source.read(sink, byteCount)
      } catch (e: IOException) {
        carrier.noNewExchanges()
        responseBodyComplete()
        throw e
      }
    }

    /**
     * Closes the cache entry and makes the socket available for reuse. This should be invoked when
     * the end of the body has been reached.
     */
    fun responseBodyComplete() {
      if (state == STATE_CLOSED) return

         * with [getCompositeScope]) avoids duplicate inner classes, as they are contained in non-static and static scopes.
         *
         * A proper combined declared member scope kind also makes it easier to cache combined scopes directly (if needed).
         */
        COMBINED,
    }

    private fun getDeclaredMemberScope(classSymbol: KtSymbolWithMembers, kind: DeclaredMemberScopeKind): KtScope {

    val commonsLang3 = "org.apache.commons:commons-lang3"
    val commonsMath = "org.apache.commons:commons-math3"
    val configurationCacheReport = "org.gradle.buildtool.internal:configuration-cache-report:$configurationCacheReportVersion"
    val eclipseSisuPlexus = "org.eclipse.sisu:org.eclipse.sisu.plexus"
    val fastutil = "it.unimi.dsi:fastutil"
    val gcs = "com.google.apis:google-api-services-storage"

    * <a href="https://github.com/Rebilly/ReDoc" class="external-link" target="_blank">ReDoc</a>

    Ces deux-là ont été choisis parce qu'ils sont populaires et stables, mais en faisant une recherche rapide, vous pourriez trouver des dizaines d'alternatives supplémentaires pour OpenAPI (que vous pouvez utiliser avec **FastAPI**).

### Frameworks REST pour Flask

platforms/core-execution/build-cache/                       @gradle/bt-execution @gradle/bt-dv-build-cache
platforms/core-execution/build-cache-base/                  @gradle/bt-execution @gradle/bt-dv-build-cache
platforms/core-execution/build-cache-http/                  @gradle/bt-execution @gradle/bt-dv-build-cache
platforms/core-execution/build-cache-packaging/             @gradle/bt-execution @gradle/bt-dv-build-cache

     * Run docs tests with the configuration cache enabled.
     */
    const val ENABLE_CONFIGURATION_CACHE_FOR_DOCS_TESTS = "enableConfigurationCacheForDocsTests"

    /**
     * Run docs tests that are knowingly broken when running with the configuration cache enabled. Only applied when #ENABLE_CONFIGURATION_CACHE_FOR_DOCS_TESTS is also set.
     */
    const val RUN_BROKEN_CONFIGURATION_CACHE_DOCS_TESTS = "runBrokenConfigurationCacheDocsTests"

`@lru_cache` is part of `functools` which is part of Python's standard library, you can read more about it in the <a href="https://docs.python.org/3/library/functools.html#functools.lru_cache" class="external-link" target="_blank">Python docs for `@lru_cache`</a>.

## Recap

        .url("https://square.com")
        .build()
    assertThat(request.headers("Cache-Control")).containsExactly("no-cache")
    assertThat(request.cacheControl.noCache).isTrue()
  }

  @Test
  fun emptyCacheControlClearsAllCacheControlHeaders() {
    val request =
      Request.Builder()
        .header("Cache-Control", "foo")
        .cacheControl(CacheControl.Builder().build())

这样，它的行为几乎就像是一个全局变量。但是由于它使用了依赖项函数，因此我们可以轻松地进行测试时的覆盖。

`@lru_cache` 是 `functools` 的一部分，它是 Python 标准库的一部分，您可以在<a href="https://docs.python.org/3/library/functools.html#functools.lru_cache" class="external-link" target="_blank">Python 文档中了解有关 `@lru_cache` 的更多信息</a>。

## 小结

您可以使用 Pydantic 设置处理应用程序的设置或配置，利用 Pydantic 模型的所有功能。

* 通过使用依赖项，您可以简化测试。
* 您可以使用 `.env` 文件。

    }

    throw unknownHostException
  }

  private fun getCacheOnlyResponse(request: Request): Response? {
    if (client.cache != null) {
      try {
        // Use the cache without hitting the network first
        // 504 code indicates that the Cache is stale
        val onlyIfCached =
          CacheControl.Builder()
            .onlyIfCached()
            .build()