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docs/nl/docs/python-types.md
//// tab | Python 3.9+ ```Python hl_lines="1" {!> ../../docs_src/python_types/tutorial008_py39.py!} ``` //// //// tab | Python 3.8+ ```Python hl_lines="1 4" {!> ../../docs_src/python_types/tutorial008.py!} ``` //// Dit betekent: * De variabele `prices` is een `dict`:
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 18.3K bytes - Viewed (0) -
docs/nl/docs/features.md
* Ontworpen op basis van deze standaarden, na zorgvuldig onderzoek. In plaats van achteraf deze laag er bovenop te bouwen. * Dit maakt het ook mogelijk om automatisch **clientcode te genereren** in verschillende programmeertalen. ### Automatische documentatie Interactieve API-documentatie en verkenning van webgebruikersinterfaces. Aangezien dit framework is gebaseerd op OpenAPI, zijn er meerdere documentatie opties mogelijk, waarvan er standaard 2 zijn inbegrepen.
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Tue Sep 03 13:50:38 UTC 2024 - 10.1K bytes - Viewed (0) -
docs/fr/docs/tutorial/first-steps.md
/// ### Étape 5 : retourner le contenu ```Python hl_lines="8" {!../../docs_src/first_steps/tutorial001.py!} ``` Vous pouvez retourner un dictionnaire (`dict`), une liste (`list`), des valeurs seules comme des chaines de caractères (`str`) et des entiers (`int`), etc. Vous pouvez aussi retourner des models **Pydantic** (qui seront détaillés plus tard).
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doap_Maven.rdf
.org/dist/maven/maven-3/3.9.9/source/apache-maven-3.9.9-src.zip https://archive.apache.org/dist/maven/maven-3/3.9.9/source/apache-maven-3.9.9-src.tar.gz Apache Maven 3.9.8 2024-06-17 3.9.8 https://archive.apache.org/dist/maven/maven-3/3.9.8/binaries/apache-maven-3.9.8-bin.zip https://archive.apache.org/dist/maven/maven-3/3.9.8/binaries/apache-maven-3.9.8-bin.tar.gz https://archive.apache.org/dist/maven/maven-3/3.9.8/source/apache-maven-3.9.8-src.zip https://archive.apache.org/dist/maven/maven-3/...
Registered: Sun Nov 03 03:35:11 UTC 2024 - Last Modified: Tue Oct 22 13:53:03 UTC 2024 - 33.9K bytes - Viewed (0) -
docs/em/docs/tutorial/extra-models.md
🖼 🔛 👥 🤚 `user_dict` ⚪️➡️ `user_in.dict()`, 👉 📟: ```Python user_dict = user_in.dict() UserInDB(**user_dict) ``` 🔜 🌓: ```Python UserInDB(**user_in.dict()) ``` ...↩️ `user_in.dict()` `dict`, & ⤴️ 👥 ⚒ 🐍 "🎁" ⚫️ 🚶♀️ ⚫️ `UserInDB` 🔠 ⏮️ `**`. , 👥 🤚 Pydantic 🏷 ⚪️➡️ 💽 ➕1️⃣ Pydantic 🏷. #### 🎁 `dict` & ➕ 🇨🇻
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docs/zh/docs/tutorial/extra-models.md
#### 用其它模型中的内容生成 Pydantic 模型 上例中 ,从 `user_in.dict()` 中得到了 `user_dict`,下面的代码: ```Python user_dict = user_in.dict() UserInDB(**user_dict) ``` 等效于: ```Python UserInDB(**user_in.dict()) ``` ……因为 `user_in.dict()` 是字典,在传递给 `UserInDB` 时,把 `**` 加在 `user_in.dict()` 前,可以让 Python 进行**解包**。 这样,就可以用其它 Pydantic 模型中的数据生成 Pydantic 模型。 #### 解包 `dict` 和更多关键字
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docs/en/docs/tutorial/extra-models.md
So, if we create a Pydantic object `user_in` like: ```Python user_in = UserIn(username="john", password="secret", email="******@****.***") ``` 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). And if we call: ```Python
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 7.7K bytes - Viewed (0) -
fastapi/params.py
"although still supported. Use examples instead." ), ] = _Unset, openapi_examples: Optional[Dict[str, Example]] = None, deprecated: Union[deprecated, str, bool, None] = None, include_in_schema: bool = True, json_schema_extra: Union[Dict[str, Any], None] = None, **extra: Any, ): if example is not _Unset: warnings.warn(
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fastapi/openapi/utils.py
if license_info: info["license"] = license_info output: Dict[str, Any] = {"openapi": openapi_version, "info": info} if servers: output["servers"] = servers components: Dict[str, Dict[str, Any]] = {} paths: Dict[str, Dict[str, Any]] = {} webhook_paths: Dict[str, Dict[str, Any]] = {} operation_ids: Set[str] = set()
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docs/de/docs/tutorial/extra-models.md
Pydantic-Modelle haben eine `.dict()`-Methode, die ein `dict` mit den Daten des Modells zurückgibt. Wenn wir also ein Pydantic-Objekt `user_in` erstellen, etwa so: ```Python user_in = UserIn(username="john", password="secret", email="******@****.***") ``` und wir rufen seine `.dict()`-Methode auf: ```Python user_dict = user_in.dict() ```
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