///

Mit dem Parameter `operation_id` können Sie die OpenAPI `operationId` festlegen, die in Ihrer *Pfadoperation* verwendet werden soll.

Sie müssten sicherstellen, dass sie für jede Operation eindeutig ist.

```Python hl_lines="6"
{!../../docs_src/path_operation_advanced_configuration/tutorial001.py!}
```

### Verwendung des Namens der *Pfadoperation-Funktion* als operationId

  }

  final Set<K> unmodifiableKeySet() {
    return new AbstractSet<K>() {
      @Override
      public UnmodifiableIterator<K> iterator() {
        Iterator<Entry<K, V>> entryIterator = backingMap.entrySet().iterator();

        return new UnmodifiableIterator<K>() {
          @Override
          public boolean hasNext() {
            return entryIterator.hasNext();
          }

## 🗄 ➕

🕐❔ 👆 📣 *➡ 🛠️* 👆 🈸, **FastAPI** 🔁 🏗 🔗 🗃 🔃 👈 *➡ 🛠️* 🔌 🗄 🔗.

/// note | "📡 ℹ"

🗄 🔧 ⚫️ 🤙 <a href="https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.3.md#operation-object" class="external-link" target="_blank">🛠️ 🎚</a>.

///

⚫️ ✔️ 🌐 ℹ 🔃 *➡ 🛠️* &amp; ⚙️ 🏗 🏧 🧾.

⚫️ 🔌 `tags`, `parameters`, `requestBody`, `responses`, ♒️.

* **Validation automatique** même pour les paramètres de *path operation* définis dans les dépendances.
* Supporte les systèmes d'authentification d'utilisateurs complexes, les **connexions de base de données**, etc.
* **Aucun compromis** avec les bases de données, les frontends, etc. Mais une intégration facile avec n'importe lequel d'entre eux.

    *   Added a new `rerandomize_each_iteration` argument for the `tf.data.Dataset.random()` operation, which controls whether the sequence of generated random numbers should be re-randomized every epoch or not (the default behavior). If `seed` is set and `rerandomize_each_iteration=True`, the `random()` operation will produce a different (deterministic) sequence of numbers every epoch.

    @Override
    public int[] call() throws Exception {
      int iterations = 100000;
      int nKeys = keys.size();
      int[] deltas = new int[nKeys];
      Operation[] operations = Operation.values();
      for (int i = 0; i < iterations; i++) {
        int keyIndex = random.nextInt(nKeys);
        String key = keys.get(keyIndex);
        Operation op = operations[random.nextInt(operations.length)];
        switch (op) {

        @Override
        protected Set<Entry<K, V>> delegate() {
          return entries;
        }

        @Override
        public Iterator<Entry<K, V>> iterator() {
          return UnmodifiableEntry.transformEntries(super.iterator());
        }

        @Override
        public Object[] toArray() {
          /*

      }
      return result.intValue();
    }

    @Override
    public UnmodifiableIterator<C> iterator() {
      return new AbstractIterator<C>() {
        final Iterator<Range<C>> rangeItr = ranges.iterator();
        Iterator<C> elemItr = emptyIterator();

        @Override
        @CheckForNull
        protected C computeNext() {
          while (!elemItr.hasNext()) {

   *
   * @throws UnsupportedOperationException if this range set does not support the {@code add}
   *     operation
   */
  void add(Range<C> range);

  /**
   * Removes the specified range from this {@code RangeSet} (optional operation). After this
   * operation, if {@code range.contains(c)}, {@code this.contains(c)} will return {@code false}.
   *
   * <p>If {@code range} is empty, this is a no-op.

  }

  @Override
  Iterator<Entry<E>> entryIterator() {
    // AbstractIterator makes this fairly clean, but it doesn't support remove(). To support
    // remove(), we create an AbstractIterator, and then use ForwardingIterator to delegate to it.
    Iterator<Entry<E>> readOnlyIterator =
        new AbstractIterator<Entry<E>>() {
          private final Iterator<Map.Entry<E, AtomicInteger>> mapEntries =