static final Iterable<Integer> ALL_INTEGER_CANDIDATES;

  static {
    ImmutableSet.Builder<Integer> intValues = ImmutableSet.builder();
    // Add boundary values manually to avoid over/under flow (this covers 2^N for 0 and 31).
    intValues.add(Integer.MAX_VALUE - 1, Integer.MAX_VALUE);
    // Add values up to 40. This covers cases like "square of a prime" and such.
    for (int i = 1; i <= 40; i++) {

   */
  ObjectCountHashMap(int capacity) {
    this(capacity, DEFAULT_LOAD_FACTOR);
  }

  ObjectCountHashMap(int expectedSize, float loadFactor) {
    init(expectedSize, loadFactor);
  }

  void init(int expectedSize, float loadFactor) {
    Preconditions.checkArgument(expectedSize >= 0, "Initial capacity must be non-negative");
    Preconditions.checkArgument(loadFactor > 0, "Illegal load factor");

      "term": {
        "type": "keyword"
      },
      "query": {
        "type": "keyword"
      },
      "maxSize": {
        "type": "integer"
      },
      "boost": {
        "type": "float"
      },
      "virtualHost": {
        "type": "keyword"
      },
      "createdBy": {
        "type": "keyword"
      },
      "createdTime": {
        "type": "long"
      },
      "updatedBy": {

from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()


class ItemGroup(BaseModel):
    items: list[tuple[str, str]]


class Coordinate(BaseModel):
    x: float
    y: float


@app.post("/model-with-tuple/")
def post_model_with_tuple(item_group: ItemGroup):
    return item_group


@app.post("/tuple-of-models/")

import configurations.applyDefaults
import configurations.applyTestDefaults
import io.mockk.every
import io.mockk.impl.annotations.MockK
import io.mockk.junit5.MockKExtension
import io.mockk.mockk
import io.mockk.slot
import jetbrains.buildServer.configs.kotlin.BuildStep
import jetbrains.buildServer.configs.kotlin.BuildSteps
import jetbrains.buildServer.configs.kotlin.DslContext
import model.CIBuildModel

		},
		{
			name:       "select-in-number-float",
			query:      `SELECT * from s3object s WHERE 3 in s.numbers[*]`,
			wantResult: `{"id":2,"title":"Second Record","desc":"another text","numbers":[2,3,4]}`,
		},
		{
			name:       "select-in-number-float-in-sql",
			query:      `SELECT * from s3object s WHERE 3.0 in s.numbers[*]`,

        final long docFreq = Long.parseLong(source.get(FieldNames.DOC_FREQ).toString());
        final long queryFreq = Long.parseLong(source.get(FieldNames.QUERY_FREQ).toString());
        final float userBoost = Float.parseFloat(source.get(FieldNames.USER_BOOST).toString());
        final List<String> tags = SuggestUtil.getAsList(source.get(FieldNames.TAGS));

                            || actual == Short.class
                            || actual == Byte.class)) {
                return true;
            }
            if (formal == Float.TYPE
                    && (actual == Float.class
                            || actual == Long.class
                            || actual == Integer.class
                            || actual == Short.class

* Конвертацію даних
* Валідацію даних
* Автоматичну документацію

## Спеціальні типи та валідація

Окрім звичайних типів, таких як `str`, `int`, `float`, та ін. Ви можете використовувати складніші типи, які наслідують `str`.

    @Override
    protected String getQueryClassName() {
        return PrefixQuery.class.getSimpleName();
    }

    @Override
    public QueryBuilder execute(final QueryContext context, final Query query, final float boost) {
        if (query instanceof final PrefixQuery prefixQuery) {
            if (logger.isDebugEnabled()) {
                logger.debug("PrefixQuery: query={}, boost={}", query, boost);
            }