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docs/ko/docs/tutorial/body.md
<img src="/img/tutorial/body/image01.png"> 이를 필요로 하는 각각의 *경로 작동*내부의 API 문서에도 사용됩니다: <img src="/img/tutorial/body/image02.png"> ## 편집기 지원 편집기에서, 함수 내에서 타입 힌트와 완성을 어디서나 (만약 Pydantic model 대신에 `dict`을 받을 경우 나타나지 않을 수 있습니다) 받을 수 있습니다: <img src="/img/tutorial/body/image03.png"> 잘못된 타입 연산에 대한 에러 확인도 받을 수 있습니다: <img src="/img/tutorial/body/image04.png">
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 8.7K bytes - Viewed (0) -
docs/features/https.md
* `COMPATIBLE_TLS` is a secure configuration that connects to secure–but not current–HTTPS servers. * `CLEARTEXT` is an insecure configuration that is used for `http://` URLs. These loosely follow the model set in [Google Cloud Policies](https://cloud.google.com/load-balancing/docs/ssl-policies-concepts). We [track changes](../security/tls_configuration_history.md) to this policy.
Registered: Fri Nov 01 11:42:11 UTC 2024 - Last Modified: Sat Dec 24 00:16:30 UTC 2022 - 10.5K bytes - Viewed (0) -
docs/em/docs/features.md
```Python from datetime import date from pydantic import BaseModel # Declare a variable as a str # and get editor support inside the function def main(user_id: str): return user_id # A Pydantic model class User(BaseModel): id: int name: str joined: date ``` 👈 💪 ⤴️ ⚙️ 💖: ```Python my_user: User = User(id=3, name="John Doe", joined="2018-07-19") second_user_data = {
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Tue Aug 06 04:48:30 UTC 2024 - 8K bytes - Viewed (0) -
docs/en/docs/advanced/openapi-callbacks.md
Temporarily adopting this point of view (of the *external developer*) can help you feel like it's more obvious where to put the parameters, the Pydantic model for the body, for the response, etc. for that *external API*. /// ### Create a callback `APIRouter` First create a new `APIRouter` that will contain one or more callbacks. ```Python hl_lines="3 25"
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/tr/docs/tutorial/first-steps.md
Ayrıca, Pydantic modelleri de döndürebilirsiniz (bu konu ileriki aşamalarda irdelenecektir). Otomatik olarak JSON'a dönüştürülecek (ORM'ler vb. dahil) başka birçok nesne ve model vardır. En beğendiklerinizi kullanmayı deneyin, yüksek ihtimalle destekleniyordur. ## Özet * `FastAPI`'yı projemize dahil ettik. * Bir `app` örneği oluşturduk.
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 10.5K bytes - Viewed (0) -
migrator/migrator.go
// // // CREATE VIEW `user_view` AS SELECT * FROM `users` WHERE age > 20 // q := DB.Model(&User{}).Where("age > ?", 20) // DB.Debug().Migrator().CreateView("user_view", gorm.ViewOption{Query: q}) // // // CREATE OR REPLACE VIEW `users_view` AS SELECT * FROM `users` WITH CHECK OPTION // q := DB.Model(&User{})
Registered: Sun Nov 03 09:35:10 UTC 2024 - Last Modified: Fri Apr 26 07:15:49 UTC 2024 - 29K bytes - Viewed (0) -
docs/de/docs/advanced/settings.md
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 17.7K bytes - Viewed (0) -
fastapi/security/oauth2.py
provided in one of multiple optional ways (for example, with OAuth2 or in a cookie). """ ), ] = True, ): self.model = OAuth2Model( flows=cast(OAuthFlowsModel, flows), description=description ) self.scheme_name = scheme_name or self.__class__.__name__ self.auto_error = auto_error
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Wed Oct 23 18:30:18 UTC 2024 - 21.1K bytes - Viewed (0) -
docs/tr/docs/tutorial/path-params.md
/// /// tip | "İpucu" Merak ediyorsanız söyleyeyim, "AlexNet", "ResNet" ve "LeNet" isimleri Makine Öğrenmesi <abbr title="Teknik olarak, Derin Öğrenme model mimarileri">modellerini</abbr> temsil eder. /// ### Bir *Yol Parametresi* Tanımlayalım Sonrasında, yarattığımız enum sınıfını (`ModelName`) kullanarak tip belirteci aracılığıyla bir *yol parametresi* oluşturalım:
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 10.8K bytes - Viewed (0) -
docs/en/docs/deployment/concepts.md
### Memory per Process Now, when the program loads things in memory, for example, a machine learning model in a variable, or the contents of a large file in a variable, all that **consumes a bit of the memory (RAM)** of the server.
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Wed Sep 18 16:09:57 UTC 2024 - 17.8K bytes - Viewed (0)