set it error.validator = error.validator or k yield error def validate(self, *args, **kwargs): """ Validate an ``instance`` under the given ``schema``. """ for error in self.iter_errors(*args, **kwargs): raise error def validate_type(self, types, instance, schema): types = _list(types) for type in types: # Ouch. Brain hurts. Two paths here, either we have a schema, then # check if the instance is valid under it if (( self.is_type(type, "object") and self.is_valid(instance, type) # Or we have a type as a string, just check if the instance is that # type. Also, HACK: we can reach the `or` here if skip_types is # something other than error. If so, bail out. ) or ( self.is_type(type, "string") and (self.is_type(instance, type) or type not in self._types) )): return else: yield ValidationError(_types_msg(instance, types)) def validate_properties(self, properties, instance, schema): if not self.is_type(instance, "object"): return for property, subschema in iteritems(properties): if property in instance: for error in self.iter_errors(instance[property], subschema): error.path.append(property) yield error elif subschema.get("required", False): error = ValidationError( "%r is a required property" % (property,) ) error.path.append(property) error.validator = "required" yield error def validate_patternProperties(self, patternProperties, instance, schema): for pattern, subschema in iteritems(patternProperties): for k, v in iteritems(instance): if re.match(pattern, k): for error in self.iter_errors(v, subschema): yield error def validate_additionalProperties(self, aP, instance, schema): if not self.is_type(instance, "object"): return extras = set(_find_additional_properties(instance, schema)) if self.is_type(aP, "object"): for extra in extras: for error in self.iter_errors(instance[extra], aP): yield error elif not aP and extras: error = "Additional properties are not allowed (%s %s unexpected)" yield ValidationError(error % _extras_msg(extras)) def validate_dependencies(self, dependencies, instance, schema): if not self.is_type(instance, "object"): return for property, dependency in iteritems(dependencies): if property not in instance: continue if self.is_type(dependency, "object"): for error in self.iter_errors(instance, dependency): yield error else: dependencies = _list(dependency) for dependency in dependencies: if dependency not in instance: yield ValidationError( "%r is a dependency of %r" % (dependency, property) ) def validate_items(self, items, instance, schema): if not self.is_type(instance, "array"): return if self.is_type(items, "object"): for index, item in enumerate(instance): for error in self.iter_errors(item, items): error.path.append(index) yield error else: for (index, item), subschema in zip(enumerate(instance), items): for error in self.iter_errors(item, subschema): error.path.append(index) yield error def validate_additionalItems(self, aI, instance, schema): if not self.is_type(instance, "array"): return if not self.is_type(schema.get("items"), "array"): return if self.is_type(aI, "object"): for item in instance[len(schema):]: for error in self.iter_errors(item, aI): yield error elif not aI and len(instance) > len(schema.get("items", [])): error = "Additional items are not allowed (%s %s unexpected)" yield ValidationError( error % _extras_msg(instance[len(schema.get("items", [])):]) ) def validate_minimum(self, minimum, instance, schema): if not self.is_type(instance, "number"): return instance = float(instance) if schema.get("exclusiveMinimum", False): failed = instance <= minimum cmp = "less than or equal to" else: failed = instance < minimum cmp = "less than" if failed: yield ValidationError( "%r is %s the minimum of %r" % (instance, cmp, minimum) ) def validate_maximum(self, maximum, instance, schema): if not self.is_type(instance, "number"): return instance = float(instance) if schema.get("exclusiveMaximum", False): failed = instance >= maximum cmp = "greater than or equal to" else: failed = instance > maximum cmp = "greater than" if failed: yield ValidationError( "%r is %s the maximum of %r" % (instance, cmp, maximum) ) def validate_minItems(self, mI, instance, schema): if self.is_type(instance, "array") and len(instance) < mI: yield ValidationError("%r is too short" % (instance,)) def validate_maxItems(self, mI, instance, schema): if self.is_type(instance, "array") and len(instance) > mI: yield ValidationError("%r is too long" % (instance,)) def validate_uniqueItems(self, uI, instance, schema): if uI and self.is_type(instance, "array") and not _uniq(instance): yield ValidationError("%r has non-unique elements" % instance) def validate_pattern(self, patrn, instance, schema): if self.is_type(instance, "string") and not re.match(patrn, instance): yield ValidationError("%r does not match %r" % (instance, patrn)) def validate_minLength(self, mL, instance, schema): if self.is_type(instance, "string") and len(instance) < mL: yield ValidationError("%r is too short" % (instance,)) def validate_maxLength(self, mL, instance, schema): if self.is_type(instance, "string") and len(instance) > mL: yield ValidationError("%r is too long" % (instance,)) def validate_enum(self, enums, instance, schema): if instance not in enums: yield ValidationError("%r is not one of %r" % (instance, enums)) def validate_divisibleBy(self, dB, instance, schema): if not self.is_type(instance, "number"): return if isinstance(dB, float): mod = instance % dB failed = (mod > FLOAT_TOLERANCE) and (dB - mod) > FLOAT_TOLERANCE else: failed = instance % dB if failed: yield ValidationError("%r is not divisible by %r" % (instance, dB)) def validate_disallow(self, disallow, instance, schema): for disallowed in _list(disallow): if self.is_valid(instance, {"type" : [disallowed]}): yield ValidationError( "%r is disallowed for %r" % (disallowed, instance) ) def validate_extends(self, extends, instance, schema): if self.is_type(extends, "object"): extends = [extends] for subschema in extends: for error in self.iter_errors(instance, subschema): yield error def validate_ref(self, ref, instance, schema): if ref != "#" and not ref.startswith("#/"): warnings.warn("jsonschema only supports json-pointer $refs") return resolved = resolve_json_pointer(self.schema, ref) for error in self.iter_errors(instance, resolved): yield error Draft3Validator.META_SCHEMA = { "$schema" : "http://json-schema.org/draft-03/schema#", "id" : "http://json-schema.org/draft-03/schema#", "type" : "object", "properties" : { "type" : { "type" : ["string", "array"], "items" : {"type" : ["string", {"$ref" : "#"}]}, "uniqueItems" : True, "default" : "any" }, "properties" : { "type" : "object", "additionalProperties" : {"$ref" : "#", "type": "object"}, "default" : {} }, "patternProperties" : { "type" : "object", "additionalProperties" : {"$ref" : "#"}, "default" : {} }, "additionalProperties" : { "type" : [{"$ref" : "#"}, "boolean"], "default" : {} }, "items" : { "type" : [{"$ref" : "#"}, "array"], "items" : {"$ref" : "#"}, "default" : {} }, "additionalItems" : { "type" : [{"$ref" : "#"}, "boolean"], "default" : {} }, "required" : {"type" : "boolean", "default" : False}, "dependencies" : { "type" : ["string", "array", "object"], "additionalProperties" : { "type" : ["string", "array", {"$ref" : "#"}], "items" : {"type" : "string"} }, "default" : {} }, "minimum" : {"type" : "number"}, "maximum" : {"type" : "number"}, "exclusiveMinimum" : {"type" : "boolean", "default" : False}, "exclusiveMaximum" : {"type" : "boolean", "default" : False}, "minItems" : {"type" : "integer", "minimum" : 0, "default" : 0}, "maxItems" : {"type" : "integer", "minimum" : 0}, "uniqueItems" : {"type" : "boolean", "default" : False}, "pattern" : {"type" : "string", "format" : "regex"}, "minLength" : {"type" : "integer", "minimum" : 0, "default" : 0}, "maxLength" : {"type" : "integer"}, "enum" : {"type" : "array", "minItems" : 1, "uniqueItems" : True}, "default" : {"type" : "any"}, "title" : {"type" : "string"}, "description" : {"type" : "string"}, "format" : {"type" : "string"}, "maxDecimal" : {"type" : "number", "minimum" : 0}, "divisibleBy" : { "type" : "number", "minimum" : 0, "exclusiveMinimum" : True, "default" : 1 }, "disallow" : { "type" : ["string", "array"], "items" : {"type" : ["string", {"$ref" : "#"}]}, "uniqueItems" : True }, "extends" : { "type" : [{"$ref" : "#"}, "array"], "items" : {"$ref" : "#"}, "default" : {} }, "id" : {"type" : "string", "format" : "uri"}, "$ref" : {"type" : "string", "format" : "uri"}, "$schema" : {"type" : "string", "format" : "uri"}, }, "dependencies" : { "exclusiveMinimum" : "minimum", "exclusiveMaximum" : "maximum" }, } class Validator(Draft3Validator): """ Deprecated: Use :class:`Draft3Validator` instead. """ def __init__( self, version=None, unknown_type="skip", unknown_property="skip", *args, **kwargs ): super(Validator, self).__init__({}, *args, **kwargs) warnings.warn( "Validator is deprecated and will be removed. " "Use Draft3Validator instead.", DeprecationWarning, stacklevel=2, ) class ErrorTree(object): """ ErrorTrees make it easier to check which validations failed. """ def __init__(self, errors=()): self.errors = {} self._contents = collections.defaultdict(self.__class__) for error in errors: container = self for element in reversed(error.path): container = container[element] container.errors[error.validator] = error def __contains__(self, k): return k in self._contents def __getitem__(self, k): return self._contents[k] def __setitem__(self, k, v): self._contents[k] = v def __iter__(self): return iter(self._contents) def __len__(self): child_errors = sum(len(tree) for _, tree in iteritems(self._contents)) return len(self.errors) + child_errors def __repr__(self): return "<%s (%s errors)>" % (self.__class__.__name__, len(self)) def resolve_json_pointer(schema, ref): """ Resolve a local reference ``ref`` within the given root ``schema``. ``ref`` should be a local ref whose ``#`` is still present. """ if ref == "#": return schema parts = ref.lstrip("#/").split("/") parts = map(unquote, parts) parts = [part.replace('~1', '/').replace('~0', '~') for part in parts] try: for part in parts: schema = schema[part] except KeyError: raise InvalidRef("Unresolvable json-pointer %r" % ref) else: return schema def _find_additional_properties(instance, schema): """ Return the set of additional properties for the given ``instance``. Weeds out properties that should have been validated by ``properties`` and / or ``patternProperties``. Assumes ``instance`` is dict-like already. """ properties = schema.get("properties", {}) patterns = "|".join(schema.get("patternProperties", {})) for property in instance: if property not in properties: if patterns and re.search(patterns, property): continue yield property def _extras_msg(extras): """ Create an error message for extra items or properties. """ if len(extras) == 1: verb = "was" else: verb = "were" return ", ".join(repr(extra) for extra in extras), verb def _types_msg(instance, types): """ Create an error message for a failure to match the given types. If the ``instance`` is an object and contains a ``name`` property, it will be considered to be a description of that object and used as its type. Otherwise the message is simply the reprs of the given ``types``. """ reprs = [] for type in types: try: reprs.append(repr(type["name"])) except Exception: reprs.append(repr(type)) return "%r is not of type %s" % (instance, ", ".join(reprs)) def _flatten(suitable_for_isinstance): """ isinstance() can accept a bunch of really annoying different types: * a single type * a tuple of types * an arbitrary nested tree of tuples Return a flattened tuple of the given argument. """ types = set() if not isinstance(suitable_for_isinstance, tuple): suitable_for_isinstance = (suitable_for_isinstance,) for thing in suitable_for_isinstance: if isinstance(thing, tuple): types.update(_flatten(thing)) else: types.add(thing) return tuple(types) def _list(thing): """ Wrap ``thing`` in a list if it's a single str. Otherwise, return it unchanged. """ if isinstance(thing, basestring): return [thing] return thing def _delist(thing): """ Unwrap ``thing`` to a single element if its a single str in a list. Otherwise, return it unchanged. """ if ( isinstance(thing, list) and len(thing) == 1 and isinstance(thing[0], basestring) ): return thing[0] return thing def _uniq(container): """ Check if all of a container's elements are unique. Successively tries first to rely that the elements are hashable, then falls back on them being sortable, and finally falls back on brute force. """ try: return len(set(container)) == len(container) except TypeError: try: sort = sorted(container) sliced = itertools.islice(container, 1, None) for i, j in zip(container, sliced): if i == j: return False except (NotImplementedError, TypeError): seen = [] for e in container: if e in seen: return False seen.append(e) return True def validate(instance, schema, cls=Draft3Validator, *args, **kwargs): """ Validate an ``instance`` under the given ``schema``. First verifies that the provided schema is itself valid, since not doing so can lead to less obvious failures when validating. If you know it is or don't care, use ``YourValidator(schema).validate(instance)`` directly instead (e.g. ``Draft3Validator``). ``cls`` is a validator class that will be used to validate the instance. By default this is a draft 3 validator. Any other provided positional and keyword arguments will be provided to this class when constructing a validator. """ meta_validate = kwargs.pop("meta_validate", None) if meta_validate is not None: warnings.warn( "meta_validate is deprecated and will be removed. If you do not " "want to validate a schema, use Draft3Validator.validate instead.", DeprecationWarning, stacklevel=2, ) if meta_validate is not False: # yes this is needed since True was default cls.check_schema(schema) cls(schema, *args, **kwargs).validate(instance)