}

    taskFaker.runTasks()
    assertEvents(
      "take plan 0",
      "plan 0 TCP connecting...",
    )

    taskFaker.advanceUntil(250.ms)
    assertEvents(
      "take plan 1",
      "plan 1 TCP connecting...",
    )

    taskFaker.advanceUntil(500.ms)
    assertEvents(
      "take plan 2",
      "plan 0 cancel",
      "plan 1 cancel",
    )

Instead of that, by being an "asynchronous" system, once finished, the task can wait in line a little bit (some microseconds) for the computer / program to finish whatever it went to do, and then come back to take the results and continue working with them.

But this way we can focus on how the **Dependency Injection** system works.

### Create a dependency, or "dependable"

Let's first focus on the dependency.

It is just a function that can take all the same parameters that a *path operation function* can take:

=== "Python 3.10+"

    ```Python hl_lines="8-9"
    {!> ../../../docs_src/dependencies/tutorial001_an_py310.py!}
    ```

=== "Python 3.9+"

    ```Python hl_lines="8-11"

From the list of deployment concepts from above, using workers would mainly help with the **replication** part, and a little bit with the **restarts**, but you still need to take care of the others:

* **Security - HTTPS**
* **Running on startup**
* ***Restarts***

    git config user.email ******@****.***

#### Import Gradle into IntelliJ

To import Gradle into IntelliJ:
- Open the `build.gradle.kts` file with IntelliJ and choose "Open as Project"
- Make sure "Create separate module per source set" is selected
- Make sure  "Use default gradle wrapper" is selected
- Select a Java 11 VM as "Gradle JVM"
- In the "File already exists" dialogue, choose "Yes" to overwrite

  latest version of some snapshot artifact. If m2 is offline, SCM operations
  cannot succeed; no artifact downloads can take place, regardless of whether
  they are snapshot versions; artifact deployment cannot take place; certain
  types of tests cannot be setup, since the container used to run them cannot be
  reached or started.

		Workload: podToWorkload(pod),
		Netns:    ns,
	}
	netns1 := p.UpsertPodCacheWithNetns(string(pod.UID), wl)
	netnsTaken := p.Take(string(pod.UID))
	if netns1 != netnsTaken {
		t.Fatalf("Expected the original Netns for the same uid, got %p and %p", netns1, ns)
	}
	if nil != p.Take(string(pod.UID)) {
		// expect nil because we already took it
		t.Fatalf("Expected nil Netns for the same uid twice")
	}
}

		w.Header().Set(xhttp.MinIOHealingDrives, strconv.Itoa(result.HealingDrives))
	}
	if !result.Healthy {
		// As a maintenance call we are purposefully asked to be taken
		// down, this is for orchestrators to know if we can safely
		// take this server down, return appropriate error.
		if opts.Maintenance {
			writeResponse(w, http.StatusPreconditionFailed, nil, mimeNone)
		} else {

    repair:
      enabled: true
      hub: ""
      tag: ""

      # Repair controller has 3 modes. Pick which one meets your use cases. Note only one may be used.
      # This defines the action the controller will take when a pod is detected as broken.

      # labelPods will label all pods with <brokenPodLabelKey>=<brokenPodLabelValue>.

# its own file.

on:
  - pr_created
  - commit
  - comment_added

automations:

  # Add a label that indicates how many minutes it will take to review the PR and categorizes it
  estimated_time_to_review:
    if:
      - {{ ('estimated_time_to_review' | isEnabledAutomation(pr)) }}
    run:
      - action: add-label@v1