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Release v1.1.0 (#75)
## Changed - string_metric.normalized_levenshtein supports now all weights - when different weights are used for Insertion and Deletion the strings can not be swapped inside the Levenshtein implementation anymore. So different weights for Insertion and Deletion are now supported. - replace C++ implementation with a Cython implementation. This has the following advantages: - The implementation is less error prone, since a lot of the complex things are done by Cython - slighly faster than the current implementation (up to 10% for some parts) - about 33% smaller binary size - reduced compile time - Added **kwargs argument to process.extract/extractOne/extract_iter that is passed to the scorer - Add max argument to hamming distance - Add support for whole Unicode range to utils.default_process ## Performance - replaced Wagner Fischer usage in the normal Levenshtein distance with a bitparallel implementation
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.gitattributes

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extern/boost/* linguist-vendored
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bench/data/* linguist-vendored
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src/cpp_process.cpp linguist-vendored
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src/cpp_fuzz.cpp linguist-vendored
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src/cpp_string_metric.cpp linguist-vendored
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src/cpp_utils.cpp linguist-vendored

.github/workflows/pythonbuild.yml

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- uses: ilammy/msvc-dev-cmd@v1
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- name: Build 64-bit wheel
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MANIFEST.in

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recursive-include src/rapidfuzz-cpp/rapidfuzz *.hpp *.h *.txx *cpp
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README.md

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### Process
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The process module makes it compare strings to lists of strings. This is generally more
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performant than using the scorers directly from Python.
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performant than using the scorers directly from Python.
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Here are some examples on the usage of processors in RapidFuzz:
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```console

VERSION

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1.0.2
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1.1.0

extern/variant/LICENSE.md

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