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docs/en/docs/tutorial/extra-models.md
Pydantic models have a `.model_dump()` method that returns a `dict` with the model's data. So, if we create a Pydantic object `user_in` like: ```Python user_in = UserIn(username="john", password="secret", email="john******@****.***") ``` and then we call: ```Python user_dict = user_in.model_dump() ```
Registered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Sat Dec 20 15:55:38 UTC 2025 - 6.9K bytes - Viewed (0) -
tests/test_tutorial/test_body_multiple_params/test_tutorial002.py
Registered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Fri Dec 26 10:43:02 UTC 2025 - 11K bytes - Viewed (0) -
docs/de/docs/tutorial/extra-models.md
Wenn wir also ein Pydantic-Objekt `user_in` erstellen, etwa so: ```Python user_in = UserIn(username="john", password="secret", email="john******@****.***") ``` und dann aufrufen: ```Python user_dict = user_in.model_dump() ```
Registered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Wed Dec 24 10:28:19 UTC 2025 - 8K bytes - Viewed (0) -
docs/ru/docs/tutorial/extra-models.md
У Pydantic-моделей есть метод `.dict()`, который возвращает `dict` с данными модели. Поэтому, если мы создадим Pydantic-объект `user_in` таким способом: ```Python user_in = UserIn(username="john", password="secret", email="john******@****.***") ``` и затем вызовем: ```Python user_dict = user_in.dict() ```
Registered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Tue Sep 30 11:24:39 UTC 2025 - 11.5K bytes - Viewed (0) -
docs_src/security/tutorial002_py39.py
full_name: Union[str, None] = None disabled: Union[bool, None] = None def fake_decode_token(token): return User( username=token + "fakedecoded", email="john@example.com", full_name="John Doe" ) async def get_current_user(token: str = Depends(oauth2_scheme)): user = fake_decode_token(token) return user @app.get("/users/me")
Registered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Wed Dec 17 20:41:43 UTC 2025 - 755 bytes - Viewed (0) -
docs/pt/docs/tutorial/extra-models.md
Os modelos Pydantic possuem um método `.dict()` que retorna um `dict` com os dados do modelo. Então, se criarmos um objeto Pydantic `user_in` como: ```Python user_in = UserIn(username="john", password="secret", email="john******@****.***") ``` e depois chamarmos: ```Python user_dict = user_in.dict() ```
Registered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Wed Nov 12 16:23:57 UTC 2025 - 7.5K bytes - Viewed (0) -
tests/test_tutorial/test_security/test_tutorial002.py
assert response.status_code == 200, response.text assert response.json() == { "username": "testtokenfakedecoded", "email": "john@example.com", "full_name": "John Doe", "disabled": None, } def test_openapi_schema(client: TestClient): response = client.get("/openapi.json") assert response.status_code == 200, response.textRegistered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Fri Dec 26 10:43:02 UTC 2025 - 2.2K bytes - Viewed (0) -
tests/test_security_http_basic_realm_description.py
client = TestClient(app) def test_security_http_basic(): response = client.get("/users/me", auth=("john", "secret")) assert response.status_code == 200, response.text assert response.json() == {"username": "john", "password": "secret"} def test_security_http_basic_no_credentials(): response = client.get("/users/me")
Registered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Mon Nov 24 19:03:06 UTC 2025 - 2.7K bytes - Viewed (0) -
tests/test_tutorial/test_custom_docs_ui/test_tutorial002.py
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tests/test_stringified_annotation_dependency.py
from inline_snapshot import snapshot if TYPE_CHECKING: # pragma: no cover from collections.abc import AsyncGenerator class DummyClient: async def get_people(self) -> list: return ["John Doe", "Jane Doe"] async def close(self) -> None: pass async def get_client() -> AsyncGenerator[DummyClient, None]: client = DummyClient() yield client await client.close()Registered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Wed Dec 17 21:25:59 UTC 2025 - 2.2K bytes - Viewed (0)