# SPDX-License-Identifier: MIT
# Copyright (C) 2022 Max Bachmann
from __future__ import annotations
from typing import Any, Callable
from rapidfuzz._utils import (
ScorerFlag,
add_scorer_attrs,
default_distance_attribute as dist_attr,
default_normalized_distance_attribute as norm_dist_attr,
default_normalized_similarity_attribute as norm_sim_attr,
default_similarity_attribute as sim_attr,
)
# DamerauLevenshtein
from rapidfuzz.distance.DamerauLevenshtein_py import (
distance as damerau_levenshtein_distance,
normalized_distance as damerau_levenshtein_normalized_distance,
normalized_similarity as damerau_levenshtein_normalized_similarity,
similarity as damerau_levenshtein_similarity,
)
# Hamming
from rapidfuzz.distance.Hamming_py import (
distance as hamming_distance,
editops as hamming_editops,
normalized_distance as hamming_normalized_distance,
normalized_similarity as hamming_normalized_similarity,
opcodes as hamming_opcodes,
similarity as hamming_similarity,
)
# Indel
from rapidfuzz.distance.Indel_py import (
distance as indel_distance,
editops as indel_editops,
normalized_distance as indel_normalized_distance,
normalized_similarity as indel_normalized_similarity,
opcodes as indel_opcodes,
similarity as indel_similarity,
)
# Jaro
from rapidfuzz.distance.Jaro_py import (
distance as jaro_distance,
normalized_distance as jaro_normalized_distance,
normalized_similarity as jaro_normalized_similarity,
similarity as jaro_similarity,
)
# JaroWinkler
from rapidfuzz.distance.JaroWinkler_py import (
distance as jaro_winkler_distance,
normalized_distance as jaro_winkler_normalized_distance,
normalized_similarity as jaro_winkler_normalized_similarity,
similarity as jaro_winkler_similarity,
)
# LCSseq
from rapidfuzz.distance.LCSseq_py import (
distance as lcs_seq_distance,
editops as lcs_seq_editops,
normalized_distance as lcs_seq_normalized_distance,
normalized_similarity as lcs_seq_normalized_similarity,
opcodes as lcs_seq_opcodes,
similarity as lcs_seq_similarity,
)
# Levenshtein
from rapidfuzz.distance.Levenshtein_py import (
distance as levenshtein_distance,
editops as levenshtein_editops,
normalized_distance as levenshtein_normalized_distance,
normalized_similarity as levenshtein_normalized_similarity,
opcodes as levenshtein_opcodes,
similarity as levenshtein_similarity,
)
# OSA
from rapidfuzz.distance.OSA_py import (
distance as osa_distance,
normalized_distance as osa_normalized_distance,
normalized_similarity as osa_normalized_similarity,
similarity as osa_similarity,
)
# Postfix
from rapidfuzz.distance.Postfix_py import (
distance as postfix_distance,
normalized_distance as postfix_normalized_distance,
normalized_similarity as postfix_normalized_similarity,
similarity as postfix_similarity,
)
# Prefix
from rapidfuzz.distance.Prefix_py import (
distance as prefix_distance,
normalized_distance as prefix_normalized_distance,
normalized_similarity as prefix_normalized_similarity,
similarity as prefix_similarity,
)
__all__ = []
add_scorer_attrs(osa_distance, dist_attr)
add_scorer_attrs(osa_similarity, sim_attr)
add_scorer_attrs(osa_normalized_distance, norm_dist_attr)
add_scorer_attrs(osa_normalized_similarity, norm_sim_attr)
__all__ += [
"osa_distance",
"osa_normalized_distance",
"osa_normalized_similarity",
"osa_similarity",
]
add_scorer_attrs(prefix_distance, dist_attr)
add_scorer_attrs(prefix_similarity, sim_attr)
add_scorer_attrs(prefix_normalized_distance, norm_dist_attr)
add_scorer_attrs(prefix_normalized_similarity, norm_sim_attr)
__all__ += [
"prefix_distance",
"prefix_normalized_distance",
"prefix_normalized_similarity",
"prefix_similarity",
]
add_scorer_attrs(postfix_distance, dist_attr)
add_scorer_attrs(postfix_similarity, sim_attr)
add_scorer_attrs(postfix_normalized_distance, norm_dist_attr)
add_scorer_attrs(postfix_normalized_similarity, norm_sim_attr)
__all__ += [
"postfix_distance",
"postfix_normalized_distance",
"postfix_normalized_similarity",
"postfix_similarity",
]
add_scorer_attrs(jaro_distance, norm_dist_attr)
add_scorer_attrs(jaro_similarity, norm_sim_attr)
add_scorer_attrs(jaro_normalized_distance, norm_dist_attr)
add_scorer_attrs(jaro_normalized_similarity, norm_sim_attr)
__all__ += [
"jaro_distance",
"jaro_normalized_distance",
"jaro_normalized_similarity",
"jaro_similarity",
]
add_scorer_attrs(jaro_winkler_distance, norm_dist_attr)
add_scorer_attrs(jaro_winkler_similarity, norm_sim_attr)
add_scorer_attrs(jaro_winkler_normalized_distance, norm_dist_attr)
add_scorer_attrs(jaro_winkler_normalized_similarity, norm_sim_attr)
__all__ += [
"jaro_winkler_distance",
"jaro_winkler_normalized_distance",
"jaro_winkler_normalized_similarity",
"jaro_winkler_similarity",
]
add_scorer_attrs(damerau_levenshtein_distance, dist_attr)
add_scorer_attrs(damerau_levenshtein_similarity, sim_attr)
add_scorer_attrs(damerau_levenshtein_normalized_distance, norm_dist_attr)
add_scorer_attrs(damerau_levenshtein_normalized_similarity, norm_sim_attr)
__all__ += [
"damerau_levenshtein_distance",
"damerau_levenshtein_normalized_distance",
"damerau_levenshtein_normalized_similarity",
"damerau_levenshtein_similarity",
]
def _get_scorer_flags_levenshtein_distance(weights: tuple[int, int, int] | None = (1, 1, 1)) -> dict[str, Any]:
flags = ScorerFlag.RESULT_SIZE_T
if weights is None or weights[0] == weights[1]:
flags |= ScorerFlag.SYMMETRIC
return {
"optimal_score": 0,
"worst_score": 2**63 - 1,
"flags": flags,
}
def _get_scorer_flags_levenshtein_similarity(weights: tuple[int, int, int] | None = (1, 1, 1)) -> dict[str, Any]:
flags = ScorerFlag.RESULT_SIZE_T
if weights is None or weights[0] == weights[1]:
flags |= ScorerFlag.SYMMETRIC
return {
"optimal_score": 2**63 - 1,
"worst_score": 0,
"flags": flags,
}
def _get_scorer_flags_levenshtein_normalized_distance(
weights: tuple[int, int, int] | None = (1, 1, 1)
) -> dict[str, Any]:
flags = ScorerFlag.RESULT_F64
if weights is None or weights[0] == weights[1]:
flags |= ScorerFlag.SYMMETRIC
return {"optimal_score": 0, "worst_score": 1, "flags": flags}
def _get_scorer_flags_levenshtein_normalized_similarity(
weights: tuple[int, int, int] | None = (1, 1, 1)
) -> dict[str, Any]:
flags = ScorerFlag.RESULT_F64
if weights is None or weights[0] == weights[1]:
flags |= ScorerFlag.SYMMETRIC
return {"optimal_score": 1, "worst_score": 0, "flags": flags}
levenshtein_dist_attr: dict[str, Callable[..., dict[str, Any]]] = {
"get_scorer_flags": _get_scorer_flags_levenshtein_distance
}
levenshtein_sim_attr: dict[str, Callable[..., dict[str, Any]]] = {
"get_scorer_flags": _get_scorer_flags_levenshtein_similarity
}
levenshtein_norm_dist_attr: dict[str, Callable[..., dict[str, Any]]] = {
"get_scorer_flags": _get_scorer_flags_levenshtein_normalized_distance
}
levenshtein_norm_sim_attr: dict[str, Callable[..., dict[str, Any]]] = {
"get_scorer_flags": _get_scorer_flags_levenshtein_normalized_similarity
}
add_scorer_attrs(levenshtein_distance, levenshtein_dist_attr)
add_scorer_attrs(levenshtein_similarity, levenshtein_sim_attr)
add_scorer_attrs(levenshtein_normalized_distance, levenshtein_norm_dist_attr)
add_scorer_attrs(levenshtein_normalized_similarity, levenshtein_norm_sim_attr)
__all__ += [
"levenshtein_distance",
"levenshtein_normalized_distance",
"levenshtein_normalized_similarity",
"levenshtein_similarity",
"levenshtein_editops",
"levenshtein_opcodes",
]
add_scorer_attrs(lcs_seq_distance, dist_attr)
add_scorer_attrs(lcs_seq_similarity, sim_attr)
add_scorer_attrs(lcs_seq_normalized_distance, norm_dist_attr)
add_scorer_attrs(lcs_seq_normalized_similarity, norm_sim_attr)
__all__ += [
"lcs_seq_distance",
"lcs_seq_normalized_distance",
"lcs_seq_normalized_similarity",
"lcs_seq_similarity",
"lcs_seq_editops",
"lcs_seq_opcodes",
]
add_scorer_attrs(indel_distance, dist_attr)
add_scorer_attrs(indel_similarity, sim_attr)
add_scorer_attrs(indel_normalized_distance, norm_dist_attr)
add_scorer_attrs(indel_normalized_similarity, norm_sim_attr)
__all__ += [
"indel_distance",
"indel_normalized_distance",
"indel_normalized_similarity",
"indel_similarity",
"indel_editops",
"indel_opcodes",
]
add_scorer_attrs(hamming_distance, dist_attr)
add_scorer_attrs(hamming_similarity, sim_attr)
add_scorer_attrs(hamming_normalized_distance, norm_dist_attr)
add_scorer_attrs(hamming_normalized_similarity, norm_sim_attr)
__all__ += [
"hamming_distance",
"hamming_normalized_distance",
"hamming_normalized_similarity",
"hamming_similarity",
"hamming_editops",
"hamming_opcodes",
]