// maximum sleep duration between objects to slow down heal operation.
	Sleep   time.Duration `json:"sleep"`
	IOCount int           `json:"iocount"`

	DriveWorkers int `json:"drive_workers"`

	// Cached value from Bitrot field
	cache struct {
		// -1: bitrot enabled, 0: bitrot disabled, > 0: bitrot cycle
		bitrotCycle time.Duration
	}
}

// BitrotScanCycle returns the configured cycle for the scanner healing
// - '-1' for not enabled

  descriptor should declare whether it requires online/offline status.
  This value should be a java.lang.Boolean, so it can implement 3VL
  (three value logic: yes, no, don't-care). The requiresOnline
  field in the mojo descriptor has the following semantics:

  [true] Online status is required for this mojo to function
         correctly.

  [false] <<(Default)>> Either status is acceptable for the mojo to

///

### Pydantic v1 and v2 on the same app { #pydantic-v1-and-v2-on-the-same-app }

It's **not supported** by Pydantic to have a model of Pydantic v2 with its own fields defined as Pydantic v1 models or vice versa.

```mermaid
graph TB
    subgraph "❌ Not Supported"
        direction TB
        subgraph V2["Pydantic v2 Model"]
            V1Field["Pydantic v1 Model"]
        end

        try {
            var f = target.getClass().getDeclaredField(name);
            f.setAccessible(true);
            return f.get(target);
        } catch (Exception e) {
            fail("access field " + name, e);
            return null;
        }
    }

    private static int invokeProtectedInt(Object target, String name, Object... params) {
        try {
            var cls = target.getClass();

{* ../../docs_src/dataclasses_/tutorial003_py310.py hl[1,4,7:10,13:16,22:24,27] *}

1. Wir importieren `field` weiterhin von Standard-`dataclasses`.

2. `pydantic.dataclasses` ist ein direkter Ersatz für `dataclasses`.

3. Die Datenklasse `Author` enthält eine Liste von `Item`-Datenklassen.

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

{* ../../docs_src/dataclasses_/tutorial003_py310.py hl[1,4,7:10,13:16,22:24,27] *}

1. We still import `field` from standard `dataclasses`.

2. `pydantic.dataclasses` is a drop-in replacement for `dataclasses`.

3. The `Author` dataclass includes a list of `Item` dataclasses.

...без додавання обов’язкового параметра `needy`, Ви побачите помилку:

```JSON
{
  "detail": [
    {
      "type": "missing",
      "loc": [
        "query",
        "needy"
      ],
      "msg": "Field required",
      "input": null
    }
  ]
}
```

Оскільки `needy` є обов’язковим параметром, вам потрібно вказати його в URL:

```
http://127.0.0.1:8000/items/foo-item?needy=sooooneedy
```

* kubectl get -o jsonpath=... will now throw an error if the path is to a field not present in the json, even if the path is for a field valid for the type.  This is a change from the pre-1.5 behavior, which would return the default value for some fields even if they were not present in the json. ([#37991](https://github.com/kubernetes/kubernetes/pull/37991), [@pwittrock](https://github.com/pwittrock))

        assertArrayEquals(key.getKey(), context.getLeaseKey().getKey());
        assertEquals(DirectoryLeaseState.DIRECTORY_READ_HANDLE, context.getLeaseState());

        // Directory-specific fields should retain defaults
        assertEquals(DirectoryCacheScope.IMMEDIATE_CHILDREN, context.getCacheScope());
        assertEquals(30000L, context.getMaxCacheAge());
        assertTrue(context.isNotificationEnabled());
    }

- AWS S3's [reserved keywords](https://docs.aws.amazon.com/AmazonS3/latest/dev/s3-glacier-select-sql-reference-keyword-list.html) list is not yet respected.