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docs/en/docs/alternatives.md
The way it works is that you write the definition of the schema using YAML format inside the docstring of each function handling a route. And it generates OpenAPI schemas. That's how it works in Flask, Starlette, Responder, etc. But then, we have again the problem of having a micro-syntax, inside of a Python string (a big YAML).
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docs/en/docs/tutorial/path-params.md
```Python hl_lines="7" {!../../../docs_src/path_params/tutorial002.py!} ``` In this case, `item_id` is declared to be an `int`. !!! check This will give you editor support inside of your function, with error checks, completion, etc. ## Data <abbr title="also known as: serialization, parsing, marshalling">conversion</abbr>
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docs/en/docs/tutorial/body-fields.md
# Body - Fields The same way you can declare additional validation and metadata in *path operation function* parameters with `Query`, `Path` and `Body`, you can declare validation and metadata inside of Pydantic models using Pydantic's `Field`. ## Import `Field` First, you have to import it: === "Python 3.10+" ```Python hl_lines="4" {!> ../../../docs_src/body_fields/tutorial001_an_py310.py!} ``` === "Python 3.9+"
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docs/en/docs/contributing.md
!!! note "Technical Details" This only happens when you install using this included `requirements.txt` instead of running `pip install fastapi` directly. That is because inside the `requirements.txt` file, the local version of FastAPI is marked to be installed in "editable" mode, with the `-e` option. ### Format the code There is a script that you can run that will format and clean all your code:
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docs/en/docs/advanced/using-request-directly.md
But there are specific cases where it's useful to get the `Request` object. ## Use the `Request` object directly Let's imagine you want to get the client's IP address/host inside of your *path operation function*. For that you need to access the request directly. ```Python hl_lines="1 7-8" {!../../../docs_src/using_request_directly/tutorial001.py!} ```
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docs/en/docs/advanced/async-tests.md
The `TestClient` does some magic inside to call the asynchronous FastAPI application in your normal `def` test functions, using standard pytest. But that magic doesn't work anymore when we're using it inside asynchronous functions. By running our tests asynchronously, we can no longer use the `TestClient` inside our test functions.
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docs/en/docs/tutorial/bigger-applications.md
* It contains an `app/main.py` file. As it is inside a Python package (a directory with a file `__init__.py`), it is a "module" of that package: `app.main`. * There's also an `app/dependencies.py` file, just like `app/main.py`, it is a "module": `app.dependencies`. * There's a subdirectory `app/routers/` with another file `__init__.py`, so it's a "Python subpackage": `app.routers`.
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docs/en/docs/tutorial/security/get-current-user.md
```Python hl_lines="31" {!> ../../../docs_src/security/tutorial002.py!} ``` Notice that we declare the type of `current_user` as the Pydantic model `User`. This will help us inside of the function with all the completion and type checks. !!! tip You might remember that request bodies are also declared with Pydantic models.
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docs/en/docs/tutorial/body-multiple-params.md
}, "user": { "username": "dave", "full_name": "Dave Grohl" } } ``` !!! note Notice that even though the `item` was declared the same way as before, it is now expected to be inside of the body with a key `item`. **FastAPI** will do the automatic conversion from the request, so that the parameter `item` receives it's specific content and the same for `user`.
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docs/en/docs/deployment/manually.md
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