public MsWordExtractor() {
        super();
    }

    /**
     * Extracts text from the Word input stream.
     * @param in The input stream.
     * @param params The parameters.
     * @return The extracted data.
     */
    @Override
    public ExtractData getText(final InputStream in, final Map<String, String> params) {
        if (in == null) {
            throw new CrawlerSystemException("The inputstream is null.");
        }

	if len(results) != 2 {
		t.Errorf("failed to return delete data, got %v", results)
	}

	var count int64
	DB.Model(&User{}).Where("name IN ?", []string{users[0].Name, users[1].Name, users[2].Name}).Count(&count)
	if count != 1 {
		t.Errorf("failed to delete data, current count %v", count)
	}
}

func TestDeleteReturning(t *testing.T) {

	callbackTypeAfterDelete  callbackType = "AfterDelete"
	callbackTypeAfterFind    callbackType = "AfterFind"
)

// ErrUnsupportedDataType unsupported data type
var ErrUnsupportedDataType = errors.New("unsupported data type")

type Schema struct {
	Name                      string
	ModelType                 reflect.Type
	Table                     string
	PrioritizedPrimaryField   *Field

Many packages that simplify it a lot have to make many compromises with the data model, database, and available features. And some of these packages that simplify things too much actually have security flaws underneath.

---

**FastAPI** doesn't make any compromise with any database, data model or tool.

It gives you all the flexibility to choose the ones that fit your project the best.

     */
    @Required
    public String scriptType;

    /**
     * The script data or code that was executed.
     * This field contains the actual script content that was run.
     */
    public String scriptData;

    /**
     * The result or output from the script execution.
     * This field contains any output or result data from the script.
     */
    public String scriptResult;

    /**

import java.util.logging.Logger;

import org.apache.commons.io.output.DeferredFileOutputStream;

/**
 * ContentOutputStream is a custom output stream that extends DeferredFileOutputStream.
 * It writes data to a temporary file once the data size exceeds a specified threshold.
 *
 * <p>This class ensures that the temporary file is deleted if it is not needed.
 * It uses a logger to log warnings if there are issues deleting the temporary file.</p>
 *

    Arrays.fill(bytez, (byte) 0x99);
    return bytez;
  }

  public void testToString() {
    byte[] data = new byte[] {127, -128, 5, -1, 14};
    assertEquals("7f8005ff0e", HashCode.fromBytes(data).toString());
    assertEquals("7f8005ff0e", base16().lowerCase().encode(data));
  }

  public void testHashCode_nulls() throws Exception {
    sanityTester().testNulls();
  }

            addMetadata(extractData, key, value);
        }
    }

    /**
     * Adds metadata to the extraction data if the value is not null.
     * @param extractData the extraction data
     * @param name the metadata name
     * @param value the metadata value
     */
    protected void addMetadata(final ExtractData extractData, final String name, final String value) {

    val data = Buffer().writeUtf8(content)
    val source: Source =
      object : Source {
        var closed = false

        override fun close() {
          closed = true
        }

        override fun read(
          sink: Buffer,
          byteCount: Long,
        ): Long {
          check(!closed)
          return data.read(sink, byteCount)
        }

Declare the **header parameters** that you need in a **Pydantic model**, and then declare the parameter as `Header`:

{* ../../docs_src/header_param_models/tutorial001_an_py310.py hl[9:14,18] *}

**FastAPI** will **extract** the data for **each field** from the **headers** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can see the required headers in the docs UI at `/docs`: