mirror of
https://github.com/PiBrewing/craftbeerpi4.git
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1301 lines
43 KiB
Python
1301 lines
43 KiB
Python
import collections
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import inspect
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import re
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from functools import wraps
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import sys
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from contextlib import contextmanager
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import itertools
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from voluptuous import error as er
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if sys.version_info >= (3,):
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long = int
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unicode = str
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basestring = str
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ifilter = filter
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def iteritems(d):
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return d.items()
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else:
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from itertools import ifilter
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def iteritems(d):
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return d.iteritems()
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if sys.version_info >= (3, 3):
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_Mapping = collections.abc.Mapping
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else:
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_Mapping = collections.Mapping
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"""Schema validation for Python data structures.
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Given eg. a nested data structure like this:
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{
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'exclude': ['Users', 'Uptime'],
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'include': [],
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'set': {
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'snmp_community': 'public',
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'snmp_timeout': 15,
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'snmp_version': '2c',
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},
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'targets': {
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'localhost': {
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'exclude': ['Uptime'],
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'features': {
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'Uptime': {
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'retries': 3,
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},
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'Users': {
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'snmp_community': 'monkey',
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'snmp_port': 15,
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},
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},
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'include': ['Users'],
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'set': {
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'snmp_community': 'monkeys',
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},
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},
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},
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}
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A schema like this:
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>>> settings = {
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... 'snmp_community': str,
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... 'retries': int,
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... 'snmp_version': All(Coerce(str), Any('3', '2c', '1')),
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... }
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>>> features = ['Ping', 'Uptime', 'Http']
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>>> schema = Schema({
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... 'exclude': features,
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... 'include': features,
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... 'set': settings,
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... 'targets': {
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... 'exclude': features,
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... 'include': features,
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... 'features': {
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... str: settings,
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... },
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... },
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... })
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Validate like so:
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>>> schema({
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... 'set': {
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... 'snmp_community': 'public',
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... 'snmp_version': '2c',
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... },
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... 'targets': {
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... 'exclude': ['Ping'],
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... 'features': {
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... 'Uptime': {'retries': 3},
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... 'Users': {'snmp_community': 'monkey'},
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... },
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... },
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... }) == {
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... 'set': {'snmp_version': '2c', 'snmp_community': 'public'},
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... 'targets': {
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... 'exclude': ['Ping'],
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... 'features': {'Uptime': {'retries': 3},
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... 'Users': {'snmp_community': 'monkey'}}}}
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True
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"""
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# options for extra keys
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PREVENT_EXTRA = 0 # any extra key not in schema will raise an error
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ALLOW_EXTRA = 1 # extra keys not in schema will be included in output
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REMOVE_EXTRA = 2 # extra keys not in schema will be excluded from output
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def _isnamedtuple(obj):
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return isinstance(obj, tuple) and hasattr(obj, '_fields')
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primitive_types = (str, unicode, bool, int, float)
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class Undefined(object):
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def __nonzero__(self):
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return False
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def __repr__(self):
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return '...'
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UNDEFINED = Undefined()
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def Self():
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raise er.SchemaError('"Self" should never be called')
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def default_factory(value):
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if value is UNDEFINED or callable(value):
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return value
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return lambda: value
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@contextmanager
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def raises(exc, msg=None, regex=None):
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try:
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yield
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except exc as e:
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if msg is not None:
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assert str(e) == msg, '%r != %r' % (str(e), msg)
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if regex is not None:
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assert re.search(regex, str(e)), '%r does not match %r' % (str(e), regex)
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def Extra(_):
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"""Allow keys in the data that are not present in the schema."""
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raise er.SchemaError('"Extra" should never be called')
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# As extra() is never called there's no way to catch references to the
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# deprecated object, so we just leave an alias here instead.
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extra = Extra
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class Schema(object):
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"""A validation schema.
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The schema is a Python tree-like structure where nodes are pattern
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matched against corresponding trees of values.
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Nodes can be values, in which case a direct comparison is used, types,
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in which case an isinstance() check is performed, or callables, which will
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validate and optionally convert the value.
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We can equate schemas also.
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For Example:
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>>> v = Schema({Required('a'): unicode})
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>>> v1 = Schema({Required('a'): unicode})
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>>> v2 = Schema({Required('b'): unicode})
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>>> assert v == v1
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>>> assert v != v2
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"""
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_extra_to_name = {
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REMOVE_EXTRA: 'REMOVE_EXTRA',
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ALLOW_EXTRA: 'ALLOW_EXTRA',
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PREVENT_EXTRA: 'PREVENT_EXTRA',
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}
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def __init__(self, schema, required=False, extra=PREVENT_EXTRA):
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"""Create a new Schema.
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:param schema: Validation schema. See :module:`voluptuous` for details.
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:param required: Keys defined in the schema must be in the data.
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:param extra: Specify how extra keys in the data are treated:
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- :const:`~voluptuous.PREVENT_EXTRA`: to disallow any undefined
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extra keys (raise ``Invalid``).
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- :const:`~voluptuous.ALLOW_EXTRA`: to include undefined extra
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keys in the output.
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- :const:`~voluptuous.REMOVE_EXTRA`: to exclude undefined extra keys
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from the output.
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- Any value other than the above defaults to
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:const:`~voluptuous.PREVENT_EXTRA`
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"""
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self.schema = schema
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self.required = required
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self.extra = int(extra) # ensure the value is an integer
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self._compiled = self._compile(schema)
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@classmethod
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def infer(cls, data, **kwargs):
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"""Create a Schema from concrete data (e.g. an API response).
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For example, this will take a dict like:
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{
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'foo': 1,
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'bar': {
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'a': True,
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'b': False
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},
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'baz': ['purple', 'monkey', 'dishwasher']
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}
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And return a Schema:
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{
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'foo': int,
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'bar': {
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'a': bool,
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'b': bool
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},
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'baz': [str]
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}
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Note: only very basic inference is supported.
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"""
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def value_to_schema_type(value):
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if isinstance(value, dict):
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if len(value) == 0:
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return dict
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return {k: value_to_schema_type(v)
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for k, v in iteritems(value)}
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if isinstance(value, list):
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if len(value) == 0:
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return list
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else:
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return [value_to_schema_type(v)
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for v in value]
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return type(value)
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return cls(value_to_schema_type(data), **kwargs)
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def __eq__(self, other):
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if not isinstance(other, Schema):
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return False
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return other.schema == self.schema
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def __ne__(self, other):
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return not (self == other)
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def __str__(self):
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return str(self.schema)
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def __repr__(self):
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return "<Schema(%s, extra=%s, required=%s) object at 0x%x>" % (
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self.schema, self._extra_to_name.get(self.extra, '??'),
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self.required, id(self))
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def __call__(self, data):
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"""Validate data against this schema."""
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try:
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return self._compiled([], data)
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except er.MultipleInvalid:
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raise
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except er.Invalid as e:
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raise er.MultipleInvalid([e])
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# return self.validate([], self.schema, data)
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def _compile(self, schema):
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if schema is Extra:
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return lambda _, v: v
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if schema is Self:
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return lambda p, v: self._compiled(p, v)
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elif hasattr(schema, "__voluptuous_compile__"):
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return schema.__voluptuous_compile__(self)
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if isinstance(schema, Object):
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return self._compile_object(schema)
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if isinstance(schema, _Mapping):
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return self._compile_dict(schema)
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elif isinstance(schema, list):
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return self._compile_list(schema)
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elif isinstance(schema, tuple):
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return self._compile_tuple(schema)
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elif isinstance(schema, (frozenset, set)):
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return self._compile_set(schema)
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type_ = type(schema)
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if inspect.isclass(schema):
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type_ = schema
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if type_ in (bool, bytes, int, long, str, unicode, float, complex, object,
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list, dict, type(None)) or callable(schema):
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return _compile_scalar(schema)
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raise er.SchemaError('unsupported schema data type %r' %
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type(schema).__name__)
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def _compile_mapping(self, schema, invalid_msg=None):
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"""Create validator for given mapping."""
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invalid_msg = invalid_msg or 'mapping value'
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# Keys that may be required
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all_required_keys = set(key for key in schema
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if key is not Extra and
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((self.required and not isinstance(key, (Optional, Remove))) or
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isinstance(key, Required)))
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# Keys that may have defaults
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all_default_keys = set(key for key in schema
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if isinstance(key, Required) or
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isinstance(key, Optional))
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_compiled_schema = {}
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for skey, svalue in iteritems(schema):
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new_key = self._compile(skey)
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new_value = self._compile(svalue)
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_compiled_schema[skey] = (new_key, new_value)
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candidates = list(_iterate_mapping_candidates(_compiled_schema))
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# After we have the list of candidates in the correct order, we want to apply some optimization so that each
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# key in the data being validated will be matched against the relevant schema keys only.
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# No point in matching against different keys
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additional_candidates = []
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candidates_by_key = {}
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for skey, (ckey, cvalue) in candidates:
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if type(skey) in primitive_types:
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candidates_by_key.setdefault(skey, []).append((skey, (ckey, cvalue)))
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elif isinstance(skey, Marker) and type(skey.schema) in primitive_types:
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candidates_by_key.setdefault(skey.schema, []).append((skey, (ckey, cvalue)))
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else:
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# These are wildcards such as 'int', 'str', 'Remove' and others which should be applied to all keys
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additional_candidates.append((skey, (ckey, cvalue)))
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def validate_mapping(path, iterable, out):
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required_keys = all_required_keys.copy()
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# Build a map of all provided key-value pairs.
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# The type(out) is used to retain ordering in case a ordered
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# map type is provided as input.
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key_value_map = type(out)()
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for key, value in iterable:
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key_value_map[key] = value
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# Insert default values for non-existing keys.
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for key in all_default_keys:
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if not isinstance(key.default, Undefined) and \
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key.schema not in key_value_map:
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# A default value has been specified for this missing
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# key, insert it.
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key_value_map[key.schema] = key.default()
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error = None
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errors = []
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for key, value in key_value_map.items():
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key_path = path + [key]
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remove_key = False
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# Optimization. Validate against the matching key first, then fallback to the rest
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relevant_candidates = itertools.chain(candidates_by_key.get(key, []), additional_candidates)
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# compare each given key/value against all compiled key/values
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# schema key, (compiled key, compiled value)
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for skey, (ckey, cvalue) in relevant_candidates:
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try:
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new_key = ckey(key_path, key)
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except er.Invalid as e:
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if len(e.path) > len(key_path):
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raise
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if not error or len(e.path) > len(error.path):
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error = e
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continue
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# Backtracking is not performed once a key is selected, so if
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# the value is invalid we immediately throw an exception.
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exception_errors = []
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# check if the key is marked for removal
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is_remove = new_key is Remove
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try:
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cval = cvalue(key_path, value)
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# include if it's not marked for removal
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if not is_remove:
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out[new_key] = cval
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else:
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remove_key = True
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continue
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except er.MultipleInvalid as e:
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exception_errors.extend(e.errors)
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except er.Invalid as e:
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exception_errors.append(e)
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if exception_errors:
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if is_remove or remove_key:
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continue
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for err in exception_errors:
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if len(err.path) <= len(key_path):
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err.error_type = invalid_msg
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errors.append(err)
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# If there is a validation error for a required
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# key, this means that the key was provided.
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# Discard the required key so it does not
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# create an additional, noisy exception.
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required_keys.discard(skey)
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break
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# Key and value okay, mark as found in case it was
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# a Required() field.
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required_keys.discard(skey)
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break
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else:
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if remove_key:
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# remove key
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continue
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elif self.extra == ALLOW_EXTRA:
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out[key] = value
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elif self.extra != REMOVE_EXTRA:
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errors.append(er.Invalid('extra keys not allowed', key_path))
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# else REMOVE_EXTRA: ignore the key so it's removed from output
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# for any required keys left that weren't found and don't have defaults:
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for key in required_keys:
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msg = key.msg if hasattr(key, 'msg') and key.msg else 'required key not provided'
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errors.append(er.RequiredFieldInvalid(msg, path + [key]))
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if errors:
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raise er.MultipleInvalid(errors)
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return out
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return validate_mapping
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def _compile_object(self, schema):
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"""Validate an object.
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Has the same behavior as dictionary validator but work with object
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attributes.
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For example:
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>>> class Structure(object):
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... def __init__(self, one=None, three=None):
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... self.one = one
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... self.three = three
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...
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>>> validate = Schema(Object({'one': 'two', 'three': 'four'}, cls=Structure))
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>>> with raises(er.MultipleInvalid, "not a valid value for object value @ data['one']"):
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... validate(Structure(one='three'))
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"""
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base_validate = self._compile_mapping(
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schema, invalid_msg='object value')
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def validate_object(path, data):
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if schema.cls is not UNDEFINED and not isinstance(data, schema.cls):
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raise er.ObjectInvalid('expected a {0!r}'.format(schema.cls), path)
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iterable = _iterate_object(data)
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iterable = ifilter(lambda item: item[1] is not None, iterable)
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out = base_validate(path, iterable, {})
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return type(data)(**out)
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return validate_object
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def _compile_dict(self, schema):
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"""Validate a dictionary.
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A dictionary schema can contain a set of values, or at most one
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validator function/type.
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A dictionary schema will only validate a dictionary:
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>>> validate = Schema({})
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>>> with raises(er.MultipleInvalid, 'expected a dictionary'):
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... validate([])
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An invalid dictionary value:
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>>> validate = Schema({'one': 'two', 'three': 'four'})
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>>> with raises(er.MultipleInvalid, "not a valid value for dictionary value @ data['one']"):
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... validate({'one': 'three'})
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An invalid key:
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>>> with raises(er.MultipleInvalid, "extra keys not allowed @ data['two']"):
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... validate({'two': 'three'})
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Validation function, in this case the "int" type:
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>>> validate = Schema({'one': 'two', 'three': 'four', int: str})
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Valid integer input:
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>>> validate({10: 'twenty'})
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{10: 'twenty'}
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By default, a "type" in the schema (in this case "int") will be used
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purely to validate that the corresponding value is of that type. It
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will not Coerce the value:
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>>> with raises(er.MultipleInvalid, "extra keys not allowed @ data['10']"):
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... validate({'10': 'twenty'})
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Wrap them in the Coerce() function to achieve this:
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>>> from voluptuous import Coerce
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>>> validate = Schema({'one': 'two', 'three': 'four',
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... Coerce(int): str})
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>>> validate({'10': 'twenty'})
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{10: 'twenty'}
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Custom message for required key
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>>> validate = Schema({Required('one', 'required'): 'two'})
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>>> with raises(er.MultipleInvalid, "required @ data['one']"):
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... validate({})
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(This is to avoid unexpected surprises.)
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Multiple errors for nested field in a dict:
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>>> validate = Schema({
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... 'adict': {
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... 'strfield': str,
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... 'intfield': int
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... }
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... })
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>>> try:
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... validate({
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... 'adict': {
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... 'strfield': 123,
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... 'intfield': 'one'
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... }
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... })
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... except er.MultipleInvalid as e:
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... print(sorted(str(i) for i in e.errors)) # doctest: +NORMALIZE_WHITESPACE
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["expected int for dictionary value @ data['adict']['intfield']",
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"expected str for dictionary value @ data['adict']['strfield']"]
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"""
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base_validate = self._compile_mapping(
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schema, invalid_msg='dictionary value')
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groups_of_exclusion = {}
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groups_of_inclusion = {}
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for node in schema:
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if isinstance(node, Exclusive):
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g = groups_of_exclusion.setdefault(node.group_of_exclusion, [])
|
|
g.append(node)
|
|
elif isinstance(node, Inclusive):
|
|
g = groups_of_inclusion.setdefault(node.group_of_inclusion, [])
|
|
g.append(node)
|
|
|
|
def validate_dict(path, data):
|
|
if not isinstance(data, dict):
|
|
raise er.DictInvalid('expected a dictionary', path)
|
|
|
|
errors = []
|
|
for label, group in groups_of_exclusion.items():
|
|
exists = False
|
|
for exclusive in group:
|
|
if exclusive.schema in data:
|
|
if exists:
|
|
msg = exclusive.msg if hasattr(exclusive, 'msg') and exclusive.msg else \
|
|
"two or more values in the same group of exclusion '%s'" % label
|
|
next_path = path + [VirtualPathComponent(label)]
|
|
errors.append(er.ExclusiveInvalid(msg, next_path))
|
|
break
|
|
exists = True
|
|
|
|
if errors:
|
|
raise er.MultipleInvalid(errors)
|
|
|
|
for label, group in groups_of_inclusion.items():
|
|
included = [node.schema in data for node in group]
|
|
if any(included) and not all(included):
|
|
msg = "some but not all values in the same group of inclusion '%s'" % label
|
|
for g in group:
|
|
if hasattr(g, 'msg') and g.msg:
|
|
msg = g.msg
|
|
break
|
|
next_path = path + [VirtualPathComponent(label)]
|
|
errors.append(er.InclusiveInvalid(msg, next_path))
|
|
break
|
|
|
|
if errors:
|
|
raise er.MultipleInvalid(errors)
|
|
|
|
out = data.__class__()
|
|
return base_validate(path, iteritems(data), out)
|
|
|
|
return validate_dict
|
|
|
|
def _compile_sequence(self, schema, seq_type):
|
|
"""Validate a sequence type.
|
|
|
|
This is a sequence of valid values or validators tried in order.
|
|
|
|
>>> validator = Schema(['one', 'two', int])
|
|
>>> validator(['one'])
|
|
['one']
|
|
>>> with raises(er.MultipleInvalid, 'expected int @ data[0]'):
|
|
... validator([3.5])
|
|
>>> validator([1])
|
|
[1]
|
|
"""
|
|
_compiled = [self._compile(s) for s in schema]
|
|
seq_type_name = seq_type.__name__
|
|
|
|
def validate_sequence(path, data):
|
|
if not isinstance(data, seq_type):
|
|
raise er.SequenceTypeInvalid('expected a %s' % seq_type_name, path)
|
|
|
|
# Empty seq schema, reject any data.
|
|
if not schema:
|
|
if data:
|
|
raise er.MultipleInvalid([
|
|
er.ValueInvalid('not a valid value', path if path else data)
|
|
])
|
|
return data
|
|
|
|
out = []
|
|
invalid = None
|
|
errors = []
|
|
index_path = UNDEFINED
|
|
for i, value in enumerate(data):
|
|
index_path = path + [i]
|
|
invalid = None
|
|
for validate in _compiled:
|
|
try:
|
|
cval = validate(index_path, value)
|
|
if cval is not Remove: # do not include Remove values
|
|
out.append(cval)
|
|
break
|
|
except er.Invalid as e:
|
|
if len(e.path) > len(index_path):
|
|
raise
|
|
invalid = e
|
|
else:
|
|
errors.append(invalid)
|
|
if errors:
|
|
raise er.MultipleInvalid(errors)
|
|
|
|
if _isnamedtuple(data):
|
|
return type(data)(*out)
|
|
else:
|
|
return type(data)(out)
|
|
|
|
return validate_sequence
|
|
|
|
def _compile_tuple(self, schema):
|
|
"""Validate a tuple.
|
|
|
|
A tuple is a sequence of valid values or validators tried in order.
|
|
|
|
>>> validator = Schema(('one', 'two', int))
|
|
>>> validator(('one',))
|
|
('one',)
|
|
>>> with raises(er.MultipleInvalid, 'expected int @ data[0]'):
|
|
... validator((3.5,))
|
|
>>> validator((1,))
|
|
(1,)
|
|
"""
|
|
return self._compile_sequence(schema, tuple)
|
|
|
|
def _compile_list(self, schema):
|
|
"""Validate a list.
|
|
|
|
A list is a sequence of valid values or validators tried in order.
|
|
|
|
>>> validator = Schema(['one', 'two', int])
|
|
>>> validator(['one'])
|
|
['one']
|
|
>>> with raises(er.MultipleInvalid, 'expected int @ data[0]'):
|
|
... validator([3.5])
|
|
>>> validator([1])
|
|
[1]
|
|
"""
|
|
return self._compile_sequence(schema, list)
|
|
|
|
def _compile_set(self, schema):
|
|
"""Validate a set.
|
|
|
|
A set is an unordered collection of unique elements.
|
|
|
|
>>> validator = Schema({int})
|
|
>>> validator(set([42])) == set([42])
|
|
True
|
|
>>> with raises(er.Invalid, 'expected a set'):
|
|
... validator(42)
|
|
>>> with raises(er.MultipleInvalid, 'invalid value in set'):
|
|
... validator(set(['a']))
|
|
"""
|
|
type_ = type(schema)
|
|
type_name = type_.__name__
|
|
|
|
def validate_set(path, data):
|
|
if not isinstance(data, type_):
|
|
raise er.Invalid('expected a %s' % type_name, path)
|
|
|
|
_compiled = [self._compile(s) for s in schema]
|
|
errors = []
|
|
for value in data:
|
|
for validate in _compiled:
|
|
try:
|
|
validate(path, value)
|
|
break
|
|
except er.Invalid:
|
|
pass
|
|
else:
|
|
invalid = er.Invalid('invalid value in %s' % type_name, path)
|
|
errors.append(invalid)
|
|
|
|
if errors:
|
|
raise er.MultipleInvalid(errors)
|
|
|
|
return data
|
|
|
|
return validate_set
|
|
|
|
def extend(self, schema, required=None, extra=None):
|
|
"""Create a new `Schema` by merging this and the provided `schema`.
|
|
|
|
Neither this `Schema` nor the provided `schema` are modified. The
|
|
resulting `Schema` inherits the `required` and `extra` parameters of
|
|
this, unless overridden.
|
|
|
|
Both schemas must be dictionary-based.
|
|
|
|
:param schema: dictionary to extend this `Schema` with
|
|
:param required: if set, overrides `required` of this `Schema`
|
|
:param extra: if set, overrides `extra` of this `Schema`
|
|
"""
|
|
|
|
assert type(self.schema) == dict and type(schema) == dict, 'Both schemas must be dictionary-based'
|
|
|
|
result = self.schema.copy()
|
|
|
|
# returns the key that may have been passed as an argument to Marker constructor
|
|
def key_literal(key):
|
|
return (key.schema if isinstance(key, Marker) else key)
|
|
|
|
# build a map that takes the key literals to the needed objects
|
|
# literal -> Required|Optional|literal
|
|
result_key_map = dict((key_literal(key), key) for key in result)
|
|
|
|
# for each item in the extension schema, replace duplicates
|
|
# or add new keys
|
|
for key, value in iteritems(schema):
|
|
|
|
# if the key is already in the dictionary, we need to replace it
|
|
# transform key to literal before checking presence
|
|
if key_literal(key) in result_key_map:
|
|
|
|
result_key = result_key_map[key_literal(key)]
|
|
result_value = result[result_key]
|
|
|
|
# if both are dictionaries, we need to extend recursively
|
|
# create the new extended sub schema, then remove the old key and add the new one
|
|
if type(result_value) == dict and type(value) == dict:
|
|
new_value = Schema(result_value).extend(value).schema
|
|
del result[result_key]
|
|
result[key] = new_value
|
|
# one or the other or both are not sub-schemas, simple replacement is fine
|
|
# remove old key and add new one
|
|
else:
|
|
del result[result_key]
|
|
result[key] = value
|
|
|
|
# key is new and can simply be added
|
|
else:
|
|
result[key] = value
|
|
|
|
# recompile and send old object
|
|
result_cls = type(self)
|
|
result_required = (required if required is not None else self.required)
|
|
result_extra = (extra if extra is not None else self.extra)
|
|
return result_cls(result, required=result_required, extra=result_extra)
|
|
|
|
|
|
def _compile_scalar(schema):
|
|
"""A scalar value.
|
|
|
|
The schema can either be a value or a type.
|
|
|
|
>>> _compile_scalar(int)([], 1)
|
|
1
|
|
>>> with raises(er.Invalid, 'expected float'):
|
|
... _compile_scalar(float)([], '1')
|
|
|
|
Callables have
|
|
>>> _compile_scalar(lambda v: float(v))([], '1')
|
|
1.0
|
|
|
|
As a convenience, ValueError's are trapped:
|
|
|
|
>>> with raises(er.Invalid, 'not a valid value'):
|
|
... _compile_scalar(lambda v: float(v))([], 'a')
|
|
"""
|
|
if inspect.isclass(schema):
|
|
def validate_instance(path, data):
|
|
if isinstance(data, schema):
|
|
return data
|
|
else:
|
|
msg = 'expected %s' % schema.__name__
|
|
raise er.TypeInvalid(msg, path)
|
|
|
|
return validate_instance
|
|
|
|
if callable(schema):
|
|
def validate_callable(path, data):
|
|
try:
|
|
return schema(data)
|
|
except ValueError:
|
|
raise er.ValueInvalid('not a valid value', path)
|
|
except er.Invalid as e:
|
|
e.prepend(path)
|
|
raise
|
|
|
|
return validate_callable
|
|
|
|
def validate_value(path, data):
|
|
if data != schema:
|
|
raise er.ScalarInvalid('not a valid value', path)
|
|
return data
|
|
|
|
return validate_value
|
|
|
|
|
|
def _compile_itemsort():
|
|
'''return sort function of mappings'''
|
|
|
|
def is_extra(key_):
|
|
return key_ is Extra
|
|
|
|
def is_remove(key_):
|
|
return isinstance(key_, Remove)
|
|
|
|
def is_marker(key_):
|
|
return isinstance(key_, Marker)
|
|
|
|
def is_type(key_):
|
|
return inspect.isclass(key_)
|
|
|
|
def is_callable(key_):
|
|
return callable(key_)
|
|
|
|
# priority list for map sorting (in order of checking)
|
|
# We want Extra to match last, because it's a catch-all. On the other hand,
|
|
# Remove markers should match first (since invalid values will not
|
|
# raise an Error, instead the validator will check if other schemas match
|
|
# the same value).
|
|
priority = [(1, is_remove), # Remove highest priority after values
|
|
(2, is_marker), # then other Markers
|
|
(4, is_type), # types/classes lowest before Extra
|
|
(3, is_callable), # callables after markers
|
|
(5, is_extra)] # Extra lowest priority
|
|
|
|
def item_priority(item_):
|
|
key_ = item_[0]
|
|
for i, check_ in priority:
|
|
if check_(key_):
|
|
return i
|
|
# values have hightest priorities
|
|
return 0
|
|
|
|
return item_priority
|
|
|
|
|
|
_sort_item = _compile_itemsort()
|
|
|
|
|
|
def _iterate_mapping_candidates(schema):
|
|
"""Iterate over schema in a meaningful order."""
|
|
# Without this, Extra might appear first in the iterator, and fail to
|
|
# validate a key even though it's a Required that has its own validation,
|
|
# generating a false positive.
|
|
return sorted(iteritems(schema), key=_sort_item)
|
|
|
|
|
|
def _iterate_object(obj):
|
|
"""Return iterator over object attributes. Respect objects with
|
|
defined __slots__.
|
|
|
|
"""
|
|
d = {}
|
|
try:
|
|
d = vars(obj)
|
|
except TypeError:
|
|
# maybe we have named tuple here?
|
|
if hasattr(obj, '_asdict'):
|
|
d = obj._asdict()
|
|
for item in iteritems(d):
|
|
yield item
|
|
try:
|
|
slots = obj.__slots__
|
|
except AttributeError:
|
|
pass
|
|
else:
|
|
for key in slots:
|
|
if key != '__dict__':
|
|
yield (key, getattr(obj, key))
|
|
|
|
|
|
class Msg(object):
|
|
"""Report a user-friendly message if a schema fails to validate.
|
|
|
|
>>> validate = Schema(
|
|
... Msg(['one', 'two', int],
|
|
... 'should be one of "one", "two" or an integer'))
|
|
>>> with raises(er.MultipleInvalid, 'should be one of "one", "two" or an integer'):
|
|
... validate(['three'])
|
|
|
|
Messages are only applied to invalid direct descendants of the schema:
|
|
|
|
>>> validate = Schema(Msg([['one', 'two', int]], 'not okay!'))
|
|
>>> with raises(er.MultipleInvalid, 'expected int @ data[0][0]'):
|
|
... validate([['three']])
|
|
|
|
The type which is thrown can be overridden but needs to be a subclass of Invalid
|
|
|
|
>>> with raises(er.SchemaError, 'Msg can only use subclases of Invalid as custom class'):
|
|
... validate = Schema(Msg([int], 'should be int', cls=KeyError))
|
|
|
|
If you do use a subclass of Invalid, that error will be thrown (wrapped in a MultipleInvalid)
|
|
|
|
>>> validate = Schema(Msg([['one', 'two', int]], 'not okay!', cls=er.RangeInvalid))
|
|
>>> try:
|
|
... validate(['three'])
|
|
... except er.MultipleInvalid as e:
|
|
... assert isinstance(e.errors[0], er.RangeInvalid)
|
|
"""
|
|
|
|
def __init__(self, schema, msg, cls=None):
|
|
if cls and not issubclass(cls, er.Invalid):
|
|
raise er.SchemaError("Msg can only use subclases of"
|
|
" Invalid as custom class")
|
|
self._schema = schema
|
|
self.schema = Schema(schema)
|
|
self.msg = msg
|
|
self.cls = cls
|
|
|
|
def __call__(self, v):
|
|
try:
|
|
return self.schema(v)
|
|
except er.Invalid as e:
|
|
if len(e.path) > 1:
|
|
raise e
|
|
else:
|
|
raise (self.cls or er.Invalid)(self.msg)
|
|
|
|
def __repr__(self):
|
|
return 'Msg(%s, %s, cls=%s)' % (self._schema, self.msg, self.cls)
|
|
|
|
|
|
class Object(dict):
|
|
"""Indicate that we should work with attributes, not keys."""
|
|
|
|
def __init__(self, schema, cls=UNDEFINED):
|
|
self.cls = cls
|
|
super(Object, self).__init__(schema)
|
|
|
|
|
|
class VirtualPathComponent(str):
|
|
def __str__(self):
|
|
return '<' + self + '>'
|
|
|
|
def __repr__(self):
|
|
return self.__str__()
|
|
|
|
|
|
# Markers.py
|
|
|
|
|
|
class Marker(object):
|
|
"""Mark nodes for special treatment."""
|
|
|
|
def __init__(self, schema_, msg=None, description=None):
|
|
self.schema = schema_
|
|
self._schema = Schema(schema_)
|
|
self.msg = msg
|
|
self.description = description
|
|
|
|
def __call__(self, v):
|
|
try:
|
|
return self._schema(v)
|
|
except er.Invalid as e:
|
|
if not self.msg or len(e.path) > 1:
|
|
raise
|
|
raise er.Invalid(self.msg)
|
|
|
|
def __str__(self):
|
|
return str(self.schema)
|
|
|
|
def __repr__(self):
|
|
return repr(self.schema)
|
|
|
|
def __lt__(self, other):
|
|
if isinstance(other, Marker):
|
|
return self.schema < other.schema
|
|
return self.schema < other
|
|
|
|
def __hash__(self):
|
|
return hash(self.schema)
|
|
|
|
def __eq__(self, other):
|
|
return self.schema == other
|
|
|
|
def __ne__(self, other):
|
|
return not(self.schema == other)
|
|
|
|
|
|
class Optional(Marker):
|
|
"""Mark a node in the schema as optional, and optionally provide a default
|
|
|
|
>>> schema = Schema({Optional('key'): str})
|
|
>>> schema({})
|
|
{}
|
|
>>> schema = Schema({Optional('key', default='value'): str})
|
|
>>> schema({})
|
|
{'key': 'value'}
|
|
>>> schema = Schema({Optional('key', default=list): list})
|
|
>>> schema({})
|
|
{'key': []}
|
|
|
|
If 'required' flag is set for an entire schema, optional keys aren't required
|
|
|
|
>>> schema = Schema({
|
|
... Optional('key'): str,
|
|
... 'key2': str
|
|
... }, required=True)
|
|
>>> schema({'key2':'value'})
|
|
{'key2': 'value'}
|
|
"""
|
|
|
|
def __init__(self, schema, msg=None, default=UNDEFINED, description=None):
|
|
super(Optional, self).__init__(schema, msg=msg,
|
|
description=description)
|
|
self.default = default_factory(default)
|
|
|
|
|
|
class Exclusive(Optional):
|
|
"""Mark a node in the schema as exclusive.
|
|
|
|
Exclusive keys inherited from Optional:
|
|
|
|
>>> schema = Schema({Exclusive('alpha', 'angles'): int, Exclusive('beta', 'angles'): int})
|
|
>>> schema({'alpha': 30})
|
|
{'alpha': 30}
|
|
|
|
Keys inside a same group of exclusion cannot be together, it only makes sense for dictionaries:
|
|
|
|
>>> with raises(er.MultipleInvalid, "two or more values in the same group of exclusion 'angles' @ data[<angles>]"):
|
|
... schema({'alpha': 30, 'beta': 45})
|
|
|
|
For example, API can provides multiple types of authentication, but only one works in the same time:
|
|
|
|
>>> msg = 'Please, use only one type of authentication at the same time.'
|
|
>>> schema = Schema({
|
|
... Exclusive('classic', 'auth', msg=msg):{
|
|
... Required('email'): basestring,
|
|
... Required('password'): basestring
|
|
... },
|
|
... Exclusive('internal', 'auth', msg=msg):{
|
|
... Required('secret_key'): basestring
|
|
... },
|
|
... Exclusive('social', 'auth', msg=msg):{
|
|
... Required('social_network'): basestring,
|
|
... Required('token'): basestring
|
|
... }
|
|
... })
|
|
|
|
>>> with raises(er.MultipleInvalid, "Please, use only one type of authentication at the same time. @ data[<auth>]"):
|
|
... schema({'classic': {'email': 'foo@example.com', 'password': 'bar'},
|
|
... 'social': {'social_network': 'barfoo', 'token': 'tEMp'}})
|
|
"""
|
|
|
|
def __init__(self, schema, group_of_exclusion, msg=None, description=None):
|
|
super(Exclusive, self).__init__(schema, msg=msg,
|
|
description=description)
|
|
self.group_of_exclusion = group_of_exclusion
|
|
|
|
|
|
class Inclusive(Optional):
|
|
""" Mark a node in the schema as inclusive.
|
|
|
|
Inclusive keys inherited from Optional:
|
|
|
|
>>> schema = Schema({
|
|
... Inclusive('filename', 'file'): str,
|
|
... Inclusive('mimetype', 'file'): str
|
|
... })
|
|
>>> data = {'filename': 'dog.jpg', 'mimetype': 'image/jpeg'}
|
|
>>> data == schema(data)
|
|
True
|
|
|
|
Keys inside a same group of inclusive must exist together, it only makes sense for dictionaries:
|
|
|
|
>>> with raises(er.MultipleInvalid, "some but not all values in the same group of inclusion 'file' @ data[<file>]"):
|
|
... schema({'filename': 'dog.jpg'})
|
|
|
|
If none of the keys in the group are present, it is accepted:
|
|
|
|
>>> schema({})
|
|
{}
|
|
|
|
For example, API can return 'height' and 'width' together, but not separately.
|
|
|
|
>>> msg = "Height and width must exist together"
|
|
>>> schema = Schema({
|
|
... Inclusive('height', 'size', msg=msg): int,
|
|
... Inclusive('width', 'size', msg=msg): int
|
|
... })
|
|
|
|
>>> with raises(er.MultipleInvalid, msg + " @ data[<size>]"):
|
|
... schema({'height': 100})
|
|
|
|
>>> with raises(er.MultipleInvalid, msg + " @ data[<size>]"):
|
|
... schema({'width': 100})
|
|
|
|
>>> data = {'height': 100, 'width': 100}
|
|
>>> data == schema(data)
|
|
True
|
|
"""
|
|
|
|
def __init__(self, schema, group_of_inclusion,
|
|
msg=None, description=None, default=UNDEFINED):
|
|
super(Inclusive, self).__init__(schema, msg=msg,
|
|
default=default,
|
|
description=description)
|
|
self.group_of_inclusion = group_of_inclusion
|
|
|
|
|
|
class Required(Marker):
|
|
"""Mark a node in the schema as being required, and optionally provide a default value.
|
|
|
|
>>> schema = Schema({Required('key'): str})
|
|
>>> with raises(er.MultipleInvalid, "required key not provided @ data['key']"):
|
|
... schema({})
|
|
|
|
>>> schema = Schema({Required('key', default='value'): str})
|
|
>>> schema({})
|
|
{'key': 'value'}
|
|
>>> schema = Schema({Required('key', default=list): list})
|
|
>>> schema({})
|
|
{'key': []}
|
|
"""
|
|
|
|
def __init__(self, schema, msg=None, default=UNDEFINED, description=None):
|
|
super(Required, self).__init__(schema, msg=msg,
|
|
description=description)
|
|
self.default = default_factory(default)
|
|
|
|
|
|
class Remove(Marker):
|
|
"""Mark a node in the schema to be removed and excluded from the validated
|
|
output. Keys that fail validation will not raise ``Invalid``. Instead, these
|
|
keys will be treated as extras.
|
|
|
|
>>> schema = Schema({str: int, Remove(int): str})
|
|
>>> with raises(er.MultipleInvalid, "extra keys not allowed @ data[1]"):
|
|
... schema({'keep': 1, 1: 1.0})
|
|
>>> schema({1: 'red', 'red': 1, 2: 'green'})
|
|
{'red': 1}
|
|
>>> schema = Schema([int, Remove(float), Extra])
|
|
>>> schema([1, 2, 3, 4.0, 5, 6.0, '7'])
|
|
[1, 2, 3, 5, '7']
|
|
"""
|
|
|
|
def __call__(self, v):
|
|
super(Remove, self).__call__(v)
|
|
return self.__class__
|
|
|
|
def __repr__(self):
|
|
return "Remove(%r)" % (self.schema,)
|
|
|
|
def __hash__(self):
|
|
return object.__hash__(self)
|
|
|
|
|
|
def message(default=None, cls=None):
|
|
"""Convenience decorator to allow functions to provide a message.
|
|
|
|
Set a default message:
|
|
|
|
>>> @message('not an integer')
|
|
... def isint(v):
|
|
... return int(v)
|
|
|
|
>>> validate = Schema(isint())
|
|
>>> with raises(er.MultipleInvalid, 'not an integer'):
|
|
... validate('a')
|
|
|
|
The message can be overridden on a per validator basis:
|
|
|
|
>>> validate = Schema(isint('bad'))
|
|
>>> with raises(er.MultipleInvalid, 'bad'):
|
|
... validate('a')
|
|
|
|
The class thrown too:
|
|
|
|
>>> class IntegerInvalid(er.Invalid): pass
|
|
>>> validate = Schema(isint('bad', clsoverride=IntegerInvalid))
|
|
>>> try:
|
|
... validate('a')
|
|
... except er.MultipleInvalid as e:
|
|
... assert isinstance(e.errors[0], IntegerInvalid)
|
|
"""
|
|
if cls and not issubclass(cls, er.Invalid):
|
|
raise er.SchemaError("message can only use subclases of Invalid as custom class")
|
|
|
|
def decorator(f):
|
|
@wraps(f)
|
|
def check(msg=None, clsoverride=None):
|
|
@wraps(f)
|
|
def wrapper(*args, **kwargs):
|
|
try:
|
|
return f(*args, **kwargs)
|
|
except ValueError:
|
|
raise (clsoverride or cls or er.ValueInvalid)(msg or default or 'invalid value')
|
|
|
|
return wrapper
|
|
|
|
return check
|
|
|
|
return decorator
|
|
|
|
|
|
def _args_to_dict(func, args):
|
|
"""Returns argument names as values as key-value pairs."""
|
|
if sys.version_info >= (3, 0):
|
|
arg_count = func.__code__.co_argcount
|
|
arg_names = func.__code__.co_varnames[:arg_count]
|
|
else:
|
|
arg_count = func.func_code.co_argcount
|
|
arg_names = func.func_code.co_varnames[:arg_count]
|
|
|
|
arg_value_list = list(args)
|
|
arguments = dict((arg_name, arg_value_list[i])
|
|
for i, arg_name in enumerate(arg_names)
|
|
if i < len(arg_value_list))
|
|
return arguments
|
|
|
|
|
|
def _merge_args_with_kwargs(args_dict, kwargs_dict):
|
|
"""Merge args with kwargs."""
|
|
ret = args_dict.copy()
|
|
ret.update(kwargs_dict)
|
|
return ret
|
|
|
|
|
|
def validate(*a, **kw):
|
|
"""Decorator for validating arguments of a function against a given schema.
|
|
|
|
Set restrictions for arguments:
|
|
|
|
>>> @validate(arg1=int, arg2=int)
|
|
... def foo(arg1, arg2):
|
|
... return arg1 * arg2
|
|
|
|
Set restriction for returned value:
|
|
|
|
>>> @validate(arg=int, __return__=int)
|
|
... def bar(arg1):
|
|
... return arg1 * 2
|
|
|
|
"""
|
|
RETURNS_KEY = '__return__'
|
|
|
|
def validate_schema_decorator(func):
|
|
|
|
returns_defined = False
|
|
returns = None
|
|
|
|
schema_args_dict = _args_to_dict(func, a)
|
|
schema_arguments = _merge_args_with_kwargs(schema_args_dict, kw)
|
|
|
|
if RETURNS_KEY in schema_arguments:
|
|
returns_defined = True
|
|
returns = schema_arguments[RETURNS_KEY]
|
|
del schema_arguments[RETURNS_KEY]
|
|
|
|
input_schema = (Schema(schema_arguments, extra=ALLOW_EXTRA)
|
|
if len(schema_arguments) != 0 else lambda x: x)
|
|
output_schema = Schema(returns) if returns_defined else lambda x: x
|
|
|
|
@wraps(func)
|
|
def func_wrapper(*args, **kwargs):
|
|
args_dict = _args_to_dict(func, args)
|
|
arguments = _merge_args_with_kwargs(args_dict, kwargs)
|
|
validated_arguments = input_schema(arguments)
|
|
output = func(**validated_arguments)
|
|
return output_schema(output)
|
|
|
|
return func_wrapper
|
|
|
|
return validate_schema_decorator
|