public void testLenientFormat_badArgumentToString() {
    assertThat(Strings.lenientFormat("boiler %s plate", new ThrowsOnToString()))
        .matches(
            // J2kt nested class name does not use "$"
            "boiler <com\\.google\\.common\\.base\\.StringsTest[.$]ThrowsOnToString@[0-9a-f]+ "
                + "threw java\\.lang\\.UnsupportedOperationException> plate");
  }

dataclass は自動的に Pydantic の dataclass に変換されます。

このため、そのスキーマは API ドキュメントの UI に表示されます:

<img src="/img/tutorial/dataclasses/image01.png">

## ネストしたデータ構造での dataclasses { #dataclasses-in-nested-data-structures }

`dataclasses` を他の型注釈と組み合わせて、ネストしたデータ構造を作成できます。

場合によっては、自動生成された API ドキュメントでエラーが発生するなどの理由で、Pydantic 版の `dataclasses` を使う必要があるかもしれません。

   */
  protected final <T> void setDistinctValues(Class<T> type, T value1, T value2) {
    tester.setDistinctValues(type, value1, value2);
  }

  /** Specifies that classes that satisfy the given predicate aren't tested for sanity. */
  protected final void ignoreClasses(Predicate<? super Class<?>> condition) {
    this.classFilter = and(this.classFilter, not(condition));
  }

  private static AssertionError sanityError(

    "docs_src/dependencies/tutorial013_an_py310.py",  # temporary code example?
    "docs_src/dependencies/tutorial014_an_py310.py",  # temporary code example?
    # Pydantic v1 migration, no longer tested
    "docs_src/pydantic_v1_in_v2/tutorial001_an_py310.py",
    "docs_src/pydantic_v1_in_v2/tutorial002_an_py310.py",
    "docs_src/pydantic_v1_in_v2/tutorial003_an_py310.py",

        assertTrue(protocolHelper.isValidFileProtocol("s3://123bucket/path"));
        assertTrue(protocolHelper.isValidFileProtocol("s3://bucket/path/to/deep/nested/file.txt"));
        assertTrue(protocolHelper.isValidFileProtocol("s3://bucket/path/ファイル.txt"));
        assertTrue(protocolHelper.isValidFileProtocol("s3://bucket/path/file%20with%20spaces.txt"));

        // GCS URLs

  public void testLog10MatchesBigInteger() {
    for (int x : POSITIVE_INTEGER_CANDIDATES) {
      for (RoundingMode mode : ALL_SAFE_ROUNDING_MODES) {
        // The BigInteger implementation is tested separately, use it as the reference.
        assertEquals(BigIntegerMath.log10(valueOf(x), mode), IntMath.log10(x, mode));
      }
    }
  }

  // Relies on the correctness of log10(int, FLOOR) and of pow(int, int).

import org.gradle.api.file.FileTree;
import org.gradle.api.model.ObjectFactory;
import org.gradle.api.tasks.Input;
import org.gradle.api.tasks.InputFiles;
import org.gradle.api.tasks.Internal;
import org.gradle.api.tasks.Nested;
import org.gradle.api.tasks.OutputDirectory;
import org.gradle.api.tasks.SkipWhenEmpty;
import org.gradle.api.tasks.TaskAction;
import org.gradle.api.tasks.util.PatternFilterable;
import org.gradle.api.tasks.util.PatternSet;

    /** The search engine client for interacting with OpenSearch. */
    @Resource
    public SearchEngineClient searchEngineClient;

    /**
     * A nested class for parsing command-line options.
     */
    protected static class Options {
        /** The session ID for the suggest creation process. */

You also get error checks for incorrect type operations:

<img src="/img/tutorial/body/image04.png">

This is not by chance, the whole framework was built around that design.

And it was thoroughly tested at the design phase, before any implementation, to ensure it would work with all the editors.

There were even some changes to Pydantic itself to support this.

        assertEquals(longMessage, exception.getMessage());
        assertNull(exception.getCause());
    }

    @Test
    public void test_getCause_withNestedExceptions() {
        // Test deeply nested exception causes
        Exception level3 = new Exception("Level 3: Database connection failed");
        Exception level2 = new Exception("Level 2: User lookup failed", level3);