Wir möchten den `current_user` *nur* erhalten, wenn dieser Benutzer aktiv ist.

Daher erstellen wir eine zusätzliche Abhängigkeit `get_current_active_user`, die wiederum `get_current_user` als Abhängigkeit verwendet.

Beide Abhängigkeiten geben nur dann einen HTTP-Error zurück, wenn der Benutzer nicht existiert oder inaktiv ist.

r||M(n(p.parentNode),t,o,i),i.push(p)}function F(e,t,o,i){o.updateBound=i,A(e).addEventListener('resize',o.updateBound,{passive:!0});var r=n(e);return M(r,'scroll',o.updateBound,o.scrollParents),o.scrollElement=r,o.eventsEnabled=!0,o}function I(){this.state.eventsEnabled||(this.state=F(this.reference,this.options,this.state,this.scheduleUpdate))}function R(e,t){return A(e).removeEventListener('resize',t.updateBound),t.scrollParents.forEach(function(e){e.removeEventListener('scroll',t.updateBound...

   * granted only 100ms ago, then we wait for another 100ms. At this rate, serving 15 fresh permits
   * (i.e. for an acquire(15) request) naturally takes 3 seconds.
   *
   * It is important to realize that such a RateLimiter has a very superficial memory of the past:
   * it only remembers the last request. What if the RateLimiter was unused for a long period of

  }

  TFE_Execute(op_.get(), unwrapped_results.data(), &real_num_outputs, status);
  if (TF_GetCode(status) != TF_OK) {
    cancellation_manager_->StartCancel();
    return;
  }
  unwrapped_results.resize(real_num_outputs);
  outputs->reserve(real_num_outputs);
  for (TFE_TensorHandle* unwrapped_result : unwrapped_results) {
    outputs->emplace_back(unwrapped_result);
  }
}

  DCHECK(tf_results->missing_unused_key_names_data.empty());

  size_t size = results.missing_unused_input_map_keys.size();
  tf_results->missing_unused_key_names.resize(size);
  tf_results->missing_unused_key_indexes.resize(size);

  for (int i = 0; i < size; ++i) {
    TensorId id = results.missing_unused_input_map_keys[i];
    tf_results->missing_unused_key_names_data.emplace_back(id.first);

///

## Validation de données

Si vous allez sur <a href="http://127.0.0.1:8000/items/foo" class="external-link" target="_blank">http://127.0.0.1:8000/items/foo</a>, vous aurez une belle erreur HTTP :

```JSON
{
    "detail": [
        {
            "loc": [
                "path",
                "item_id"
            ],
            "msg": "value is not a valid integer",

     * fit comfortably within a single ethernet packet (1500 bytes) even with framing overhead.
     *
     * For tests this must be big enough to realize real compression on test messages like
     * 'aaaaaaaaaa...'. Our tests check if compression was applied just by looking at the size if
     * the inbound buffer.
     */
    const val DEFAULT_MINIMUM_DEFLATE_SIZE = 1024L

```Python hl_lines="3  5-6"
{
    "name": "Baz",
    "description": None,
    "price": 50.2,
    "tax": 10.5,
    "tags": []
}
```

FastAPI is smart enough (actually, Pydantic is smart enough) to realize that, even though `description`, `tax`, and `tags` have the same values as the defaults, they were set explicitly (instead of taken from the defaults).

So, they will be included in the JSON response.

/// tip

and then take a look at the
[issues with the "contributions welcome" label](https://github.com/tensorflow/tensorflow/labels/stat%3Acontributions%20welcome).
These are issues that we believe are particularly well suited for outside
contributions, often because we probably won't get to them right now. If you
decide to start on an issue, leave a comment so that other people know that

		// or space is needed.
		if s.start > 0 && (s.end == len(s.buf) || s.start > len(s.buf)/2) {
			copy(s.buf, s.buf[s.start:s.end])
			s.end -= s.start
			s.start = 0
		}
		// Is the buffer full? If so, resize.
		if s.end == len(s.buf) {
			// Guarantee no overflow in the multiplication below.
			const maxInt = int(^uint(0) >> 1)
			if len(s.buf) >= s.maxTokenSize || len(s.buf) > maxInt/2 {
				s.setErr(ErrTooLong)