@Timeout(value = 1, unit = TimeUnit.SECONDS) // Very short timeout
    void testBroadcastTimeout() {
        // Configure for broadcast-only resolution with very short timeout
        when(mockConfig.getResolveOrder()).thenReturn(Arrays.asList(ResolverType.RESOLVER_BCAST));
        when(mockConfig.getNetbiosSoTimeout()).thenReturn(50); // Very short
        when(mockConfig.getNetbiosRetryCount()).thenReturn(1);

That should make more sense now. ✨

All that is what powers FastAPI (through Starlette) and what makes it have such an impressive performance.

## Very Technical Details { #very-technical-details }

/// warning

You can probably skip this.

These are very technical details of how **FastAPI** works underneath.

They are, more or less, at opposite ends, complementing each other.

Requests has a very simple and intuitive design, it's very easy to use, with sensible defaults. But at the same time, it's very powerful and customizable.

That's why, as said in the official website:

> Requests is one of the most downloaded Python packages of all time

The way you use it is very simple. For example, to do a `GET` request, you would write:

```Python

 * cases the consuming thread must call [close] when it has finished reading the response
 * body.
 *
 * ### The response body can be consumed only once.
 *
 * This class may be used to stream very large responses. For example, it is possible to use this
 * class to read a response that is larger than the entire memory allocated to the current process.

   */
  @IgnoreJRERequirement // Users will use this only if they're already using streams.
  public static ImmutableLongArray copyOf(LongStream stream) {
    // Note this uses very different growth behavior from copyOf(Iterable) and the builder.
    long[] array = stream.toArray();
    return (array.length == 0) ? EMPTY : new ImmutableLongArray(array);
  }

  /**

   *
   * @since 22.0 (but only since 33.4.0 in the Android flavor)
   */
  public static ImmutableIntArray copyOf(IntStream stream) {
    // Note this uses very different growth behavior from copyOf(Iterable) and the builder.
    int[] array = stream.toArray();
    return (array.length == 0) ? EMPTY : new ImmutableIntArray(array);
  }

  /**

        value = "${spaces}";
        assertEquals("   ", ResourceUtil.resolve(value));

        // Test long property name
        System.setProperty("very.long.property.name.with.many.dots", "long");
        value = "${very.long.property.name.with.many.dots}";
        assertEquals("long", ResourceUtil.resolve(value));

        // Test multiple occurrences of same variable

///

### Create the `Settings` object { #create-the-settings-object }

Import `BaseSettings` from Pydantic and create a sub-class, very much like with a Pydantic model.

The same way as with Pydantic models, you declare class attributes with type annotations, and possibly default values.

        assertEquals(SmbComTransaction.NET_SERVER_ENUM2, subCommand);
    }

    @Test
    @DisplayName("Test with very long domain name")
    void testVeryLongDomainName() {
        String longDomain = "A".repeat(256); // Very long domain name
        netServerEnum2 = new NetServerEnum2(realConfig, longDomain, NetServerEnum2.SV_TYPE_ALL);

        byte[] dst = new byte[2048];

        assertEquals(componentName, exception.getComponentName());
    }

    public void test_longComponentName() {
        // Test with a very long component name
        String longName = "com.example.very.long.package.name.with.many.nested.levels.MyVeryLongComponentNameThatExceedsNormalLength";
        ContainerNotAvailableException exception = new ContainerNotAvailableException(longName, null);