void testDecode() throws NdrException {
            // Given: Mocked buffer data with pre-created entries to avoid complex entry decode chain
            samr.SamrSamArray array = new samr.SamrSamArray();
            array.entries = new samr.SamrSamEntry[1]; // Pre-populate to avoid decoding
            array.entries[0] = new samr.SamrSamEntry();

 *
 * <p>
 * Usage example:
 * </p>
 *
 * <pre>
 * {@code
 * FtpClient ftpClient = new FtpClient();
 * ftpClient.init(); // Initialize with configured parameters
 * ResponseData responseData = ftpClient.doGet("ftp://example.com/path/to/file.txt");
 * // Process the responseData
 * ftpClient.close(); // Close and release resources
 * }
 * </pre>
 *
 * @author shinsuke
 */

 *
 * <p>This class should not be assumed to be universally superior to {@code
 * java.util.LinkedHashMap}. Generally speaking, this class reduces object allocation and memory
 * consumption at the price of moderately increased constant factors of CPU. Only use this class
 * when there is a specific reason to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 */

    // Add boundary values manually to avoid over/under flow (this covers 2^N for 0 and 31).
    intValues.add(Integer.MAX_VALUE - 1, Integer.MAX_VALUE);
    // Add values up to 40. This covers cases like "square of a prime" and such.
    for (int i = 1; i <= 40; i++) {
      intValues.add(i);
    }
    // Now add values near 2^N for lots of values of N.
    for (int exponent : asList(2, 3, 4, 9, 15, 16, 17, 24, 25, 30)) {

            return curlHelper.delete(path);
        default:
            break;
        }
        return null;
    }

    /**
     * Creates an HTML response for the list page with optional pre-processing.
     *
     * @param runnable optional runnable to execute before rendering (can be null)
     * @return HTML response for the search request list page
     */

		return
	}

	if r.Header.Get(xhttp.Range) != "" {
		writeErrorResponse(ctx, w, errorCodes.ToAPIErr(ErrInvalidRange), r.URL)
		return
	}

	// Validate pre-conditions if any.
	opts.CheckPrecondFn = func(oi ObjectInfo) bool {
		if _, err := DecryptObjectInfo(&oi, r); err != nil {
			writeErrorResponse(ctx, w, toAPIError(ctx, err), r.URL)
			return true
		}

     * </p>
     * <pre>{@code
     * Optional<Path> configured = targetPath();
     * if (configured.isPresent() && configured.get().isAbsolute()) {
     *     return configured.get();
     * }
     * Path outputDir = project.getOutputDirectory(scope());
     * return configured.map(outputDir::resolve).orElse(outputDir);
     * }</pre>
     *

Pydantic 덕분에 표준 Python 타입을 사용해 본문을 선언합니다.

```Python hl_lines="2  7-10 23-25"
from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: bool | None = None


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: str | None = None):

        // language=javascript
        return """
            <script type="text/javascript">
                function getAllErrorCorrections() {
                    var changeElements = document.querySelectorAll(".well pre");
                    var result = [];
                    changeElements.forEach((val, idx) => result.push(JSON.parse(val.textContent)));
                    return result;
                }

Depois, vamos melhorá-lo aumentando a segurança e versatilidade com **múltiplos modelos** abaixo. 🤓

### Criar Modelos { #create-models }

Importe o `SQLModel` e crie um modelo de banco de dados:

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}

A classe `Hero` é muito semelhante a um modelo Pydantic (na verdade, por baixo dos panos, ela *é um modelo Pydantic*).