* to avoid the extra class for the lambda (and maybe more for memoizingSupplier itself) and the
     * indirection.
     *
     * One thing to *avoid* is a change to make each Logger user use memoizingSupplier directly:
     * That may introduce an extra class for each lambda (currently a dozen).
     */
    Logger local = logger;
    if (local != null) {
      return local;

     * This method looks up the user by their code and creates a new favorite log entry
     * using the provided lambda function to populate the favorite log data.
     *
     * @param userCode the unique code identifying the user
     * @param favoriteLogLambda a lambda function that accepts UserInfo and FavoriteLog to populate the favorite log data

 * someGraphAlgorithm(startNode, MyNode::getParents);
 * }
 *
 * <p>If you have some other mechanism for returning the predecessors of a node, or one that doesn't
 * return a {@code Iterable<? extends N>}, then you can use a lambda to perform a more general
 * transformation:
 *
 * {@snippet :
 * someGraphAlgorithm(startNode, node -> ImmutableList.of(node.mother(), node.father()));
 * }
 *

 * someGraphAlgorithm(startNode, MyNode::getChildren);
 * }
 *
 * <p>If you have some other mechanism for returning the successors of a node, or one that doesn't
 * return an {@code Iterable<? extends N>}, then you can use a lambda to perform a more general
 * transformation:
 *
 * {@snippet :
 * someGraphAlgorithm(startNode, node -> ImmutableList.of(node.leftChild(), node.rightChild()));
 * }
 *

// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package lambda

import (
	"context"
	"errors"
	"fmt"
	"net/http"

	"github.com/minio/minio/internal/config"
	"github.com/minio/minio/internal/config/lambda/event"
	"github.com/minio/minio/internal/config/lambda/target"
	"github.com/minio/minio/internal/logger"
	"github.com/minio/pkg/v3/env"

        def __init__(self):
            self.data = [1.0, 2.0, 3.0]

    FakeNumpyArrayPydantic = Annotated[
        FakeNumpyArray,
        WithJsonSchema(TypeAdapter(list[float]).json_schema()),
        PlainSerializer(lambda v: v.data),
    ]

    class MyModel(BaseModel):
        model_config = ConfigDict(arbitrary_types_allowed=True)
        custom_field: FakeNumpyArrayPydantic

    app = FastAPI()

    @app.get("/")

ENCODERS_BY_TYPE: dict[type[Any], Callable[[Any], Any]] = {
    bytes: lambda o: o.decode(),
    Color: str,  # ty: ignore[deprecated]
    datetime.date: isoformat,
    datetime.datetime: isoformat,
    datetime.time: isoformat,
    datetime.timedelta: lambda td: td.total_seconds(),
    Decimal: decimal_encoder,
    Enum: lambda o: o.value,
    frozenset: list,
    deque: list,
    GeneratorType: list,

    en_links = lang_links.get("en", [])
    en_links.sort(key=lambda x: x.preview_link)
    links.extend(en_links)

    langs = list(lang_links.keys())
    langs.sort()
    for lang in langs:
        if lang == "en":
            continue
        current_lang_links = lang_links[lang]
        current_lang_links.sort(key=lambda x: x.preview_link)
        links.extend(current_lang_links)

    encoded_instance = jsonable_encoder(
        instance, custom_encoder={safe_datetime: lambda o: o.strftime("%H:%M:%S")}
    )
    assert encoded_instance["dt_field"] == instance["dt_field"].strftime("%H:%M:%S")

    encoded_instance = jsonable_encoder(
        instance, custom_encoder={datetime: lambda o: o.strftime("%H:%M:%S")}
    )
    assert encoded_instance["dt_field"] == instance["dt_field"].strftime("%H:%M:%S")

		configLogIf(ctx, fmt.Errorf("Unable to initialize notification target(s): %w", err))
	}

	bootstrapTraceMsg("initialize the lambda targets")
	globalLambdaTargetList, err = lambda.FetchEnabledTargets(GlobalContext, s, transport)
	if err != nil {
		configLogIf(ctx, fmt.Errorf("Unable to initialize lambda target(s): %w", err))
	}

	bootstrapTraceMsg("applying the dynamic configuration")
	// Apply dynamic config values