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

1. Мы по-прежнему импортируем `field` из стандартных `dataclasses`.

2. `pydantic.dataclasses` — полностью совместимая замена (drop-in replacement) для `dataclasses`.

3. Dataclass `Author` содержит список dataclass `Item`.

async def unrelated(foo: Annotated[str, object()]):
    return {"foo": foo}


client = TestClient(app)

foo_is_missing = {
    "detail": [
        {
            "loc": ["query", "foo"],
            "msg": "Field required",
            "type": "missing",
            "input": None,
        }
    ]
}
foo_is_short = {
    "detail": [
        {
            "ctx": {"min_length": 1},
            "loc": ["query", "foo"],

in this list response. If the list request contained label or field selectors, then the number of remaining items is unknown and the field will be left unset and omitted during serialization. If the list is complete (either because it is not chunking or because this is the last chunk), then there are no more remaining items and this field will be left unset and omitted during serialization. Servers older than v1.15 do not set this field. The intended use of the remainingItemCount is *estimating* the...

  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

  sftp: # settings for MinIO to act as an sftp server
    address: ":8022"
    ssh-private-key: "/home/user/.ssh/id_rsa"
```

If you are using the config `v1` YAML you should migrate your `pools:` field values to the following format

`v1` format
```yaml
pools: # Specify the nodes and drives with pools
  -
    - "https://server-example-pool1:9000/mnt/disk{1...4}/"

find the definition of xxx.  If xxx is a type, cgo replaces C.xxx with
a Go translation.  C arithmetic types translate to precisely-sized Go
arithmetic types.  A C struct translates to a Go struct, field by
field; unrepresentable fields are replaced with opaque byte arrays.  A
C union translates into a struct containing the first union member and
perhaps additional padding.  C arrays become Go arrays.  C pointers

Nesse caso, você pode simplesmente trocar as `dataclasses` padrão por `pydantic.dataclasses`, que é um substituto direto:

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

1. Ainda importamos `field` das `dataclasses` padrão.

2. `pydantic.dataclasses` é um substituto direto para `dataclasses`.

3. A dataclass `Author` inclui uma lista de dataclasses `Item`.

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

1. Todavía importamos `field` de los `dataclasses` estándar.

2. `pydantic.dataclasses` es un reemplazo directo para `dataclasses`.

3. El dataclass `Author` incluye una lista de dataclasses `Item`.

{* ../../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.