t.Errorf("parseHexUint(%q) = %v, %v; want error %q", tt.in, got, err, tt.wantErr)
			}
		} else {
			if err != nil || got != tt.want {
				t.Errorf("parseHexUint(%q) = %v, %v; want %v", tt.in, got, err, tt.want)
			}
		}
	}

   *
   * @param reference any array of the desired type
   * @param length the length of the new array
   */
  /*
   * The new array contains nulls, even if the old array did not. If we wanted to be accurate, we
   * would declare a return type of `@Nullable T[]`. However, we've decided not to think too hard
   * about arrays for now, as they're a mess. (We previously discussed this in the review of

## Return Type and Data Filtering { #return-type-and-data-filtering }

Let's continue from the previous example. We wanted to **annotate the function with one type**, but we wanted to be able to return from the function something that actually includes **more data**.

## Design { #design }

Then I spent some time designing the developer "API" I wanted to have as a user (as a developer using FastAPI).

I tested several ideas in the most popular Python editors: PyCharm, VS Code, Jedi based editors.

   *
   * @param reference any array of the desired type
   * @param length the length of the new array
   */
  /*
   * The new array contains nulls, even if the old array did not. If we wanted to be accurate, we
   * would declare a return type of `@Nullable T[]`. However, we've decided not to think too hard
   * about arrays for now, as they're a mess. (We previously discussed this in the review of

      return if (!fieldType.isInstance(value)) null else fieldType.cast(value)
    } catch (_: NoSuchFieldException) {
    }

    c = c.superclass
  }

  // Didn't find the field we wanted. As a last gasp attempt,
  // try to find the value on a delegate.
  if (fieldName != "delegate") {
    val delegate = readFieldOrNull(instance, Any::class.java, "delegate")

This decoupling of parts, and being a "microframework" that could be extended to cover exactly what is needed was a key feature that I wanted to keep.

Given the simplicity of Flask, it seemed like a good match for building APIs. The next thing to find was a "Django REST Framework" for Flask.

/// check | Inspired **FastAPI** to

---

"_Honestly, what you've built looks super solid and polished. In many ways, it's what I wanted **Hug** to be - it's really inspiring to see someone build that._"

You can check it at <a href="http://127.0.0.1:9999/api/v1/docs" class="external-link" target="_blank">http://127.0.0.1:9999/api/v1/docs</a>:

<img src="/img/tutorial/behind-a-proxy/image02.png">

Right as we wanted it. ✔️

This is because FastAPI uses this `root_path` to create the default `server` in OpenAPI with the URL provided by `root_path`.

## Additional servers { #additional-servers }

/// warning

---

"_Honestly, what you've built looks super solid and polished. In many ways, it's what I wanted **Hug** to be - it's really inspiring to see someone build that._"