Coverage for pydantic/_internal/_known_annotated_metadata.py: 91.47%

1from __future__ import annotations 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

2 

3from collections import defaultdict 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

4from copy import copy 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

5from functools import lru_cache, partial 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

6from typing import TYPE_CHECKING, Any, Callable, Iterable 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

7 

8from pydantic_core import CoreSchema, PydanticCustomError, to_jsonable_python 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

9from pydantic_core import core_schema as cs 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

10 

11from ._fields import PydanticMetadata 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

12 

13if TYPE_CHECKING: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

14 from ..annotated_handlers import GetJsonSchemaHandler 

15 

16STRICT = {'strict'} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

17FAIL_FAST = {'fail_fast'} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

18LENGTH_CONSTRAINTS = {'min_length', 'max_length'} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

19INEQUALITY = {'le', 'ge', 'lt', 'gt'} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

20NUMERIC_CONSTRAINTS = {'multiple_of', *INEQUALITY} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

21ALLOW_INF_NAN = {'allow_inf_nan'} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

22 

23STR_CONSTRAINTS = { 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

24 *LENGTH_CONSTRAINTS, 

25 *STRICT, 

26 'strip_whitespace', 

27 'to_lower', 

28 'to_upper', 

29 'pattern', 

30 'coerce_numbers_to_str', 

31} 

32BYTES_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

33 

34LIST_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT, *FAIL_FAST} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

35TUPLE_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT, *FAIL_FAST} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

36SET_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT, *FAIL_FAST} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

37DICT_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

38GENERATOR_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *STRICT} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

39SEQUENCE_CONSTRAINTS = {*LENGTH_CONSTRAINTS, *FAIL_FAST} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

40 

41FLOAT_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *ALLOW_INF_NAN, *STRICT} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

42DECIMAL_CONSTRAINTS = {'max_digits', 'decimal_places', *FLOAT_CONSTRAINTS} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

43INT_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *ALLOW_INF_NAN, *STRICT} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

44BOOL_CONSTRAINTS = STRICT 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

45UUID_CONSTRAINTS = STRICT 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

46 

47DATE_TIME_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

48TIMEDELTA_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

49TIME_CONSTRAINTS = {*NUMERIC_CONSTRAINTS, *STRICT} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

50LAX_OR_STRICT_CONSTRAINTS = STRICT 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

51ENUM_CONSTRAINTS = STRICT 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

52 

53UNION_CONSTRAINTS = {'union_mode'} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

54URL_CONSTRAINTS = { 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

55 'max_length', 

56 'allowed_schemes', 

57 'host_required', 

58 'default_host', 

59 'default_port', 

60 'default_path', 

61} 

62 

63TEXT_SCHEMA_TYPES = ('str', 'bytes', 'url', 'multi-host-url') 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

64SEQUENCE_SCHEMA_TYPES = ('list', 'tuple', 'set', 'frozenset', 'generator', *TEXT_SCHEMA_TYPES) 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

65NUMERIC_SCHEMA_TYPES = ('float', 'int', 'date', 'time', 'timedelta', 'datetime') 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

66 

67CONSTRAINTS_TO_ALLOWED_SCHEMAS: dict[str, set[str]] = defaultdict(set) 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

68 

69constraint_schema_pairings: list[tuple[set[str], tuple[str, ...]]] = [ 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

70 (STR_CONSTRAINTS, TEXT_SCHEMA_TYPES), 

71 (BYTES_CONSTRAINTS, ('bytes',)), 

72 (LIST_CONSTRAINTS, ('list',)), 

73 (TUPLE_CONSTRAINTS, ('tuple',)), 

74 (SET_CONSTRAINTS, ('set', 'frozenset')), 

75 (DICT_CONSTRAINTS, ('dict',)), 

76 (GENERATOR_CONSTRAINTS, ('generator',)), 

77 (FLOAT_CONSTRAINTS, ('float',)), 

78 (INT_CONSTRAINTS, ('int',)), 

79 (DATE_TIME_CONSTRAINTS, ('date', 'time', 'datetime')), 

80 (TIMEDELTA_CONSTRAINTS, ('timedelta',)), 

81 (TIME_CONSTRAINTS, ('time',)), 

82 # TODO: this is a bit redundant, we could probably avoid some of these 

83 (STRICT, (*TEXT_SCHEMA_TYPES, *SEQUENCE_SCHEMA_TYPES, *NUMERIC_SCHEMA_TYPES, 'typed-dict', 'model')), 

84 (UNION_CONSTRAINTS, ('union',)), 

85 (URL_CONSTRAINTS, ('url', 'multi-host-url')), 

86 (BOOL_CONSTRAINTS, ('bool',)), 

87 (UUID_CONSTRAINTS, ('uuid',)), 

88 (LAX_OR_STRICT_CONSTRAINTS, ('lax-or-strict',)), 

89 (ENUM_CONSTRAINTS, ('enum',)), 

90 (DECIMAL_CONSTRAINTS, ('decimal',)), 

91] 

92 

93for constraints, schemas in constraint_schema_pairings: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

94 for c in constraints: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

95 CONSTRAINTS_TO_ALLOWED_SCHEMAS[c].update(schemas) 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

96 

97 

98def add_js_update_schema(s: cs.CoreSchema, f: Callable[[], dict[str, Any]]) -> None: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

99 def update_js_schema(s: cs.CoreSchema, handler: GetJsonSchemaHandler) -> dict[str, Any]: 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

100 js_schema = handler(s) 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

101 js_schema.update(f()) 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

102 return js_schema 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

103 

104 if 'metadata' in s: 104 ↛ 105line 104 didn't jump to line 105 because the condition on line 104 was never true38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

105 metadata = s['metadata'] 

106 if 'pydantic_js_functions' in s: 

107 metadata['pydantic_js_functions'].append(update_js_schema) 

108 else: 

109 metadata['pydantic_js_functions'] = [update_js_schema] 

110 else: 

111 s['metadata'] = {'pydantic_js_functions': [update_js_schema]} 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

112 

113 

114def as_jsonable_value(v: Any) -> Any: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

115 if type(v) not in (int, str, float, bytes, bool, type(None)): 115 ↛ 116line 115 didn't jump to line 116 because the condition on line 115 was never true38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

116 return to_jsonable_python(v) 

117 return v 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

118 

119 

120def expand_grouped_metadata(annotations: Iterable[Any]) -> Iterable[Any]: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

121 """Expand the annotations. 

122 

123 Args: 

124 annotations: An iterable of annotations. 

125 

126 Returns: 

127 An iterable of expanded annotations. 

128 

129 Example: 

130 ```py 

131 from annotated_types import Ge, Len 

132 

133 from pydantic._internal._known_annotated_metadata import expand_grouped_metadata 

134 

135 print(list(expand_grouped_metadata([Ge(4), Len(5)]))) 

136 #> [Ge(ge=4), MinLen(min_length=5)] 

137 ``` 

138 """ 

139 import annotated_types as at 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

140 

141 from pydantic.fields import FieldInfo # circular import 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

142 

143 for annotation in annotations: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

144 if isinstance(annotation, at.GroupedMetadata): 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

145 yield from annotation 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

146 elif isinstance(annotation, FieldInfo): 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

147 yield from annotation.metadata 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

148 # this is a bit problematic in that it results in duplicate metadata 

149 # all of our "consumers" can handle it, but it is not ideal 

150 # we probably should split up FieldInfo into: 

151 # - annotated types metadata 

152 # - individual metadata known only to Pydantic 

153 annotation = copy(annotation) 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

154 annotation.metadata = [] 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

155 yield annotation 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

156 else: 

157 yield annotation 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

158 

159 

160@lru_cache 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

161def _get_at_to_constraint_map() -> dict[type, str]: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

162 """Return a mapping of annotated types to constraints. 

163 

164 Normally, we would define a mapping like this in the module scope, but we can't do that 

165 because we don't permit module level imports of `annotated_types`, in an attempt to speed up 

166 the import time of `pydantic`. We still only want to have this dictionary defined in one place, 

167 so we use this function to cache the result. 

168 """ 

169 import annotated_types as at 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

170 

171 return { 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

172 at.Gt: 'gt', 

173 at.Ge: 'ge', 

174 at.Lt: 'lt', 

175 at.Le: 'le', 

176 at.MultipleOf: 'multiple_of', 

177 at.MinLen: 'min_length', 

178 at.MaxLen: 'max_length', 

179 } 

180 

181 

182def apply_known_metadata(annotation: Any, schema: CoreSchema) -> CoreSchema | None: # noqa: C901 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

183 """Apply `annotation` to `schema` if it is an annotation we know about (Gt, Le, etc.). 

184 Otherwise return `None`. 

185 

186 This does not handle all known annotations. If / when it does, it can always 

187 return a CoreSchema and return the unmodified schema if the annotation should be ignored. 

188 

189 Assumes that GroupedMetadata has already been expanded via `expand_grouped_metadata`. 

190 

191 Args: 

192 annotation: The annotation. 

193 schema: The schema. 

194 

195 Returns: 

196 An updated schema with annotation if it is an annotation we know about, `None` otherwise. 

197 

198 Raises: 

199 PydanticCustomError: If `Predicate` fails. 

200 """ 

201 import annotated_types as at 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

202 

203 from ._validators import forbid_inf_nan_check, get_constraint_validator 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

204 

205 schema = schema.copy() 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

206 schema_update, other_metadata = collect_known_metadata([annotation]) 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

207 schema_type = schema['type'] 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

208 

209 chain_schema_constraints: set[str] = { 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

210 'pattern', 

211 'strip_whitespace', 

212 'to_lower', 

213 'to_upper', 

214 'coerce_numbers_to_str', 

215 } 

216 chain_schema_steps: list[CoreSchema] = [] 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

217 

218 for constraint, value in schema_update.items(): 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

219 if constraint not in CONSTRAINTS_TO_ALLOWED_SCHEMAS: 219 ↛ 220line 219 didn't jump to line 220 because the condition on line 219 was never true38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

220 raise ValueError(f'Unknown constraint {constraint}') 

221 allowed_schemas = CONSTRAINTS_TO_ALLOWED_SCHEMAS[constraint] 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

222 

223 # if it becomes necessary to handle more than one constraint 

224 # in this recursive case with function-after or function-wrap, we should refactor 

225 # this is a bit challenging because we sometimes want to apply constraints to the inner schema, 

226 # whereas other times we want to wrap the existing schema with a new one that enforces a new constraint. 

227 if schema_type in {'function-before', 'function-wrap', 'function-after'} and constraint == 'strict': 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

228 schema['schema'] = apply_known_metadata(annotation, schema['schema']) # type: ignore # schema is function-after schema 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

229 return schema 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

230 

231 if schema_type in allowed_schemas: 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

232 if constraint == 'union_mode' and schema_type == 'union': 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

233 schema['mode'] = value # type: ignore # schema is UnionSchema 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

234 else: 

235 schema[constraint] = value 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

236 continue 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

237 

238 if constraint in chain_schema_constraints: 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

239 chain_schema_steps.append(cs.str_schema(**{constraint: value})) 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

240 elif constraint in {*NUMERIC_CONSTRAINTS, *LENGTH_CONSTRAINTS}: 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

241 if constraint in NUMERIC_CONSTRAINTS: 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

242 json_schema_constraint = constraint 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

243 elif constraint in LENGTH_CONSTRAINTS: 243 ↛ 255line 243 didn't jump to line 255 because the condition on line 243 was always true38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

244 inner_schema = schema 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

245 while inner_schema['type'] in {'function-before', 'function-wrap', 'function-after'}: 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

246 inner_schema = inner_schema['schema'] # type: ignore 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

247 inner_schema_type = inner_schema['type'] 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

248 if inner_schema_type == 'list' or ( 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

249 inner_schema_type == 'json-or-python' and inner_schema['json_schema']['type'] == 'list' # type: ignore 

250 ): 

251 json_schema_constraint = 'minItems' if constraint == 'min_length' else 'maxItems' 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

252 else: 

253 json_schema_constraint = 'minLength' if constraint == 'min_length' else 'maxLength' 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

254 

255 schema = cs.no_info_after_validator_function( 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

256 partial(get_constraint_validator(constraint), **{constraint: value}), schema 

257 ) 

258 add_js_update_schema(schema, lambda: {json_schema_constraint: as_jsonable_value(value)}) 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

259 elif constraint == 'allow_inf_nan' and value is False: 259 ↛ 265line 259 didn't jump to line 265 because the condition on line 259 was always true38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

260 schema = cs.no_info_after_validator_function( 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

261 forbid_inf_nan_check, 

262 schema, 

263 ) 

264 else: 

265 raise RuntimeError(f'Unable to apply constraint {constraint} to schema {schema_type}') 

266 

267 for annotation in other_metadata: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

268 if (annotation_type := type(annotation)) in (at_to_constraint_map := _get_at_to_constraint_map()): 268 ↛ 269line 268 didn't jump to line 269 because the condition on line 268 was never true48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

269 constraint = at_to_constraint_map[annotation_type] 

270 schema = cs.no_info_after_validator_function( 

271 partial(get_constraint_validator(constraint), {constraint: getattr(annotation, constraint)}), schema 

272 ) 

273 continue 

274 elif isinstance(annotation, at.Predicate): 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

275 predicate_name = f'{annotation.func.__qualname__} ' if hasattr(annotation.func, '__qualname__') else '' 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

276 

277 def val_func(v: Any) -> Any: 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

278 # annotation.func may also raise an exception, let it pass through 

279 if not annotation.func(v): 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

280 raise PydanticCustomError( 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

281 'predicate_failed', 

282 f'Predicate {predicate_name}failed', # type: ignore 

283 ) 

284 return v 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

285 

286 schema = cs.no_info_after_validator_function(val_func, schema) 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

287 else: 

288 # ignore any other unknown metadata 

289 return None 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

290 

291 if chain_schema_steps: 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

292 chain_schema_steps = [schema] + chain_schema_steps 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

293 return cs.chain_schema(chain_schema_steps) 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

294 

295 return schema 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

296 

297 

298def collect_known_metadata(annotations: Iterable[Any]) -> tuple[dict[str, Any], list[Any]]: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

299 """Split `annotations` into known metadata and unknown annotations. 

300 

301 Args: 

302 annotations: An iterable of annotations. 

303 

304 Returns: 

305 A tuple contains a dict of known metadata and a list of unknown annotations. 

306 

307 Example: 

308 ```py 

309 from annotated_types import Gt, Len 

310 

311 from pydantic._internal._known_annotated_metadata import collect_known_metadata 

312 

313 print(collect_known_metadata([Gt(1), Len(42), ...])) 

314 #> ({'gt': 1, 'min_length': 42}, [Ellipsis]) 

315 ``` 

316 """ 

317 annotations = expand_grouped_metadata(annotations) 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

318 

319 res: dict[str, Any] = {} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

320 remaining: list[Any] = [] 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

321 

322 for annotation in annotations: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

323 # isinstance(annotation, PydanticMetadata) also covers ._fields:_PydanticGeneralMetadata 

324 if isinstance(annotation, PydanticMetadata): 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

325 res.update(annotation.__dict__) 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

326 # we don't use dataclasses.asdict because that recursively calls asdict on the field values 

327 elif (annotation_type := type(annotation)) in (at_to_constraint_map := _get_at_to_constraint_map()): 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

328 constraint = at_to_constraint_map[annotation_type] 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

329 res[constraint] = getattr(annotation, constraint) 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

330 elif isinstance(annotation, type) and issubclass(annotation, PydanticMetadata): 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

331 # also support PydanticMetadata classes being used without initialisation, 

332 # e.g. `Annotated[int, Strict]` as well as `Annotated[int, Strict()]` 

333 res.update({k: v for k, v in vars(annotation).items() if not k.startswith('_')}) 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

334 else: 

335 remaining.append(annotation) 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

336 # Nones can sneak in but pydantic-core will reject them 

337 # it'd be nice to clean things up so we don't put in None (we probably don't _need_ to, it was just easier) 

338 # but this is simple enough to kick that can down the road 

339 res = {k: v for k, v in res.items() if v is not None} 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

340 return res, remaining 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

341 

342 

343def check_metadata(metadata: dict[str, Any], allowed: Iterable[str], source_type: Any) -> None: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

344 """A small utility function to validate that the given metadata can be applied to the target. 

345 More than saving lines of code, this gives us a consistent error message for all of our internal implementations. 

346 

347 Args: 

348 metadata: A dict of metadata. 

349 allowed: An iterable of allowed metadata. 

350 source_type: The source type. 

351 

352 Raises: 

353 TypeError: If there is metadatas that can't be applied on source type. 

354 """ 

355 unknown = metadata.keys() - set(allowed) 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

356 if unknown: 48 ctx1abcdefghijklmnopqrstuvwxyzMNOPQRSTUVABCDEFGHIJKL

357 raise TypeError( 38 ctx1abcdefghijklmnopqrstuvwxyzABCDEFGHIJKL

358 f'The following constraints cannot be applied to {source_type!r}: {", ".join([f"{k!r}" for k in unknown])}' 

359 )