.named("Doubles.asList, tail subList"),
            ListTestSuiteBuilder.using(new DoublesAsListMiddleSubListGenerator())
                .named("Doubles.asList, middle subList"));

    TestSuite suite = new TestSuite();
    for (ListTestSuiteBuilder<Double> builder : builders) {
      suite.addTest(
          builder
              .withFeatures(
                  CollectionSize.ONE,

///

So, you should be able to pin to a version like:

```txt
fastapi>=0.45.0,<0.46.0
```

Breaking changes and new features are added in "MINOR" versions.

/// tip

The "MINOR" is the number in the middle, for example, in `0.2.3`, the MINOR version is `2`.

///

## Upgrading the FastAPI versions { #upgrading-the-fastapi-versions }

You should add tests for your app.

``` hl_lines="5"
.
├── app
│   ├── __init__.py
│   ├── main.py
│   └── test_main.py
```

Como esse arquivo está no mesmo pacote, você pode usar importações relativas para importar o objeto `app` do módulo `main` (`main.py`):

{* ../../docs_src/app_testing/app_a_py39/test_main.py hl[3] *}

...e ter o código para os testes como antes.

## Testando: exemplo estendido { #testing-extended-example }

* iSCSI sessions managed by kubernetes will now explicitly set startup.mode to 'manual' to  prevent automatic login after node failure recovery. This is the default open-iscsi mode, so this change will only impact users who have changed their startup.mode to be 'automatic' in /etc/iscsi/iscsid.conf. ([#57475](https://github.com/kubernetes/kubernetes/pull/57475), [@stmcginnis](https://github.com/stmcginnis))

  }

  @ListFeature.Require(SUPPORTS_ADD_WITH_INDEX)
  @CollectionSize.Require(absent = {ZERO, ONE})
  public void testAddAllAtIndex_middle() {
    assertTrue(
        "addAll(middle, disjoint) should return true",
        getList().addAll(getNumElements() / 2, createDisjointCollection()));
    expectAdded(getNumElements() / 2, createDisjointCollection());
  }

    // Test that listeners added both before and after the value is available
    // get called correctly.
    for (int i = 0; i < 20; i++) {

      // Right in the middle start up a thread to close the latch.
      if (i == 10) {
        new Thread(() -> latch.countDown()).start();
      }

      future.addListener(listenerLatch::countDown, exec);
    }

        <artifactId>modello-maven-plugin</artifactId>
        <configuration>
          <version>1.2.0</version>
          <models>
            <model>../../api/maven-api-cli/src/main/mdo/core-extensions.mdo</model>
          </models>
          <templates>
            <template>reader-stax.vm</template>
            <template>writer-stax.vm</template>
          </templates>
          <params>

Using this same trick, you could use a Pydantic model to define the JSON Schema that is then included in the custom OpenAPI schema section for the *path operation*.

And you could do this even if the data type in the request is not JSON.

        int result = response.readParametersWireFormat(buffer, 0, 3);

        // Assert
        assertEquals(6, result);
    }

    @Test
    @DisplayName("Test readParametersWireFormat ignores middle 2 bytes")
    void testReadParametersWireFormatIgnoresMiddleBytes() {
        // Arrange
        byte[] buffer = new byte[10];
        SMBUtil.writeInt2(200, buffer, 0);
        // These bytes should be ignored

TensorFlow
[**models**](https://developers.google.com/machine-learning/glossary/#model) (to
use a term commonly used by machine learning practitioners) are expressed as
programs that TensorFlow executes. TensorFlow programs are encoded as
computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).
Since models are practically programs that TensorFlow executes, using untrusted