Sonra, kullanılabilir geçerli değerler olacak sabit değerli class attribute'ları oluşturun:

{* ../../docs_src/path_params/tutorial005_py310.py hl[1,6:9] *}

/// tip | İpucu

Merak ediyorsanız: "AlexNet", "ResNet" ve "LeNet", Makine Öğrenmesi <dfn title="Teknik olarak, Derin Öğrenme model mimarileri">modelleri</dfn>nin sadece isimleridir.

///

### Bir *Path Parameter* Tanımlayalım { #declare-a-path-parameter }

Luego crea atributos de clase con valores fijos, que serán los valores válidos disponibles:

{* ../../docs_src/path_params/tutorial005_py310.py hl[1,6:9] *}

/// tip | Consejo

Si te estás preguntando, "AlexNet", "ResNet" y "LeNet" son solo nombres de <dfn title="Técnicamente, arquitecturas de modelos de Deep Learning">modelos</dfn> de Machine Learning.

///

### Declarar un *path parameter* { #declare-a-path-parameter }

Then create class attributes with fixed values, which will be the available valid values:

{* ../../docs_src/path_params/tutorial005_py310.py hl[1,6:9] *}

/// tip

If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <dfn title="Technically, Deep Learning model architectures">models</dfn>.

///

### Declare a *path parameter* { #declare-a-path-parameter }

  }

  private static Iterable<@Nullable Object> iterable(
      @Nullable Object first, @Nullable Object second, @Nullable Object[] rest) {
    checkNotNull(rest);
    return new AbstractList<@Nullable Object>() {
      @Override
      public int size() {
        return rest.length + 2;
      }

      @Override
      public @Nullable Object get(int index) {
        switch (index) {
          case 0:

Після цього створіть атрибути класу з фіксованими значеннями, які будуть доступними коректними значеннями:

{* ../../docs_src/path_params/tutorial005_py310.py hl[1,6:9] *}

/// tip | Порада

Якщо вам цікаво, «AlexNet», «ResNet» та «LeNet» — це просто назви моделей машинного навчання <dfn title="Технічно, архітектури моделей глибокого навчання">моделі</dfn>.

///

### Оголосіть *параметр шляху* { #declare-a-path-parameter }

### Read Heroes { #read-heroes }

We can **read** `Hero`s from the database using a `select()`. We can include a `limit` and `offset` to paginate the results.

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[48:55] hl[51:52,54] *}

### Read One Hero { #read-one-hero }

We can **read** a single `Hero`.

operations to be executed and the obtained results that need to be tested.

The YAML tests support various operators defined in the link:/rest-api-spec/src/yamlRestTest/resources/rest-api-spec/test/README.asciidoc[rest-api-spec] and adhere to the link:/rest-api-spec/README.markdown[Elasticsearch REST API JSON specification]
In order to run the YAML tests, the relevant API specification needs

# Broken IPv6
http://[google.com]

# Misc Unicode
http://foo:\uD83D\******@****.***/bar  s:http h:example.com p:/bar u:foo pass:%F0%9F%92%A9

# resolving a relative reference against an unknown scheme results in an error

{* ../../docs_src/path_params/tutorial005_py310.py hl[1,6:9] *}

/// tip | Astuce

Si vous vous demandez, « AlexNet », « ResNet » et « LeNet » sont juste des noms de <dfn title="Techniquement, architectures de modèles de Deep Learning">modèles</dfn> de Machine Learning.

///

### Déclarer un paramètre de chemin { #declare-a-path-parameter }

  @Throws(IOException::class)
  fun loopReader(response: Response) {
    try {
      listener.onOpen(this@RealWebSocket, response)
      while (receivedCloseCode == -1) {
        // This method call results in one or more onRead* methods being called on this thread.
        reader!!.processNextFrame()
      }
    } catch (e: Exception) {
      failWebSocket(e = e)
    } finally {
      finishReader()
    }