}
			f.Close()
		}

		bs, err := os.ReadFile(goldenFile)
		if err != nil {
			t.Fatalf("opening golden.txt for package %q: %v", fi.Name(), err)
		}
		wanted := strings.Split(string(bs), "\n")
		slices.Sort(wanted)
		for _, feature := range wanted {
			if feature == "" {
				continue
			}
			_, ok := w.features[feature]
			if !ok {
				t.Errorf("package %s: missing feature %q", fi.Name(), feature)
			}

				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

     * when we run AbstractFutureTest itself.
     */

    /*
     * We don't test UnsafeAtomicHelper here, since guava-android doesn't provide a way to use it
     * under the JVM. (We could arrange for one if we really wanted, but that will break once the
     * JDK further restricts access to Unsafe.) But we have coverage under an Android emulator,
     * which uses UnsafeAtomicHelper when it runs AbstractFutureTest itself.
     */

      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._"