@Test
    @DisplayName("MonotonicClock singleton instance should always return the same instance")
    void testSingletonInstance() {
        MonotonicClock clock1 = MonotonicClock.get();
        MonotonicClock clock2 = MonotonicClock.get();

        assertSame(clock1, clock2, "Multiple calls to get() should return the same instance");
    }

    @Test
    @DisplayName("MonotonicClock should always use UTC timezone")

query_extractor --> query_or_cookie_extractor --> read_query
```

## Using the same dependency multiple times { #using-the-same-dependency-multiple-times }

If one of your dependencies is declared multiple times for the same *path operation*, for example, multiple dependencies have a common sub-dependency, **FastAPI** will know to call that sub-dependency only once per request.

  }

  @Test
  fun testNoUncompress() {
    val response = response("https://httpbin.org/brotli", "XXXX".encodeUtf8())

    val same = brotliInterceptor.decompress(response)

    val responseString = same.body.string()
    assertThat(responseString).isEqualTo("XXXX")
  }

  @Test
  fun testFailsUncompress() {
    val response =

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

You might notice that to create an instance of a Python class, you use that same syntax.

For example:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

In this case, `fluffy` is an instance of the class `Cat`.

And to create `fluffy`, you are "calling" `Cat`.

You should never save plaintext passwords, so, we'll use the (fake) password hashing system.

If the passwords don't match, we return the same error.

#### Password hashing { #password-hashing }

"Hashing" means: converting some content (a password in this case) into a sequence of bytes (just a string) that looks like gibberish.

    * So, by using FastAPI you are saving development time, bugs, lines of code, and you would probably get the same performance (or better) you would if you didn't use it (as you would have to implement it all in your code).

After that, all of the processing logic is the same.

But because of our changes in `GzipRequest.body`, the request body will be automatically decompressed when it is loaded by **FastAPI** when needed.

## Accessing the request body in an exception handler { #accessing-the-request-body-in-an-exception-handler }

/// tip

The parameter `name` is defined as `Optional[str]`, but it is **not optional**, you cannot call the function without the parameter:

```Python
say_hi()  # Oh, no, this throws an error! 😱
```

The `name` parameter is **still required** (not *optional*) because it doesn't have a default value. Still, `name` accepts `None` as the value:

```Python
say_hi(name=None)  # This works, None is valid 🎉
```

* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.

///

### Pydantic v1 and v2 on the same app { #pydantic-v1-and-v2-on-the-same-app }

It's **not supported** by Pydantic to have a model of Pydantic v2 with its own fields defined as Pydantic v1 models or vice versa.

```mermaid
graph TB
    subgraph "❌ Not Supported"