get() = withValidityAssertion { descriptor.setter != null }

    override val setter: KtPropertySetterSymbol?
        get() = withValidityAssertion {
            if (!descriptor.isVar) {
                return null
            }

            val setter = descriptor.setter ?: return KtFe10DescDefaultPropertySetterSymbol(descriptor, analysisContext)
            KtFe10DescPropertySetterSymbol(setter, analysisContext)
        }

        val jvmNameFromProperty = property.getJvmNameFromAnnotation(analysisSession.useSiteSession, useSiteTarget)
        if (jvmNameFromProperty != null) {
            return jvmNameFromProperty
        }

        val accessor = if (isSetter) property.setter else property.getter

         * (via generateReflectiveAccessForGetter) and it is called for the private access member lowered to the getter/setter call.
         * If a private property has no getter/setter (the typical situation for simple private properties without explicitly defined
         * getter/setter) then this method is not used at all. Instead

                        backingField?.findAnnotationTypeRef(annotationEntry)
                            ?: getter?.findAnnotationTypeRef(annotationEntry)
                            ?: setter?.findAnnotationTypeRef(annotationEntry)
                    }
                } else null
            }
            else -> null
        }
    }

  AnnotationTarget.FIELD,
  AnnotationTarget.LOCAL_VARIABLE,
  AnnotationTarget.VALUE_PARAMETER,
  AnnotationTarget.CONSTRUCTOR,
  AnnotationTarget.FUNCTION,
  AnnotationTarget.PROPERTY_GETTER,
  AnnotationTarget.PROPERTY_SETTER,
  AnnotationTarget.TYPEALIAS,
)
@RequiresOptIn(level = RequiresOptIn.Level.ERROR)

Specifically, to see Uvicorn, Starlette and FastAPI compared together (among many other tools).

The simpler the problem solved by the tool, the better performance it will get. And most of the benchmarks don't test the additional features provided by the tool.

The hierarchy is like:

* **Uvicorn**: an ASGI server
    * **Starlette**: (uses Uvicorn) a web microframework

not looking for eggs, as it happens; and if I was, I shouldn't
want YOURS:  I don't like them raw.'

  `Well, be off, then!' said the Pigeon in a sulky tone, as it
settled down again into its nest.  Alice crouched down among the
trees as well as she could, for her neck kept getting entangled
among the branches, and every now and then she had to stop and

These **"type hints"** or annotations are a special syntax that allow declaring the <abbr title="for example: str, int, float, bool">type</abbr> of a variable.

By declaring types for your variables, editors and tools can give you better support.

This is just a **quick tutorial / refresher** about Python type hints. It covers only the minimum necessary to use them with **FastAPI**... which is actually very little.

```console
$ hypercorn main:app --worker-class trio
```

</div>

And that will start Hypercorn with your app using Trio as the backend.

Now you can use Trio internally in your app. Or even better, you can use AnyIO, to keep your code compatible with both Trio and asyncio. 🎉

## Deployment Concepts

## Storage usage

The selection of varying data and parity drives has a direct impact on the drive space usage. With storage class, you can optimize for high
redundancy or better drive space utilization.

To get an idea of how various combinations of data and parity drives affect the storage usage, let’s take an example of a 100 MiB file stored