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"""
An implementation of JSON Schema for Python
The main functionality is provided by the :class:`Validator` class, with the
:function:`validate` function being the most common way to quickly create a
:class:`Validator` object and validate an instance with a given schema.
The :class:`Validator` class generally attempts to be as strict as possible
under the JSON Schema specification. See its docstring for details.
What's Missing
--------------
* ``uniqueItems``
* ``format``
* ``extends``
* ``$ref``
* ``$schema``
"""
from __future__ import division, with_statement
import re
import types
import warnings
__version__ = "0.2"
try: # pragma: no cover, 2.5 support
next
except NameError: # pragma: no cover
_none = object()
def next(iterator, default=_none):
try:
return iterator.next()
except StopIteration:
if default is not _none:
return default
raise
class SchemaError(Exception):
"""
The provided schema is malformed.
"""
class ValidationError(Exception):
"""
The instance didn't properly validate with the provided schema.
"""
def __init__(self, *args, **kwargs):
self.errors = kwargs.pop("errors", [])
super(ValidationError, self).__init__(*args, **kwargs)
class Validator(object):
"""
A JSON Schema validator.
"""
_SKIPPED = set([ # handled in:
u"dependencies", u"required", # properties
u"exclusiveMinimum", u"exclusiveMaximum", # min/max
u"default", u"description", u"links", u"name", u"title", # none needed
])
_TYPES = {
u"array" : list, u"boolean" : bool, u"integer" : int,
u"null" : types.NoneType, u"object" : dict,
}
def __init__(
self, stop_on_error=True, unknown_type="error",
unknown_property="error", string_types=basestring,
number_types=(int, float)
):
"""
Initialize a Validator.
If ``stop_on_error`` is ``True`` (default), immediately stop validation
when an error occurs. Otherwise, wait until validation is completed,
then display all validation errors at once.
``unknown_type`` and ``unknown_property`` control what to do when an
unknown type (resp. property) is encountered. By default an error is
raised (``"error"``). Other valid inputs are ``"warn"``, raising a
warning, and ``"skip"`` to ignore.
``string_types`` and ``number_types`` control which Python types are
considered to be JSON ``String``s and ``Number``s respectively. By
default, ``basestring`` (which means, ``str`` + ``unicode``) is used
for ``string_types``, and ``int`` and ``float`` are the number_types.
To override this behavior (e.g. for ``decimal.Decimal``), provide a
type or tuple of types to use (*including* the default types if so
desired).
"""
self.stop_on_error = stop_on_error
self._unknown_type = unknown_type
self._unknown_property = unknown_property
self._types = dict(
self._TYPES, string=string_types, number=number_types
)
self._types[u"any"] = tuple(self._types.values())
def _is_type(self, instance, type):
"""
Check if an ``instance`` is of the provided ``type``.
"""
py_type = self._types.get(type)
if py_type is None:
return self._schema_error(
self._unknown_type, u"%r is not a known type" % (type,)
)
# the only thing we're careful about here is evading bool inheriting
# from int, so let's be even dirtier than usual
elif (
# it's not a bool, so no worries
not isinstance(instance, bool) or
# it is a bool, but we're checking for a bool, so no worries
(
py_type is bool or
isinstance(py_type, tuple) and bool in py_type
)
):
return isinstance(instance, py_type)
def _error(self, msg):
"""
Something failed to validate. ``msg`` will have details.
"""
if self.stop_on_error:
raise ValidationError(msg)
else:
self._errors.append(msg)
def _schema_error(self, level, msg):
if level == "skip":
return
elif level == "warn":
warnings.warn(msg)
else:
raise SchemaError(msg)
def is_valid(self, instance, schema):
"""
Check if the ``instance`` is valid under the ``schema``.
Returns a bool containing whether validation succeeded.
"""
# HACK: Temporarily patches self._errors, just in case we're not
# stopping on errors, so that errors raised during the validity
# check don't pollute self._errors as part of a subroutine
current_errors = self._errors
try:
self.validate(instance, schema)
except ValidationError:
return False
else:
if self._errors:
return False
return True
finally:
self._errors = current_errors
def _validate(self, instance, schema):
"""
Validate an ``instance`` under the given ``schema``.
"""
for k, v in schema.iteritems():
if k in self._SKIPPED:
continue
validator = getattr(self, u"validate_%s" % (k,), None)
if validator is None:
self._schema_error(
self._unknown_property,
u"%r is not a known schema property" % (k,)
)
return
validator(v, instance, schema)
def validate(self, instance, schema):
self._errors = []
self._validate(instance, schema)
if self._errors:
raise ValidationError(
u"Validation failed with errors (see .errors for details)",
errors=list(self._errors)
)
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_type(instance, "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:
self._error(u"%r is not of type %r" % (instance, _delist(types)))
def validate_properties(self, properties, instance, schema):
for property, subschema in properties.iteritems():
if property in instance:
dependencies = _list(subschema.get(u"dependencies", []))
if self._is_type(dependencies, "object"):
self._validate(instance, dependencies)
else:
missing = (d for d in dependencies if d not in instance)
first = next(missing, None)
if first is not None:
self._error(
u"%r is a dependency of %r" % (first, property)
)
self._validate(instance[property], subschema)
elif subschema.get(u"required", False):
self._error(u"%r is a required property" % (property,))
def validate_patternProperties(self, patternProperties, instance, schema):
for pattern, subschema in patternProperties.iteritems():
for k, v in instance.iteritems():
if re.match(pattern, k):
self._validate(v, subschema)
def validate_additionalProperties(self, aP, instance, schema):
# no viewkeys in <2.7, and pypy seems to fail on vk - vk anyhow, so...
extras = set(instance) - set(schema.get(u"properties", {}))
if self._is_type(aP, "object"):
for extra in extras:
self._validate(instance[extra], aP)
elif not aP and extras:
self._error(u"Additional properties are not allowed")
def validate_items(self, items, instance, schema):
if self._is_type(items, "object"):
for item in instance:
self._validate(item, items)
else:
for item, subschema in zip(instance, items):
self._validate(item, subschema)
def validate_additionalItems(self, aI, instance, schema):
if self._is_type(aI, "object"):
for item in instance[len(schema):]:
self._validate(item, aI)
elif not aI and len(instance) > len(schema):
self._error(u"Additional items are not allowed")
def validate_minimum(self, minimum, instance, schema):
if schema.get(u"exclusiveMinimum", False):
failed = instance <= minimum
cmp = u"less than or equal to"
else:
failed = instance < minimum
cmp = u"less than"
if failed:
self._error(
u"%r is %s the minimum of %r" % (instance, cmp, minimum)
)
def validate_maximum(self, maximum, instance, schema):
if schema.get(u"exclusiveMaximum", False):
failed = instance >= maximum
cmp = u"greater than or equal to"
else:
failed = instance > maximum
cmp = u"greater than"
if failed:
self._error(
u"%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:
self._error(u"%r is too short" % (instance,))
def validate_maxItems(self, mI, instance, schema):
if self._is_type(instance, "array") and len(instance) > mI:
self._error(u"%r is too long" % (instance,))
def validate_pattern(self, patrn, instance, schema):
if self._is_type(instance, "string") and not re.match(patrn, instance):
self._error(u"%r does not match %r" % (instance, patrn))
def validate_minLength(self, mL, instance, schema):
if self._is_type(instance, "string") and len(instance) < mL:
self._error(u"%r is too short" % (instance,))
def validate_maxLength(self, mL, instance, schema):
if self._is_type(instance, "string") and len(instance) > mL:
self._error(u"%r is too long" % (instance,))
def validate_enum(self, enums, instance, schema):
if instance not in enums:
self._error(u"%r is not one of %r" % (instance, enums))
def validate_divisibleBy(self, dB, instance, schema):
if isinstance(dB, float):
failed = dB - instance % dB > .0000000001
else:
failed = instance % dB
if failed:
self._error(u"%r is not divisible by %r" % (instance, dB))
def validate_disallow(self, disallow, instance, schema):
disallow = _list(disallow)
if any(self.is_valid(instance, {"type" : [d]}) for d in disallow):
self._error(
u"%r is disallowed for %r" % (_delist(disallow), instance)
)
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 validate(instance, schema, cls=Validator, *args, **kwargs):
"""
Validate an ``instance`` under the given ``schema``.
By default, the :class:`Validator` class from this module is used to
perform the validation. To use another validator, pass it into the ``cls``
argument.
Any other provided positional and keyword arguments will be provided to the
``cls``. See the :class:`Validator` class' docstring for details on the
arguments it accepts.
"""
validator = cls(*args, **kwargs)
validator.validate(instance, schema)
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