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docs/en/docs/tutorial/body-multiple-params.md
Let's say you only have a single `item` body parameter from a Pydantic model `Item`. By default, **FastAPI** will then expect its body directly. But if you want it to expect a JSON with a key `item` and inside of it the model contents, as it does when you declare extra body parameters, you can use the special `Body` parameter `embed`: ```Python item: Item = Body(embed=True) ``` as in: === "Python 3.10+"
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docs/en/docs/deployment/https.md
* **After** obtaining a secure connection, the communication protocol is **still HTTP**. * The contents are **encrypted**, even though they are being sent with the **HTTP protocol**.
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docs/ru/docs/tutorial/dependencies/index.md
В приведенном выше примере есть небольшое **повторение кода**. Когда вам нужно использовать `common_parameters()` зависимость, вы должны написать весь параметр с аннотацией типов и `Depends()`: ```Python commons: Annotated[dict, Depends(common_parameters)] ``` Но потому что мы используем `Annotated`, мы можем хранить `Annotated` значение в переменной и использовать его в нескольких местах: === "Python 3.10+"
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docs/en/docs/tutorial/security/oauth2-jwt.md
eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiaWF0IjoxNTE2MjM5MDIyfQ.SflKxwRJSMeKKF2QT4fwpMeJf36POk6yJV_adQssw5c ``` It is not encrypted, so, anyone could recover the information from the contents. But it's signed. So, when you receive a token that you emitted, you can verify that you actually emitted it.
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docs/de/docs/tutorial/dependencies/index.md
Wenn Sie die Abhängigkeit `common_parameters()` verwenden, müssen Sie den gesamten Parameter mit der Typannotation und `Depends()` schreiben: ```Python commons: Annotated[dict, Depends(common_parameters)] ``` Da wir jedoch `Annotated` verwenden, können wir diesen `Annotated`-Wert in einer Variablen speichern und an mehreren Stellen verwenden: === "Python 3.10+"
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docs/en/docs/deployment/concepts.md
### Memory per Process Now, when the program loads things in memory, for example, a machine learning model in a variable, or the contents of a large file in a variable, all that **consumes a bit of the memory (RAM)** of the server.
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docs/en/docs/python-types.md
``` John Doe ``` The function does the following: * Takes a `first_name` and `last_name`. * Converts the first letter of each one to upper case with `title()`. * <abbr title="Puts them together, as one. With the contents of one after the other.">Concatenates</abbr> them with a space in the middle. ```Python hl_lines="2" {!../../../docs_src/python_types/tutorial001.py!} ``` ### Edit it It's a very simple program.
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.github/actions/comment-docs-preview-in-pr/action.yml
name: Comment Docs Preview in PR description: Comment with the docs URL preview in the PR author: Sebastián Ramírez <******@****.***> inputs: token: description: Token for the repo. Can be passed in using {{ secrets.GITHUB_TOKEN }} required: true deploy_url: description: The deployment URL to comment in the PR required: true runs: using: docker
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docs_src/dependencies/tutorial002_an_py310.py
self.skip = skip self.limit = limit @app.get("/items/") async def read_items(commons: Annotated[CommonQueryParams, Depends(CommonQueryParams)]): response = {} if commons.q: response.update({"q": commons.q}) items = fake_items_db[commons.skip : commons.skip + commons.limit] response.update({"items": items})
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docs_src/dependencies/tutorial004_an_py310.py
self.q = q self.skip = skip self.limit = limit @app.get("/items/") async def read_items(commons: Annotated[CommonQueryParams, Depends()]): response = {} if commons.q: response.update({"q": commons.q}) items = fake_items_db[commons.skip : commons.skip + commons.limit] response.update({"items": items})
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