openai/openai-python
Publicmirrored from https://github.com/openai/openai-pythonAvailable
tests/test_models.py
1017lines · modecode
| 1 | import json |
| 2 | from typing import TYPE_CHECKING, Any, Dict, List, Union, Iterable, Optional, cast |
| 3 | from datetime import datetime, timezone |
| 4 | from collections import deque |
| 5 | from typing_extensions import Literal, Annotated, TypedDict, TypeAliasType |
| 6 | |
| 7 | import pytest |
| 8 | import pydantic |
| 9 | from pydantic import Field |
| 10 | |
| 11 | from openai._utils import PropertyInfo |
| 12 | from openai._compat import PYDANTIC_V1, parse_obj, model_dump, model_json |
| 13 | from openai._models import DISCRIMINATOR_CACHE, BaseModel, EagerIterable, construct_type |
| 14 | |
| 15 | |
| 16 | class BasicModel(BaseModel): |
| 17 | foo: str |
| 18 | |
| 19 | |
| 20 | @pytest.mark.parametrize("value", ["hello", 1], ids=["correct type", "mismatched"]) |
| 21 | def test_basic(value: object) -> None: |
| 22 | m = BasicModel.construct(foo=value) |
| 23 | assert m.foo == value |
| 24 | |
| 25 | |
| 26 | def test_directly_nested_model() -> None: |
| 27 | class NestedModel(BaseModel): |
| 28 | nested: BasicModel |
| 29 | |
| 30 | m = NestedModel.construct(nested={"foo": "Foo!"}) |
| 31 | assert m.nested.foo == "Foo!" |
| 32 | |
| 33 | # mismatched types |
| 34 | m = NestedModel.construct(nested="hello!") |
| 35 | assert cast(Any, m.nested) == "hello!" |
| 36 | |
| 37 | |
| 38 | def test_optional_nested_model() -> None: |
| 39 | class NestedModel(BaseModel): |
| 40 | nested: Optional[BasicModel] |
| 41 | |
| 42 | m1 = NestedModel.construct(nested=None) |
| 43 | assert m1.nested is None |
| 44 | |
| 45 | m2 = NestedModel.construct(nested={"foo": "bar"}) |
| 46 | assert m2.nested is not None |
| 47 | assert m2.nested.foo == "bar" |
| 48 | |
| 49 | # mismatched types |
| 50 | m3 = NestedModel.construct(nested={"foo"}) |
| 51 | assert isinstance(cast(Any, m3.nested), set) |
| 52 | assert cast(Any, m3.nested) == {"foo"} |
| 53 | |
| 54 | |
| 55 | def test_list_nested_model() -> None: |
| 56 | class NestedModel(BaseModel): |
| 57 | nested: List[BasicModel] |
| 58 | |
| 59 | m = NestedModel.construct(nested=[{"foo": "bar"}, {"foo": "2"}]) |
| 60 | assert m.nested is not None |
| 61 | assert isinstance(m.nested, list) |
| 62 | assert len(m.nested) == 2 |
| 63 | assert m.nested[0].foo == "bar" |
| 64 | assert m.nested[1].foo == "2" |
| 65 | |
| 66 | # mismatched types |
| 67 | m = NestedModel.construct(nested=True) |
| 68 | assert cast(Any, m.nested) is True |
| 69 | |
| 70 | m = NestedModel.construct(nested=[False]) |
| 71 | assert cast(Any, m.nested) == [False] |
| 72 | |
| 73 | |
| 74 | def test_optional_list_nested_model() -> None: |
| 75 | class NestedModel(BaseModel): |
| 76 | nested: Optional[List[BasicModel]] |
| 77 | |
| 78 | m1 = NestedModel.construct(nested=[{"foo": "bar"}, {"foo": "2"}]) |
| 79 | assert m1.nested is not None |
| 80 | assert isinstance(m1.nested, list) |
| 81 | assert len(m1.nested) == 2 |
| 82 | assert m1.nested[0].foo == "bar" |
| 83 | assert m1.nested[1].foo == "2" |
| 84 | |
| 85 | m2 = NestedModel.construct(nested=None) |
| 86 | assert m2.nested is None |
| 87 | |
| 88 | # mismatched types |
| 89 | m3 = NestedModel.construct(nested={1}) |
| 90 | assert cast(Any, m3.nested) == {1} |
| 91 | |
| 92 | m4 = NestedModel.construct(nested=[False]) |
| 93 | assert cast(Any, m4.nested) == [False] |
| 94 | |
| 95 | |
| 96 | def test_list_optional_items_nested_model() -> None: |
| 97 | class NestedModel(BaseModel): |
| 98 | nested: List[Optional[BasicModel]] |
| 99 | |
| 100 | m = NestedModel.construct(nested=[None, {"foo": "bar"}]) |
| 101 | assert m.nested is not None |
| 102 | assert isinstance(m.nested, list) |
| 103 | assert len(m.nested) == 2 |
| 104 | assert m.nested[0] is None |
| 105 | assert m.nested[1] is not None |
| 106 | assert m.nested[1].foo == "bar" |
| 107 | |
| 108 | # mismatched types |
| 109 | m3 = NestedModel.construct(nested="foo") |
| 110 | assert cast(Any, m3.nested) == "foo" |
| 111 | |
| 112 | m4 = NestedModel.construct(nested=[False]) |
| 113 | assert cast(Any, m4.nested) == [False] |
| 114 | |
| 115 | |
| 116 | def test_list_mismatched_type() -> None: |
| 117 | class NestedModel(BaseModel): |
| 118 | nested: List[str] |
| 119 | |
| 120 | m = NestedModel.construct(nested=False) |
| 121 | assert cast(Any, m.nested) is False |
| 122 | |
| 123 | |
| 124 | def test_raw_dictionary() -> None: |
| 125 | class NestedModel(BaseModel): |
| 126 | nested: Dict[str, str] |
| 127 | |
| 128 | m = NestedModel.construct(nested={"hello": "world"}) |
| 129 | assert m.nested == {"hello": "world"} |
| 130 | |
| 131 | # mismatched types |
| 132 | m = NestedModel.construct(nested=False) |
| 133 | assert cast(Any, m.nested) is False |
| 134 | |
| 135 | |
| 136 | def test_nested_dictionary_model() -> None: |
| 137 | class NestedModel(BaseModel): |
| 138 | nested: Dict[str, BasicModel] |
| 139 | |
| 140 | m = NestedModel.construct(nested={"hello": {"foo": "bar"}}) |
| 141 | assert isinstance(m.nested, dict) |
| 142 | assert m.nested["hello"].foo == "bar" |
| 143 | |
| 144 | # mismatched types |
| 145 | m = NestedModel.construct(nested={"hello": False}) |
| 146 | assert cast(Any, m.nested["hello"]) is False |
| 147 | |
| 148 | |
| 149 | def test_unknown_fields() -> None: |
| 150 | m1 = BasicModel.construct(foo="foo", unknown=1) |
| 151 | assert m1.foo == "foo" |
| 152 | assert cast(Any, m1).unknown == 1 |
| 153 | |
| 154 | m2 = BasicModel.construct(foo="foo", unknown={"foo_bar": True}) |
| 155 | assert m2.foo == "foo" |
| 156 | assert cast(Any, m2).unknown == {"foo_bar": True} |
| 157 | |
| 158 | assert model_dump(m2) == {"foo": "foo", "unknown": {"foo_bar": True}} |
| 159 | |
| 160 | |
| 161 | def test_strict_validation_unknown_fields() -> None: |
| 162 | class Model(BaseModel): |
| 163 | foo: str |
| 164 | |
| 165 | model = parse_obj(Model, dict(foo="hello!", user="Robert")) |
| 166 | assert model.foo == "hello!" |
| 167 | assert cast(Any, model).user == "Robert" |
| 168 | |
| 169 | assert model_dump(model) == {"foo": "hello!", "user": "Robert"} |
| 170 | |
| 171 | |
| 172 | def test_aliases() -> None: |
| 173 | class Model(BaseModel): |
| 174 | my_field: int = Field(alias="myField") |
| 175 | |
| 176 | m = Model.construct(myField=1) |
| 177 | assert m.my_field == 1 |
| 178 | |
| 179 | # mismatched types |
| 180 | m = Model.construct(myField={"hello": False}) |
| 181 | assert cast(Any, m.my_field) == {"hello": False} |
| 182 | |
| 183 | |
| 184 | def test_repr() -> None: |
| 185 | model = BasicModel(foo="bar") |
| 186 | assert str(model) == "BasicModel(foo='bar')" |
| 187 | assert repr(model) == "BasicModel(foo='bar')" |
| 188 | |
| 189 | |
| 190 | def test_repr_nested_model() -> None: |
| 191 | class Child(BaseModel): |
| 192 | name: str |
| 193 | age: int |
| 194 | |
| 195 | class Parent(BaseModel): |
| 196 | name: str |
| 197 | child: Child |
| 198 | |
| 199 | model = Parent(name="Robert", child=Child(name="Foo", age=5)) |
| 200 | assert str(model) == "Parent(name='Robert', child=Child(name='Foo', age=5))" |
| 201 | assert repr(model) == "Parent(name='Robert', child=Child(name='Foo', age=5))" |
| 202 | |
| 203 | |
| 204 | def test_optional_list() -> None: |
| 205 | class Submodel(BaseModel): |
| 206 | name: str |
| 207 | |
| 208 | class Model(BaseModel): |
| 209 | items: Optional[List[Submodel]] |
| 210 | |
| 211 | m = Model.construct(items=None) |
| 212 | assert m.items is None |
| 213 | |
| 214 | m = Model.construct(items=[]) |
| 215 | assert m.items == [] |
| 216 | |
| 217 | m = Model.construct(items=[{"name": "Robert"}]) |
| 218 | assert m.items is not None |
| 219 | assert len(m.items) == 1 |
| 220 | assert m.items[0].name == "Robert" |
| 221 | |
| 222 | |
| 223 | def test_nested_union_of_models() -> None: |
| 224 | class Submodel1(BaseModel): |
| 225 | bar: bool |
| 226 | |
| 227 | class Submodel2(BaseModel): |
| 228 | thing: str |
| 229 | |
| 230 | class Model(BaseModel): |
| 231 | foo: Union[Submodel1, Submodel2] |
| 232 | |
| 233 | m = Model.construct(foo={"thing": "hello"}) |
| 234 | assert isinstance(m.foo, Submodel2) |
| 235 | assert m.foo.thing == "hello" |
| 236 | |
| 237 | |
| 238 | def test_nested_union_of_mixed_types() -> None: |
| 239 | class Submodel1(BaseModel): |
| 240 | bar: bool |
| 241 | |
| 242 | class Model(BaseModel): |
| 243 | foo: Union[Submodel1, Literal[True], Literal["CARD_HOLDER"]] |
| 244 | |
| 245 | m = Model.construct(foo=True) |
| 246 | assert m.foo is True |
| 247 | |
| 248 | m = Model.construct(foo="CARD_HOLDER") |
| 249 | assert m.foo == "CARD_HOLDER" |
| 250 | |
| 251 | m = Model.construct(foo={"bar": False}) |
| 252 | assert isinstance(m.foo, Submodel1) |
| 253 | assert m.foo.bar is False |
| 254 | |
| 255 | |
| 256 | def test_nested_union_multiple_variants() -> None: |
| 257 | class Submodel1(BaseModel): |
| 258 | bar: bool |
| 259 | |
| 260 | class Submodel2(BaseModel): |
| 261 | thing: str |
| 262 | |
| 263 | class Submodel3(BaseModel): |
| 264 | foo: int |
| 265 | |
| 266 | class Model(BaseModel): |
| 267 | foo: Union[Submodel1, Submodel2, None, Submodel3] |
| 268 | |
| 269 | m = Model.construct(foo={"thing": "hello"}) |
| 270 | assert isinstance(m.foo, Submodel2) |
| 271 | assert m.foo.thing == "hello" |
| 272 | |
| 273 | m = Model.construct(foo=None) |
| 274 | assert m.foo is None |
| 275 | |
| 276 | m = Model.construct() |
| 277 | assert m.foo is None |
| 278 | |
| 279 | m = Model.construct(foo={"foo": "1"}) |
| 280 | assert isinstance(m.foo, Submodel3) |
| 281 | assert m.foo.foo == 1 |
| 282 | |
| 283 | |
| 284 | def test_nested_union_invalid_data() -> None: |
| 285 | class Submodel1(BaseModel): |
| 286 | level: int |
| 287 | |
| 288 | class Submodel2(BaseModel): |
| 289 | name: str |
| 290 | |
| 291 | class Model(BaseModel): |
| 292 | foo: Union[Submodel1, Submodel2] |
| 293 | |
| 294 | m = Model.construct(foo=True) |
| 295 | assert cast(bool, m.foo) is True |
| 296 | |
| 297 | m = Model.construct(foo={"name": 3}) |
| 298 | if PYDANTIC_V1: |
| 299 | assert isinstance(m.foo, Submodel2) |
| 300 | assert m.foo.name == "3" |
| 301 | else: |
| 302 | assert isinstance(m.foo, Submodel1) |
| 303 | assert m.foo.name == 3 # type: ignore |
| 304 | |
| 305 | |
| 306 | def test_list_of_unions() -> None: |
| 307 | class Submodel1(BaseModel): |
| 308 | level: int |
| 309 | |
| 310 | class Submodel2(BaseModel): |
| 311 | name: str |
| 312 | |
| 313 | class Model(BaseModel): |
| 314 | items: List[Union[Submodel1, Submodel2]] |
| 315 | |
| 316 | m = Model.construct(items=[{"level": 1}, {"name": "Robert"}]) |
| 317 | assert len(m.items) == 2 |
| 318 | assert isinstance(m.items[0], Submodel1) |
| 319 | assert m.items[0].level == 1 |
| 320 | assert isinstance(m.items[1], Submodel2) |
| 321 | assert m.items[1].name == "Robert" |
| 322 | |
| 323 | m = Model.construct(items=[{"level": -1}, 156]) |
| 324 | assert len(m.items) == 2 |
| 325 | assert isinstance(m.items[0], Submodel1) |
| 326 | assert m.items[0].level == -1 |
| 327 | assert cast(Any, m.items[1]) == 156 |
| 328 | |
| 329 | |
| 330 | def test_union_of_lists() -> None: |
| 331 | class SubModel1(BaseModel): |
| 332 | level: int |
| 333 | |
| 334 | class SubModel2(BaseModel): |
| 335 | name: str |
| 336 | |
| 337 | class Model(BaseModel): |
| 338 | items: Union[List[SubModel1], List[SubModel2]] |
| 339 | |
| 340 | # with one valid entry |
| 341 | m = Model.construct(items=[{"name": "Robert"}]) |
| 342 | assert len(m.items) == 1 |
| 343 | assert isinstance(m.items[0], SubModel2) |
| 344 | assert m.items[0].name == "Robert" |
| 345 | |
| 346 | # with two entries pointing to different types |
| 347 | m = Model.construct(items=[{"level": 1}, {"name": "Robert"}]) |
| 348 | assert len(m.items) == 2 |
| 349 | assert isinstance(m.items[0], SubModel1) |
| 350 | assert m.items[0].level == 1 |
| 351 | assert isinstance(m.items[1], SubModel1) |
| 352 | assert cast(Any, m.items[1]).name == "Robert" |
| 353 | |
| 354 | # with two entries pointing to *completely* different types |
| 355 | m = Model.construct(items=[{"level": -1}, 156]) |
| 356 | assert len(m.items) == 2 |
| 357 | assert isinstance(m.items[0], SubModel1) |
| 358 | assert m.items[0].level == -1 |
| 359 | assert cast(Any, m.items[1]) == 156 |
| 360 | |
| 361 | |
| 362 | def test_dict_of_union() -> None: |
| 363 | class SubModel1(BaseModel): |
| 364 | name: str |
| 365 | |
| 366 | class SubModel2(BaseModel): |
| 367 | foo: str |
| 368 | |
| 369 | class Model(BaseModel): |
| 370 | data: Dict[str, Union[SubModel1, SubModel2]] |
| 371 | |
| 372 | m = Model.construct(data={"hello": {"name": "there"}, "foo": {"foo": "bar"}}) |
| 373 | assert len(list(m.data.keys())) == 2 |
| 374 | assert isinstance(m.data["hello"], SubModel1) |
| 375 | assert m.data["hello"].name == "there" |
| 376 | assert isinstance(m.data["foo"], SubModel2) |
| 377 | assert m.data["foo"].foo == "bar" |
| 378 | |
| 379 | # TODO: test mismatched type |
| 380 | |
| 381 | |
| 382 | def test_double_nested_union() -> None: |
| 383 | class SubModel1(BaseModel): |
| 384 | name: str |
| 385 | |
| 386 | class SubModel2(BaseModel): |
| 387 | bar: str |
| 388 | |
| 389 | class Model(BaseModel): |
| 390 | data: Dict[str, List[Union[SubModel1, SubModel2]]] |
| 391 | |
| 392 | m = Model.construct(data={"foo": [{"bar": "baz"}, {"name": "Robert"}]}) |
| 393 | assert len(m.data["foo"]) == 2 |
| 394 | |
| 395 | entry1 = m.data["foo"][0] |
| 396 | assert isinstance(entry1, SubModel2) |
| 397 | assert entry1.bar == "baz" |
| 398 | |
| 399 | entry2 = m.data["foo"][1] |
| 400 | assert isinstance(entry2, SubModel1) |
| 401 | assert entry2.name == "Robert" |
| 402 | |
| 403 | # TODO: test mismatched type |
| 404 | |
| 405 | |
| 406 | def test_union_of_dict() -> None: |
| 407 | class SubModel1(BaseModel): |
| 408 | name: str |
| 409 | |
| 410 | class SubModel2(BaseModel): |
| 411 | foo: str |
| 412 | |
| 413 | class Model(BaseModel): |
| 414 | data: Union[Dict[str, SubModel1], Dict[str, SubModel2]] |
| 415 | |
| 416 | m = Model.construct(data={"hello": {"name": "there"}, "foo": {"foo": "bar"}}) |
| 417 | assert len(list(m.data.keys())) == 2 |
| 418 | assert isinstance(m.data["hello"], SubModel1) |
| 419 | assert m.data["hello"].name == "there" |
| 420 | assert isinstance(m.data["foo"], SubModel1) |
| 421 | assert cast(Any, m.data["foo"]).foo == "bar" |
| 422 | |
| 423 | |
| 424 | def test_iso8601_datetime() -> None: |
| 425 | class Model(BaseModel): |
| 426 | created_at: datetime |
| 427 | |
| 428 | expected = datetime(2019, 12, 27, 18, 11, 19, 117000, tzinfo=timezone.utc) |
| 429 | |
| 430 | if PYDANTIC_V1: |
| 431 | expected_json = '{"created_at": "2019-12-27T18:11:19.117000+00:00"}' |
| 432 | else: |
| 433 | expected_json = '{"created_at":"2019-12-27T18:11:19.117000Z"}' |
| 434 | |
| 435 | model = Model.construct(created_at="2019-12-27T18:11:19.117Z") |
| 436 | assert model.created_at == expected |
| 437 | assert model_json(model) == expected_json |
| 438 | |
| 439 | model = parse_obj(Model, dict(created_at="2019-12-27T18:11:19.117Z")) |
| 440 | assert model.created_at == expected |
| 441 | assert model_json(model) == expected_json |
| 442 | |
| 443 | |
| 444 | def test_does_not_coerce_int() -> None: |
| 445 | class Model(BaseModel): |
| 446 | bar: int |
| 447 | |
| 448 | assert Model.construct(bar=1).bar == 1 |
| 449 | assert Model.construct(bar=10.9).bar == 10.9 |
| 450 | assert Model.construct(bar="19").bar == "19" # type: ignore[comparison-overlap] |
| 451 | assert Model.construct(bar=False).bar is False |
| 452 | |
| 453 | |
| 454 | def test_int_to_float_safe_conversion() -> None: |
| 455 | class Model(BaseModel): |
| 456 | float_field: float |
| 457 | |
| 458 | m = Model.construct(float_field=10) |
| 459 | assert m.float_field == 10.0 |
| 460 | assert isinstance(m.float_field, float) |
| 461 | |
| 462 | m = Model.construct(float_field=10.12) |
| 463 | assert m.float_field == 10.12 |
| 464 | assert isinstance(m.float_field, float) |
| 465 | |
| 466 | # number too big |
| 467 | m = Model.construct(float_field=2**53 + 1) |
| 468 | assert m.float_field == 2**53 + 1 |
| 469 | assert isinstance(m.float_field, int) |
| 470 | |
| 471 | |
| 472 | def test_deprecated_alias() -> None: |
| 473 | class Model(BaseModel): |
| 474 | resource_id: str = Field(alias="model_id") |
| 475 | |
| 476 | @property |
| 477 | def model_id(self) -> str: |
| 478 | return self.resource_id |
| 479 | |
| 480 | m = Model.construct(model_id="id") |
| 481 | assert m.model_id == "id" |
| 482 | assert m.resource_id == "id" |
| 483 | assert m.resource_id is m.model_id |
| 484 | |
| 485 | m = parse_obj(Model, {"model_id": "id"}) |
| 486 | assert m.model_id == "id" |
| 487 | assert m.resource_id == "id" |
| 488 | assert m.resource_id is m.model_id |
| 489 | |
| 490 | |
| 491 | def test_omitted_fields() -> None: |
| 492 | class Model(BaseModel): |
| 493 | resource_id: Optional[str] = None |
| 494 | |
| 495 | m = Model.construct() |
| 496 | assert m.resource_id is None |
| 497 | assert "resource_id" not in m.model_fields_set |
| 498 | |
| 499 | m = Model.construct(resource_id=None) |
| 500 | assert m.resource_id is None |
| 501 | assert "resource_id" in m.model_fields_set |
| 502 | |
| 503 | m = Model.construct(resource_id="foo") |
| 504 | assert m.resource_id == "foo" |
| 505 | assert "resource_id" in m.model_fields_set |
| 506 | |
| 507 | |
| 508 | def test_to_dict() -> None: |
| 509 | class Model(BaseModel): |
| 510 | foo: Optional[str] = Field(alias="FOO", default=None) |
| 511 | |
| 512 | m = Model(FOO="hello") |
| 513 | assert m.to_dict() == {"FOO": "hello"} |
| 514 | assert m.to_dict(use_api_names=False) == {"foo": "hello"} |
| 515 | |
| 516 | m2 = Model() |
| 517 | assert m2.to_dict() == {} |
| 518 | assert m2.to_dict(exclude_unset=False) == {"FOO": None} |
| 519 | assert m2.to_dict(exclude_unset=False, exclude_none=True) == {} |
| 520 | assert m2.to_dict(exclude_unset=False, exclude_defaults=True) == {} |
| 521 | |
| 522 | m3 = Model(FOO=None) |
| 523 | assert m3.to_dict() == {"FOO": None} |
| 524 | assert m3.to_dict(exclude_none=True) == {} |
| 525 | assert m3.to_dict(exclude_defaults=True) == {} |
| 526 | |
| 527 | class Model2(BaseModel): |
| 528 | created_at: datetime |
| 529 | |
| 530 | time_str = "2024-03-21T11:39:01.275859" |
| 531 | m4 = Model2.construct(created_at=time_str) |
| 532 | assert m4.to_dict(mode="python") == {"created_at": datetime.fromisoformat(time_str)} |
| 533 | assert m4.to_dict(mode="json") == {"created_at": time_str} |
| 534 | |
| 535 | if PYDANTIC_V1: |
| 536 | with pytest.raises(ValueError, match="warnings is only supported in Pydantic v2"): |
| 537 | m.to_dict(warnings=False) |
| 538 | |
| 539 | |
| 540 | def test_forwards_compat_model_dump_method() -> None: |
| 541 | class Model(BaseModel): |
| 542 | foo: Optional[str] = Field(alias="FOO", default=None) |
| 543 | |
| 544 | m = Model(FOO="hello") |
| 545 | assert m.model_dump() == {"foo": "hello"} |
| 546 | assert m.model_dump(include={"bar"}) == {} |
| 547 | assert m.model_dump(exclude={"foo"}) == {} |
| 548 | assert m.model_dump(by_alias=True) == {"FOO": "hello"} |
| 549 | |
| 550 | m2 = Model() |
| 551 | assert m2.model_dump() == {"foo": None} |
| 552 | assert m2.model_dump(exclude_unset=True) == {} |
| 553 | assert m2.model_dump(exclude_none=True) == {} |
| 554 | assert m2.model_dump(exclude_defaults=True) == {} |
| 555 | |
| 556 | m3 = Model(FOO=None) |
| 557 | assert m3.model_dump() == {"foo": None} |
| 558 | assert m3.model_dump(exclude_none=True) == {} |
| 559 | |
| 560 | if PYDANTIC_V1: |
| 561 | with pytest.raises(ValueError, match="round_trip is only supported in Pydantic v2"): |
| 562 | m.model_dump(round_trip=True) |
| 563 | |
| 564 | with pytest.raises(ValueError, match="warnings is only supported in Pydantic v2"): |
| 565 | m.model_dump(warnings=False) |
| 566 | |
| 567 | |
| 568 | def test_compat_method_no_error_for_warnings() -> None: |
| 569 | class Model(BaseModel): |
| 570 | foo: Optional[str] |
| 571 | |
| 572 | m = Model(foo="hello") |
| 573 | assert isinstance(model_dump(m, warnings=False), dict) |
| 574 | |
| 575 | |
| 576 | def test_to_json() -> None: |
| 577 | class Model(BaseModel): |
| 578 | foo: Optional[str] = Field(alias="FOO", default=None) |
| 579 | |
| 580 | m = Model(FOO="hello") |
| 581 | assert json.loads(m.to_json()) == {"FOO": "hello"} |
| 582 | assert json.loads(m.to_json(use_api_names=False)) == {"foo": "hello"} |
| 583 | |
| 584 | if PYDANTIC_V1: |
| 585 | assert m.to_json(indent=None) == '{"FOO": "hello"}' |
| 586 | else: |
| 587 | assert m.to_json(indent=None) == '{"FOO":"hello"}' |
| 588 | |
| 589 | m2 = Model() |
| 590 | assert json.loads(m2.to_json()) == {} |
| 591 | assert json.loads(m2.to_json(exclude_unset=False)) == {"FOO": None} |
| 592 | assert json.loads(m2.to_json(exclude_unset=False, exclude_none=True)) == {} |
| 593 | assert json.loads(m2.to_json(exclude_unset=False, exclude_defaults=True)) == {} |
| 594 | |
| 595 | m3 = Model(FOO=None) |
| 596 | assert json.loads(m3.to_json()) == {"FOO": None} |
| 597 | assert json.loads(m3.to_json(exclude_none=True)) == {} |
| 598 | |
| 599 | if PYDANTIC_V1: |
| 600 | with pytest.raises(ValueError, match="warnings is only supported in Pydantic v2"): |
| 601 | m.to_json(warnings=False) |
| 602 | |
| 603 | |
| 604 | def test_forwards_compat_model_dump_json_method() -> None: |
| 605 | class Model(BaseModel): |
| 606 | foo: Optional[str] = Field(alias="FOO", default=None) |
| 607 | |
| 608 | m = Model(FOO="hello") |
| 609 | assert json.loads(m.model_dump_json()) == {"foo": "hello"} |
| 610 | assert json.loads(m.model_dump_json(include={"bar"})) == {} |
| 611 | assert json.loads(m.model_dump_json(include={"foo"})) == {"foo": "hello"} |
| 612 | assert json.loads(m.model_dump_json(by_alias=True)) == {"FOO": "hello"} |
| 613 | |
| 614 | assert m.model_dump_json(indent=2) == '{\n "foo": "hello"\n}' |
| 615 | |
| 616 | m2 = Model() |
| 617 | assert json.loads(m2.model_dump_json()) == {"foo": None} |
| 618 | assert json.loads(m2.model_dump_json(exclude_unset=True)) == {} |
| 619 | assert json.loads(m2.model_dump_json(exclude_none=True)) == {} |
| 620 | assert json.loads(m2.model_dump_json(exclude_defaults=True)) == {} |
| 621 | |
| 622 | m3 = Model(FOO=None) |
| 623 | assert json.loads(m3.model_dump_json()) == {"foo": None} |
| 624 | assert json.loads(m3.model_dump_json(exclude_none=True)) == {} |
| 625 | |
| 626 | if PYDANTIC_V1: |
| 627 | with pytest.raises(ValueError, match="round_trip is only supported in Pydantic v2"): |
| 628 | m.model_dump_json(round_trip=True) |
| 629 | |
| 630 | with pytest.raises(ValueError, match="warnings is only supported in Pydantic v2"): |
| 631 | m.model_dump_json(warnings=False) |
| 632 | |
| 633 | |
| 634 | def test_type_compat() -> None: |
| 635 | # our model type can be assigned to Pydantic's model type |
| 636 | |
| 637 | def takes_pydantic(model: pydantic.BaseModel) -> None: # noqa: ARG001 |
| 638 | ... |
| 639 | |
| 640 | class OurModel(BaseModel): |
| 641 | foo: Optional[str] = None |
| 642 | |
| 643 | takes_pydantic(OurModel()) |
| 644 | |
| 645 | |
| 646 | def test_annotated_types() -> None: |
| 647 | class Model(BaseModel): |
| 648 | value: str |
| 649 | |
| 650 | m = construct_type( |
| 651 | value={"value": "foo"}, |
| 652 | type_=cast(Any, Annotated[Model, "random metadata"]), |
| 653 | ) |
| 654 | assert isinstance(m, Model) |
| 655 | assert m.value == "foo" |
| 656 | |
| 657 | |
| 658 | def test_discriminated_unions_invalid_data() -> None: |
| 659 | class A(BaseModel): |
| 660 | type: Literal["a"] |
| 661 | |
| 662 | data: str |
| 663 | |
| 664 | class B(BaseModel): |
| 665 | type: Literal["b"] |
| 666 | |
| 667 | data: int |
| 668 | |
| 669 | m = construct_type( |
| 670 | value={"type": "b", "data": "foo"}, |
| 671 | type_=cast(Any, Annotated[Union[A, B], PropertyInfo(discriminator="type")]), |
| 672 | ) |
| 673 | assert isinstance(m, B) |
| 674 | assert m.type == "b" |
| 675 | assert m.data == "foo" # type: ignore[comparison-overlap] |
| 676 | |
| 677 | m = construct_type( |
| 678 | value={"type": "a", "data": 100}, |
| 679 | type_=cast(Any, Annotated[Union[A, B], PropertyInfo(discriminator="type")]), |
| 680 | ) |
| 681 | assert isinstance(m, A) |
| 682 | assert m.type == "a" |
| 683 | if PYDANTIC_V1: |
| 684 | # pydantic v1 automatically converts inputs to strings |
| 685 | # if the expected type is a str |
| 686 | assert m.data == "100" |
| 687 | else: |
| 688 | assert m.data == 100 # type: ignore[comparison-overlap] |
| 689 | |
| 690 | |
| 691 | def test_discriminated_unions_unknown_variant() -> None: |
| 692 | class A(BaseModel): |
| 693 | type: Literal["a"] |
| 694 | |
| 695 | data: str |
| 696 | |
| 697 | class B(BaseModel): |
| 698 | type: Literal["b"] |
| 699 | |
| 700 | data: int |
| 701 | |
| 702 | m = construct_type( |
| 703 | value={"type": "c", "data": None, "new_thing": "bar"}, |
| 704 | type_=cast(Any, Annotated[Union[A, B], PropertyInfo(discriminator="type")]), |
| 705 | ) |
| 706 | |
| 707 | # just chooses the first variant |
| 708 | assert isinstance(m, A) |
| 709 | assert m.type == "c" # type: ignore[comparison-overlap] |
| 710 | assert m.data == None # type: ignore[unreachable] |
| 711 | assert m.new_thing == "bar" |
| 712 | |
| 713 | |
| 714 | def test_discriminated_unions_invalid_data_nested_unions() -> None: |
| 715 | class A(BaseModel): |
| 716 | type: Literal["a"] |
| 717 | |
| 718 | data: str |
| 719 | |
| 720 | class B(BaseModel): |
| 721 | type: Literal["b"] |
| 722 | |
| 723 | data: int |
| 724 | |
| 725 | class C(BaseModel): |
| 726 | type: Literal["c"] |
| 727 | |
| 728 | data: bool |
| 729 | |
| 730 | m = construct_type( |
| 731 | value={"type": "b", "data": "foo"}, |
| 732 | type_=cast(Any, Annotated[Union[Union[A, B], C], PropertyInfo(discriminator="type")]), |
| 733 | ) |
| 734 | assert isinstance(m, B) |
| 735 | assert m.type == "b" |
| 736 | assert m.data == "foo" # type: ignore[comparison-overlap] |
| 737 | |
| 738 | m = construct_type( |
| 739 | value={"type": "c", "data": "foo"}, |
| 740 | type_=cast(Any, Annotated[Union[Union[A, B], C], PropertyInfo(discriminator="type")]), |
| 741 | ) |
| 742 | assert isinstance(m, C) |
| 743 | assert m.type == "c" |
| 744 | assert m.data == "foo" # type: ignore[comparison-overlap] |
| 745 | |
| 746 | |
| 747 | def test_discriminated_unions_with_aliases_invalid_data() -> None: |
| 748 | class A(BaseModel): |
| 749 | foo_type: Literal["a"] = Field(alias="type") |
| 750 | |
| 751 | data: str |
| 752 | |
| 753 | class B(BaseModel): |
| 754 | foo_type: Literal["b"] = Field(alias="type") |
| 755 | |
| 756 | data: int |
| 757 | |
| 758 | m = construct_type( |
| 759 | value={"type": "b", "data": "foo"}, |
| 760 | type_=cast(Any, Annotated[Union[A, B], PropertyInfo(discriminator="foo_type")]), |
| 761 | ) |
| 762 | assert isinstance(m, B) |
| 763 | assert m.foo_type == "b" |
| 764 | assert m.data == "foo" # type: ignore[comparison-overlap] |
| 765 | |
| 766 | m = construct_type( |
| 767 | value={"type": "a", "data": 100}, |
| 768 | type_=cast(Any, Annotated[Union[A, B], PropertyInfo(discriminator="foo_type")]), |
| 769 | ) |
| 770 | assert isinstance(m, A) |
| 771 | assert m.foo_type == "a" |
| 772 | if PYDANTIC_V1: |
| 773 | # pydantic v1 automatically converts inputs to strings |
| 774 | # if the expected type is a str |
| 775 | assert m.data == "100" |
| 776 | else: |
| 777 | assert m.data == 100 # type: ignore[comparison-overlap] |
| 778 | |
| 779 | |
| 780 | def test_discriminated_unions_overlapping_discriminators_invalid_data() -> None: |
| 781 | class A(BaseModel): |
| 782 | type: Literal["a"] |
| 783 | |
| 784 | data: bool |
| 785 | |
| 786 | class B(BaseModel): |
| 787 | type: Literal["a"] |
| 788 | |
| 789 | data: int |
| 790 | |
| 791 | m = construct_type( |
| 792 | value={"type": "a", "data": "foo"}, |
| 793 | type_=cast(Any, Annotated[Union[A, B], PropertyInfo(discriminator="type")]), |
| 794 | ) |
| 795 | assert isinstance(m, B) |
| 796 | assert m.type == "a" |
| 797 | assert m.data == "foo" # type: ignore[comparison-overlap] |
| 798 | |
| 799 | |
| 800 | def test_discriminated_unions_invalid_data_uses_cache() -> None: |
| 801 | class A(BaseModel): |
| 802 | type: Literal["a"] |
| 803 | |
| 804 | data: str |
| 805 | |
| 806 | class B(BaseModel): |
| 807 | type: Literal["b"] |
| 808 | |
| 809 | data: int |
| 810 | |
| 811 | UnionType = cast(Any, Union[A, B]) |
| 812 | |
| 813 | assert not DISCRIMINATOR_CACHE.get(UnionType) |
| 814 | |
| 815 | m = construct_type( |
| 816 | value={"type": "b", "data": "foo"}, type_=cast(Any, Annotated[UnionType, PropertyInfo(discriminator="type")]) |
| 817 | ) |
| 818 | assert isinstance(m, B) |
| 819 | assert m.type == "b" |
| 820 | assert m.data == "foo" # type: ignore[comparison-overlap] |
| 821 | |
| 822 | discriminator = DISCRIMINATOR_CACHE.get(UnionType) |
| 823 | assert discriminator is not None |
| 824 | |
| 825 | m = construct_type( |
| 826 | value={"type": "b", "data": "foo"}, type_=cast(Any, Annotated[UnionType, PropertyInfo(discriminator="type")]) |
| 827 | ) |
| 828 | assert isinstance(m, B) |
| 829 | assert m.type == "b" |
| 830 | assert m.data == "foo" # type: ignore[comparison-overlap] |
| 831 | |
| 832 | # if the discriminator details object stays the same between invocations then |
| 833 | # we hit the cache |
| 834 | assert DISCRIMINATOR_CACHE.get(UnionType) is discriminator |
| 835 | |
| 836 | |
| 837 | @pytest.mark.skipif(PYDANTIC_V1, reason="TypeAliasType is not supported in Pydantic v1") |
| 838 | def test_type_alias_type() -> None: |
| 839 | Alias = TypeAliasType("Alias", str) # pyright: ignore |
| 840 | |
| 841 | class Model(BaseModel): |
| 842 | alias: Alias |
| 843 | union: Union[int, Alias] |
| 844 | |
| 845 | m = construct_type(value={"alias": "foo", "union": "bar"}, type_=Model) |
| 846 | assert isinstance(m, Model) |
| 847 | assert isinstance(m.alias, str) |
| 848 | assert m.alias == "foo" |
| 849 | assert isinstance(m.union, str) |
| 850 | assert m.union == "bar" |
| 851 | |
| 852 | |
| 853 | @pytest.mark.skipif(PYDANTIC_V1, reason="TypeAliasType is not supported in Pydantic v1") |
| 854 | def test_field_named_cls() -> None: |
| 855 | class Model(BaseModel): |
| 856 | cls: str |
| 857 | |
| 858 | m = construct_type(value={"cls": "foo"}, type_=Model) |
| 859 | assert isinstance(m, Model) |
| 860 | assert isinstance(m.cls, str) |
| 861 | |
| 862 | |
| 863 | def test_discriminated_union_case() -> None: |
| 864 | class A(BaseModel): |
| 865 | type: Literal["a"] |
| 866 | |
| 867 | data: bool |
| 868 | |
| 869 | class B(BaseModel): |
| 870 | type: Literal["b"] |
| 871 | |
| 872 | data: List[Union[A, object]] |
| 873 | |
| 874 | class ModelA(BaseModel): |
| 875 | type: Literal["modelA"] |
| 876 | |
| 877 | data: int |
| 878 | |
| 879 | class ModelB(BaseModel): |
| 880 | type: Literal["modelB"] |
| 881 | |
| 882 | required: str |
| 883 | |
| 884 | data: Union[A, B] |
| 885 | |
| 886 | # when constructing ModelA | ModelB, value data doesn't match ModelB exactly - missing `required` |
| 887 | m = construct_type( |
| 888 | value={"type": "modelB", "data": {"type": "a", "data": True}}, |
| 889 | type_=cast(Any, Annotated[Union[ModelA, ModelB], PropertyInfo(discriminator="type")]), |
| 890 | ) |
| 891 | |
| 892 | assert isinstance(m, ModelB) |
| 893 | |
| 894 | |
| 895 | def test_nested_discriminated_union() -> None: |
| 896 | class InnerType1(BaseModel): |
| 897 | type: Literal["type_1"] |
| 898 | |
| 899 | class InnerModel(BaseModel): |
| 900 | inner_value: str |
| 901 | |
| 902 | class InnerType2(BaseModel): |
| 903 | type: Literal["type_2"] |
| 904 | some_inner_model: InnerModel |
| 905 | |
| 906 | class Type1(BaseModel): |
| 907 | base_type: Literal["base_type_1"] |
| 908 | value: Annotated[ |
| 909 | Union[ |
| 910 | InnerType1, |
| 911 | InnerType2, |
| 912 | ], |
| 913 | PropertyInfo(discriminator="type"), |
| 914 | ] |
| 915 | |
| 916 | class Type2(BaseModel): |
| 917 | base_type: Literal["base_type_2"] |
| 918 | |
| 919 | T = Annotated[ |
| 920 | Union[ |
| 921 | Type1, |
| 922 | Type2, |
| 923 | ], |
| 924 | PropertyInfo(discriminator="base_type"), |
| 925 | ] |
| 926 | |
| 927 | model = construct_type( |
| 928 | type_=T, |
| 929 | value={ |
| 930 | "base_type": "base_type_1", |
| 931 | "value": { |
| 932 | "type": "type_2", |
| 933 | }, |
| 934 | }, |
| 935 | ) |
| 936 | assert isinstance(model, Type1) |
| 937 | assert isinstance(model.value, InnerType2) |
| 938 | |
| 939 | |
| 940 | @pytest.mark.skipif(PYDANTIC_V1, reason="this is only supported in pydantic v2 for now") |
| 941 | def test_extra_properties() -> None: |
| 942 | class Item(BaseModel): |
| 943 | prop: int |
| 944 | |
| 945 | class Model(BaseModel): |
| 946 | __pydantic_extra__: Dict[str, Item] = Field(init=False) # pyright: ignore[reportIncompatibleVariableOverride] |
| 947 | |
| 948 | other: str |
| 949 | |
| 950 | if TYPE_CHECKING: |
| 951 | |
| 952 | def __getattr__(self, attr: str) -> Item: ... |
| 953 | |
| 954 | model = construct_type( |
| 955 | type_=Model, |
| 956 | value={ |
| 957 | "a": {"prop": 1}, |
| 958 | "other": "foo", |
| 959 | }, |
| 960 | ) |
| 961 | assert isinstance(model, Model) |
| 962 | assert model.a.prop == 1 |
| 963 | assert isinstance(model.a, Item) |
| 964 | assert model.other == "foo" |
| 965 | |
| 966 | |
| 967 | # NOTE: Workaround for Pydantic Iterable behavior. |
| 968 | # Iterable fields are replaced with a ValidatorIterator and may be consumed |
| 969 | # during serialization, which can cause subsequent dumps to return empty data. |
| 970 | # See: https://github.com/pydantic/pydantic/issues/9541 |
| 971 | @pytest.mark.parametrize( |
| 972 | "data, expected_validated", |
| 973 | [ |
| 974 | ([1, 2, 3], [1, 2, 3]), |
| 975 | ((1, 2, 3), (1, 2, 3)), |
| 976 | (set([1, 2, 3]), set([1, 2, 3])), |
| 977 | (iter([1, 2, 3]), [1, 2, 3]), |
| 978 | ([], []), |
| 979 | ((x for x in [1, 2, 3]), [1, 2, 3]), |
| 980 | (map(lambda x: x, [1, 2, 3]), [1, 2, 3]), |
| 981 | (frozenset([1, 2, 3]), frozenset([1, 2, 3])), |
| 982 | (deque([1, 2, 3]), deque([1, 2, 3])), |
| 983 | ], |
| 984 | ids=["list", "tuple", "set", "iterator", "empty", "generator", "map", "frozenset", "deque"], |
| 985 | ) |
| 986 | @pytest.mark.skipif(PYDANTIC_V1, reason="this is only supported in pydantic v2") |
| 987 | def test_iterable_construction(data: Iterable[int], expected_validated: Iterable[int]) -> None: |
| 988 | class TypeWithIterable(TypedDict): |
| 989 | items: EagerIterable[int] |
| 990 | |
| 991 | class Model(BaseModel): |
| 992 | data: TypeWithIterable |
| 993 | |
| 994 | m = Model.model_validate({"data": {"items": data}}) |
| 995 | assert m.data["items"] == expected_validated |
| 996 | |
| 997 | # Verify repeated dumps don't lose data (the original bug) |
| 998 | assert m.model_dump()["data"]["items"] == list(expected_validated) |
| 999 | assert m.model_dump()["data"]["items"] == list(expected_validated) |
| 1000 | |
| 1001 | |
| 1002 | @pytest.mark.skipif(PYDANTIC_V1, reason="this is only supported in pydantic v2") |
| 1003 | def test_iterable_construction_str_falls_back_to_list() -> None: |
| 1004 | # str is iterable (over chars), but str(list_of_chars) produces the list's repr |
| 1005 | # rather than reconstructing a string from items. We special-case str to fall |
| 1006 | # back to list instead of attempting reconstruction. |
| 1007 | class TypeWithIterable(TypedDict): |
| 1008 | items: EagerIterable[str] |
| 1009 | |
| 1010 | class Model(BaseModel): |
| 1011 | data: TypeWithIterable |
| 1012 | |
| 1013 | m = Model.model_validate({"data": {"items": "hello"}}) |
| 1014 | |
| 1015 | # falls back to list of chars rather than calling str(["h", "e", "l", "l", "o"]) |
| 1016 | assert m.data["items"] == ["h", "e", "l", "l", "o"] |
| 1017 | assert m.model_dump()["data"]["items"] == ["h", "e", "l", "l", "o"] |