## Ein TypeScript-SDK erstellen { #create-a-typescript-sdk }

Beginnen wir mit einer einfachen FastAPI-Anwendung:

{* ../../docs_src/generate_clients/tutorial001_py39.py hl[7:9,12:13,16:17,21] *}

## Crie um SDK em TypeScript { #create-a-typescript-sdk }

Vamos começar com uma aplicação FastAPI simples:

{* ../../docs_src/generate_clients/tutorial001_py39.py hl[7:9,12:13,16:17,21] *}

    private boolean useMultiChannelExplicitlySet = false;
    private boolean channelBindingPolicyExplicitlySet = false;

    /**
     * Create a configuration backed by properties
     *
     * @param props properties object containing JCIFS configuration settings
     * @throws CIFSException if configuration initialization fails
     */

        int typeWithUpperBits = 0xFFFF0001; // Should be treated as type 1 (printer)
        SmbShareInfo info = new SmbShareInfo(TEST_NET_NAME, typeWithUpperBits, TEST_REMARK);
        assertEquals(SmbConstants.TYPE_PRINTER, info.getType());

        typeWithUpperBits = 0x12340003; // Should be treated as type 3 (named pipe)
        info = new SmbShareInfo(TEST_NET_NAME, typeWithUpperBits, TEST_REMARK);

        verify(request, times(1)).getOverrideTimeout();
    }

    @Test
    @DisplayName("Test Request with concrete implementation")
    void testConcreteImplementation() {
        // Create a concrete implementation for testing
        TestRequest testRequest = new TestRequest();

        // Test initResponse
        CommonServerMessageBlockResponse testResponse = testRequest.initResponse(context);

            tasks.add(new Callable<Integer>() {
                public Integer call() throws Exception {
                    final UrlQueue q = new UrlQueueImpl();
                    // Use modulo to create multiple accesses to same hosts
                    q.setUrl("http://host" + (index % 5) + ".com/page" + index);
                    CrawlingParameterUtil.setUrlQueue(q);
                    controller.delayBeforeProcessing();

## Pydantics `BaseModel` importieren { #import-pydantics-basemodel }

Zuerst müssen Sie `BaseModel` von `pydantic` importieren:

{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Ihr Datenmodell erstellen { #create-your-data-model }

Dann deklarieren Sie Ihr Datenmodell als eine Klasse, die von `BaseModel` erbt.

Verwenden Sie Standard-Python-Typen für alle Attribute:

{* ../../docs_src/body/tutorial001_py310.py hl[5:9] *}

{* ../../docs_src/dependencies/tutorial011_an_py39.py hl[9] *}

В этом случае **FastAPI** вовсе не трогает `__init__` и не зависит от него — мы используем его напрямую в нашем коде.

## Создаём экземпляр { #create-an-instance }

Мы можем создать экземпляр этого класса так:

{* ../../docs_src/dependencies/tutorial011_an_py39.py hl[18] *}

      service.shutdown();
    }
  }

  public void testRejectedExecutionThrownWithMultipleCalls() throws Exception {
    CountDownLatch latch = new CountDownLatch(1);
    SettableFuture<?> future = SettableFuture.create();
    Executor delegate =
        new Executor() {
          @Override
          public void execute(Runnable task) {
            if (future.set(null)) {
              awaitUninterruptibly(latch);

			int64(len(testCase.body)), bytes.NewReader(testCase.body), testCase.accessKey, testCase.secretKey, nil)
		if err != nil {
			t.Fatalf("Test %d: %s: Failed to create HTTP request for GetBucketLocationHandler: <ERROR> %v", i+1, instanceType, err)
		}
		// Since `apiRouter` satisfies `http.Handler` it has a ServeHTTP to execute the logic of the handler.