// Required.
  optional PriorityLevelConfigurationReference priorityLevelConfiguration = 1;

  // `matchingPrecedence` is used to choose among the FlowSchemas that match a given request. The chosen
  // FlowSchema is among those with the numerically lowest (which we take to be logically highest)
  // MatchingPrecedence.  Each MatchingPrecedence value must be ranged in [1,10000].

     *
     * <ul>
     *   <li>For an empty list, it is 1 (base case).
     *   <li>When r numbers are added to a list of n-r elements, the number of permutations is
     *       increased by a factor of (n choose r).
     * </ul>
     */
    private static <E> int calculateSize(
        List<E> sortedInputList, Comparator<? super E> comparator) {
      int permutations = 1;
      int n = 1;
      int r = 1;

And then, you could give that JWT token to a user (or bot), and they could use it to perform those actions (drive the car, or edit the blog post) without even needing to have an account, just with the JWT token your API generated for that.

Using these ideas, JWT can be used for way more sophisticated scenarios.

In those cases, several of those entities could have the same ID, let's say `foo` (a user `foo`, a car `foo`, and a blog post `foo`).

       * run the supermethod as usual.
       *
       * TODO: b/292578973: Use @AndroidIncompatible if we change our system to keep the methods in
       * place but to have the test runner skip them. However, note that if we choose to *both*
       * strip the methods *and* have the test runner not run them (for some unusual cases in which
       * we don't run the stripping test for technical reasons), then we'd be back to the problem

```console
$ pip install "fastapi[all]"
---> 100%
```

</div>

!!! info
    In Pydantic v1 it came included with the main package. Now it is distributed as this independent package so that you can choose to install it or not if you don't need that functionality.

### Create the `Settings` object

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

  // Required.
  optional PriorityLevelConfigurationReference priorityLevelConfiguration = 1;

  // `matchingPrecedence` is used to choose among the FlowSchemas that match a given request. The chosen
  // FlowSchema is among those with the numerically lowest (which we take to be logically highest)
  // MatchingPrecedence.  Each MatchingPrecedence value must be ranged in [1,10000].

  // Required.
  optional PriorityLevelConfigurationReference priorityLevelConfiguration = 1;

  // `matchingPrecedence` is used to choose among the FlowSchemas that match a given request. The chosen
  // FlowSchema is among those with the numerically lowest (which we take to be logically highest)
  // MatchingPrecedence.  Each MatchingPrecedence value must be ranged in [1,10000].

     *
     * <ul>
     *   <li>For an empty list, it is 1 (base case).
     *   <li>When r numbers are added to a list of n-r elements, the number of permutations is
     *       increased by a factor of (n choose r).
     * </ul>
     */
    private static <E> int calculateSize(
        List<E> sortedInputList, Comparator<? super E> comparator) {
      int permutations = 1;
      int n = 1;
      int r = 1;

As Python advances, **newer versions** come with improved support for these type annotations and in many cases you won't even need to import and use the `typing` module to declare the type annotations.

If you can choose a more recent version of Python for your project, you will be able to take advantage of that extra simplicity.

In all the docs there are examples compatible with each version of Python (when there's a difference).

   * iterated are the individual lists created, and these are not retained after iteration.
   *
   * @param sets the sets to choose elements from, in the order that the elements chosen from those
   *     sets should appear in the resulting lists
   * @param <B> any common base class shared by all axes (often just {@link Object})