object : EventListener() {
        override fun requestHeadersStart(call: Call) {
          try {
            // Cancel call from another thread to avoid reentrance.
            cancelLater(call, 0).join()
          } catch (e: InterruptedException) {
            throw AssertionError()
          }
        }
      }
    client = client.newBuilder().eventListener(listener).build()

binator","disabled","dir","next","childNodes","e","els","find","seed","m","nid","match","groups","newSelector","newContext","exec","getElementById","id","getElementsByTagName","getElementsByClassName","testContext","scope","tokenize","toSelector","join","querySelectorAll","qsaError","removeAttribute","select","keys","cache","key","cacheLength","shift","markFunction","assert","el","createInputPseudo","createButtonPseudo","createDisabledPseudo","isDisabled","createPositionalPseudo","argument","mat...

- Kubeadm: when adding new control plane nodes with "kubeadm join", ensure that the etcd member addition is performed only if a given member URL does not already exist in the list of members. Similarly, on "kubeadm reset" only remove an etcd member if its ID exists. ([#127622](https://github.com/kubernetes/kubernetes/pull/127622),...

```Python
user_in = UserIn(username="john", password="secret", email="john******@****.***")
```

& ⤴️ 👥 🤙:

```Python
user_dict = user_in.dict()
```

👥 🔜 ✔️ `dict` ⏮️ 💽 🔢 `user_dict` (⚫️ `dict` ↩️ Pydantic 🏷 🎚).

& 🚥 👥 🤙:

```Python
print(user_dict)
```

👥 🔜 🤚 🐍 `dict` ⏮️:

```Python
{
    'username': 'john',
    'password': 'secret',

Pydantic models have a `.dict()` method that returns a `dict` with the model's data.

So, if we create a Pydantic object `user_in` like:

```Python
user_in = UserIn(username="john", password="secret", email="john******@****.***")
```

and then we call:

```Python
user_dict = user_in.dict()
```

Los modelos Pydantic tienen un método `.dict()` que devuelve un `dict` con los datos del modelo.

Así que, si creamos un objeto Pydantic `user_in` como:

```Python
user_in = UserIn(username="john", password="secret", email="john******@****.***")
```

y luego llamamos a:

```Python
user_dict = user_in.dict()
```

						} else {
							fv, _ := ref.PrimaryKey.ValueOf(db.Statement.Context, elem)
							db.AddError(ref.ForeignKey.Set(db.Statement.Context, joinValue, fv))
						}
					}
					joins = reflect.Append(joins, joinValue)
				}

				identityMap := map[string]bool{}
				appendToElems := func(v reflect.Value) {
					if _, zero := rel.Field.ValueOf(db.Statement.Context, v); !zero {

Os modelos Pydantic possuem um método `.dict()` que retorna um `dict` com os dados do modelo.

Então, se criarmos um objeto Pydantic `user_in` como:

```Python
user_in = UserIn(username="john", password="secret", email="john******@****.***")
```

e depois chamarmos:

```Python
user_dict = user_in.dict()
```

У Pydantic-моделей есть метод `.dict()`, который возвращает `dict` с данными модели.

Поэтому, если мы создадим Pydantic-объект `user_in` таким способом:

```Python
user_in = UserIn(username="john", password="secret", email="john******@****.***")
```

и затем вызовем:

```Python
user_dict = user_in.dict()
```

Pydantic-Modelle haben eine `.dict()`-Methode, die ein `dict` mit den Daten des Modells zurückgibt.

Wenn wir also ein Pydantic-Objekt `user_in` erstellen, etwa so:

```Python
user_in = UserIn(username="john", password="secret", email="john******@****.***")
```

und wir rufen seine `.dict()`-Methode auf:

```Python
user_dict = user_in.dict()
```