"reminder": {
                    "before": "P3D",
                    "message": "Heads-up: this will be closed in 3 days unless there's new activity."
                }
              },
              "invalid": {
                "delay": 0,
                "message": "This was marked as invalid and will be closed now. If this is an error, please provide additional details."
              },
              "maybe-ai": {

{* ../../docs_src/dependencies/tutorial008c_an_py310.py hl[15:16] *}

In this case, the client will see an *HTTP 500 Internal Server Error* response as it should, given that we are not raising an `HTTPException` or similar, but the server will **not have any logs** or any other indication of what was the error. 😱

 * factory specifies what content should be expected to be read from a source or contained in a sink
 * given the content data that was used to create the source or that was written to the sink.
 *
 * <p>A single {@code SourceSinkFactory} implementation generally corresponds to one specific way of
 * creating a source or sink, such as {@link Files#asByteSource(File)}. Implementations of {@code

 * factory specifies what content should be expected to be read from a source or contained in a sink
 * given the content data that was used to create the source or that was written to the sink.
 *
 * <p>A single {@code SourceSinkFactory} implementation generally corresponds to one specific way of
 * creating a source or sink, such as {@link Files#asByteSource(File)}. Implementations of {@code

 *     .build();
 * Response forceCacheResponse = client.newCall(request).execute();
 * if (forceCacheResponse.code() != 504) {
 *   // The resource was cached! Show it.
 * } else {
 *   // The resource was not cached.
 * }
 * ```
 *
 * This technique works even better in situations where a stale response is better than no response.

#### `lru_cache` Technical Details { #lru-cache-technical-details }

`@lru_cache` modifies the function it decorates to return the same value that was returned the first time, instead of computing it again, executing the code of the function every time.

   * {@code key} while the new value was loading then a removal notification will be sent for the
   * new value.
   *
   * <p>If the cache loader associated with this cache is known not to throw checked exceptions,
   * then prefer {@link #getUnchecked} over this method.
   *
   * @throws ExecutionException if a checked exception was thrown while loading the value. ({@code

   * {@code key} while the new value was loading then a removal notification will be sent for the
   * new value.
   *
   * <p>If the cache loader associated with this cache is known not to throw checked exceptions,
   * then prefer {@link #getUnchecked} over this method.
   *
   * @throws ExecutionException if a checked exception was thrown while loading the value. ({@code

	}

	if retention.Days == nil && retention.Years == nil {
		return fmt.Errorf("either Days or Years must be specified")
	}

	if retention.Days != nil && retention.Years != nil {
		return fmt.Errorf("either Days or Years must be specified, not both")
	}

	//nolint:gocritic
	if retention.Days != nil {
		if *retention.Days == 0 {

{* ../../docs_src/security/tutorial001_an_py310.py hl[12] *}

But that is still not that useful.

Let's make it give us the current user.

## Create a user model { #create-a-user-model }

First, let's create a Pydantic user model.

The same way we use Pydantic to declare bodies, we can use it anywhere else: