* the interrupting thread doesn't interrupt the _next_ thing to run on this thread.
     *
     * Note: We don't reset the interrupted bit, just wait for it to be set. If this is a thread
     * pool thread, the thread pool will reset it for us. Otherwise, the interrupted bit may have
     * been intended for something else, so don't clear it.
     */

 */
@GwtCompatible
public final class MoreExecutors {
  private MoreExecutors() {}

  /**
   * Converts the given ThreadPoolExecutor into an ExecutorService that exits when the application
   * is complete. It does so by using daemon threads and adding a shutdown hook to wait for their
   * completion.
   *
   * <p>This is mainly for fixed thread pools. See {@link Executors#newFixedThreadPool(int)}.
   *

// UnmarshalJSON - decodes JSON data.
func (a *Args) UnmarshalJSON(data []byte) error {
	// subtype to avoid recursive call to UnmarshalJSON()
	type subArgs Args
	var so subArgs

	if err := json.Unmarshal(data, &so); err != nil {
		return err
	}

	oa := Args(so)
	if oa.URL == nil || oa.URL.String() == "" {
		*a = oa
		return nil
	}

	*a = oa
	return nil
}

// Opa - implements opa policy agent calls.

RUN ln -sf /usr/lib/python3.12 /usr/lib/tf_python

# Link the compat driver to the location if available.
RUN if [ -e "/usr/local/cuda/compat/libcuda.so.1" ]; then ln -s /usr/local/cuda/compat/libcuda.so.1 /usr/lib/x86_64-linux-gnu/libcuda.so.1; fi

# Install various tools.
# - bats: bash unit testing framework
# - bazelisk: always use the correct bazel version
# - buildifier: clean bazel build deps

      // requested by the user. Do not allow edits so we do not go over that limit any further. If
      // the journal rebuild failed, the journal writer will not be active, meaning we will not be
      // able to record the edit, causing file leaks. In both cases, we want to retry the clean up
      // so we can get out of this state!
      cleanupQueue.schedule(cleanupTask)
      return null
    }

    e.execute(intCounter);
    // Our executor hasn't run any tasks yet.
    assertEquals(0, totalCalls.get());
    fakePool.runAll();
    assertEquals(2, totalCalls.get());
    // Queue is empty so no runner should be scheduled.
    assertFalse(fakePool.hasNext());

    // Check that execute can be safely repeated
    e.execute(intCounter);
    e.execute(intCounter);
    e.execute(intCounter);

* „Python“ auswählen.
* Den Debugger mit der Option „`Python: Current File (Integrated Terminal)`“ ausführen.

Der Server wird dann mit Ihrem **FastAPI**-Code gestartet, an Ihren Haltepunkten angehalten, usw.

So könnte es aussehen:

<img src="/img/tutorial/debugging/image01.png">

---

Wenn Sie Pycharm verwenden, können Sie:

* Das Menü „Run“ öffnen.
* Die Option „Debug ...“ auswählen.

# Tag definitions can come from the .hgtags file stored in
# any head of any branch, and the server protocol does not
# expose the tags directly. However, the protocol does expose
# the hashes of all the branch heads, so we can use a hash of
# all those branch names and heads as a conservative snapshot
# of the entire remote repo state, and use that as the tag sum.
# Any change on the server then invalidates the tag sum,

{* ../../docs_src/path_params/tutorial001_py39.py hl[6:7] *}

The value of the path parameter `item_id` will be passed to your function as the argument `item_id`.

So, if you run this example and go to <a href="http://127.0.0.1:8000/items/foo" class="external-link" target="_blank">http://127.0.0.1:8000/items/foo</a>, you will see a response of:

```JSON
{"item_id":"foo"}
```

///

`response_model` receives the same type you would declare for a Pydantic model field, so, it can be a Pydantic model, but it can also be, e.g. a `list` of Pydantic models, like `List[Item]`.