Para rodar seu app FastAPI em desenvolvimento, você pode usar o comando `fastapi dev`:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> dev <u style="text-decoration-style:single">main.py</u>
<font color="#3465A4">INFO    </font> Using path <font color="#3465A4">main.py</font>

///

## Nachrichten erwarten und Nachrichten senden

In Ihrer WebSocket-Route können Sie Nachrichten `await`en und Nachrichten senden.

{* ../../docs_src/websockets/tutorial001.py hl[48:52] *}

Sie können Binär-, Text- und JSON-Daten empfangen und senden.

## Es ausprobieren

Wenn Ihre Datei `main.py` heißt, führen Sie Ihre Anwendung so aus:

<div class="termy">

```console
$ uvicorn main:app --reload

    }

    public void test_messageWithSpecialCharacters() {
        // Test message with special characters
        String message = "Theme error: 日本語 & special <characters> \"quoted\" 'text'";
        ThemeException exception = new ThemeException(message);

        assertNotNull(exception);
        assertEquals(message, exception.getMessage());
    }

    public void test_veryLongMessage() {

    @Throws(IOException::class)
    fun onReadMessage(text: String)

    @Throws(IOException::class)
    fun onReadMessage(bytes: ByteString)

    fun onReadPing(payload: ByteString)

    fun onReadPong(payload: ByteString)

    fun onReadClose(
      code: Int,
      reason: String,
    )
  }

  /**
   * Process the next protocol frame.
   *

package org.codelibs.fess.api.json;

import static org.codelibs.core.stream.StreamUtil.stream;

import java.io.IOException;
import java.io.PrintWriter;
import java.io.StringWriter;
import java.net.URLDecoder;
import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Date;
import java.util.HashMap;
import java.util.List;
import java.util.Locale;
import java.util.Map;

### **4.2 WordCount**

WordCount is a simple program that counts how often a word occurs in a text file. The code builds a dataset of (String, Int) pairs called counts, and saves the dataset to a file.

The following example submits WordCount code to the Scala shell. Select an input file for the Spark WordCount example. We can use any text file as input.

- Login as user **‘spark’**.

                <copy toDir="${project.build.directory}/guava-gwt-sources">
                  <fileset dir="${project.build.directory}/guava-sources">
                    <contains text="@GwtCompatible"/>
                  </fileset>
                </copy>
                <!-- The following don't contain @GwtCompatible for dependency reasons. -->

  tensorflow::GraphDef gdef;
  if (!tensorflow::protobuf::TextFormat::ParseFromString(text_proto, &gdef)) {
    status->status = tensorflow::errors::Internal(
        "Invalid text proto for GraphDef: ", text_proto);
    return {};
  }
  const auto& fdef_lib = gdef.library();
  if (fdef_lib.gradient_size() > 0) {
    status->status = tensorflow::errors::Internal(

    public void test_isTarget_withVariousMimeTypes() {
        // Test with various MIME types
        String[] supportedTypes = { "application/pdf", "image/jpeg", "image/png" };
        String[] unsupportedTypes = { "text/plain", "application/xml", "audio/mp3" };

        for (String mimeType : supportedTypes) {
            Map<String, Object> docMap = new HashMap<>();
            docMap.put("mimetype", mimeType);

/**
 * Service class for managing character mapping operations.
 * <p>
 * This service handles character mapping management including CRUD operations
 * and list retrieval. Character mappings are used for text normalization
 * and character substitution during document processing and search operations.
 * </p>
 */
public class CharMappingService {

    /**
     * Creates a new instance of CharMappingService.
     */