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docs_src/security/tutorial005_an.py
@app.get("/users/me/", response_model=User) async def read_users_me( current_user: Annotated[User, Depends(get_current_active_user)], ): return current_user @app.get("/users/me/items/") async def read_own_items( current_user: Annotated[User, Security(get_current_active_user, scopes=["items"])], ): return [{"item_id": "Foo", "owner": current_user.username}] @app.get("/status/")
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docs/en/docs/tutorial/response-model.md
## See it in the docs When you see the automatic docs, you can check that the input model and output model will both have their own JSON Schema: <img src="/img/tutorial/response-model/image01.png"> And both models will be used for the interactive API documentation: <img src="/img/tutorial/response-model/image02.png">
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docs/en/docs/deployment/concepts.md
By considering these concepts, you will be able to **evaluate and design** the best way to deploy **your own APIs**. In the next chapters, I'll give you more **concrete recipes** to deploy FastAPI applications. But for now, let's check these important **conceptual ideas**. These concepts also apply to any other type of web API. 💡
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docs/en/docs/alternatives.md
* Based on Python type hints. * Validation and documentation from these types. * Dependency Injection system. It doesn't use a data validation, serialization and documentation third-party library like Pydantic, it has its own. So, these data type definitions would not be reusable as easily.
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docs/en/docs/how-to/nosql-databases-couchbase.md
### `UserInDB` model Now, let's create a `UserInDB` model. This will have the data that is actually stored in the database. We don't create it as a subclass of Pydantic's `BaseModel` but as a subclass of our own `User`, because it will have all the attributes in `User` plus a couple more: ```Python hl_lines="31-33" {!../../../docs_src/nosql_databases/tutorial001.py!} ``` !!! note
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docs/en/docs/tutorial/metadata.md
| `description` | `str` | A short description of the API. It can use Markdown. | | `version` | `string` | The version of the API. This is the version of your own application, not of OpenAPI. For example `2.5.0`. | | `terms_of_service` | `str` | A URL to the Terms of Service for the API. If provided, this has to be a URL. |
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docs/en/docs/advanced/openapi-webhooks.md
All the **logic** about how to register the URLs for webhooks and the code to actually send those requests is up to you. You write it however you want to in **your own code**. ## Documenting webhooks with **FastAPI** and OpenAPI
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fastapi/param_functions.py
from fastapi import Depends, FastAPI from .db import User from .security import get_current_active_user app = FastAPI() @app.get("/users/me/items/") async def read_own_items( current_user: Annotated[User, Security(get_current_active_user, scopes=["items"])] ): return [{"item_id": "Foo", "owner": current_user.username}] ``` """
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tests/test_tutorial/test_metadata/test_tutorial004.py
"description": "Operations with users. The **login** logic is also here.", }, { "name": "items", "description": "Manage items. So _fancy_ they have their own docs.", "externalDocs": { "description": "Items external docs", "url": "https://fastapi.tiangolo.com/", }, }, ],
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docs/en/docs/python-types.md
{!../../../docs_src/python_types/tutorial005.py!} ``` ### Generic types with type parameters There are some data structures that can contain other values, like `dict`, `list`, `set` and `tuple`. And the internal values can have their own type too. These types that have internal types are called "**generic**" types. And it's possible to declare them, even with their internal types.
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