* We don't *need* to use reflection to access Optional: It's available on all JDKs we
         * support, and Android code won't get this far, anyway, because ProcessHandle is
         * unavailable. But given how much other reflection we're using, we might as well use it
         * here, too, so that we don't need to also suppress an AndroidApiChecker error.
         */

   *
   * <p><i>Performance notes:</i> while the cartesian product of lists of size {@code m, n, p} is a
   * list of size {@code m x n x p}, its actual memory consumption is much smaller. When the
   * cartesian product is constructed, the input lists are merely copied. Only as the resulting list
   * is iterated are the individual lists created, and these are not retained after iteration.
   *

First of all, be nice. 😊

You probably are super nice if you were added to the team, but it's worth mentioning it. 🤓

### When Things are Difficult

When things are great, everything is easier, so that doesn't need much instructions. But when things are difficult, here are some guidelines.

            //we're making an assumption that all <pre> elements contain java code
            //this should mostly be true :)
            //if it isn't true then the syntax highlighting won't spoil the view too much anyway
            newElement.setAttribute("language", "java");
            nodes.push(newElement);
            return true;
        }

        @Override
        public void onText(String text) {

   * to reduce cache contention on most processors. Padding is
   * overkill for most Atomics because they are usually irregularly
   * scattered in memory and thus don't interfere much with each
   * other. But Atomic objects residing in arrays will tend to be
   * placed adjacent to each other, and so will most often share
   * cache lines (with a huge negative performance impact) without
   * this precaution.

///

### 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.

    checkState(boxedBoolean.booleanValue(), "", s);
  }

  @J2ktIncompatible
  @GwtIncompatible // NullPointerTester
  public void testNullPointers() {
    /*
     * Don't bother testing: Preconditions defines a bunch of methods that accept a template (or
     * even entire message) that simultaneously:
     *
     * - _shouldn't_ be null, so we don't annotate it with @Nullable
     *

    assertThat((long) arraysDim1 * arraysDim2).isNotEqualTo((long) (arraysDim1 * arraysDim2));

    char[][] arrays = new char[arraysDim1][];
    // it's shared to avoid using too much memory in tests
    char[] sharedArray = new char[arraysDim2];
    Arrays.fill(arrays, sharedArray);

    try {
      Chars.concat(arrays);
      fail();
    } catch (IllegalArgumentException expected) {

And we can add a list of `dependencies` that will be added to all the *path operations* in the router and will be executed/solved for each request made to them.

/// tip

Note that, much like [dependencies in *path operation decorators*](dependencies/dependencies-in-path-operation-decorators.md){.internal-link target=_blank}, no value will be passed to your *path operation function*.

///

FastAPI does several things internally with Pydantic to make sure that those same rules of class inheritance are not used for the returned data filtering, otherwise you could end up returning much more data than what you expected.

This way, you can get the best of both worlds: type annotations with **tooling support** and **data filtering**.

## See it in the docs