```
0001 https://www.washingtonpost.com/
0001 0.000 callStart
0002 https://www.nytimes.com/
0002 0.000 callStart
0002 0.010 dnsStart
0001 0.013 dnsStart
0001 0.022 dnsEnd
0002 0.019 dnsEnd
0001 0.028 connectStart
0002 0.025 connectStart
0002 0.072 secureConnectStart
0001 0.075 secureConnectStart
0001 0.386 secureConnectEnd

        assertEquals(0, new BigDecimal("0.00001").compareTo(BigDecimalConversionUtil.toBigDecimal(new Double(0.00001D))));
        assertEquals(0, new BigDecimal("0.0000001").compareTo(BigDecimalConversionUtil.toBigDecimal(new Double(0.0000001D))));

        assertEquals(0, new BigDecimal("0.123").compareTo(BigDecimalConversionUtil.toBigDecimal(new Double(0.123D))));

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();

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(
        {

    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)
	}

    def get_model():
        return model

    client = TestClient(app)
    with client:
        response = client.get("/model")
    assert response.json() == {"dt_field": "2019-01-01T08:00:00+00:00"}


# TODO: remove when deprecating Pydantic v1
@needs_pydanticv1
def test_pydanticv1():
    class ModelWithDatetimeField(BaseModel):
        dt_field: datetime

        class Config:

    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():

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(
        {