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fastapi/dependencies/models.py
Sebastián Ramírez <******@****.***> 1725135570 +0200
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sat Aug 31 20:19:30 UTC 2024 - 1.5K bytes - Viewed (0) -
fastapi/openapi/models.py
Paul <******@****.***> 1713480573 -0400
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docs/ru/docs/tutorial/response-model.md
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 30.4K bytes - Viewed (0) -
docs/pt/docs/tutorial/body-updates.md
* Recuperar os dados armazenados. * Colocar esses dados em um modelo do Pydantic. * Gerar um `dict` sem valores padrão a partir do modelo de entrada (usando `exclude_unset`). * Dessa forma, você pode atualizar apenas os valores definidos pelo usuário, em vez de substituir os valores já armazenados com valores padrão em seu modelo.
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Mon Oct 14 09:16:06 UTC 2024 - 6K bytes - Viewed (0) -
docs/em/docs/tutorial/body-nested-models.md
```Python hl_lines="13" {!> ../../docs_src/body_nested_models/tutorial008_py39.py!} ``` //// ## 👨🎨 🐕🦺 🌐 & 👆 🤚 👨🎨 🐕🦺 🌐. 🏬 🔘 📇: <img src="/img/tutorial/body-nested-models/image01.png"> 👆 🚫 🚫 🤚 👉 😇 👨🎨 🐕🦺 🚥 👆 👷 🔗 ⏮️ `dict` ↩️ Pydantic 🏷. ✋️ 👆 🚫 ✔️ 😟 🔃 👫 👯♂️, 📨 #️⃣ 🗜 🔁 & 👆 🔢 🗜 🔁 🎻 💁♂️. ## 💪 ❌ `dict`Ⓜ
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 9.1K bytes - Viewed (0) -
docs/zh/docs/tutorial/extra-models.md
Sebastián Ramírez <******@****.***> 1728247014 +0200
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 6.6K bytes - Viewed (0) -
docs/fr/docs/advanced/additional-responses.md
**FastAPI** prendra ce modèle, générera son schéma JSON et l'inclura au bon endroit dans OpenAPI. Par exemple, pour déclarer une autre réponse avec un code HTTP `404` et un modèle Pydantic `Message`, vous pouvez écrire : ```Python hl_lines="18 22" {!../../docs_src/additional_responses/tutorial001.py!} ``` /// note | "Remarque" Gardez à l'esprit que vous devez renvoyer directement `JSONResponse`. /// /// info
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 9.6K bytes - Viewed (0) -
docs/de/docs/tutorial/encoder.md
Genauso würde die Datenbank kein Pydantic-Modell (ein Objekt mit Attributen) akzeptieren, sondern nur ein `dict`. Sie können für diese Fälle `jsonable_encoder` verwenden. Es nimmt ein Objekt entgegen, wie etwa ein Pydantic-Modell, und gibt eine JSON-kompatible Version zurück: //// tab | Python 3.10+ ```Python hl_lines="4 21"
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 1.9K bytes - Viewed (0) -
model.go
package gorm import "time" // Model a basic GoLang struct which includes the following fields: ID, CreatedAt, UpdatedAt, DeletedAt // It may be embedded into your model or you may build your own model without it // // type User struct { // gorm.Model // } type Model struct { ID uint `gorm:"primarykey"` CreatedAt time.Time UpdatedAt time.Time DeletedAt DeletedAt `gorm:"index"`
Registered: Sun Nov 03 09:35:10 UTC 2024 - Last Modified: Sat Feb 18 01:06:43 UTC 2023 - 396 bytes - Viewed (0) -
SECURITY.md
TensorFlow [**models**](https://developers.google.com/machine-learning/glossary/#model) (to use a term commonly used by machine learning practitioners) are expressed as programs that TensorFlow executes. TensorFlow programs are encoded as computation [**graphs**](https://developers.google.com/machine-learning/glossary/#graph). Since models are practically programs that TensorFlow executes, using untrusted
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Wed Oct 16 16:10:43 UTC 2024 - 9.6K bytes - Viewed (0)