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docs/en/docs/advanced/sub-applications.md
## Mounting a **FastAPI** application "Mounting" means adding a completely "independent" application in a specific path, that then takes care of handling everything under that path, with the _path operations_ declared in that sub-application. ### Top-level application
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Apr 18 19:53:19 UTC 2024 - 2.9K bytes - Viewed (0) -
docs_src/security/tutorial005.py
from datetime import datetime, timedelta, timezone from typing import List, Union import jwt from fastapi import Depends, FastAPI, HTTPException, Security, status from fastapi.security import ( OAuth2PasswordBearer, OAuth2PasswordRequestForm, SecurityScopes, ) from jwt.exceptions import InvalidTokenError from passlib.context import CryptContext from pydantic import BaseModel, ValidationError # to get a string like this run:
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docs_src/security/tutorial005_an.py
from datetime import datetime, timedelta, timezone from typing import List, Union import jwt from fastapi import Depends, FastAPI, HTTPException, Security, status from fastapi.security import ( OAuth2PasswordBearer, OAuth2PasswordRequestForm, SecurityScopes, ) from jwt.exceptions import InvalidTokenError from passlib.context import CryptContext from pydantic import BaseModel, ValidationError from typing_extensions import Annotated
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docs/em/docs/features.md
* ↩️ Pydantic 📊 📊 👐 🎓 👆 🔬; 🚘-🛠️, 🧽, ✍ & 👆 🤔 🔜 🌐 👷 ☑ ⏮️ 👆 ✔ 💽. * ✔ **🏗 📊**: * ⚙️ 🔗 Pydantic 🏷, 🐍 `typing`'Ⓜ `List` & `Dict`, ♒️. * & 💳 ✔ 🏗 💽 🔗 🎯 & 💪 🔬, ✅ & 📄 🎻 🔗. * 👆 💪 ✔️ 🙇 **🐦 🎻** 🎚 & ✔️ 👫 🌐 ✔ & ✍. * **🏧**:
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docs/en/docs/advanced/openapi-callbacks.md
## The normal **FastAPI** app Let's first see how the normal API app would look like before adding the callback. It will have a *path operation* that will receive an `Invoice` body, and a query parameter `callback_url` that will contain the URL for the callback.
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docs/zh/docs/features.md
* 和你 **<abbr title="集成开发环境,和代码编辑器类似">IDE</abbr>/<abbr title="一个检查代码错误的程序">linter</abbr>/brain** 适配: * 因为 pydantic 数据结构仅仅是你定义的类的实例;自动补全,linting,mypy 以及你的直觉应该可以和你验证的数据一起正常工作。 * 验证**复杂结构**: * 使用分层的 Pydantic 模型, Python `typing`的 `List` 和 `Dict` 等等。 * 验证器使我们能够简单清楚的将复杂的数据模式定义、检查并记录为 JSON Schema。 * 你可以拥有深度**嵌套的 JSON** 对象并对它们进行验证和注释。 * **可扩展**: * Pydantic 允许定义自定义数据类型或者你可以用验证器装饰器对被装饰的模型上的方法扩展验证。
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Apr 18 19:53:19 UTC 2024 - 9K bytes - Viewed (0)