*
 * Doing it correctly would require running a Gradle build with the full
 * distribution and extracting the generated api jar from its Gradle user home,
 * slowing down building documentation.
 *
 * All this would be so much simpler if the Kotlin extensions to the Gradle API
 * were generated at build time instead.
 *
 * This is a first step to get the doc to be complete and will be revisited.
 */
@CacheableTask

### Summary { #summary }

I used to say I didn't like history that much... and look at me now giving "tech history" lessons. 😅

title: "import/path: issue title"

body:
  - type: markdown
    attributes:
      value: |
        Thanks for helping us improve! 🙏 Please answer these questions and provide as much information as possible about your problem.

  - type: input
    id: go-version
    attributes:
      label: Go version
      description: |
        What version of Go are you using (`go version`)?

        token_url, data=data, verify=False,
        allow_redirects=False, auth=(client_id, client_secret))

    print('body: ' + id_token_response.text)

    # we can now use the id_token as much as we want to access protected resources.
    tokens = json.loads(id_token_response.text)
    id_token = tokens['id_token']

    response = sts_client.assume_role_with_web_identity(

		// Unlock the 1st lock; ref=1 after this line
		nsLk.unlock("volume", "path", false)

		// Taking another lockMapMutex here allows queuing up additional lockers. This should
		// not be required but makes reproduction much easier.
		nsLk.lockMapMutex.Lock()

		// lk3 blocks.
		lk3ch := make(chan bool)
		go func() {
			lk3ch <- nsLk.lock(ctx, "volume", "path", "source", "opsID", false, 0)
		}()

		// lk4, blocks.

 * arbitrary Charset.
 *
 * <p>This is an alternative to copying the data to an {@code OutputStream} via a {@code Writer},
 * which is necessarily blocking. By implementing an {@code InputStream} it allows consumers to
 * "pull" as much data as they can handle, which is more convenient when dealing with flow
 * controlled, async APIs.
 *
 * @author Chris Nokleberg
 */
@J2ktIncompatible
@GwtIncompatible

Having the return model ensure that a value is always available and always `int` (not `None`) is very useful for the API clients, they can write much simpler code having this certainty.

Also, **automatically generated clients** will have simpler interfaces, so that the developers communicating with your API can have a much better time working with your API. 😎

///

            "2000-10-29 to 2000-10-30", // A date right around daylight savings time.
            "2000-06-01 to 2000-06-02"  // A date fully in one time zone. Should be much faster than above.
        }
    )
    public String range;

    @Param({ "java time", "es" })
    public String rounder;

    @Param({ "UTC", "America/New_York" })
    public String zone;

 * </p>
 * <p>
 * Wise voices have suggested that maybe aggregators shouldn't be bound to the ordinary
 * lifecycle at all, in which case we wouldn't be needing this class at all ( and
 * ProjectBuildList.getByTaskSegments). Or maybe they should be introduced in the calculation
 * of the execution plan instead, which seems much nicer.
 * </p>
 * <p>

 *       does it offer a way to batch multiple events from a single producer together.
 *   <li>It doesn't support backpressure and other features needed for resilience.
 *   <li>It doesn't provide much control of threading.
 *   <li>It doesn't offer much monitoring.
 *   <li>It doesn't propagate exceptions, so apps don't have a way to react to them.
 *   <li>It doesn't interoperate well with RxJava, coroutines, and other more commonly used