<Filter></Filter>
	                       <Status>Enabled</Status>
			       <ID>DeleteAllVersions</ID>
	                    </Rule>
	                 </LifecycleConfiguration>`
	delMarkerILM := `<LifecycleConfiguration>
                            <Rule>
                              <ID>DelMarkerExpiration</ID>
                              <Filter></Filter>

                .map(Dependency::getArtifact)
                .filter(d -> "org.apache.maven".equals(d.getGroupId()))
                .filter(d -> !DefaultPluginValidationManager.EXPECTED_PROVIDED_SCOPE_EXCLUSIONS_GA.contains(
                        d.getGroupId() + ":" + d.getArtifactId()))
                .map(Artifact::getVersion)
                .filter(v -> v.startsWith("2."))
                .collect(Collectors.toSet());

                }
            }
        }
    }
}


fun FileSystemOperations.removeCachedScripts(cachesDir: File) {
    if (cachesDir.isDirectory) {
        cachesDir.listFiles()
            .filter { it.isDirectory }
            .flatMap { scriptsCacheDirsUnder(it) }
            .forEach { scriptsCacheDir ->
                logger.lifecycle("Removing scripts cache directory : $scriptsCacheDir")

  @Override
  NavigableSet<Integer> createUnfiltered(Iterable<Integer> contents) {
    return Sets.newTreeSet(contents);
  }

  @Override
  NavigableSet<Integer> filter(
      NavigableSet<Integer> elements, Predicate<? super Integer> predicate) {
    return Sets.filter(elements, predicate);
  }

    /**
     * Adds a boost function with a filter to modify document scoring during search.
     * This method adds a boost function that applies only to documents matching the filter.
     *
     * @param filter the query filter to determine which documents the boost applies to
     * @param scoreFunction the score function to add for boosting
     */
    public void addBoostFunction(final QueryBuilder filter, final ScoreFunctionBuilder<?> scoreFunction) {

  @Override
  Set<Integer> createUnfiltered(Iterable<Integer> contents) {
    return newHashSet(contents);
  }

  @Override
  Set<Integer> filter(Set<Integer> elements, Predicate<? super Integer> predicate) {
    return Sets.filter(elements, predicate);
  }

            if (prPage.size < PAGE_SIZE) {
                break
            }
        }
        return prs
            .filter { it.milestone?.title?.startsWith(milestone.get()) == true }
            // Filter out the ghost user that replaces deleted users
            .filter { it.user.login != "ghost" }
            .map { it.user.login }
            .toSet()
            .map { getUserInfo(it) }
            .toSet()

            subProjectToClassTimes
                .entries
                .filter { "UNKNOWN" != it.key }
                .filter { model.subprojects.getSubprojectByName(it.key) != null }
                .map {
                    SubprojectTestClassTime(
                        model.subprojects.getSubprojectByName(it.key)!!,
                        it.value.filter { tct ->
                            tct.sourceSet != "test"

                                                <th class="text-center" style="width: 10%"><la:message
                                                        key="labels.suggest_word_number"/></th>
                                                <th class="text-center" style="width: 20%"></th>
                                            </tr>
                                            </thead>

* **更简单**：
    * 没有新的模式定义 micro-language 需要学习。
    * 如果你知道 Python types，你就知道如何使用 Pydantic。
* 和你 **<abbr title="集成开发环境，和代码编辑器类似">IDE</abbr>/<abbr title="一个检查代码错误的程序">linter</abbr>/brain** 适配:
    * 因为 pydantic 数据结构仅仅是你定义的类的实例；自动补全，linting，mypy 以及你的直觉应该可以和你验证的数据一起正常工作。
* 验证**复杂结构**:
    * 使用分层的 Pydantic 模型, Python `typing`的 `List` 和 `Dict` 等等。
    * 验证器使我们能够简单清楚的将复杂的数据模式定义、检查并记录为 JSON Schema。