import okhttp3.internal.url.canonicalize
import okhttp3.internal.url.percentDecode

/**
 * A uniform resource locator (URL) with a scheme of either `http` or `https`. Use this class to
 * compose and decompose Internet addresses. For example, this code will compose and print a URL for
 * Google search:
 *
 * ```java
 * HttpUrl url = new HttpUrl.Builder()
 *     .scheme("https")
 *     .host("www.google.com")
 *     .addPathSegment("search")

  * This puts a much tighter budget on CPU, memory, latency, and throughput requirements than traditional Istio sidecars.

Ztunnel was not designed to be a feature-rich data plane.
Quite the opposite - an *aggressively* small feature set is the key feature that makes ztunnel viable.

   * predicate returns {@code predicate(function(x))}.
   *
   * @return the composition of the provided function and predicate
   */
  public static <A extends @Nullable Object, B extends @Nullable Object> Predicate<A> compose(
      Predicate<B> predicate, Function<A, ? extends B> function) {
    return new CompositionPredicate<>(predicate, function);
  }

  /**

      runnables = null; // allow GC to free listeners even if this stays around for a while.
    }
    // If we succeeded then list holds all the runnables we to execute. The pairs in the stack are
    // in the opposite order from how they were added so we need to reverse the list to fulfill our
    // contract.
    // This is somewhat annoying, but turns out to be very fast in practice. Alternatively, we could

#### Docker Compose

    this.replacements = escaperMap.getReplacementArray();
    this.replacementsLength = replacements.length;
    if (safeMax < safeMin) {
      // If the safe range is empty, set the range limits to opposite extremes
      // to ensure the first test of either value will (almost certainly) fail.
      safeMax = Character.MIN_VALUE;
      safeMin = Character.MAX_VALUE;
    }
    this.safeMin = safeMin;

    title: Why I'm Leaving Flask
  - author: Mike Moritz
    author_link: https://medium.com/@mike.p.moritz
    link: https://medium.com/@mike.p.moritz/using-docker-compose-to-deploy-a-lightweight-python-rest-api-with-a-job-queue-37e6072a209b
    title: Using Docker Compose to deploy a lightweight Python REST API with a job queue
  - author: '@euri10'
    author_link: https://gitlab.com/euri10
    link: https://gitlab.com/euri10/fastapi_cheatsheet

### Full Stack FastAPI PostgreSQL - Özellikler

* Full **Docker** entegrasyonu (Docker based).
* Docker Swarm Mode ile deployment.
* **Docker Compose** entegrasyonu ve lokal geliştirme için optimizasyon.
* Uvicorn ve Gunicorn ile **Production ready** Python web server'ı.

### 全栈 FastAPI + PostgreSQL - 功能

* 完整的 **Docker** 集成（基于 Docker）
* Docker Swarm 开发模式
* **Docker Compose** 本地开发集成与优化
* **生产可用**的 Python 网络服务器，使用 Uvicorn 或 Gunicorn
* Python <a href="https://github.com/tiangolo/fastapi" class="external-link" target="_blank">**FastAPI**</a> 后端：

### Beispieltools zur Ausführung beim Hochfahren

Einige Beispiele für Tools, die diese Aufgabe übernehmen können, sind:

* Docker
* Kubernetes
* Docker Compose
* Docker im Schwarm-Modus
* Systemd
* Supervisor
* Es wird intern von einem Cloud-Anbieter im Rahmen seiner Dienste verwaltet
* Andere ...

In den nächsten Kapiteln werde ich Ihnen konkretere Beispiele geben.