RapidFuzz 1.0.0 on Python PyPI

Changed

all normalized string_metrics can now be used as scorer for process.extract/extractOne
Implementation of the C++ Wrapper completely refactored to make it easier to add more scorers, processors and string matching algorithms in the future.
increased test coverage, that already helped to fix some bugs and help to prevent regressions in the future
improved docstrings of functions

Added bit-parallel implementation of the Levenshtein distance for the weights (1,1,1) and (1,1,2).
Added specialized implementation of the Levenshtein distance for cases with a small maximum edit distance, that is even faster, than the bit-parallel implementation.
Improved performance of fuzz.partial_ratio
-> Since fuzz.ratio and fuzz.partial_ratio are used in most scorers, this improves the overall performance.
Improved performance of process.extract and process.extractOne

the rapidfuzz.levenshtein module is now deprecated and will be removed in v2.0.0
These functions are now placed in rapidfuzz.string_metric. distance, normalized_distance, weighted_distance and weighted_normalized_distance are combined into levenshtein and normalized_levenshtein.

added normalized version of the hamming distance in string_metric.normalized_hamming
process.extract_iter as a generator, that yields the similarity of all elements, that have a similarity >= score_cutoff