def test_process_items():
    with patch("builtins.print") as mock_print:
        process_items(["item_a", "item_b", "item_c"])

    assert mock_print.call_count == 3
    call_args = [arg.args for arg in mock_print.call_args_list]
    assert call_args == [
        ("item_a",),
        ("item_b",),
        ("item_c",),

    with patch("builtins.print") as mock_print:
        runpy.run_module(f"docs_src.python_types.{module_name}", run_name="__main__")

    assert mock_print.call_count == 2
    call_args = [str(arg.args[0]) for arg in mock_print.call_args_list]
    assert call_args == [
        "id=123 name='John Doe' signup_ts=datetime.datetime(2017, 6, 1, 12, 22) friends=[1, 2, 3]",
        "123",

def test_process_items():
    with patch("builtins.print") as mock_print:
        process_items({"a": 1.0, "b": 2.5})

    assert mock_print.call_count == 4
    call_args = [arg.args for arg in mock_print.call_args_list]
    assert call_args == [
        ("a",),
        (1.0,),
        ("b",),
        (2.5,),

def test_say_hi(module: ModuleType):
    with patch("builtins.print") as mock_print:
        module.say_hi("FastAPI")
        module.say_hi()

    assert mock_print.call_count == 2
    call_args = [arg.args for arg in mock_print.call_args_list]
    assert call_args == [
        ("Hey FastAPI!",),
        ("Hello World",),

def get_path_param_names(path: str) -> set[str]:
    return set(re.findall("{(.*?)}", path))


_invalid_args_message = (
    "Invalid args for response field! Hint: "
    "check that {type_} is a valid Pydantic field type. "
    "If you are using a return type annotation that is not a valid Pydantic "

repos:
  - repo: https://github.com/pre-commit/pre-commit-hooks
    rev: v6.0.0
    hooks:
      - id: check-added-large-files
        args: ['--maxkb=750']
      - id: check-toml
      - id: check-yaml
        args:
        - --unsafe
      - id: end-of-file-fixer
      - id: trailing-whitespace

  - repo: local
    hooks:
      - id: local-ruff-check
        name: ruff check

    if origin is Union or origin is UnionType:
        at_least_one_scalar_sequence = False
        for arg in get_args(annotation):
            if field_annotation_is_scalar_sequence(arg):
                at_least_one_scalar_sequence = True
                continue
            elif not field_annotation_is_scalar(arg):
                return False
        return at_least_one_scalar_sequence

    if origin is not None:
        for arg in get_args(annotation):
            if lenient_issubclass(arg, (BaseModel, Enum)) and arg not in known_models:
                known_models.add(arg)
                if lenient_issubclass(arg, BaseModel):
                    get_flat_models_from_model(arg, known_models=known_models)
            else:
                get_flat_models_from_annotation(arg, known_models=known_models)

        type_annotation = annotated_args[0]
        fastapi_annotations = [
            arg
            for arg in annotated_args[1:]
            if isinstance(arg, (FieldInfo, params.Depends))
        ]
        fastapi_specific_annotations = [
            arg
            for arg in fastapi_annotations
            if isinstance(
                arg,
                (
                    params.Param,

        lang = "en"
    lang_path: Path = docs_path / lang
    # Enable line numbers during local development to make it easier to highlight
    args = ["mkdocs", "serve", "--dev-addr", "127.0.0.1:8008"]
    if dirty:
        args.append("--dirty")
    subprocess.run(
        args, env={**os.environ, "LINENUMS": "true"}, cwd=lang_path, check=True
    )


def get_updated_config_content() -> dict[str, Any]: