- url: https://www.stainlessapi.com/?utm_source=fastapi&utm_medium=referral
    title: Stainless | Generate best-in-class SDKs
    img: https://fastapi.tiangolo.com/img/sponsors/stainless.png
bronze:
  - url: https://www.exoflare.com/open-source/?utm_source=FastAPI&utm_campaign=open_source
    title: Biosecurity risk assessments made easy.
    img: https://fastapi.tiangolo.com/img/sponsors/exoflare.png

Genauso würde die Datenbank kein Pydantic-Modell (ein Objekt mit Attributen) akzeptieren, sondern nur ein `dict`.

Sie können für diese Fälle `jsonable_encoder` verwenden.

Es nimmt ein Objekt entgegen, wie etwa ein Pydantic-Modell, und gibt eine JSON-kompatible Version zurück:

//// tab | Python 3.10+

```Python hl_lines="4  21"

        }
    )


def test_post_broken_body(client: TestClient):
    response = client.post(
        "/items/",
        headers={"content-type": "application/json"},
        content="{some broken json}",
    )
    assert response.status_code == 422, response.text
    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "json_invalid",

        }
    )


@needs_py310
def test_post_broken_body(client: TestClient):
    response = client.post(
        "/items/",
        headers={"content-type": "application/json"},
        content="{some broken json}",
    )
    assert response.status_code == 422, response.text
    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "json_invalid",

we don't consider this as a vulnerability, given that models can exhaust
resources in many different ways and solutions exist to prevent this from
happening (e.g., rate limits, ACLs, monitors to restart broken servers).

### Model sharing

If the multitenant design allows sharing models, make sure that tenants and
users are aware of the security risks detailed here and that they are going to

        if [[ ! -f $target ]] && [[ ! -d $target ]]; then
            echo "$i" >> errors.txt
        fi
        if [[ -e errors.txt ]]; then
            echo "Broken links found:"
            cat errors.txt
            rm errors.txt
            false
        fi
    done
}

@test "No duplicate files on Windows" {
    cat <<EOF

                             else 0)
    while k > bazel_comm_min_line_i:
      backtrack_line = log_lines[k]
      # Don't attempt to parse multi-line commands broken up by backslashes
      if 'bazel ' in backtrack_line and not backtrack_line.endswith('\\'):
        bazel_line = BAZEL_COMMAND_RE.search(backtrack_line)
        if bazel_line:

Vous ne devriez pas épingler la version de `starlette`.

Différentes versions de **FastAPI** utiliseront une version spécifique plus récente de Starlette.

Ainsi, vous pouvez simplement laisser **FastAPI** utiliser la bonne version de Starlette.

## À propos de Pydantic

Pydantic inclut des tests pour **FastAPI** avec ses propres tests, ainsi les nouvelles versions de Pydantic (au-dessus
de `1.0.0`) sont toujours compatibles avec **FastAPI**.

  Please upgrade your code to TensorFlow 2.0:
    * https://www.tensorflow.org/guide/migrate

  Or install the latest stable TensorFlow 1.X release:
    * `pip install -U "tensorflow==1.*"`

  Otherwise your code may be broken by the change.

  """)

# Make sure directory containing top level submodules is in
# the __path__ so that "from tensorflow.foo import bar" works.
# We're using bitwise, but there's nothing special about that.

Vous pouvez aussi déclarer un **corps**, et des paramètres de **chemin** et de **requête** dans la même *opération de chemin*.

**FastAPI** saura reconnaître chacun d'entre eux et récupérer la bonne donnée au bon endroit.

```Python hl_lines="18"
{!../../docs_src/body/tutorial004.py!}
```

Les paramètres de la fonction seront reconnus comme tel :