spaCy/spacy/pipeline/pipe.pyi

from pathlib import Path
from typing import (
    Any,
    Callable,
    Dict,
    Iterable,
    Iterator,
    List,
    NoReturn,
    Optional,
    Tuple,
    Union,
)

from ..language import Language
from ..tokens.doc import Doc
from ..training import Example

class Pipe:
    def __call__(self, doc: Doc) -> Doc: ...
    def pipe(
        self, stream: Iterable[Doc], *, batch_size: int = ...
    ) -> Iterator[Doc]: ...
    def initialize(
        self,
        get_examples: Callable[[], Iterable[Example]],
        *,
        nlp: Language = ...,
    ) -> None: ...
    def score(
        self, examples: Iterable[Example], **kwargs: Any
    ) -> Dict[str, Union[float, Dict[str, float]]]: ...
    @property
    def is_trainable(self) -> bool: ...
    @property
    def labels(self) -> Tuple[str, ...]: ...
    @property
    def hide_labels(self) -> bool: ...
    @property
    def label_data(self) -> Any: ...
    def _require_labels(self) -> None: ...
    def set_error_handler(
        self, error_handler: Callable[[str, "Pipe", List[Doc], Exception], NoReturn]
    ) -> None: ...
    def get_error_handler(
        self,
    ) -> Callable[[str, "Pipe", List[Doc], Exception], NoReturn]: ...

def deserialize_config(path: Path) -> Any: ...