xbmcbackup/resources/lib/dropbox/stone_validators.py

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"""
Defines classes to represent each Stone type in Python. These classes should
be used to validate Python objects and normalize them for a given type.
The data types defined here should not be specific to an RPC or serialization
format.
This module should be dropped into a project that requires the use of Stone. In
the future, this could be imported from a pre-installed Python package, rather
than being added to a project.
"""
from __future__ import absolute_import, unicode_literals
from abc import ABCMeta, abstractmethod
import datetime
import hashlib
import math
import numbers
import re
import six
_MYPY = False
if _MYPY:
import typing # noqa: F401 # pylint: disable=import-error,unused-import,useless-suppression
# See <http://python3porting.com/differences.html#buffer>
if six.PY3:
_binary_types = (bytes, memoryview) # noqa: E501,F821 # pylint: disable=undefined-variable,useless-suppression
else:
_binary_types = (bytes, buffer) # noqa: E501,F821 # pylint: disable=undefined-variable,useless-suppression
class ValidationError(Exception):
"""Raised when a value doesn't pass validation by its validator."""
def __init__(self, message, parent=None):
"""
Args:
message (str): Error message detailing validation failure.
parent (str): Adds the parent as the closest reference point for
the error. Use :meth:`add_parent` to add more.
"""
super(ValidationError, self).__init__(message)
self.message = message
self._parents = []
if parent:
self._parents.append(parent)
def add_parent(self, parent):
"""
Args:
parent (str): Adds the parent to the top of the tree of references
that lead to the validator that failed.
"""
self._parents.append(parent)
def __str__(self):
"""
Returns:
str: A descriptive message of the validation error that may also
include the path to the validator that failed.
"""
if self._parents:
return '{}: {}'.format('.'.join(self._parents[::-1]), self.message)
else:
return self.message
def __repr__(self):
# Not a perfect repr, but includes the error location information.
return 'ValidationError(%r)' % six.text_type(self)
def generic_type_name(v):
"""Return a descriptive type name that isn't Python specific. For example,
an int value will return 'integer' rather than 'int'."""
if isinstance(v, bool):
# Must come before any numbers checks since booleans are integers too
return 'boolean'
elif isinstance(v, numbers.Integral):
# Must come before real numbers check since integrals are reals too
return 'integer'
elif isinstance(v, numbers.Real):
return 'float'
elif isinstance(v, (tuple, list)):
return 'list'
elif isinstance(v, six.string_types):
return 'string'
elif v is None:
return 'null'
else:
return type(v).__name__
class Validator(object):
"""All primitive and composite data types should be a subclass of this."""
__metaclass__ = ABCMeta
@abstractmethod
def validate(self, val):
"""Validates that val is of this data type.
Returns: A normalized value if validation succeeds.
Raises: ValidationError
"""
pass
def has_default(self):
return False
def get_default(self):
raise AssertionError('No default available.')
class Primitive(Validator):
"""A basic type that is defined by Stone."""
# pylint: disable=abstract-method
pass
class Boolean(Primitive):
def validate(self, val):
if not isinstance(val, bool):
raise ValidationError('%r is not a valid boolean' % val)
return val
class Integer(Primitive):
"""
Do not use this class directly. Extend it and specify a 'minimum' and
'maximum' value as class variables for a more restrictive integer range.
"""
minimum = None # type: typing.Optional[int]
maximum = None # type: typing.Optional[int]
def __init__(self, min_value=None, max_value=None):
"""
A more restrictive minimum or maximum value can be specified than the
range inherent to the defined type.
"""
if min_value is not None:
assert isinstance(min_value, numbers.Integral), \
'min_value must be an integral number'
assert min_value >= self.minimum, \
'min_value cannot be less than the minimum value for this ' \
'type (%d < %d)' % (min_value, self.minimum)
self.minimum = min_value
if max_value is not None:
assert isinstance(max_value, numbers.Integral), \
'max_value must be an integral number'
assert max_value <= self.maximum, \
'max_value cannot be greater than the maximum value for ' \
'this type (%d < %d)' % (max_value, self.maximum)
self.maximum = max_value
def validate(self, val):
if not isinstance(val, numbers.Integral):
raise ValidationError('expected integer, got %s'
% generic_type_name(val))
elif not (self.minimum <= val <= self.maximum):
raise ValidationError('%d is not within range [%d, %d]'
% (val, self.minimum, self.maximum))
return val
def __repr__(self):
return '%s()' % self.__class__.__name__
class Int32(Integer):
minimum = -2**31
maximum = 2**31 - 1
class UInt32(Integer):
minimum = 0
maximum = 2**32 - 1
class Int64(Integer):
minimum = -2**63
maximum = 2**63 - 1
class UInt64(Integer):
minimum = 0
maximum = 2**64 - 1
class Real(Primitive):
"""
Do not use this class directly. Extend it and optionally set a 'minimum'
and 'maximum' value to enforce a range that's a subset of the Python float
implementation. Python floats are doubles.
"""
minimum = None # type: typing.Optional[float]
maximum = None # type: typing.Optional[float]
def __init__(self, min_value=None, max_value=None):
"""
A more restrictive minimum or maximum value can be specified than the
range inherent to the defined type.
"""
if min_value is not None:
assert isinstance(min_value, numbers.Real), \
'min_value must be a real number'
if not isinstance(min_value, float):
try:
min_value = float(min_value)
except OverflowError:
raise AssertionError('min_value is too small for a float')
if self.minimum is not None and min_value < self.minimum:
raise AssertionError('min_value cannot be less than the '
'minimum value for this type (%f < %f)' %
(min_value, self.minimum))
self.minimum = min_value
if max_value is not None:
assert isinstance(max_value, numbers.Real), \
'max_value must be a real number'
if not isinstance(max_value, float):
try:
max_value = float(max_value)
except OverflowError:
raise AssertionError('max_value is too large for a float')
if self.maximum is not None and max_value > self.maximum:
raise AssertionError('max_value cannot be greater than the '
'maximum value for this type (%f < %f)' %
(max_value, self.maximum))
self.maximum = max_value
def validate(self, val):
if not isinstance(val, numbers.Real):
raise ValidationError('expected real number, got %s' %
generic_type_name(val))
if not isinstance(val, float):
# This checks for the case where a number is passed in with a
# magnitude larger than supported by float64.
try:
val = float(val)
except OverflowError:
raise ValidationError('too large for float')
if math.isnan(val) or math.isinf(val):
raise ValidationError('%f values are not supported' % val)
if self.minimum is not None and val < self.minimum:
raise ValidationError('%f is not greater than %f' %
(val, self.minimum))
if self.maximum is not None and val > self.maximum:
raise ValidationError('%f is not less than %f' %
(val, self.maximum))
return val
def __repr__(self):
return '%s()' % self.__class__.__name__
class Float32(Real):
# Maximum and minimums from the IEEE 754-1985 standard
minimum = -3.40282 * 10**38
maximum = 3.40282 * 10**38
class Float64(Real):
pass
class String(Primitive):
"""Represents a unicode string."""
def __init__(self, min_length=None, max_length=None, pattern=None):
if min_length is not None:
assert isinstance(min_length, numbers.Integral), \
'min_length must be an integral number'
assert min_length >= 0, 'min_length must be >= 0'
if max_length is not None:
assert isinstance(max_length, numbers.Integral), \
'max_length must be an integral number'
assert max_length > 0, 'max_length must be > 0'
if min_length and max_length:
assert max_length >= min_length, 'max_length must be >= min_length'
if pattern is not None:
assert isinstance(pattern, six.string_types), \
'pattern must be a string'
self.min_length = min_length
self.max_length = max_length
self.pattern = pattern
self.pattern_re = None
if pattern:
try:
self.pattern_re = re.compile(r"\A(?:" + pattern + r")\Z")
except re.error as e:
raise AssertionError('Regex {!r} failed: {}'.format(
pattern, e.args[0]))
def validate(self, val):
"""
A unicode string of the correct length and pattern will pass validation.
In PY2, we enforce that a str type must be valid utf-8, and a unicode
string will be returned.
"""
if not isinstance(val, six.string_types):
raise ValidationError("'%s' expected to be a string, got %s"
% (val, generic_type_name(val)))
if not six.PY3 and isinstance(val, str):
try:
val = val.decode('utf-8')
except UnicodeDecodeError:
raise ValidationError("'%s' was not valid utf-8")
if self.max_length is not None and len(val) > self.max_length:
raise ValidationError("'%s' must be at most %d characters, got %d"
% (val, self.max_length, len(val)))
if self.min_length is not None and len(val) < self.min_length:
raise ValidationError("'%s' must be at least %d characters, got %d"
% (val, self.min_length, len(val)))
if self.pattern and not self.pattern_re.match(val):
raise ValidationError("'%s' did not match pattern '%s'"
% (val, self.pattern))
return val
class Bytes(Primitive):
def __init__(self, min_length=None, max_length=None):
if min_length is not None:
assert isinstance(min_length, numbers.Integral), \
'min_length must be an integral number'
assert min_length >= 0, 'min_length must be >= 0'
if max_length is not None:
assert isinstance(max_length, numbers.Integral), \
'max_length must be an integral number'
assert max_length > 0, 'max_length must be > 0'
if min_length is not None and max_length is not None:
assert max_length >= min_length, 'max_length must be >= min_length'
self.min_length = min_length
self.max_length = max_length
def validate(self, val):
if not isinstance(val, _binary_types):
raise ValidationError("expected bytes type, got %s"
% generic_type_name(val))
elif self.max_length is not None and len(val) > self.max_length:
raise ValidationError("'%s' must have at most %d bytes, got %d"
% (val, self.max_length, len(val)))
elif self.min_length is not None and len(val) < self.min_length:
raise ValidationError("'%s' has fewer than %d bytes, got %d"
% (val, self.min_length, len(val)))
return val
class Timestamp(Primitive):
"""Note that while a format is specified, it isn't used in validation
since a native Python datetime object is preferred. The format, however,
can and should be used by serializers."""
def __init__(self, fmt):
"""fmt must be composed of format codes that the C standard (1989)
supports, most notably in its strftime() function."""
assert isinstance(fmt, six.text_type), 'format must be a string'
self.format = fmt
def validate(self, val):
if not isinstance(val, datetime.datetime):
raise ValidationError('expected timestamp, got %s'
% generic_type_name(val))
elif val.tzinfo is not None and \
val.tzinfo.utcoffset(val).total_seconds() != 0:
raise ValidationError('timestamp should have either a UTC '
'timezone or none set at all')
return val
class Composite(Validator):
"""Validator for a type that builds on other primitive and composite
types."""
# pylint: disable=abstract-method
pass
class List(Composite):
"""Assumes list contents are homogeneous with respect to types."""
def __init__(self, item_validator, min_items=None, max_items=None):
"""Every list item will be validated with item_validator."""
self.item_validator = item_validator
if min_items is not None:
assert isinstance(min_items, numbers.Integral), \
'min_items must be an integral number'
assert min_items >= 0, 'min_items must be >= 0'
if max_items is not None:
assert isinstance(max_items, numbers.Integral), \
'max_items must be an integral number'
assert max_items > 0, 'max_items must be > 0'
if min_items is not None and max_items is not None:
assert max_items >= min_items, 'max_items must be >= min_items'
self.min_items = min_items
self.max_items = max_items
def validate(self, val):
if not isinstance(val, (tuple, list)):
raise ValidationError('%r is not a valid list' % val)
elif self.max_items is not None and len(val) > self.max_items:
raise ValidationError('%r has more than %s items'
% (val, self.max_items))
elif self.min_items is not None and len(val) < self.min_items:
raise ValidationError('%r has fewer than %s items'
% (val, self.min_items))
return [self.item_validator.validate(item) for item in val]
class Map(Composite):
"""Assumes map keys and values are homogeneous with respect to types."""
def __init__(self, key_validator, value_validator):
"""
Every Map key/value pair will be validated with item_validator.
key validators must be a subclass of a String validator
"""
self.key_validator = key_validator
self.value_validator = value_validator
def validate(self, val):
if not isinstance(val, dict):
raise ValidationError('%r is not a valid dict' % val)
return {
self.key_validator.validate(key):
self.value_validator.validate(value) for key, value in val.items()
}
class Struct(Composite):
def __init__(self, definition):
"""
Args:
definition (class): A generated class representing a Stone struct
from a spec. Must have a _fields_ attribute with the following
structure:
_fields_ = [(field_name, validator), ...]
where
field_name: Name of the field (str).
validator: Validator object.
"""
super(Struct, self).__init__()
self.definition = definition
def validate(self, val):
"""
For a val to pass validation, val must be of the correct type and have
all required fields present.
"""
self.validate_type_only(val)
self.validate_fields_only(val)
return val
def validate_with_permissions(self, val, caller_permissions):
"""
For a val to pass validation, val must be of the correct type and have
all required permissioned fields present. Should only be called
for callers with extra permissions.
"""
self.validate(val)
self.validate_fields_only_with_permissions(val, caller_permissions)
return val
def validate_fields_only(self, val):
"""
To pass field validation, no required field should be missing.
This method assumes that the contents of each field have already been
validated on assignment, so it's merely a presence check.
FIXME(kelkabany): Since the definition object does not maintain a list
of which fields are required, all fields are scanned.
"""
for field_name in self.definition._all_field_names_:
if not hasattr(val, field_name):
raise ValidationError("missing required field '%s'" %
field_name)
def validate_fields_only_with_permissions(self, val, caller_permissions):
"""
To pass field validation, no required field should be missing.
This method assumes that the contents of each field have already been
validated on assignment, so it's merely a presence check.
Should only be called for callers with extra permissions.
"""
self.validate_fields_only(val)
# check if type has been patched
for extra_permission in caller_permissions.permissions:
all_field_names = '_all_{}_field_names_'.format(extra_permission)
for field_name in getattr(self.definition, all_field_names, set()):
if not hasattr(val, field_name):
raise ValidationError("missing required field '%s'" % field_name)
def validate_type_only(self, val):
"""
Use this when you only want to validate that the type of an object
is correct, but not yet validate each field.
"""
# Since the definition maintains the list of fields for serialization,
# we're okay with a subclass that might have extra information. This
# makes it easier to return one subclass for two routes, one of which
# relies on the parent class.
if not isinstance(val, self.definition):
raise ValidationError('expected type %s, got %s' %
(self.definition.__name__, generic_type_name(val)))
def has_default(self):
return not self.definition._has_required_fields
def get_default(self):
assert not self.definition._has_required_fields, 'No default available.'
return self.definition()
class StructTree(Struct):
"""Validator for structs with enumerated subtypes.
NOTE: validate_fields_only() validates the fields known to this base
struct, but does not do any validation specific to the subtype.
"""
# See PyCQA/pylint#1043 for why this is disabled; this should show up
# as a usless-suppression (and can be removed) once a fix is released
def __init__(self, definition): # pylint: disable=useless-super-delegation
super(StructTree, self).__init__(definition)
class Union(Composite):
def __init__(self, definition):
"""
Args:
definition (class): A generated class representing a Stone union
from a spec. Must have a _tagmap attribute with the following
structure:
_tagmap = {field_name: validator, ...}
where
field_name (str): Tag name.
validator (Validator): Tag value validator.
"""
self.definition = definition
def validate(self, val):
"""
For a val to pass validation, it must have a _tag set. This assumes
that the object validated that _tag is a valid tag, and that any
associated value has also been validated.
"""
self.validate_type_only(val)
if not hasattr(val, '_tag') or val._tag is None:
raise ValidationError('no tag set')
return val
def validate_type_only(self, val):
"""
Use this when you only want to validate that the type of an object
is correct, but not yet validate each field.
We check whether val is a Python parent class of the definition. This
is because Union subtyping works in the opposite direction of Python
inheritance. For example, if a union U2 extends U1 in Python, this
validator will accept U1 in places where U2 is expected.
"""
if not issubclass(self.definition, type(val)):
raise ValidationError('expected type %s or subtype, got %s' %
(self.definition.__name__, generic_type_name(val)))
class Void(Primitive):
def validate(self, val):
if val is not None:
raise ValidationError('expected NoneType, got %s' %
generic_type_name(val))
def has_default(self):
return True
def get_default(self):
return None
class Nullable(Validator):
def __init__(self, validator):
assert isinstance(validator, (Primitive, Composite)), \
'validator must be for a primitive or composite type'
assert not isinstance(validator, Nullable), \
'nullables cannot be stacked'
assert not isinstance(validator, Void), \
'void cannot be made nullable'
self.validator = validator
def validate(self, val):
if val is None:
return
else:
return self.validator.validate(val)
def validate_type_only(self, val):
"""Use this only if Nullable is wrapping a Composite."""
if val is None:
return
else:
return self.validator.validate_type_only(val)
def has_default(self):
return True
def get_default(self):
return None
class Redactor(object):
def __init__(self, regex):
"""
Args:
regex: What parts of the field to redact.
"""
self.regex = regex
@abstractmethod
def apply(self, val):
"""Redacts information from annotated field.
Returns: A redacted version of the string provided.
"""
pass
def _get_matches(self, val):
if not self.regex:
return None
try:
return re.search(self.regex, val)
except TypeError:
return None
class HashRedactor(Redactor):
def apply(self, val):
matches = self._get_matches(val)
val_to_hash = str(val) if isinstance(val, int) or isinstance(val, float) else val
try:
# add string literal to ensure unicode
hashed = hashlib.md5(val_to_hash.encode('utf-8')).hexdigest() + ''
except [AttributeError, ValueError]:
hashed = None
if matches:
blotted = '***'.join(matches.groups())
if hashed:
return '{} ({})'.format(hashed, blotted)
return blotted
return hashed
class BlotRedactor(Redactor):
def apply(self, val):
matches = self._get_matches(val)
if matches:
return '***'.join(matches.groups())
return '********'