spaCy/spacy/tokens/doc.pyi
github-actions[bot] 5cdb7eb5c2
Auto-format code with black (#9631)
Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
2021-11-05 09:58:36 +01:00

176 lines
5.6 KiB
Python

from typing import Callable, Protocol, Iterable, Iterator, Optional
from typing import Union, Tuple, List, Dict, Any, overload
from cymem.cymem import Pool
from thinc.types import Floats1d, Floats2d, Ints2d
from .span import Span
from .token import Token
from ._dict_proxies import SpanGroups
from ._retokenize import Retokenizer
from ..lexeme import Lexeme
from ..vocab import Vocab
from .underscore import Underscore
from pathlib import Path
import numpy
class DocMethod(Protocol):
def __call__(self: Doc, *args: Any, **kwargs: Any) -> Any: ... # type: ignore[misc]
class Doc:
vocab: Vocab
mem: Pool
spans: SpanGroups
max_length: int
length: int
sentiment: float
cats: Dict[str, float]
user_hooks: Dict[str, Callable[..., Any]]
user_token_hooks: Dict[str, Callable[..., Any]]
user_span_hooks: Dict[str, Callable[..., Any]]
tensor: numpy.ndarray
user_data: Dict[str, Any]
has_unknown_spaces: bool
_context: Any
@classmethod
def set_extension(
cls,
name: str,
default: Optional[Any] = ...,
getter: Optional[Callable[[Doc], Any]] = ...,
setter: Optional[Callable[[Doc, Any], None]] = ...,
method: Optional[DocMethod] = ...,
force: bool = ...,
) -> None: ...
@classmethod
def get_extension(
cls, name: str
) -> Tuple[
Optional[Any],
Optional[DocMethod],
Optional[Callable[[Doc], Any]],
Optional[Callable[[Doc, Any], None]],
]: ...
@classmethod
def has_extension(cls, name: str) -> bool: ...
@classmethod
def remove_extension(
cls, name: str
) -> Tuple[
Optional[Any],
Optional[DocMethod],
Optional[Callable[[Doc], Any]],
Optional[Callable[[Doc, Any], None]],
]: ...
def __init__(
self,
vocab: Vocab,
words: Optional[List[str]] = ...,
spaces: Optional[List[bool]] = ...,
user_data: Optional[Dict[Any, Any]] = ...,
tags: Optional[List[str]] = ...,
pos: Optional[List[str]] = ...,
morphs: Optional[List[str]] = ...,
lemmas: Optional[List[str]] = ...,
heads: Optional[List[int]] = ...,
deps: Optional[List[str]] = ...,
sent_starts: Optional[List[Union[bool, None]]] = ...,
ents: Optional[List[str]] = ...,
) -> None: ...
@property
def _(self) -> Underscore: ...
@property
def is_tagged(self) -> bool: ...
@property
def is_parsed(self) -> bool: ...
@property
def is_nered(self) -> bool: ...
@property
def is_sentenced(self) -> bool: ...
def has_annotation(
self, attr: Union[int, str], *, require_complete: bool = ...
) -> bool: ...
@overload
def __getitem__(self, i: int) -> Token: ...
@overload
def __getitem__(self, i: slice) -> Span: ...
def __iter__(self) -> Iterator[Token]: ...
def __len__(self) -> int: ...
def __unicode__(self) -> str: ...
def __bytes__(self) -> bytes: ...
def __str__(self) -> str: ...
def __repr__(self) -> str: ...
@property
def doc(self) -> Doc: ...
def char_span(
self,
start_idx: int,
end_idx: int,
label: Union[int, str] = ...,
kb_id: Union[int, str] = ...,
vector: Optional[Floats1d] = ...,
alignment_mode: str = ...,
) -> Span: ...
def similarity(self, other: Union[Doc, Span, Token, Lexeme]) -> float: ...
@property
def has_vector(self) -> bool: ...
vector: Floats1d
vector_norm: float
@property
def text(self) -> str: ...
@property
def text_with_ws(self) -> str: ...
ents: Tuple[Span]
def set_ents(
self,
entities: List[Span],
*,
blocked: Optional[List[Span]] = ...,
missing: Optional[List[Span]] = ...,
outside: Optional[List[Span]] = ...,
default: str = ...
) -> None: ...
@property
def noun_chunks(self) -> Iterator[Span]: ...
@property
def sents(self) -> Iterator[Span]: ...
@property
def lang(self) -> int: ...
@property
def lang_(self) -> str: ...
def count_by(
self, attr_id: int, exclude: Optional[Any] = ..., counts: Optional[Any] = ...
) -> Dict[Any, int]: ...
def from_array(
self, attrs: Union[int, str, List[Union[int, str]]], array: Ints2d
) -> Doc: ...
def to_array(
self, py_attr_ids: Union[int, str, List[Union[int, str]]]
) -> numpy.ndarray: ...
@staticmethod
def from_docs(
docs: List[Doc],
ensure_whitespace: bool = ...,
attrs: Optional[Union[Tuple[Union[str, int]], List[Union[int, str]]]] = ...,
) -> Doc: ...
def get_lca_matrix(self) -> Ints2d: ...
def copy(self) -> Doc: ...
def to_disk(
self, path: Union[str, Path], *, exclude: Iterable[str] = ...
) -> None: ...
def from_disk(
self, path: Union[str, Path], *, exclude: Union[List[str], Tuple[str]] = ...
) -> Doc: ...
def to_bytes(self, *, exclude: Union[List[str], Tuple[str]] = ...) -> bytes: ...
def from_bytes(
self, bytes_data: bytes, *, exclude: Union[List[str], Tuple[str]] = ...
) -> Doc: ...
def to_dict(self, *, exclude: Union[List[str], Tuple[str]] = ...) -> bytes: ...
def from_dict(
self, msg: bytes, *, exclude: Union[List[str], Tuple[str]] = ...
) -> Doc: ...
def extend_tensor(self, tensor: Floats2d) -> None: ...
def retokenize(self) -> Retokenizer: ...
def to_json(self, underscore: Optional[List[str]] = ...) -> Dict[str, Any]: ...
def to_utf8_array(self, nr_char: int = ...) -> Ints2d: ...
@staticmethod
def _get_array_attrs() -> Tuple[Any]: ...