ここでは<a href="https://gunicorn.org/" class="external-link" target="_blank">**Gunicorn**</a>が**Uvicornのワーカー・プロセス**を管理する場合の使い方について紹介していきます。

/// info

<!-- NOTE: the current version of docker.md is outdated compared to English one.  -->
DockerやKubernetesなどのコンテナを使用している場合は、次の章で詳しく説明します： [コンテナ内のFastAPI - Docker](docker.md){.internal-link target=_blank}

    assertThat("hello".map()).isEqualTo("hello")
    assertThat("hello-world".map()).isEqualTo("hello-world")
    assertThat("HELLO".map()).isEqualTo("hello")
    assertThat("Hello".map()).isEqualTo("hello")

    // These compound characters map their its components.
    assertThat("¼".map()).isEqualTo("1⁄4")
    assertThat("™".map()).isEqualTo("tm")
  }

  /** Confirm the compact table satisfies is documented invariants. */

 * function doing a good job of distributing the elements to the buckets to a distribution not far
 * from uniform), and amortized since some operations can trigger a hash table resize.
 *
 * <p>As compared with {@link java.util.LinkedHashMap}, this structure places significantly reduced
 * load on the garbage collector by only using a constant number of internal objects.
 *

#### シンプルなアプリケーション

アプリケーションを**シンプル**な形で実行する場合、プロセス数の細かい調整が必要ない場合、自動化されたデフォルトを使用するだけで、コンテナ内にプロセスマネージャが必要かもしれません。例えば、公式Dockerイメージでシンプルな設定が可能です。

#### Docker Compose

Docker Composeで**シングルサーバ**（クラスタではない）にデプロイすることもできますので、共有ネットワークと**ロードバランシング**を維持しながら（Docker Composeで）コンテナのレプリケーションを管理する簡単な方法はないでしょう。

その場合、**単一のコンテナ**で、**プロセスマネージャ**が内部で**複数のワーカープロセス**を起動するようにします。

#### Prometheusとその他の理由

build:dbg --per_file_copt=+tensorflow/core/kernels.*@-g0
# for now, disable arm_neon. see: https://github.com/tensorflow/tensorflow/issues/33360
build:dbg --cxxopt -DTF_LITE_DISABLE_X86_NEON
# AWS SDK must be compiled in release mode. see: https://github.com/tensorflow/tensorflow/issues/37498
build:dbg --copt -DDEBUG_BUILD

# Config to build TF TPU
build:tpu --define=with_tpu_support=true

)

config_setting(
    name = "with_xla_support",
    define_values = {"with_xla_support": "true"},
    visibility = ["//visibility:public"],
)

# By default, XLA GPU is compiled into tensorflow when building with
# --config=cuda even when `with_xla_support` is false. The config setting
# here allows us to override the behavior if needed.
config_setting(
    name = "no_xla_deps_in_cuda",

#       requires all of these POSIX shell features:
#         * functions;
#         * expansions «$var», «${var}», «${var:-default}», «${var+SET}»,
#           «${var#prefix}», «${var%suffix}», and «$( cmd )»;
#         * compound commands having a testable exit status, especially «case»;
#         * various built-in commands including «command», «set», and «ulimit».
#
#   Important for patching:
#

    * 阅读我的其它想法、文章，了解我创建的工具
    * 关注我，这样就可以随时看到我发布的新文章

## Tweet about **FastAPI**

<a href="https://twitter.com/compose/tweet?text=I'm loving @fastapi because... https://github.com/fastapi/fastapi" class="external-link" target="_blank">Tweet about **FastAPI**</a> 让我和大家知道您为什么喜欢 FastAPI。🎉

     */

    @Override
    public int hashCode () {
        return this.address;
    }


    /**
     * Determines if this address is equal two another. Only the IP Addresses
     * are compared. Similar to the {@link #hashCode} method, the comparison
     * is based on the integer IP address and not the string representation.
     */

    @Override
    public boolean equals ( Object obj ) {

multiprecision library gmp's integer type mpz_t wrapped to look like
the Go package big's integer type Int.

This is a syntactically valid Go program—it can be parsed with the Go
parser and processed by godoc—but it is not compiled directly by gc.
Instead, a separate tool, cgo, processes it to produce three output
files.  The first two, 6g.go and 6c.c, are a Go source file for 6g and
a C source file for 6c; both compile as part of the named package