Flask is a "microframework", it doesn't include database integrations nor many of the things that come by default in Django.

This simplicity and flexibility allow doing things like using NoSQL databases as the main data storage system.

As it is very simple, it's relatively intuitive to learn, although the documentation gets somewhat technical at some points.

     */
    @Test
    public void testErrorMessage_ja() throws Exception {
        // ## Arrange ##
        Locale.setDefault(Locale.JAPANESE);
        final SQLException sqlException = new SQLException("some reason", "fooState", 7650);
        final SQLException sqlException2 = new SQLException("hoge reason", "barState", 7660);
        final SQLException sqlException3 = new SQLException("fuga reason", "bazState", 7670);

They have different levels of permissions and [specific instructions](./management-tasks.md){.internal-link target=_blank}.

Some of the tasks they can perform include:

* Adding labels to PRs.
* Editing PR titles.
* Adding commits on top of PRs to tweak them.
* Mark answers in GitHub Discussions questions, etc.
* Merge some specific types of PRs.

```

...this would work:

```JSON
{
    "item_id": "foo-item",
    "needy": "sooooneedy"
}
```

And of course, you can define some parameters as required, some as having a default value, and some entirely optional:

//// tab | Python 3.10+

```Python hl_lines="8"
{!> ../../docs_src/query_params/tutorial006_py310.py!}
```

////

//// tab | Python 3.8+

issue if there is one) requesting the feature and describing specific use cases
for it.

If the feature has merit, it will go through a thorough process of API design
and review. Any code should come after this.

[APIs]: https://en.wikipedia.org/wiki/Application_programming_interface
[issue]: https://github.com/google/guava/issues

Pull requests
-------------

                "price": 0.2,
                "description": "Some bar",
                "tax": "5.4",
            }
        },
    )
    assert response.status_code == 200
    assert response.json() == {
        "item_id": 6,
        "item": {
            "name": "Bar",
            "price": 0.2,
            "description": "Some bar",
            "tax": 5.4,
        },
    }

                "price": 0.2,
                "description": "Some bar",
                "tax": "5.4",
            }
        },
    )
    assert response.status_code == 200
    assert response.json() == {
        "item_id": 6,
        "item": {
            "name": "Bar",
            "price": 0.2,
            "description": "Some bar",
            "tax": 5.4,
        },
    }


@needs_py39

       *
       * TODO(b/112550045): Allocating a single, cheaper listener is (I think) only an optimization.
       * If we make some other optimizations, this one will no longer be necessary. The optimization
       * could actually hurt in some cases, as it forces us to keep all inputs in memory until the
       * final input completes.
       */
      @RetainedLocalRef

# Configure Swagger UI

You can configure some extra <a href="https://swagger.io/docs/open-source-tools/swagger-ui/usage/configuration/" class="external-link" target="_blank">Swagger UI parameters</a>.

To configure them, pass the `swagger_ui_parameters` argument when creating the `FastAPI()` app object or to the `get_swagger_ui_html()` function.

`swagger_ui_parameters` receives a dictionary with the configurations passed to Swagger UI directly.

import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collection;
import java.util.Collections;

/**
 * An {@link ClusterException} is a data structure that allows for some code to "throw multiple
 * exceptions", or something close to it. The prototypical code that calls for this class is
 * presented below:
 *
 * <pre>
 * void runManyThings({@literal List<ThingToRun>} thingsToRun) {