echo "Running container(s) found" && \
            docker stop $running_containers;
          fi
          docker container prune -f
      - name: Clean repository
        shell: bash
        run: find /home/ubuntu/actions-runner/_work/tensorflow/tensorflow/. -name . -o -prune -exec sudo rm -rf -- {} + || true
      - name: Checkout repository
        uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0

        Collections.addAll(fieldList, item1.getFields());
        for (final String field : item2.getFields()) {
            if (!fieldList.contains(field)) {
                fieldList.add(field);
            }
        }
        mergedItem.fields = fieldList.toArray(new String[fieldList.size()]);

        try {
            var f = target.getClass().getDeclaredField(name);
            f.setAccessible(true);
            return f.get(target);
        } catch (Exception e) {
            fail("access field " + name, e);
            return null;
        }
    }

    private static int invokeProtectedInt(Object target, String name, Object... params) {
        try {
            var cls = target.getClass();

                    throw new PACDecodingException("Decryption failed " + serverKey.getKeyType(), e);
                }
                break;
            default:
                throw new PACDecodingException("Unrecognized field " + tagged.getTagNo());
            }
        }

    }

    /**
     * Returns the user principal name from the ticket.
     *
     * @return the user principal name
     */

{* ../../docs_src/dataclasses_/tutorial003_py310.py hl[1,4,7:10,13:16,22:24,27] *}

1. Wir importieren `field` weiterhin von Standard-`dataclasses`.

2. `pydantic.dataclasses` ist ein direkter Ersatz für `dataclasses`.

3. Die Datenklasse `Author` enthält eine Liste von `Item`-Datenklassen.

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

{* ../../docs_src/dataclasses_/tutorial003_py310.py hl[1,4,7:10,13:16,22:24,27] *}

1. We still import `field` from standard `dataclasses`.

2. `pydantic.dataclasses` is a drop-in replacement for `dataclasses`.

3. The `Author` dataclass includes a list of `Item` dataclasses.

...без додавання обов’язкового параметра `needy`, Ви побачите помилку:

```JSON
{
  "detail": [
    {
      "type": "missing",
      "loc": [
        "query",
        "needy"
      ],
      "msg": "Field required",
      "input": null
    }
  ]
}
```

Оскільки `needy` є обов’язковим параметром, вам потрібно вказати його в URL:

```
http://127.0.0.1:8000/items/foo-item?needy=sooooneedy
```

    writing it has test supersource but no prod supersource.

    GWT happens to use the prod .gwt.xml, so it looks for no supersource for
    tests, either. This causes it to fail to find AtomicLongMapTest.

    Our workaround is to tell GWT that util.concurrent and all other packages
    have prod supersource, even if they have none. GWT is happy to ignore us
    when we specify a nonexistent path.

            }
            return URI.create(url);
        }
        return null;
    }

    /**
     * Adds a field extraction rule with pruning option.
     *
     * @param name the field name
     * @param xpath the XPath expression for extraction
     * @param isPruned whether the extracted content should be pruned
     */

import java.util.Collections;
import java.util.List;
import java.util.Queue;
import java.util.concurrent.Executor;
import java.util.logging.Level;

/**
 * A list of listeners for implementing a concurrency friendly observable object.
 *
 * <p>Listeners are registered once via {@link #addListener} and then may be invoked by {@linkplain
 * #enqueue enqueueing} and then {@linkplain #dispatch dispatching} events.
 *