SettingsBuildingRequest request = new DefaultSettingsBuildingRequest();
        request.setUserSettingsFile(userSettingsFile);
        request.setGlobalSettingsFile(globalSettingsFile);
        request.setSystemProperties(SystemProperties.getSystemProperties());
        return build(request);
    }

    @Override

Y guardará el valor devuelto en un <abbr title="Una utilidad/sistema para almacenar valores calculados/generados, para reutilizarlos en lugar de calcularlos nuevamente.">"cache"</abbr> y lo pasará a todos los "dependants" que lo necesiten en ese request específico, en lugar de llamar a la dependencia varias veces para el mismo request.

            modelBuildingRequest.systemProperties(toMap(request.getSystemProperties()));
            modelBuildingRequest.userProperties(toMap(request.getUserProperties()));
            modelBuildingRequest.repositoryMerging(ModelBuilderRequest.RepositoryMerging.valueOf(
                    request.getRepositoryMerging().name()));
            modelBuildingRequest.repositories(request.getRemoteRepositories().stream()

    now served with tensorflow/serving, it will accept requests using 'inputs'
    and 'outputs'. Starting at 1.2, such a model will accept the keys specified
    during export. Therefore, inference requests using 'inputs' and 'outputs'
    may start to fail. To fix this, either update any inference clients to send
    requests with the actual input and output keys used by the trainer code, or

from starlette.responses import JSONResponse


def http_exception_handler(request, exception):
    return JSONResponse({"exception": "http-exception"})


def request_validation_exception_handler(request, exception):
    return JSONResponse({"exception": "request-validation"})


def server_error_exception_handler(request, exception):
    return JSONResponse(status_code=500, content={"exception": "server-error"})

            pluginSession.setDependencyGraphTransformer(session.getDependencyGraphTransformer());

            CollectRequest request = new CollectRequest();
            request.setRequestContext(REPOSITORY_CONTEXT);
            request.setRepositories(repositories);
            request.setRoot(new org.eclipse.aether.graph.Dependency(pluginArtifact, null));
            for (Dependency dependency : plugin.getDependencies()) {

        this.executionProperties = executionProperties;
        this.request = new DefaultMavenExecutionRequest();
        this.request.setUserProperties(userProperties);
        this.request.setLocalRepository(localRepository);
        this.request.setGoals(goals);
        this.request.setBaseDirectory((executionRootDir != null) ? new File(executionRootDir) : null);
        this.request.setStartTime(startTime);
        this.result = null;

from fastapi import FastAPI, Request
from fastapi.responses import HTMLResponse
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates

app = FastAPI()

app.mount("/static", StaticFiles(directory="static"), name="static")


templates = Jinja2Templates(directory="templates")


@app.get("/items/{id}", response_class=HTMLResponse)
async def read_item(request: Request, id: str):

            VersionRangeRequest request,
            Metadata.Nature wantedNature) {
        RequestTrace trace = RequestTrace.newChild(request.getTrace(), request);

        Map<String, ArtifactRepository> versionIndex = new HashMap<>();

        Metadata metadata = new DefaultMetadata(
                request.getArtifact().getGroupId(),
                request.getArtifact().getArtifactId(),

@pytest.fixture(
    name="mod",
    params=[
        pytest.param("tutorial008c_py39"),
        pytest.param("tutorial008c_an_py39"),
    ],
)
def get_mod(request: pytest.FixtureRequest):
    mod = importlib.import_module(f"docs_src.dependencies.{request.param}")

    return mod


def test_get_no_item(mod: ModuleType):
    client = TestClient(mod.app)
    response = client.get("/items/foo")