k*ilSSKJr SSKJr SSKJrJr SSS.SjrSSS.SjrSSS.Sjr SSS.S jr g) ) annotations)conv_sequences)is_none setupPandasN) processor score_cutoffcUbU"U5nU"U5n[X5up[[U5[U55n[X5nXE- nUbXc::aU$US-$)a Calculates the Prefix distance between two strings. Parameters ---------- s1 : Sequence[Hashable] First string to compare. s2 : Sequence[Hashable] Second string to compare. processor: callable, optional Optional callable that is used to preprocess the strings before comparing them. Default is None, which deactivates this behaviour. score_cutoff : int or None, optional Maximum distance between s1 and s2, that is considered as a result. If the distance is bigger than score_cutoff, score_cutoff + 1 is returned instead. Default is None, which deactivates this behaviour. Returns ------- distance : int distance between s1 and s2 )rmaxlen similarity)s1s2rrmaximumsimdists \/var/www/html/land-doc-ocr/venv/lib/python3.13/site-packages/rapidfuzz/distance/Prefix_py.pydistancer sh< r] r] B #FB#b'3r7#G R C =D (D,@4W|VWGWWcUbU"U5nU"U5n[X5upSn[X5HupVXV:wa O US- nM UbXC:aU$S$)a Calculates the prefix similarity between two strings. This is calculated as ``len1 - distance``. Parameters ---------- s1 : Sequence[Hashable] First string to compare. s2 : Sequence[Hashable] Second string to compare. processor: callable, optional Optional callable that is used to preprocess the strings before comparing them. Default is None, which deactivates this behaviour. score_cutoff : int, optional Maximum distance between s1 and s2, that is considered as a result. If the similarity is smaller than score_cutoff, 0 is returned instead. Default is None, which deactivates this behaviour. Returns ------- distance : int distance between s1 and s2 rr )rzip)rrrrrch1ch2s rr r 3sf@ r] r] B #FB CK :  q  '3+>3FQFrc[5 [U5(d[U5(ag[XUS9nSU- nUbXS::aU$S$)a Calculates a normalized prefix similarity in the range [1, 0]. This is calculated as ``distance / (len1 + len2)``. Parameters ---------- s1 : Sequence[Hashable] First string to compare. s2 : Sequence[Hashable] Second string to compare. processor: callable, optional Optional callable that is used to preprocess the strings before comparing them. Default is None, which deactivates this behaviour. score_cutoff : float, optional Optional argument for a score threshold as a float between 0 and 1.0. For norm_dist > score_cutoff 1.0 is returned instead. Default is 1.0, which deactivates this behaviour. Returns ------- norm_dist : float normalized distance between s1 and s2 as a float between 0 and 1.0 ?)r)rrnormalized_similarity)rrrrnorm_sim norm_dists rnormalized_distancerasH>Mr{{gbkk$RyAHhI%-1J9TQTTrc[5 [U5(d[U5(agUbU"U5nU"U5n[X5up[[ U5[ U55n[ X5nU(aXT- OSnUbXc:aU$S$)a Calculates a normalized prefix similarity in the range [0, 1]. This is calculated as ``1 - normalized_distance`` Parameters ---------- s1 : Sequence[Hashable] First string to compare. s2 : Sequence[Hashable] Second string to compare. processor: callable, optional Optional callable that is used to preprocess the strings before comparing them. Default is None, which deactivates this behaviour. score_cutoff : float, optional Optional argument for a score threshold as a float between 0 and 1.0. For norm_sim < score_cutoff 0 is returned instead. Default is 0, which deactivates this behaviour. Returns ------- norm_sim : float normalized similarity between s1 and s2 as a float between 0 and 1.0 gr)rrrr r r )rrrrrrrs rrrs>Mr{{gbkk r] r] B #FB#b'3r7#G R C 's}SH$,0H8RsRr) __future__rrapidfuzz._common_pyrrapidfuzz._utilsrrrr rrrrr%sK#/1 'X\ +Gd &UZ ,Sr