}

    assertTrue(c1.isClosed());
    assertTrue(c2.isClosed());

    ImmutableSet<Throwable> suppressed = ImmutableSet.copyOf(thrownException.getSuppressed());
    assertEquals(2, suppressed.size());

    assertEquals(ImmutableSet.of(c1Exception, c2Exception), suppressed);
  }

  public void testNullCloseable() throws IOException {
    Closer closer = Closer.create();

    }
    // The top bit is set, which means that the double value is going to come from the top 53 bits.
    // So we can ignore the bottom 11, except for rounding. We can unsigned-shift right 1, aka
    // unsigned-divide by 2, and convert that. Then we'll get exactly half of the desired double
    // value. But in the specific case where the bottom two bits of the original number are 01, we

///

## Import Pydantic's `BaseModel`

First, you need to import `BaseModel` from `pydantic`:

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

## Create your data model

Then you declare your data model as a class that inherits from `BaseModel`.

Use standard Python types for all the attributes:

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

Вы можете использовать всю функциональность <a href="https://www.starlette.io/" class="external-link" target="_blank">Starlette</a> в `FastAPI`.

///

### Шаг 2: создайте экземпляр `FastAPI`

```Python hl_lines="3"
{!../../docs_src/first_steps/tutorial001.py!}
```

Переменная `app` является экземпляром класса `FastAPI`.

	if err != nil {
		fmt.Printf("unreadable on target: %s (%s)\n", tgtCtnt.Key, err)
		return false
	}

	var sourceFailed, targetFailed bool
	var wg sync.WaitGroup

	wg.Add(2)
	go func() {
		defer wg.Done()
		srcSize, err := io.Copy(srcSha256, sobj)
		if err != nil {
			fmt.Printf("unreadable on source: %s (%s)\n", srcCtnt.Key, err)
			sourceFailed = true

                    /*expected_shape*/ make_shape({3, kUnknownDim}));

  // Infer shape when some dimensions are unknown.
  CheckOutputShapes(
      matmul_op,
      /*input_shapes*/ {make_shape({kUnknownDim, 2}), make_shape({2, 4})},
      /*input_tensors*/ {},
      /*expected_shape*/ make_shape({kUnknownDim, 4}));

  // Infer shape when everything is unknown.
  CheckOutputShapes(matmul_op,

          Security.insertProviderAt(BouncyCastleProvider(), 1)
          Security.insertProviderAt(BouncyCastleJsseProvider(), 2)
        } else if (platformSystemProperty == CORRETTO_PROPERTY) {
          AmazonCorrettoCryptoProvider.install()

          AmazonCorrettoCryptoProvider.INSTANCE.assertHealthy()
        }

      }
      in 40L until 80L -> {
        result.writeDecimalLong(1)
        result.writeByte(dot)
        result.writeDecimalLong(xy - 40L)
      }
      else -> {
        result.writeDecimalLong(2)
        result.writeByte(dot)
        result.writeDecimalLong(xy - 80L)
      }
    }
    while (byteCount < limit) {
      result.writeByte(dot)
      result.writeDecimalLong(readVariableLengthLong())
    }

    checkPublicSuffix("biz", null)
    checkPublicSuffix("domain.biz", "domain.biz")
    checkPublicSuffix("b.domain.biz", "domain.biz")
    checkPublicSuffix("a.b.domain.biz", "domain.biz")
    // TLD with some 2-level rules.
    checkPublicSuffix("com", null)
    checkPublicSuffix("example.com", "example.com")
    checkPublicSuffix("b.example.com", "example.com")
    checkPublicSuffix("a.b.example.com", "example.com")

 * <p>
 * 本クラスをstatic importすることにより、次のように{@literal Map}のインスタンスを簡潔に初期化することができます。
 * </p>
 *
 * <pre>
 * import static org.codelibs.core.collection.Maps.*;
 *
 * Map&lt;String, Integer&gt; map = map("a", 1).$("b", 2).$("c", 3).$();
 * </pre>
 *
 * @author koichik
 * @param <K>
 *            {@literal Map}のキーの型
 * @param <V>
 *            {@literal Map}の値の型
 */
public class Maps<K, V> {