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docs_src/python_types/tutorial011_py39.py
class User(BaseModel): id: int name: str = "John Doe" signup_ts: Union[datetime, None] = None friends: list[int] = [] external_data = { "id": "123", "signup_ts": "2017-06-01 12:22", "friends": [1, "2", b"3"], } user = User(**external_data) print(user) # > User id=123 name='John Doe' signup_ts=datetime.datetime(2017, 6, 1, 12, 22) friends=[1, 2, 3] print(user.id)
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sat Sep 02 15:56:35 UTC 2023 - 492 bytes - Viewed (0) -
docs_src/python_types/tutorial011.py
class User(BaseModel): id: int name: str = "John Doe" signup_ts: Union[datetime, None] = None friends: List[int] = [] external_data = { "id": "123", "signup_ts": "2017-06-01 12:22", "friends": [1, "2", b"3"], } user = User(**external_data) print(user) # > User id=123 name='John Doe' signup_ts=datetime.datetime(2017, 6, 1, 12, 22) friends=[1, 2, 3] print(user.id)
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sat Sep 02 15:56:35 UTC 2023 - 498 bytes - Viewed (0) -
tests/test_response_model_as_return_annotation.py
return User(name="John", surname="Doe") @app.get("/no_response_model-no_annotation-return_dict") def no_response_model_no_annotation_return_dict(): return {"name": "John", "surname": "Doe"} @app.get("/response_model-no_annotation-return_same_model", response_model=User) def response_model_no_annotation_return_same_model(): return User(name="John", surname="Doe")
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Mon Aug 14 09:49:57 UTC 2023 - 47.7K bytes - Viewed (0) -
docs_src/python_types/tutorial011_py310.py
from pydantic import BaseModel class User(BaseModel): id: int name: str = "John Doe" signup_ts: datetime | None = None friends: list[int] = [] external_data = { "id": "123", "signup_ts": "2017-06-01 12:22", "friends": [1, "2", b"3"], } user = User(**external_data) print(user) # > User id=123 name='John Doe' signup_ts=datetime.datetime(2017, 6, 1, 12, 22) friends=[1, 2, 3] print(user.id)
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sat Sep 02 15:56:35 UTC 2023 - 461 bytes - Viewed (0) -
src/test/java/org/codelibs/fess/sso/oic/OpenIdConnectAuthenticatorTest.java
String jwtClaim = "{\"email\":\"******@****.***\",\"sub\":\"1234567890\",\"name\":\"John Doe\",\"groups\":[\"group1\",\"group2\"]}"; // Execute authenticator.parseJwtClaim(jwtClaim, attributes); // Verify assertEquals("1234567890", attributes.get("sub")); assertEquals("John Doe", attributes.get("name")); // Check groups array
Registered: Thu Oct 31 13:40:30 UTC 2024 - Last Modified: Fri Oct 11 21:11:58 UTC 2024 - 2K bytes - Viewed (0) -
docs/em/docs/tutorial/extra-models.md
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docs/zh/docs/tutorial/extra-models.md
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docs_src/python_types/tutorial002.py
def get_full_name(first_name: str, last_name: str): full_name = first_name.title() + " " + last_name.title() return full_name
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Thu Mar 26 19:09:53 UTC 2020 - 172 bytes - Viewed (0) -
docs/en/docs/tutorial/extra-models.md
Pydantic models have a `.dict()` 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.doe@example.com") ``` and then we call: ```Python user_dict = user_in.dict() ``` we now have a `dict` with the data in the variable `user_dict` (it's a `dict` instead of a Pydantic model object).
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 7.7K bytes - Viewed (0) -
docs_src/security/tutorial002_an_py39.py
full_name: Union[str, None] = None disabled: Union[bool, None] = None def fake_decode_token(token): return User( username=token + "fakedecoded", email="******@****.***", full_name="John Doe" ) async def get_current_user(token: Annotated[str, Depends(oauth2_scheme)]): user = fake_decode_token(token) return user @app.get("/users/me")
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sat Mar 18 12:29:59 UTC 2023 - 786 bytes - Viewed (0)