*
 * <p><b>Note:</b> The dispatcher is orthogonal to the subscriber's {@code Executor}. The dispatcher
 * controls the order in which events are dispatched, while the executor controls how (i.e. on which
 * thread) the subscriber is actually called when an event is dispatched to it.
 *
 * @author Colin Decker
 */
abstract class Dispatcher {

  /**
   * Returns a dispatcher that queues events that are posted reentrantly on a thread that is already

Import `SQLModel` and create a database model:

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}

The `Hero` class is very similar to a Pydantic model (in fact, underneath, it actually *is a Pydantic model*).

There are a few differences:

   *
   * <p>Note that, in cases where {@code sizeIfKnown} returns zero, it is <i>possible</i> that bytes
   * are actually available for reading. (For example, some special files may return a size of 0
   * despite actually having content when read.) This means that a source may return {@code true}
   * from {@code isEmpty()} despite having readable content.
   *

      Arrays.fill((short[]) table, (short) 0);
    } else {
      Arrays.fill((int[]) table, 0);
    }
  }

  /**
   * Returns {@code table[index]}, where {@code table} is actually a {@code byte[]}, {@code
   * short[]}, or {@code int[]}. When it is a {@code byte[]} or {@code short[]}, the returned value
   * is unsigned, so the range of possible returned values is 0–255 or 0–65535, respectively.
   */

# ----------------------------------------------------------
#                                                      Mail
#                                                     ------
# Does it send mock mail? (true: no send actually, logging only)
mail.send.mock = false

# SMTP server settings for main: host:port
mail.smtp.server.main.host.and.port = localhost:25

# The prefix of subject to show test environment or not

* Retrieve the stored data.
* Put that data in a Pydantic model.
* Generate a `dict` without default values from the input model (using `exclude_unset`).
    * This way you can update only the values actually set by the user, instead of overriding values already stored with default values in your model.
* Create a copy of the stored model, updating its attributes with the received partial updates (using the `update` parameter).

from fastapi.testclient import TestClient

from docs_src.path_operation_advanced_configuration.tutorial006_py39 import app

client = TestClient(app)


def test_post():
    response = client.post("/items/", content=b"this is actually not validated")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "size": 30,
        "content": {
            "name": "Maaaagic",
            "price": 42,

      E expected = expectedList.get(i);
      E actual = getList().get(i);
      if (expected != actual && (expected == null || !expected.equals(actual))) {
        fail("mismatch at index " + i + ": " + reportContext(expectedList));
      }
    }
  }

  /**
   * Used to delay string formatting until actually required, as it otherwise shows up in the test

    attributes:
      label: Expected Behavior
      description: What did you expect to happen?
    validations:
      required: true

  - type: textarea
    attributes:
      label: Actual Behavior
      description: What actually happened?
    validations:
      required: true

  - type: dropdown
    attributes:
      label: Packages

Do you want to just have a `str`? Or just a `dict`? Or a database class model instance directly? It all works the same way.

You actually don't have users that log in to your application but robots, bots, or other systems, that have just an access token? Again, it all works the same.