spaCy/spacy/tokens/span.pyi

140 lines
3.9 KiB
Python

from typing import Any, Callable, Iterator, Optional, Protocol, Tuple, Union, overload
from thinc.types import Floats1d, FloatsXd, Ints2d
from ..lexeme import Lexeme
from ..vocab import Vocab
from .doc import Doc
from .token import Token
from .underscore import Underscore
class SpanMethod(Protocol):
def __call__(self: Span, *args: Any, **kwargs: Any) -> Any: ... # type: ignore[misc]
class Span:
@classmethod
def set_extension(
cls,
name: str,
default: Optional[Any] = ...,
getter: Optional[Callable[[Span], Any]] = ...,
setter: Optional[Callable[[Span, Any], None]] = ...,
method: Optional[SpanMethod] = ...,
force: bool = ...,
) -> None: ...
@classmethod
def get_extension(
cls, name: str
) -> Tuple[
Optional[Any],
Optional[SpanMethod],
Optional[Callable[[Span], Any]],
Optional[Callable[[Span, Any], None]],
]: ...
@classmethod
def has_extension(cls, name: str) -> bool: ...
@classmethod
def remove_extension(
cls, name: str
) -> Tuple[
Optional[Any],
Optional[SpanMethod],
Optional[Callable[[Span], Any]],
Optional[Callable[[Span, Any], None]],
]: ...
def __init__(
self,
doc: Doc,
start: int,
end: int,
label: Union[str, int] = ...,
vector: Optional[Floats1d] = ...,
vector_norm: Optional[float] = ...,
kb_id: Union[str, int] = ...,
span_id: Union[str, int] = ...,
) -> None: ...
def __lt__(self, other: Any) -> bool: ...
def __le__(self, other: Any) -> bool: ...
def __eq__(self, other: Any) -> bool: ...
def __ne__(self, other: Any) -> bool: ...
def __gt__(self, other: Any) -> bool: ...
def __ge__(self, other: Any) -> bool: ...
def __hash__(self) -> int: ...
def __len__(self) -> int: ...
def __repr__(self) -> str: ...
@overload
def __getitem__(self, i: int) -> Token: ...
@overload
def __getitem__(self, i: slice) -> Span: ...
def __iter__(self) -> Iterator[Token]: ...
@property
def _(self) -> Underscore: ...
def as_doc(self, *, copy_user_data: bool = ...) -> Doc: ...
def get_lca_matrix(self) -> Ints2d: ...
def similarity(self, other: Union[Doc, Span, Token, Lexeme]) -> float: ...
@property
def doc(self) -> Doc: ...
@property
def vocab(self) -> Vocab: ...
@property
def sent(self) -> Span: ...
@property
def ents(self) -> Tuple[Span]: ...
@property
def has_vector(self) -> bool: ...
@property
def vector(self) -> Floats1d: ...
@property
def vector_norm(self) -> float: ...
@property
def tensor(self) -> FloatsXd: ...
@property
def sentiment(self) -> float: ...
@property
def text(self) -> str: ...
@property
def text_with_ws(self) -> str: ...
@property
def noun_chunks(self) -> Iterator[Span]: ...
@property
def root(self) -> Token: ...
def char_span(
self,
start_idx: int,
end_idx: int,
label: Union[int, str] = ...,
kb_id: Union[int, str] = ...,
vector: Optional[Floats1d] = ...,
id: Union[int, str] = ...,
alignment_mode: str = ...,
span_id: Union[int, str] = ...,
) -> Span: ...
@property
def conjuncts(self) -> Tuple[Token]: ...
@property
def lefts(self) -> Iterator[Token]: ...
@property
def rights(self) -> Iterator[Token]: ...
@property
def n_lefts(self) -> int: ...
@property
def n_rights(self) -> int: ...
@property
def subtree(self) -> Iterator[Token]: ...
start: int
end: int
start_char: int
end_char: int
label: int
kb_id: int
id: int
ent_id: int
ent_id_: str
@property
def orth_(self) -> str: ...
@property
def lemma_(self) -> str: ...
label_: str
kb_id_: str
id_: str