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docs/de/docs/deployment/server-workers.md
!!! info Wenn Sie Container verwenden, beispielsweise mit Docker oder Kubernetes, erzähle ich Ihnen mehr darüber im nächsten Kapitel: [FastAPI in Containern – Docker](docker.md){.internal-link target=_blank}.
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docs/en/docs/how-to/sql-databases-peewee.md
Most of the code is actually the same. So, we are going to focus only on the differences. ## File structure Let's say you have a directory named `my_super_project` that contains a sub-directory called `sql_app` with a structure like this: ``` . └── sql_app ├── __init__.py ├── crud.py ├── database.py ├── main.py └── schemas.py ```
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fastapi/openapi/models.py
# It generales a list of schemas for tuples, before prefixItems was available # items: Optional["SchemaOrBool"] = None items: Optional[Union["SchemaOrBool", List["SchemaOrBool"]]] = None contains: Optional["SchemaOrBool"] = None properties: Optional[Dict[str, "SchemaOrBool"]] = None patternProperties: Optional[Dict[str, "SchemaOrBool"]] = None additionalProperties: Optional["SchemaOrBool"] = None
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docs/en/docs/advanced/custom-response.md
```{ .python .annotate hl_lines="2 10-12 14" } {!../../../docs_src/custom_response/tutorial008.py!} ``` 1. This is the generator function. It's a "generator function" because it contains `yield` statements inside. 2. By using a `with` block, we make sure that the file-like object is closed after the generator function is done. So, after it finishes sending the response.
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docs/en/data/external_links.yml
- author: Raf Rasenberg author_link: https://rafrasenberg.com/about/ link: https://rafrasenberg.com/fastapi-lambda/ title: 'FastAPI lambda container: serverless simplified' - author: Teresa N. Fontanella De Santis author_link: https://dev.to/ link: https://dev.to/teresafds/authorization-on-fastapi-with-casbin-41og title: Authorization on FastAPI with Casbin
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docs/en/docs/tutorial/sql-databases.md
The examples here use `.dict()` for compatibility with Pydantic v1, but you should use `.model_dump()` instead if you can use Pydantic v2. !!! tip The SQLAlchemy model for `User` contains a `hashed_password` that should contain a secure hashed version of the password. But as what the API client provides is the original password, you need to extract it and generate the hashed password in your application.
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docs/de/docs/deployment/concepts.md
* **Cloud-Dienste**, welche das für Sie erledigen
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docs/en/docs/deployment/docker.md
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docs/de/docs/deployment/docker.md
Wenn Sie in hier **mehrere Container** hätten, würde Prometheus beim **Lesen der Metriken** standardmäßig jedes Mal diejenigen für **einen einzelnen Container** abrufen (für den Container, der den spezifischen Request verarbeitet hat), anstatt die **akkumulierten Metriken** für alle replizierten Container abzurufen.
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docs/en/docs/tutorial/schema-extra-example.md
* `Form()` * `File()` The keys of the `dict` identify each example, and each value is another `dict`. Each specific example `dict` in the `examples` can contain: * `summary`: Short description for the example. * `description`: A long description that can contain Markdown text. * `value`: This is the actual example shown, e.g. a `dict`.
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