For example, you could declare that something could be a `str` or `None`:

```python
from typing import Union


def say_hi(name: Union[str, None]):
        print(f"Hi {name}!")
```

`typing` also has a shortcut to declare that something could be `None`, with `Optional`.

      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;
  }

    model_config = {
        "json_schema_extra": {
            "x-something-internal": {"level": 4},
        }
    }


@app.get("/foo", response_model=Item)
def foo():
    return {"name": "Foo item"}


client = TestClient(app)


item_schema = {
    "title": "Item",
    "required": ["name"],
    "type": "object",
    "x-something-internal": {
        "level": 4,
    },
    "properties": {

      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;
  }

        String details = testableJob.testFormatDetails(events);

        assertNotNull(details);
        assertTrue(details.contains("Total: 1 event(s)"));
        assertTrue(details.contains("ERROR"));
        assertTrue(details.contains("org.codelibs.fess.TestClass"));
        assertTrue(details.contains("Something went wrong"));
    }

    @Test

            "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():

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_py310.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:

# JSON Compatible Encoder { #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` { #using-the-jsonable-encoder }

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.

A "**callable**" in Python is anything that Python can "call" like a function.

So, if you have an object `something` (that might _not_ be a function) and you can "call" it (execute it) like:

```Python
something()
```

or

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

then it is a "callable".

## Classes as dependencies { #classes-as-dependencies_1 }