Jaro¶

Functions¶

distance¶

rapidfuzz.distance.Jaro.distance(s1, s2, *, processor=None, score_cutoff=None)¶

Calculates the jaro 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 ratio < score_cutoff 0 is returned instead. Default is None, which deactivates this behaviour.

Returns:

distance – distance between s1 and s2 as a float between 1.0 and 0.0

Return type:

float

normalized_distance¶

rapidfuzz.distance.Jaro.normalized_distance(s1, s2, *, processor=None, score_cutoff=None)¶

Calculates the normalized jaro 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 ratio < score_cutoff 0 is returned instead. Default is None, which deactivates this behaviour.

Returns:

normalized distance – normalized distance between s1 and s2 as a float between 1.0 and 0.0

Return type:

float

similarity¶

rapidfuzz.distance.Jaro.similarity(s1, s2, *, processor=None, score_cutoff=None)¶

Calculates the jaro similarity

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 ratio < score_cutoff 0 is returned instead. Default is None, which deactivates this behaviour.

Returns:

similarity – similarity between s1 and s2 as a float between 0 and 1.0

Return type:

float

normalized_similarity¶

rapidfuzz.distance.Jaro.normalized_similarity(s1, s2, *, processor=None, score_cutoff=None)¶

Calculates the normalized jaro similarity

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 ratio < score_cutoff 0 is returned instead. Default is None, which deactivates this behaviour.

Returns:

normalized similarity – normalized similarity between s1 and s2 as a float between 0 and 1.0

Return type:

float

Performance¶

The following image shows a benchmark of the Jaro similarity in RapidFuzz and jellyfish. Jellyfish uses an implementation with a time complexity of O(NM), while RapidFuzz has a time complexity of O([N/64]M).