275 lines
7.2 KiB
Python
275 lines
7.2 KiB
Python
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from __future__ import annotations
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from typing import Callable, Hashable, Optional, Sequence, Tuple, TypeVar
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from rapidfuzz.distance import Editops, Opcodes
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_StringType = Sequence[Hashable]
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_S1 = TypeVar("_S1")
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_S2 = TypeVar("_S2")
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def levenshtein_distance(
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s1: _S1,
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s2: _S2,
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*,
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weights: Optional[Tuple[int, int, int]] = (1, 1, 1),
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> int: ...
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def levenshtein_normalized_distance(
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s1: _S1,
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s2: _S2,
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*,
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weights: Optional[Tuple[int, int, int]] = (1, 1, 1),
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def levenshtein_similarity(
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s1: _S1,
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s2: _S2,
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*,
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weights: Optional[Tuple[int, int, int]] = (1, 1, 1),
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> int: ...
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def levenshtein_normalized_similarity(
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s1: _S1,
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s2: _S2,
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*,
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weights: Optional[Tuple[int, int, int]] = (1, 1, 1),
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def levenshtein_editops(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_hint: Optional[int] = None,
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) -> Editops: ...
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def levenshtein_opcodes(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_hint: Optional[int] = None,
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) -> Opcodes: ...
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def indel_distance(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> int: ...
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def indel_normalized_distance(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def indel_similarity(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> int: ...
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def indel_normalized_similarity(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def indel_editops(
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s1: _S1, s2: _S2, *, processor: Optional[Callable[..., _StringType]] = None
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) -> Editops: ...
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def indel_opcodes(
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s1: _S1, s2: _S2, *, processor: Optional[Callable[..., _StringType]] = None
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) -> Opcodes: ...
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def lcs_seq_distance(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> int: ...
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def lcs_seq_normalized_distance(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def lcs_seq_similarity(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> int: ...
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def lcs_seq_normalized_similarity(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def lcs_seq_editops(
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s1: _S1, s2: _S2, *, processor: Optional[Callable[..., _StringType]] = None
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) -> Editops: ...
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def lcs_seq_opcodes(
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s1: _S1, s2: _S2, *, processor: Optional[Callable[..., _StringType]] = None
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) -> Opcodes: ...
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def hamming_distance(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> int: ...
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def hamming_normalized_distance(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def hamming_similarity(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> int: ...
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def hamming_normalized_similarity(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def hamming_editops(
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s1: _S1, s2: _S2, *, processor: Optional[Callable[..., _StringType]] = None
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) -> Editops: ...
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def hamming_opcodes(
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s1: _S1, s2: _S2, *, processor: Optional[Callable[..., _StringType]] = None
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) -> Opcodes: ...
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def damerau_levenshtein_distance(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> int: ...
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def damerau_levenshtein_normalized_distance(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def damerau_levenshtein_similarity(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> int: ...
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def damerau_levenshtein_normalized_similarity(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def osa_distance(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> int: ...
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def osa_normalized_distance(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def osa_similarity(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> int: ...
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def osa_normalized_similarity(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def jaro_distance(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> float: ...
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def jaro_normalized_distance(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def jaro_similarity(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> float: ...
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def jaro_normalized_similarity(
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s1: _S1,
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s2: _S2,
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*,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def jaro_winkler_distance(
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s1: _S1,
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s2: _S2,
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*,
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prefix_weight: float = 0.1,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> float: ...
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def jaro_winkler_normalized_distance(
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s1: _S1,
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s2: _S2,
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*,
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prefix_weight: float = 0.1,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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def jaro_winkler_similarity(
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s1: _S1,
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s2: _S2,
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*,
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prefix_weight: float = 0.1,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[int] = None,
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) -> float: ...
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def jaro_winkler_normalized_similarity(
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s1: _S1,
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s2: _S2,
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*,
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prefix_weight: float = 0.1,
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processor: Optional[Callable[..., _StringType]] = None,
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score_cutoff: Optional[float] = 0,
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) -> float: ...
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