Let's put that data in the Pydantic `UserInDB` model first.

You should never save plaintext passwords, so, we'll use the (fake) password hashing system.

If the passwords don't match, we return the same error.

#### Password hashing

"Hashing" means: converting some content (a password in this case) into a sequence of bytes (just a string) that looks like gibberish.

That, plus the simple fact that Python is the main language for **Data Science**, Machine Learning and especially Deep Learning, make FastAPI a very good match for Data Science / Machine Learning web APIs and applications (among many others).

To see how to achieve this parallelism in production see the section about [Deployment](deployment/index.md){.internal-link target=_blank}.

    with pytest.raises(RuntimeError, match=multipart_incorrect_install_error):
        app = FastAPI()

        @app.post("/")
        async def root(f: bytes = File()):
            return f  # pragma: nocover


def test_incorrect_multipart_installed_multi_form(monkeypatch):
    monkeypatch.delattr("multipart.multipart.parse_options_header", raising=False)
    with pytest.raises(RuntimeError, match=multipart_incorrect_install_error):

def test_no_annotated_defaults():
    with pytest.raises(
        AssertionError, match="Path parameters cannot have a default value"
    ):

        @app.get("/items/{item_id}/")
        async def get_item(item_id: Annotated[int, Path(default=1)]):
            pass  # pragma: nocover

    with pytest.raises(
        AssertionError,
        match=(
            "`Query` default value cannot be set in `Annotated` for 'item_id'. Set the"

        {
            "detail": [
                {
                    "type": "string_pattern_mismatch",
                    "loc": ["query", "item-query"],
                    "msg": "String should match pattern '^fixedquery$'",
                    "input": "nonregexquery",
                    "ctx": {"pattern": "^fixedquery$"},
                }
            ]
        }
    ) | IsDict(

    content = en_index.read_text("utf-8")
    match_pre = re.search(r"</style>\n\n", content)
    match_start = re.search(r"<!-- sponsors -->", content)
    match_end = re.search(r"<!-- /sponsors -->", content)
    sponsors_data_path = en_docs_path / "data" / "sponsors.yml"
    sponsors = mkdocs.utils.yaml_load(sponsors_data_path.read_text(encoding="utf-8"))
    if not (match_start and match_end):

        {
            "detail": [
                {
                    "type": "string_pattern_mismatch",
                    "loc": ["body", "q"],
                    "msg": "String should match pattern '^fixedquery$'",
                    "input": "nonregexquery",
                    "ctx": {"pattern": "^fixedquery$"},
                }
            ]
        }
    ) | IsDict(

@app.get("/items/")
async def read_items(
    q: Annotated[
        Union[str, None],
        Query(
            title="Query string",
            description="Query string for the items to search in the database that have a good match",
            min_length=3,
        ),
    ] = None,
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

@app.get("/items/")
async def read_items(
    q: str | None = Query(
        default=None,
        title="Query string",
        description="Query string for the items to search in the database that have a good match",
        min_length=3,
    ),
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

@app.get("/items/")
async def read_items(
    q: str | None = Query(
        default=None,
        alias="item-query",
        title="Query string",
        description="Query string for the items to search in the database that have a good match",
        min_length=3,
        max_length=50,
        pattern="^fixedquery$",
        deprecated=True,
    ),
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q: