}

    /**
     * Sets the boost expression used to calculate boost values.
     *
     * @param expression the boost expression string
     */
    public void setBoostExpression(final String expression) {
        boostExpression = expression;
    }

    /**
     * Gets the current match expression.
     *
     * @return the match expression string
     */
    public String getMatchExpression() {

        violations = validator.validate(bean);
        assertTrue(violations.isEmpty());
    }

    // Test validation with invalid cron expressions
    @Test
    public void test_invalidCronExpressions() {
        TestBean bean = new TestBean();

        // Test invalid cron expression
        bean.setCronExpression("invalid");
        Set<ConstraintViolation<TestBean>> violations = validator.validate(bean);

## Add regular expressions { #add-regular-expressions }

You can define a <dfn title="A regular expression, regex or regexp is a sequence of characters that define a search pattern for strings.">regular expression</dfn> `pattern` that the parameter should match:

{* ../../docs_src/query_params_str_validations/tutorial004_an_py310.py hl[11] *}

This specific regular expression pattern checks that the received parameter value:

                    filters.add(new HighestVersionFilter(num));
                } else if ("l".equals(expression)) {
                    filters.add(new LowestVersionFilter());
                } else if (expression.startsWith("l(") && expression.endsWith(")")) {
                    int num = Integer.parseInt(expression.substring(2, expression.length() - 1));

Syntax      = { Production } .
Production  = production_name "=" [ Expression ] "." .
Expression  = Term { "|" Term } .
Term        = Factor { Factor } .
Factor      = production_name | token [ "…" token ] | Group | Option | Repetition .
Group       = "(" Expression ")" .
Option      = "[" Expression "]" .
Repetition  = "{" Expression "}" .
</pre>

<p>
Productions are expressions constructed from terms and the following

   * that pass this regex are valid -- only a performance hit is incurred, not a semantics bug.
   */
  @GwtIncompatible // regular expressions
  static final
  java.util.regex.Pattern
      FLOATING_POINT_PATTERN = fpPattern();

  @GwtIncompatible // regular expressions
  private static
  java.util.regex.Pattern
      fpPattern() {
    /*

Create functions with a name that starts with `test_` (this is standard `pytest` conventions).

Use the `TestClient` object the same way as you do with `httpx`.

Write simple `assert` statements with the standard Python expressions that you need to check (again, standard `pytest`).

{* ../../docs_src/app_testing/tutorial001_py310.py hl[2,12,15:18] *}

/// tip

Notice that the testing functions are normal `def`, not `async def`.

 *
 * <p>Note on class-level isolation: Compiled Script classes are cached and reused.
 * Class-level state (static fields, metaclass mutations) persists across evaluations
 * of the same script. In Fess, scripts are short expressions configured by
 * administrators (e.g., "data1 &gt; 10", "10 * boost1 + boost2") and do not use
 * static state, so this is acceptable.</p>
 *
 * <p>Resource Management: Each cached entry's GroovyClassLoader is closed on

    /** HTTP header name for robots tag */
    private static final String X_ROBOTS_TAG = "X-Robots-Tag";

    /** XPath expression for extracting thumbnail content from meta tags */
    private static final String META_NAME_THUMBNAIL_CONTENT = "//META[@name=\"thumbnail\" or @name=\"THUMBNAIL\"]/@content";

    /** XPath expression for extracting Open Graph image content from meta tags */

## 검증 더 추가하기 { #add-more-validations }

`min_length` 매개변수도 추가할 수 있습니다:

{* ../../docs_src/query_params_str_validations/tutorial003_an_py310.py hl[10] *}

## 정규식 추가 { #add-regular-expressions }

매개변수와 일치해야 하는 <dfn title="정규 표현식(regex 또는 regexp)은 문자열에 대한 검색 패턴을 정의하는 문자 시퀀스입니다.">정규 표현식</dfn> `pattern`을 정의할 수 있습니다:

{* ../../docs_src/query_params_str_validations/tutorial004_an_py310.py hl[11] *}