Stopwatch s = Stopwatch.createStarted();
      // here is where you would do something
      total += s.elapsed(NANOSECONDS);
    }
    return total;
  }

  @Benchmark
  long manual(int reps) {
    long total = 0;
    for (int i = 0; i < reps; i++) {
      long start = System.nanoTime();
      // here is where you would do something
      total += (System.nanoTime() - start);
    }
    return total;
  }

      Stopwatch s = Stopwatch.createStarted();
      // here is where you would do something
      total += s.elapsed(NANOSECONDS);
    }
    return total;
  }

  @Benchmark
  long manual(int reps) {
    long total = 0;
    for (int i = 0; i < reps; i++) {
      long start = System.nanoTime();
      // here is where you would do something
      total += (System.nanoTime() - start);
    }
    return total;
  }

            "age": "70",
            "tags": ["plumbus", "citadel"],
            "with": "something",
        },
    )
    assert response.status_code == 200, response.text
    assert response.json() == {
        "username": "Rick",
        "lastname": "Sanchez",
        "age": 70,
        "tags": ["plumbus", "citadel"],
        "with": "something",
    }


def test_defaults():

### Async Context Manager

If you check, the function is decorated with an `@asynccontextmanager`.

That converts the function into something called an "**async context manager**".

{* ../../docs_src/events/tutorial003.py hl[1,13] *}

A **context manager** in Python is something that you can use in a `with` statement, for example, `open()` can be used as a context manager:

```Python
with open("file.txt") as file:

    return suite;
  }

  private static final String STRING = ASCII + I18N;
  private static final String LINES = "foo\nbar\r\nbaz\rsomething";
  private static final ImmutableList<String> SPLIT_LINES =
      ImmutableList.of("foo", "bar", "baz", "something");

  private TestCharSource source;

  @Override
  public void setUp() {
    source = new TestCharSource(STRING);
  }

# JSON Compatible Encoder

There are some cases where you might need to convert a data type (like a Pydantic model) to something compatible with JSON (like a `dict`, `list`, etc).

For example, if you need to store it in a database.

For that, **FastAPI** provides a `jsonable_encoder()` function.

## Using the `jsonable_encoder`

Let's imagine that you have a database `fake_db` that only receives JSON compatible data.

name: Regression
description: Report a problem about something that used to work
labels: [ "a:regression", "to-triage" ]
assignees: [ ]
body:
  - type: markdown
    attributes:
      value: |
        Please use our bug report template to report problems with something that has never worked.
        Regressions reports are greatly appreciated during our RC phase and before a final release.
  - type: textarea
    id: current-behavior
    attributes:

Most of these ideas would be more or less **independent**, and in most cases you should only need to study them if they apply directly to **your project**.

If something seems interesting and useful to your project, go ahead and check it, but otherwise, you might probably just skip them.

/// tip

В Python "**вызываемый**" - это все, что Python может "вызвать", как функцию.

Так, если у вас есть объект `something` (который может _не_ быть функцией) и вы можете "вызвать" его (выполнить) как:

```Python
something()
```

или

```Python
something(some_argument, some_keyword_argument="foo")
```

в таком случае он является "вызываемым".

## Классы как зависимости

Asynchronous code just means that the language 💬 has a way to tell the computer / program 🤖 that at some point in the code, it 🤖 will have to wait for *something else* to finish somewhere else. Let's say that *something else* is called "slow-file" 📝.

So, during that time, the computer can go and do some other work, while "slow-file" 📝 finishes.