294 lines
11 KiB
Python
294 lines
11 KiB
Python
|
"""User input parameter validation.
|
||
|
|
|
||
|
|
This module handles user input parameter validation
|
||
|
|
against a provided input model.
|
||
|
|
|
||
|
|
Note that the objects in this module do *not* mutate any
|
||
|
|
arguments. No type version happens here. It is up to another
|
||
|
|
layer to properly convert arguments to any required types.
|
||
|
|
|
||
|
|
Validation Errors
|
||
|
|
-----------------
|
||
|
|
|
||
|
|
|
||
|
|
"""
|
||
|
|
|
||
|
|
from botocore.compat import six
|
||
|
|
import decimal
|
||
|
|
import json
|
||
|
|
from datetime import datetime
|
||
|
|
|
||
|
|
from botocore.utils import parse_to_aware_datetime
|
||
|
|
from botocore.utils import is_json_value_header
|
||
|
|
from botocore.exceptions import ParamValidationError
|
||
|
|
|
||
|
|
|
||
|
|
def validate_parameters(params, shape):
|
||
|
|
"""Validates input parameters against a schema.
|
||
|
|
|
||
|
|
This is a convenience function that validates parameters against a schema.
|
||
|
|
You can also instantiate and use the ParamValidator class directly if you
|
||
|
|
want more control.
|
||
|
|
|
||
|
|
If there are any validation errors then a ParamValidationError
|
||
|
|
will be raised. If there are no validation errors than no exception
|
||
|
|
is raised and a value of None is returned.
|
||
|
|
|
||
|
|
:param params: The user provided input parameters.
|
||
|
|
|
||
|
|
:type shape: botocore.model.Shape
|
||
|
|
:param shape: The schema which the input parameters should
|
||
|
|
adhere to.
|
||
|
|
|
||
|
|
:raise: ParamValidationError
|
||
|
|
|
||
|
|
"""
|
||
|
|
validator = ParamValidator()
|
||
|
|
report = validator.validate(params, shape)
|
||
|
|
if report.has_errors():
|
||
|
|
raise ParamValidationError(report=report.generate_report())
|
||
|
|
|
||
|
|
|
||
|
|
def type_check(valid_types):
|
||
|
|
def _create_type_check_guard(func):
|
||
|
|
def _on_passes_type_check(self, param, shape, errors, name):
|
||
|
|
if _type_check(param, errors, name):
|
||
|
|
return func(self, param, shape, errors, name)
|
||
|
|
|
||
|
|
def _type_check(param, errors, name):
|
||
|
|
if not isinstance(param, valid_types):
|
||
|
|
valid_type_names = [six.text_type(t) for t in valid_types]
|
||
|
|
errors.report(name, 'invalid type', param=param,
|
||
|
|
valid_types=valid_type_names)
|
||
|
|
return False
|
||
|
|
return True
|
||
|
|
|
||
|
|
return _on_passes_type_check
|
||
|
|
return _create_type_check_guard
|
||
|
|
|
||
|
|
|
||
|
|
def range_check(name, value, shape, error_type, errors):
|
||
|
|
failed = False
|
||
|
|
min_allowed = float('-inf')
|
||
|
|
max_allowed = float('inf')
|
||
|
|
if 'min' in shape.metadata:
|
||
|
|
min_allowed = shape.metadata['min']
|
||
|
|
if value < min_allowed:
|
||
|
|
failed = True
|
||
|
|
if failed:
|
||
|
|
errors.report(name, error_type, param=value,
|
||
|
|
valid_range=[min_allowed, max_allowed])
|
||
|
|
|
||
|
|
|
||
|
|
class ValidationErrors(object):
|
||
|
|
def __init__(self):
|
||
|
|
self._errors = []
|
||
|
|
|
||
|
|
def has_errors(self):
|
||
|
|
if self._errors:
|
||
|
|
return True
|
||
|
|
return False
|
||
|
|
|
||
|
|
def generate_report(self):
|
||
|
|
error_messages = []
|
||
|
|
for error in self._errors:
|
||
|
|
error_messages.append(self._format_error(error))
|
||
|
|
return '\n'.join(error_messages)
|
||
|
|
|
||
|
|
def _format_error(self, error):
|
||
|
|
error_type, name, additional = error
|
||
|
|
name = self._get_name(name)
|
||
|
|
if error_type == 'missing required field':
|
||
|
|
return 'Missing required parameter in %s: "%s"' % (
|
||
|
|
name, additional['required_name'])
|
||
|
|
elif error_type == 'unknown field':
|
||
|
|
return 'Unknown parameter in %s: "%s", must be one of: %s' % (
|
||
|
|
name, additional['unknown_param'],
|
||
|
|
', '.join(additional['valid_names']))
|
||
|
|
elif error_type == 'invalid type':
|
||
|
|
return 'Invalid type for parameter %s, value: %s, type: %s, ' \
|
||
|
|
'valid types: %s' % (name, additional['param'],
|
||
|
|
str(type(additional['param'])),
|
||
|
|
', '.join(additional['valid_types']))
|
||
|
|
elif error_type == 'invalid range':
|
||
|
|
min_allowed = additional['valid_range'][0]
|
||
|
|
max_allowed = additional['valid_range'][1]
|
||
|
|
return ('Invalid range for parameter %s, value: %s, valid range: '
|
||
|
|
'%s-%s' % (name, additional['param'],
|
||
|
|
min_allowed, max_allowed))
|
||
|
|
elif error_type == 'invalid length':
|
||
|
|
min_allowed = additional['valid_range'][0]
|
||
|
|
max_allowed = additional['valid_range'][1]
|
||
|
|
return ('Invalid length for parameter %s, value: %s, valid range: '
|
||
|
|
'%s-%s' % (name, additional['param'],
|
||
|
|
min_allowed, max_allowed))
|
||
|
|
elif error_type == 'unable to encode to json':
|
||
|
|
return 'Invalid parameter %s must be json serializable: %s' \
|
||
|
|
% (name, additional['type_error'])
|
||
|
|
|
||
|
|
def _get_name(self, name):
|
||
|
|
if not name:
|
||
|
|
return 'input'
|
||
|
|
elif name.startswith('.'):
|
||
|
|
return name[1:]
|
||
|
|
else:
|
||
|
|
return name
|
||
|
|
|
||
|
|
def report(self, name, reason, **kwargs):
|
||
|
|
self._errors.append((reason, name, kwargs))
|
||
|
|
|
||
|
|
|
||
|
|
class ParamValidator(object):
|
||
|
|
"""Validates parameters against a shape model."""
|
||
|
|
|
||
|
|
def validate(self, params, shape):
|
||
|
|
"""Validate parameters against a shape model.
|
||
|
|
|
||
|
|
This method will validate the parameters against a provided shape model.
|
||
|
|
All errors will be collected before returning to the caller. This means
|
||
|
|
that this method will not stop at the first error, it will return all
|
||
|
|
possible errors.
|
||
|
|
|
||
|
|
:param params: User provided dict of parameters
|
||
|
|
:param shape: A shape model describing the expected input.
|
||
|
|
|
||
|
|
:return: A list of errors.
|
||
|
|
|
||
|
|
"""
|
||
|
|
errors = ValidationErrors()
|
||
|
|
self._validate(params, shape, errors, name='')
|
||
|
|
return errors
|
||
|
|
|
||
|
|
def _check_special_validation_cases(self, shape):
|
||
|
|
if is_json_value_header(shape):
|
||
|
|
return self._validate_jsonvalue_string
|
||
|
|
|
||
|
|
def _validate(self, params, shape, errors, name):
|
||
|
|
special_validator = self._check_special_validation_cases(shape)
|
||
|
|
if special_validator:
|
||
|
|
special_validator(params, shape, errors, name)
|
||
|
|
else:
|
||
|
|
getattr(self, '_validate_%s' % shape.type_name)(
|
||
|
|
params, shape, errors, name)
|
||
|
|
|
||
|
|
def _validate_jsonvalue_string(self, params, shape, errors, name):
|
||
|
|
# Check to see if a value marked as a jsonvalue can be dumped to
|
||
|
|
# a json string.
|
||
|
|
try:
|
||
|
|
json.dumps(params)
|
||
|
|
except (ValueError, TypeError) as e:
|
||
|
|
errors.report(name, 'unable to encode to json', type_error=e)
|
||
|
|
|
||
|
|
@type_check(valid_types=(dict,))
|
||
|
|
def _validate_structure(self, params, shape, errors, name):
|
||
|
|
# Validate required fields.
|
||
|
|
for required_member in shape.metadata.get('required', []):
|
||
|
|
if required_member not in params:
|
||
|
|
errors.report(name, 'missing required field',
|
||
|
|
required_name=required_member, user_params=params)
|
||
|
|
members = shape.members
|
||
|
|
known_params = []
|
||
|
|
# Validate known params.
|
||
|
|
for param in params:
|
||
|
|
if param not in members:
|
||
|
|
errors.report(name, 'unknown field', unknown_param=param,
|
||
|
|
valid_names=list(members))
|
||
|
|
else:
|
||
|
|
known_params.append(param)
|
||
|
|
# Validate structure members.
|
||
|
|
for param in known_params:
|
||
|
|
self._validate(params[param], shape.members[param],
|
||
|
|
errors, '%s.%s' % (name, param))
|
||
|
|
|
||
|
|
@type_check(valid_types=six.string_types)
|
||
|
|
def _validate_string(self, param, shape, errors, name):
|
||
|
|
# Validate range. For a string, the min/max contraints
|
||
|
|
# are of the string length.
|
||
|
|
# Looks like:
|
||
|
|
# "WorkflowId":{
|
||
|
|
# "type":"string",
|
||
|
|
# "min":1,
|
||
|
|
# "max":256
|
||
|
|
# }
|
||
|
|
range_check(name, len(param), shape, 'invalid length', errors)
|
||
|
|
|
||
|
|
@type_check(valid_types=(list, tuple))
|
||
|
|
def _validate_list(self, param, shape, errors, name):
|
||
|
|
member_shape = shape.member
|
||
|
|
range_check(name, len(param), shape, 'invalid length', errors)
|
||
|
|
for i, item in enumerate(param):
|
||
|
|
self._validate(item, member_shape, errors, '%s[%s]' % (name, i))
|
||
|
|
|
||
|
|
@type_check(valid_types=(dict,))
|
||
|
|
def _validate_map(self, param, shape, errors, name):
|
||
|
|
key_shape = shape.key
|
||
|
|
value_shape = shape.value
|
||
|
|
for key, value in param.items():
|
||
|
|
self._validate(key, key_shape, errors, "%s (key: %s)"
|
||
|
|
% (name, key))
|
||
|
|
self._validate(value, value_shape, errors, '%s.%s' % (name, key))
|
||
|
|
|
||
|
|
@type_check(valid_types=six.integer_types)
|
||
|
|
def _validate_integer(self, param, shape, errors, name):
|
||
|
|
range_check(name, param, shape, 'invalid range', errors)
|
||
|
|
|
||
|
|
def _validate_blob(self, param, shape, errors, name):
|
||
|
|
if isinstance(param, (bytes, bytearray, six.text_type)):
|
||
|
|
return
|
||
|
|
elif hasattr(param, 'read'):
|
||
|
|
# File like objects are also allowed for blob types.
|
||
|
|
return
|
||
|
|
else:
|
||
|
|
errors.report(name, 'invalid type', param=param,
|
||
|
|
valid_types=[str(bytes), str(bytearray),
|
||
|
|
'file-like object'])
|
||
|
|
|
||
|
|
@type_check(valid_types=(bool,))
|
||
|
|
def _validate_boolean(self, param, shape, errors, name):
|
||
|
|
pass
|
||
|
|
|
||
|
|
@type_check(valid_types=(float, decimal.Decimal) + six.integer_types)
|
||
|
|
def _validate_double(self, param, shape, errors, name):
|
||
|
|
range_check(name, param, shape, 'invalid range', errors)
|
||
|
|
|
||
|
|
_validate_float = _validate_double
|
||
|
|
|
||
|
|
@type_check(valid_types=six.integer_types)
|
||
|
|
def _validate_long(self, param, shape, errors, name):
|
||
|
|
range_check(name, param, shape, 'invalid range', errors)
|
||
|
|
|
||
|
|
def _validate_timestamp(self, param, shape, errors, name):
|
||
|
|
# We don't use @type_check because datetimes are a bit
|
||
|
|
# more flexible. You can either provide a datetime
|
||
|
|
# object, or a string that parses to a datetime.
|
||
|
|
is_valid_type = self._type_check_datetime(param)
|
||
|
|
if not is_valid_type:
|
||
|
|
valid_type_names = [six.text_type(datetime), 'timestamp-string']
|
||
|
|
errors.report(name, 'invalid type', param=param,
|
||
|
|
valid_types=valid_type_names)
|
||
|
|
|
||
|
|
def _type_check_datetime(self, value):
|
||
|
|
try:
|
||
|
|
parse_to_aware_datetime(value)
|
||
|
|
return True
|
||
|
|
except (TypeError, ValueError, AttributeError):
|
||
|
|
# Yes, dateutil can sometimes raise an AttributeError
|
||
|
|
# when parsing timestamps.
|
||
|
|
return False
|
||
|
|
|
||
|
|
|
||
|
|
class ParamValidationDecorator(object):
|
||
|
|
def __init__(self, param_validator, serializer):
|
||
|
|
self._param_validator = param_validator
|
||
|
|
self._serializer = serializer
|
||
|
|
|
||
|
|
def serialize_to_request(self, parameters, operation_model):
|
||
|
|
input_shape = operation_model.input_shape
|
||
|
|
if input_shape is not None:
|
||
|
|
report = self._param_validator.validate(parameters,
|
||
|
|
operation_model.input_shape)
|
||
|
|
if report.has_errors():
|
||
|
|
raise ParamValidationError(report=report.generate_report())
|
||
|
|
return self._serializer.serialize_to_request(parameters,
|
||
|
|
operation_model)
|