And multiple processes normally **don't share any memory**. This means that each running process has its own things, variables, and memory. And if you are consuming a large amount of memory in your code, **each process** will consume an equivalent amount of memory.

* Fix broken link in docs about OAuth 2.0 with scopes. PR [#275](https://github.com/tiangolo/fastapi/pull/275) by [@dmontagu](https://github.com/dmontagu).

* Refactor param extraction using Pydantic `Field`:
    * Large refactor, improvement, and simplification of param extraction from *path operations*.

# See https://pre-commit.com/hooks.html for more hooks
default_language_version:
    python: python3.10
repos:
-   repo: https://github.com/pre-commit/pre-commit-hooks
    rev: v4.4.0
    hooks:
    -   id: check-added-large-files
    -   id: check-toml
    -   id: check-yaml
        args:
        -   --unsafe
    -   id: end-of-file-fixer
    -   id: trailing-whitespace
-   repo: https://github.com/charliermarsh/ruff-pre-commit

* It uses a "spooled" file:
    * A file stored in memory up to a maximum size limit, and after passing this limit it will be stored in disk.
* This means that it will work well for large files like images, videos, large binaries, etc. without consuming all the memory.
* You can get metadata from the uploaded file.

This will be especially useful when you use it in a **large code base** where you use **the same dependencies** over and over again in **many *path operations***.

## To `async` or not to `async`

* Testclient basierend auf HTTPX.
* CORS, GZip, statische Dateien, Streamende Responses.
* Session- und Cookie-Unterstützung.
* 100 % Testabdeckung.
* 100 % Typannotierte Codebasis.
* Wenige starke Abhängigkeiten.

Starlette ist derzeit das schnellste getestete Python-Framework. Nur übertroffen von Uvicorn, welches kein Framework, sondern ein Server ist.

!!! note "Hinweis"
    Es ist üblich, dass jeder Authentifizierungsanbieter seine Flows anders benennt, um sie zu einem Teil seiner Marke zu machen.

    Aber am Ende implementieren sie denselben OAuth2-Standard.

**FastAPI** enthält Werkzeuge für alle diese OAuth2-Authentifizierungs-Flows in `fastapi.security.oauth2`.

    with path.open("rb") as file:
        response = client.post("/files/", files={"file": file})
    assert response.status_code == 200, response.text
    assert response.json() == {"file_size": 14}


def test_post_large_file(tmp_path):
    default_pydantic_max_size = 2**16
    path = tmp_path / "test.txt"
    path.write_bytes(b"x" * (default_pydantic_max_size + 1))

    client = TestClient(app)
    with path.open("rb") as file:

Import the `Response` class (sub-class) you want to use and declare it in the *path operation decorator*.

For large responses, returning a `Response` directly is much faster than returning a dictionary.

    with path.open("rb") as file:
        response = client.post("/files/", files={"file": file})
    assert response.status_code == 200, response.text
    assert response.json() == {"file_size": 14}


def test_post_large_file(tmp_path):
    default_pydantic_max_size = 2**16
    path = tmp_path / "test.txt"
    path.write_bytes(b"x" * (default_pydantic_max_size + 1))

    client = TestClient(app)
    with path.open("rb") as file: