assertCorrectSlice(0, 0, 0, 0);
    assertCorrectSlice(0, 0, 1, 0);
    assertCorrectSlice(100, 0, 10, 10);
    assertCorrectSlice(100, 0, 100, 100);
    assertCorrectSlice(100, 5, 10, 10);
    assertCorrectSlice(100, 5, 100, 95);
    assertCorrectSlice(100, 100, 0, 0);
    assertCorrectSlice(100, 100, 10, 0);
    assertCorrectSlice(100, 101, 10, 0);
  }

  /**

        InetAddresses.toAddrString(InetAddresses.forString("0:0:0:4:0:0:0:ffff")));
    assertEquals(
        "::5:0:0:ffff", InetAddresses.toAddrString(InetAddresses.forString("0:0:0:0:5:0:0:ffff")));
    assertEquals(
        "1::4:0:0:7:8", InetAddresses.toAddrString(InetAddresses.forString("1:0:0:4:0:0:7:8")));
    assertEquals("::", InetAddresses.toAddrString(InetAddresses.forString("0:0:0:0:0:0:0:0")));

client = TestClient(app)


def test_extra_types():
    item_id = "ff97dd87-a4a5-4a12-b412-cde99f33e00e"
    data = {
        "start_datetime": "2018-12-22T14:00:00+00:00",
        "end_datetime": "2018-12-24T15:00:00+00:00",
        "repeat_at": "15:30:00",
        "process_after": 300,
    }
    expected_response = data.copy()
    expected_response.update(
        {

    return client


@needs_py310
def test_extra_types(client: TestClient):
    item_id = "ff97dd87-a4a5-4a12-b412-cde99f33e00e"
    data = {
        "start_datetime": "2018-12-22T14:00:00+00:00",
        "end_datetime": "2018-12-24T15:00:00+00:00",
        "repeat_at": "15:30:00",
        "process_after": 300,
    }
    expected_response = data.copy()
    expected_response.update(
        {

import java.util.Random;

/** A benchmark that tries invoking {@code Set.contains} on many different sets. */
public class MultipleSetContainsBenchmark {

  @Param({"0.0", "0.1", "0.7", "1.0"})
  double emptySetProportion;

  @Param({"0.0", "0.1", "0.7", "1.0"})
  double singletonSetProportion;

  @Param({"0.2", "0.8"})
  double hitRate;

  static final Object PRESENT = new Object();

    return client


@needs_py310
def test_extra_types(client: TestClient):
    item_id = "ff97dd87-a4a5-4a12-b412-cde99f33e00e"
    data = {
        "start_datetime": "2018-12-22T14:00:00+00:00",
        "end_datetime": "2018-12-24T15:00:00+00:00",
        "repeat_at": "15:30:00",
        "process_after": 300,
    }
    expected_response = data.copy()
    expected_response.update(
        {

		cpuUserVal := math.Round(ts.User/tot*100*100) / 100
		m.Set(sysCPUUser, cpuUserVal)
		cpuSystemVal := math.Round(ts.System/tot*100*100) / 100
		m.Set(sysCPUSystem, cpuSystemVal)
		cpuNiceVal := math.Round(ts.Nice/tot*100*100) / 100
		m.Set(sysCPUNice, cpuNiceVal)
		cpuStealVal := math.Round(ts.Steal/tot*100*100) / 100
		m.Set(sysCPUSteal, cpuStealVal)
	}

00000b0 00 14 00 eb ff 42 88 21 c4 00 00 14 00 eb ff 42
00000c0 88 21 c4 00 00 14 00 eb ff 42 88 21 c4 00 00 14
00000d0 00 eb ff 42 88 21 c4 00 00 14 00 eb ff 42 88 21
00000e0 c4 00 00 00 00 ff ff 00 00 00 ff ff 00 34 00 cb
00000f0 ff 42 88 21 c4 00 00 00 00 ff ff 00 00 00 ff ff
0000100 00 34 00 cb ff 42 e8 21 5e 0f 00 00 00 ff ff 0a
0000110 f0 66 64 12 61 c0 15 dc e8 a0 48 bf 48 af 2a b3

    model = ModelWithCustomEncoder(dt_field=datetime(2019, 1, 1, 8))
    assert jsonable_encoder(model) == {"dt_field": "2019-01-01T08:00:00+00:00"}
    subclass_model = ModelWithCustomEncoderSubclass(dt_field=datetime(2019, 1, 1, 8))
    assert jsonable_encoder(subclass_model) == {"dt_field": "2019-01-01T08:00:00+00:00"}


# TODO: remove when deprecating Pydantic v1
@needs_pydanticv1
def test_encode_custom_json_encoders_model_pydanticv1():

    testThreshold(0, 100, true, false);
    testThreshold(10, 100, true, false);
    testThreshold(100, 100, true, false);
    testThreshold(1000, 100, true, false);
    testThreshold(0, 100, false, false);
    testThreshold(10, 100, false, false);
    testThreshold(100, 100, false, false);
    testThreshold(1000, 100, false, false);
  }

  private void testThreshold(
      int fileThreshold, int dataSize, boolean singleByte, boolean resetOnFinalize)