// instead of using an AtomicReferenceFieldUpdater. This reference stores Thread instances
// and DONE/INTERRUPTED - they have a common ancestor of Runnable.
abstract class InterruptibleTask<T extends @Nullable Object>
    extends AtomicReference<@Nullable Runnable> implements Runnable {
  static {
    // Prevent rare disastrous classloading in first call to LockSupport.park.
    // See: https://bugs.openjdk.java.net/browse/JDK-8074773

* Você pode receber metadados do arquivo enviado.
* Ele tem uma <a href="https://docs.python.org/3/glossary.html#term-file-like-object" class="external-link" target="_blank">file-like</a> interface `assíncrona`.

// Copyright (c) 2015-2023 MinIO, Inc.
//
// This file is part of MinIO Object Storage stack
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU Affero General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful

  // Resources with empty groups are located at /api/v1/<APIResourceDiscovery.Resource>
  optional string resource = 1;

  // responseKind describes the group, version, and kind of the serialization schema for the object type this endpoint typically returns.
  // APIs may return other objects types at their discretion, such as error conditions, requests for alternate representations, or other operation specific behavior.

    return object : BaseMatcher<Long?>() {
      override fun describeTo(description: Description?) {
        description!!.appendText("> $value")
      }

      override fun matches(o: Any?): Boolean {
        return (o as Long?)!! > value
      }
    }
  }

  private fun matchesProtocol(protocol: Protocol?): Matcher<Response?> {
    return object : BaseMatcher<Response?>() {

// Graphs are thread-safe when used as directed below.
typedef struct TF_Graph TF_Graph;

// Return a new graph object.
TF_CAPI_EXPORT extern TF_Graph* TF_NewGraph(void);

// Destroy an options object. Graph will be deleted once no more
// TFSession's are referencing it.
TF_CAPI_EXPORT extern void TF_DeleteGraph(TF_Graph*);

         * the andx command will not be written and therefore the
         * response will not read a batched command and therefore
         * the 'received' member of the response object will not
         * be set to true indicating the send and sendTransaction
         * methods that the next part should be sent. This is a
         * very indirect and simple batching control mechanism.
         */

Zum Beispiel deklariert das obige Modell ein JSON "`object`" (oder Python-`dict`) wie dieses:

```JSON
{
    "name": "Foo",
    "description": "An optional description",
    "price": 45.2,
    "tax": 3.5
}
```

Da `description` und `tax` optional sind (mit `None` als Defaultwert), wäre folgendes JSON "`object`" auch gültig:

```JSON
{
    "name": "Foo",
    "price": 45.2
}
```

Por exemplo, o modelo acima declara um JSON "`object`" (ou `dict` no Python) como esse:

```JSON
{
    "name": "Foo",
    "description": "Uma descrição opcional",
    "price": 45.2,
    "tax": 3.5
}
```

...como `description` e `tax` são opcionais (Com um valor padrão de `None`), esse JSON "`object`" também é válido:

```JSON
{
    "name": "Foo",
    "price": 45.2
}
```

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

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

and then we call:

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

we now have a `dict` with the data in the variable `user_dict` (it's a `dict` instead of a Pydantic model object).

And if we call:

```Python
print(user_dict)
```