rapid fuzzy string matching

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for maxbachmann from gravatar.com maxbachmann

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Max Bachmann
  • Requires: Python >=3.8
Classifiers

Project description

RapidFuzz

Rapid fuzzy string matching in Python and C++ using the Levenshtein Distance

Continuous Integration PyPI package version Conda Version Python versions
Documentation Code Coverage GitHub license

Description • Installation • Usage • License

Description

RapidFuzz is a fast string matching library for Python and C++, which is using the string similarity calculations from FuzzyWuzzy. However there are a couple of aspects that set RapidFuzz apart from FuzzyWuzzy:

  1. It is MIT licensed so it can be used whichever License you might want to choose for your project, while you're forced to adopt the GPL license when using FuzzyWuzzy
  2. It provides many string_metrics like hamming or jaro_winkler, which are not included in FuzzyWuzzy
  3. It is mostly written in C++ and on top of this comes with a lot of Algorithmic improvements to make string matching even faster, while still providing the same results. For detailed benchmarks check the documentation
  4. Fixes multiple bugs in the partial_ratio implementation
  5. It can be largely used as a drop in replacement for fuzzywuzzy. However there are a couple API differences described here

Requirements

Installation

There are several ways to install RapidFuzz, the recommended methods are to either use pip(the Python package manager) or conda (an open-source, cross-platform, package manager)

with pip

RapidFuzz can be installed with pip the following way:

pip install rapidfuzz

There are pre-built binaries (wheels) of RapidFuzz for MacOS (10.9 and later), Linux x86_64 and Windows. Wheels for armv6l (Raspberry Pi Zero) and armv7l (Raspberry Pi) are available on piwheels.

:heavy_multiplication_x:   failure "ImportError: DLL load failed"

If you run into this error on Windows the reason is most likely, that the Visual C++ 2019 redistributable is not installed, which is required to find C++ Libraries (The C++ 2019 version includes the 2015, 2017 and 2019 version).

with conda

RapidFuzz can be installed with conda:

conda install -c conda-forge rapidfuzz

from git

RapidFuzz can be installed directly from the source distribution by cloning the repository. This requires a C++17 capable compiler.

git clone --recursive https://github.com/maxbachmann/rapidfuzz.git
cd rapidfuzz
pip install .

Usage

Some simple functions are shown below. A complete documentation of all functions can be found here.
Note that from RapidFuzz 3.0.0, strings are not preprocessed(removing all non alphanumeric characters, trimming whitespaces, converting all characters to lower case) by default. Which means that when comparing two strings that have the same characters but different cases("this is a word", "THIS IS A WORD") their similarity score value might be different, so when comparing such strings you might see a difference in score value compared to previous versions. Some examples of string matching with preprocessing can be found here.

Scorers

Scorers in RapidFuzz can be found in the modules fuzz and distance.

Simple Ratio

> from rapidfuzz import fuzz
> fuzz.ratio("this is a test", "this is a test!")
96.55172413793103

Partial Ratio

> from rapidfuzz import fuzz
> fuzz.partial_ratio("this is a test", "this is a test!")
100.0

Token Sort Ratio

> from rapidfuzz import fuzz
> fuzz.ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear")
90.9090909090909
> fuzz.token_sort_ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear")
100.0

Token Set Ratio

> from rapidfuzz import fuzz
> fuzz.token_sort_ratio("fuzzy was a bear", "fuzzy fuzzy was a bear")
84.21052631578947
> fuzz.token_set_ratio("fuzzy was a bear", "fuzzy fuzzy was a bear")
100.0

Weighted Ratio

> from rapidfuzz import fuzz
> fuzz.WRatio("this is a test", "this is a new test!!!")
85.5

> from rapidfuzz import fuzz, utils
> # Removing non alpha numeric characters("!") from the string
> fuzz.WRatio("this is a test", "this is a new test!!!", processor=utils.default_process) # here "this is a new test!!!" is converted to "this is a new test"
95.0
> fuzz.WRatio("this is a test", "this is a new test")
95.0

> # Converting string to lower case
> fuzz.WRatio("this is a word", "THIS IS A WORD")
21.42857142857143
> fuzz.WRatio("this is a word", "THIS IS A WORD", processor=utils.default_process) # here "THIS IS A WORD" is converted to "this is a word"
100.0

Quick Ratio

> from rapidfuzz import fuzz
> fuzz.QRatio("this is a test", "this is a new test!!!")
80.0

> from rapidfuzz import fuzz, utils
> # Removing non alpha numeric characters("!") from the string
> fuzz.QRatio("this is a test", "this is a new test!!!", processor=utils.default_process)
87.5
> fuzz.QRatio("this is a test", "this is a new test")
87.5

> # Converting string to lower case
> fuzz.QRatio("this is a word", "THIS IS A WORD")
21.42857142857143
> fuzz.QRatio("this is a word", "THIS IS A WORD", processor=utils.default_process)
100.0

Process

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

> from rapidfuzz import process, fuzz
> choices = ["Atlanta Falcons", "New York Jets", "New York Giants", "Dallas Cowboys"]
> process.extract("new york jets", choices, scorer=fuzz.WRatio, limit=2)
[('New York Jets', 76.92307692307692, 1), ('New York Giants', 64.28571428571428, 2)]
> process.extractOne("cowboys", choices, scorer=fuzz.WRatio)
('Dallas Cowboys', 83.07692307692308, 3)

> # With preprocessing
> from rapidfuzz import process, fuzz, utils
> process.extract("new york jets", choices, scorer=fuzz.WRatio, limit=2, processor=utils.default_process)
[('New York Jets', 100.0, 1), ('New York Giants', 78.57142857142857, 2)]
> process.extractOne("cowboys", choices, scorer=fuzz.WRatio, processor=utils.default_process)
('Dallas Cowboys', 90.0, 3)

The full documentation of processors can be found here

Benchmark

The following benchmark gives a quick performance comparison between RapidFuzz and FuzzyWuzzy. More detailed benchmarks for the string metrics can be found in the documentation. For this simple comparison I generated a list of 10.000 strings with length 10, that is compared to a sample of 100 elements from this list:

words = [
    "".join(random.choice(string.ascii_letters + string.digits) for _ in range(10))
    for _ in range(10_000)
]
samples = words[:: len(words) // 100]

The first benchmark compares the performance of the scorers in FuzzyWuzzy and RapidFuzz when they are used directly from Python in the following way:

for sample in samples:
  for word in words:
    scorer(sample, word)

The following graph shows how many elements are processed per second with each of the scorers. There are big performance differences between the different scorers. However each of the scorers is faster in RapidFuzz

Benchmark Scorer

The second benchmark compares the performance when the scorers are used in combination with cdist in the following way:

cdist(samples, words, scorer=scorer)

The following graph shows how many elements are processed per second with each of the scorers. In RapidFuzz the usage of scorers through processors like cdist is a lot faster than directly using it. That's why they should be used whenever possible.

Benchmark cdist

Support the project

If you are using RapidFuzz for your work and feel like giving a bit of your own benefit back to support the project, consider sending us money through GitHub Sponsors or PayPal that we can use to buy us free time for the maintenance of this great library, to fix bugs in the software, review and integrate code contributions, to improve its features and documentation, or to just take a deep breath and have a cup of tea every once in a while. Thank you for your support.

Support the project through GitHub Sponsors or via PayPal:

.

License

RapidFuzz is licensed under the MIT license since I believe that everyone should be able to use it without being forced to adopt the GPL license. That's why the library is based on an older version of fuzzywuzzy that was MIT licensed as well. This old version of fuzzywuzzy can be found here.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for maxbachmann from gravatar.com maxbachmann

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Max Bachmann
  • Requires: Python >=3.8
Classifiers

Release history Release notifications | RSS feed

3.10.1

3.10.0

3.9.7

3.9.6

3.9.5

3.9.4

3.9.3

3.9.2

3.9.1

3.9.0

3.8.1

3.8.0

3.7.0

3.6.2

3.6.1

3.6.0

This version

3.5.2

3.5.1

3.4.0

3.3.1

3.3.0

3.2.0

3.1.2

3.1.1

3.1.0

3.0.0

2.15.2

2.15.1

2.15.0

2.14.0

2.13.7

2.13.6

2.13.5

2.13.4

2.13.3

2.13.2

2.13.1

2.13.0

2.12.0

2.11.1

2.11.0

2.10.3

2.10.2

2.10.1

2.10.0

2.9.0

2.8.0

2.7.0

2.6.1

2.6.0

2.5.0

2.4.3

2.4.2

2.4.1

2.3.0

2.2.0

2.1.4

2.1.3

2.1.2

2.1.1

2.1.0

2.0.15

2.0.14

2.0.13

2.0.12

2.0.11

2.0.10

2.0.9

2.0.8

2.0.7

2.0.6

2.0.5

2.0.4

2.0.3

2.0.2

2.0.1

2.0.0

1.9.1

1.9.0

1.8.3

1.8.2

1.8.1

1.8.0

1.7.1

1.7.0

1.6.2

1.6.1

1.6.0

1.5.1

1.5.0

1.4.1

1.4.0

1.3.3

1.3.2

1.3.1

1.3.0

1.2.1

1.2.0

1.1.2

1.1.1

1.1.0

1.0.2

1.0.1

1.0.0

0.14.2

0.14.1

0.14.0

0.13.4

0.13.3

0.13.2

0.13.1

0.13.0

0.12.5

0.12.4

0.12.3

0.12.2

0.12.1

0.12.0

0.11.3

0.11.2

0.11.1

0.11.0

0.10.0

0.9.1

0.9.0

0.8.2

0.8.1

0.8.0

0.7.12

0.7.11

0.7.10

0.7.9

0.7.8

0.7.7

0.7.6

0.7.5

0.7.4

0.7.3

0.7.2

0.7.1

0.7.0

0.6.8

0.6.7

0.6.6

0.6.5

0.6.4

0.6.3

0.6.2

0.6.1

0.6.0

0.5.3

0.5.2

0.5.1

0.5.0

0.4.0

0.3.0

0.2.2

0.2.1

0.2.0

0.1.1

0.1.0

0.0.8

0.0.7

0.0.6

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rapidfuzz-3.5.2.tar.gz (1.5 MB view details)

Uploaded Source

Built Distributions

rapidfuzz-3.5.2-pp39-pypy39_pp73-win_amd64.whl (1.6 MB view details)

Uploaded PyPy Windows x86-64

rapidfuzz-3.5.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.2 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

rapidfuzz-3.5.2-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (5.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

rapidfuzz-3.5.2-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

rapidfuzz-3.5.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl (2.5 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

rapidfuzz-3.5.2-pp38-pypy38_pp73-win_amd64.whl (1.6 MB view details)

Uploaded PyPy Windows x86-64

rapidfuzz-3.5.2-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.2 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

rapidfuzz-3.5.2-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (5.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

rapidfuzz-3.5.2-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

rapidfuzz-3.5.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl (2.5 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

rapidfuzz-3.5.2-cp312-cp312-win_arm64.whl (855.8 kB view details)

Uploaded CPython 3.12 Windows ARM64

rapidfuzz-3.5.2-cp312-cp312-win_amd64.whl (1.7 MB view details)

Uploaded CPython 3.12 Windows x86-64

rapidfuzz-3.5.2-cp312-cp312-win32.whl (2.1 MB view details)

Uploaded CPython 3.12 Windows x86

rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.12 musllinux: musl 1.1+ x86-64

rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.12 musllinux: musl 1.1+ s390x

rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_ppc64le.whl (2.0 MB view details)

Uploaded CPython 3.12 musllinux: musl 1.1+ ppc64le

rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_i686.whl (5.1 MB view details)

Uploaded CPython 3.12 musllinux: musl 1.1+ i686

rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_aarch64.whl (1.8 MB view details)

Uploaded CPython 3.12 musllinux: musl 1.1+ ARM64

rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.2 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ s390x

rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ ppc64le

rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl (5.5 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ i686

rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ ARM64

rapidfuzz-3.5.2-cp312-cp312-macosx_11_0_arm64.whl (1.1 MB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

rapidfuzz-3.5.2-cp312-cp312-macosx_10_9_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.12 macOS 10.9+ x86-64

rapidfuzz-3.5.2-cp312-cp312-macosx_10_9_universal2.whl (2.6 MB view details)

Uploaded CPython 3.12 macOS 10.9+ universal2 (ARM64, x86-64)

rapidfuzz-3.5.2-cp311-cp311-win_arm64.whl (860.6 kB view details)

Uploaded CPython 3.11 Windows ARM64

rapidfuzz-3.5.2-cp311-cp311-win_amd64.whl (1.7 MB view details)

Uploaded CPython 3.11 Windows x86-64

rapidfuzz-3.5.2-cp311-cp311-win32.whl (2.1 MB view details)

Uploaded CPython 3.11 Windows x86

rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ x86-64

rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ s390x

rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_ppc64le.whl (2.0 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ ppc64le

rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_i686.whl (5.1 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ i686

rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_aarch64.whl (1.8 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ ARM64

rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ s390x

rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ppc64le

rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl (5.5 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ i686

rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

rapidfuzz-3.5.2-cp311-cp311-macosx_11_0_arm64.whl (1.1 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

rapidfuzz-3.5.2-cp311-cp311-macosx_10_9_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

rapidfuzz-3.5.2-cp311-cp311-macosx_10_9_universal2.whl (2.6 MB view details)

Uploaded CPython 3.11 macOS 10.9+ universal2 (ARM64, x86-64)

rapidfuzz-3.5.2-cp310-cp310-win_arm64.whl (859.7 kB view details)

Uploaded CPython 3.10 Windows ARM64

rapidfuzz-3.5.2-cp310-cp310-win_amd64.whl (1.7 MB view details)

Uploaded CPython 3.10 Windows x86-64

rapidfuzz-3.5.2-cp310-cp310-win32.whl (2.1 MB view details)

Uploaded CPython 3.10 Windows x86

rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ s390x

rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_ppc64le.whl (2.0 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ ppc64le

rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_i686.whl (5.1 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ i686

rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_aarch64.whl (1.8 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ ARM64

rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ s390x

rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ppc64le

rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl (5.5 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686

rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

rapidfuzz-3.5.2-cp310-cp310-macosx_11_0_arm64.whl (1.1 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

rapidfuzz-3.5.2-cp310-cp310-macosx_10_9_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

rapidfuzz-3.5.2-cp310-cp310-macosx_10_9_universal2.whl (2.6 MB view details)

Uploaded CPython 3.10 macOS 10.9+ universal2 (ARM64, x86-64)

rapidfuzz-3.5.2-cp39-cp39-win_arm64.whl (861.8 kB view details)

Uploaded CPython 3.9 Windows ARM64

rapidfuzz-3.5.2-cp39-cp39-win_amd64.whl (1.7 MB view details)

Uploaded CPython 3.9 Windows x86-64

rapidfuzz-3.5.2-cp39-cp39-win32.whl (2.1 MB view details)

Uploaded CPython 3.9 Windows x86

rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ s390x

rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_ppc64le.whl (2.0 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ ppc64le

rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_i686.whl (5.1 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ i686

rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_aarch64.whl (1.8 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ ARM64

rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ s390x

rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ppc64le

rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl (5.5 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686

rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

rapidfuzz-3.5.2-cp39-cp39-macosx_11_0_arm64.whl (1.1 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

rapidfuzz-3.5.2-cp39-cp39-macosx_10_9_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

rapidfuzz-3.5.2-cp39-cp39-macosx_10_9_universal2.whl (2.6 MB view details)

Uploaded CPython 3.9 macOS 10.9+ universal2 (ARM64, x86-64)

rapidfuzz-3.5.2-cp38-cp38-win_amd64.whl (1.7 MB view details)

Uploaded CPython 3.8 Windows x86-64

rapidfuzz-3.5.2-cp38-cp38-win32.whl (2.1 MB view details)

Uploaded CPython 3.8 Windows x86

rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ s390x

rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_ppc64le.whl (2.0 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ ppc64le

rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_i686.whl (5.1 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ i686

rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_aarch64.whl (1.8 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ ARM64

rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ s390x

rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ppc64le

rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl (5.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686

rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

rapidfuzz-3.5.2-cp38-cp38-macosx_11_0_arm64.whl (1.1 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

rapidfuzz-3.5.2-cp38-cp38-macosx_10_9_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

rapidfuzz-3.5.2-cp38-cp38-macosx_10_9_universal2.whl (2.6 MB view details)

Uploaded CPython 3.8 macOS 10.9+ universal2 (ARM64, x86-64)

File details

Details for the file rapidfuzz-3.5.2.tar.gz.

File metadata

  • Download URL: rapidfuzz-3.5.2.tar.gz
  • Upload date:
  • Size: 1.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.6

File hashes

Hashes for rapidfuzz-3.5.2.tar.gz
Algorithm Hash digest
SHA256 9e9b395743e12c36a3167a3a9fd1b4e11d92fb0aa21ec98017ee6df639ed385e
MD5 74fb54274edf15d58db24e0842cd18c1
BLAKE2b-256 8bf3bf5e82eca3b88853a5fe596bf8c94fb6f2775dc1b55b7bfee9de21afab03

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 d4b05a8f4ab7e7344459394094587b033fe259eea3a8720035e8ba30e79ab39b
MD5 e44817645b0fa7ea1ea3ec71daae11d0
BLAKE2b-256 6fa657f3bd9655c25e62699d42ab4abbc779b415c66075ab1f40527f298973f9

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 8f808dcb0088a7a496cc9895e66a7b8de55ffea0eb9b547c75dfb216dd5f76ed
MD5 3af357dbcf90d276f4b44b9207697254
BLAKE2b-256 739720df8ca80a9b29acebc61fbb5f55ef4ab35646ec3340f606470841c43ba2

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 51b5166be86e09e011e92d9862b1fe64c4c7b9385f443fb535024e646d890460
MD5 9700f77b28374c2a80847e801b338a1f
BLAKE2b-256 e87393b92e211197ac1a78179bd449be99e4355d6a34394b21400bf9bf9acaa3

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 a42c7a8c62b29c4810e39da22b42524295fcb793f41c395c2cb07c126b729e83
MD5 333b275bfff1d40a6fb1b957a57df495
BLAKE2b-256 201a867d2d79b5ad5e900fe7b2cac02ce49606eb7b2fe91c1ac1b1c1c84cd8a6

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 b847a49377e64e92e11ef3d0a793de75451526c83af015bdafdd5d04de8a058a
MD5 8188c8f17538deb83b62c505bf48f1dc
BLAKE2b-256 dcd846bb81543ef893c0871d86a8c2d4cce0b0715814a79be8cf195a6794fc91

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 58e3e21f6f13a7cca265cce492bc797425bd4cb2025fdd161a9e86a824ad65ce
MD5 c1ca29cdaddf2bcb8f9ce3baacb2fa1b
BLAKE2b-256 cdce0df880c30710512069319ae2ce4af0e118d2cb9cfbde07de11cd6906ca4d

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f2059cd73b7ea779a9307d7a78ed743f0e3d33b88ccdcd84569abd2953cd859f
MD5 85a8211955d72b4c16dcd0040bf9d253
BLAKE2b-256 1f0426d9f2dcbd4ed0645622565d6a6f0ba523c05b6e690c3cda5d4f0433af33

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 e414e1ca40386deda4291aa2d45062fea0fbaa14f95015738f8bb75c4d27f862
MD5 f5b12528d8919799eb5035a44384d997
BLAKE2b-256 36b4e3bc29fc38184a8b55975381933b8ed541e353988f0a5e2388046c9676a0

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 8501d7875b176930e6ed9dbc1bc35adb37ef312f6106bd6bb5c204adb90160ac
MD5 89471368e326629d0d8c8617a10cd62e
BLAKE2b-256 758e3970839b034a405797968c56a2bb407ec15d69f94fb0eec73255ad01f831

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 af5221e4f7800db3e84c46b79dba4112e3b3cc2678f808bdff4fcd2487073846
MD5 11b1a65ef8f1059ae4c33c85ae096a77
BLAKE2b-256 216657f734d85158c43de30b158a5b5861a5a8562f5db37877a08332b0c825d1

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-win_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-win_arm64.whl
Algorithm Hash digest
SHA256 dfc63fabb7d8da8483ca836bae7e55766fe39c63253571e103c034ba8ea80950
MD5 afd430eb1439d66cd6b483d725c6540a
BLAKE2b-256 5650306a37c0d3f1f965bcdedc5e1937bd145a20163c50f717b00d87230fae77

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 a8162d81486de85ab1606e48e076431b66d44cf431b2b678e9cae458832e7147
MD5 854709e7174b3fe56c3f8fe7b322eeeb
BLAKE2b-256 055d047dccefe6f9865109bb9b852e279d1067f5722aaf4602251192a2ade801

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-win32.whl.

File metadata

  • Download URL: rapidfuzz-3.5.2-cp312-cp312-win32.whl
  • Upload date:
  • Size: 2.1 MB
  • Tags: CPython 3.12, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.6

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-win32.whl
Algorithm Hash digest
SHA256 f823fd1977071486739f484e27092765d693da6beedaceece54edce1dfeec9b2
MD5 6f5ef9799aa9e8f4d65bf28b2e465b1e
BLAKE2b-256 ec7ec991b83968db02a5203b1f9ac93d252429407f127bfdd31eafc055d1e033

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 f6da61cc38c1a95efc5edcedf258759e6dbab73191651a28c5719587f32a56ad
MD5 6326bdbc043be5d8169a0cb918dd3a1f
BLAKE2b-256 804aa0bce4b339b266f88859542fd02bf6b243a99592748393dca53eef4a75d3

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 c04f9f1310ce414ab00bdcbf26d0906755094bfc59402cb66a7722c6f06d70b2
MD5 6aa97d68a740e3e08606a061fc48515f
BLAKE2b-256 0a8ffe7c96028349a933b3326c78d5729a58f783f7f6c2f48607b45581bd483a

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 7fb21e182dc6d83617e88dea002963d5cf99cf5eabbdbf04094f503d8fe8d723
MD5 c75a5ed78fed32980fcdef9b76928611
BLAKE2b-256 90d0200a5f6b56d73b4dc7d6084f90a8e96dc36d1b26a500e79391c7125176a8

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 fb379ac0ddfc86c5542a225d194f76ed468b071b6f79ff57c4b72e635605ad7d
MD5 5439d66bc82fced6a2c5900fae67c7f7
BLAKE2b-256 1fbdeffe2419c12762da155e809599314e7c43446f9eada8f1785222a947244a

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 358a0fbc49343de20fee8ebdb33c7fa8f55a9ff93ff42d1ffe097d2caa248f1b
MD5 6e67e0437454785b43c50682e1280ba8
BLAKE2b-256 baa55a79897ae628215c6b981dfea856fb4c676e1bf73b72f032107b076c0e85

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 32d580df0e130ed85400ff77e1c32d965e9bc7be29ac4072ab637f57e26d29fb
MD5 3c3ea91647b309e6c99e1592403312da
BLAKE2b-256 48a5ab923d7f3b9d2a10f52d77ddbbcb070319e3d3b91c4aa845262140c4e04f

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 2fbaf546f15a924613f89d609ff66b85b4f4c2307ac14d93b80fe1025b713138
MD5 3c09047b74af5589546f1aebc373ee98
BLAKE2b-256 49a87a6b64c5dfd41581953fc81cfa6871df8bebe587e570f697f7efead820e4

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 bf3093443751e5a419834162af358d1e31dec75f84747a91dbbc47b2c04fc085
MD5 8b8c89119fbb0e04e544b2c7c0205cae
BLAKE2b-256 a44b8bf19247ff5fde35e73ea3b8beaa2fa43cc1d5ca7a0158f58213bacdaf7d

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 25510b5d142c47786dbd27cfd9da7cae5bdea28d458379377a3644d8460a3404
MD5 3f265e8eac4e3a4b67e2b15aac00238c
BLAKE2b-256 1cac9c28e48cffc586d81cb92c1da74da6992ee2f2758818374bea6d3eb10794

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 43fb368998b9703fa8c63db292a8ab9e988bf6da0c8a635754be8e69da1e7c1d
MD5 42493c5c731af8289f807e4c8286aa86
BLAKE2b-256 10dc3c414f17a972c2bbe2ffbf66895661ebfcee2d6d8f3a2edea1cd14544d80

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b61f77d834f94b0099fa9ed35c189b7829759d4e9c2743697a130dd7ba62259f
MD5 2deb686469218b7ffac5be4b0e31b320
BLAKE2b-256 aed98ee5d8425c36404a835523a6becbd569ba839bdda83e128a95b56ae6299b

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 365e544aba3ac13acf1a62cb2e5909ad2ba078d0bfc7d69b1f801dfd673b9782
MD5 74baab46b39bddf873b2fca1d2a8ffc7
BLAKE2b-256 23e7a9d1082a1d8ee4175a303da4e0a67e8a7313019401b5bc81c083db4e36a8

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp312-cp312-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp312-cp312-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 04e1e02b182283c43c866e215317735e91d22f5d34e65400121c04d5ed7ed859
MD5 e5d5eaf3ffbf6e6ecd587daf55d3ec48
BLAKE2b-256 41ea77c8ff89f299f97f29860f7c0877ca3cf2b454c0df67cee21a551608d68b

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-win_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-win_arm64.whl
Algorithm Hash digest
SHA256 d55de67c48f06b7772541e8d4c062a2679205799ce904236e2836cb04c106442
MD5 9d4d4c8b2e9e9093dae05176c7f1bae3
BLAKE2b-256 8faea79d360fb34d6245a462b9e61ea284be89e25ac1125385569f29f1b7f8c4

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 666928ee735562a909d81bd2f63207b3214afd4ca41f790ab3025d066975c814
MD5 713971f16067dec92676a21c8e9573fe
BLAKE2b-256 8949e95e84ed1e5c3c69ea8849d06f8f475c41303533c86710b1c01a4f50d353

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-win32.whl.

File metadata

  • Download URL: rapidfuzz-3.5.2-cp311-cp311-win32.whl
  • Upload date:
  • Size: 2.1 MB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.6

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 99c9fc5265566fb94731dc6826f43c5109e797078264e6389a36d47814473692
MD5 0cad81b2ed512e87252f81fe689d8145
BLAKE2b-256 ec299ee7ceb8513896182ef9f9afe4ed6ad4396fed62526ec114e2e9881e2324

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 27689361c747b5f7b8a26056bc60979875323f1c3dcaaa9e2fec88f03b20a365
MD5 24cfe29c512df89745ea86a34fb7e602
BLAKE2b-256 b1790f9982858f16d7775865f3b9249f709cf343ba1ef94a15c202a7b151b827

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 76639dca5eb0afc6424ac5f42d43d3bd342ac710e06f38a8c877d5b96de09589
MD5 c4bbbf2bf30aecdae19eb368c572ab73
BLAKE2b-256 a450bfa906b3f91847126b7e76af38f9458d65531d19fe385a2d1d514a455fe7

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 53df7aea3cf301633cfa2b4b2c2d2441a87dfc878ef810e5b4eddcd3e68723ad
MD5 72dbdaf046b8537b23ee4135a9d332da
BLAKE2b-256 e2c2e489c191bf4db06b07c11921bb59c93b772df7a6071f392ca20e2bf19d13

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 66be181965aff13301dd5f9b94b646ce39d99c7fe2fd5de1656f4ca7fafcb38c
MD5 ec9b9ea33e42f5bdce2255a1926ebe1c
BLAKE2b-256 34d4a7bd84bda071942ba2070f49cbf073a51fe66bc0bd016fd9081d14705b9d

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 1062425c8358a547ae5ebad148f2e0f02417716a571b803b0c68e4d552e99d32
MD5 c9d98e81ff2a36682e34f219a1821081
BLAKE2b-256 add461417ef482de9023f85308881e810c06641cda38e66aee881e8d24375ac7

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9cdbe8e80cc186d55f748a34393533a052d855357d5398a1ccb71a5021b58e8d
MD5 e586c4a5165d925aa062adc70edb6500
BLAKE2b-256 9eae33dd7c9a6f06c25dfb7e556756fb4adbcea1ec2c8c7efc8aaecb106ac882

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 120316824333e376b88b284724cfd394c6ccfcb9818519eab5d58a502e5533f0
MD5 388eb8b17528565fcd09228dc6433a4a
BLAKE2b-256 69014098276f5ca7abb336bb6b32653147d4504c802a899d7cf333798652880e

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 fa4c0612893716bbb6595066ca9ecb517c982355abe39ba9d1f4ab834ace91ad
MD5 54ace30c0cb6098efa83ebff1a2d5c02
BLAKE2b-256 fb79749e7861e7ff070795505468d4fa511ba63d1b90203313cecff96933e71b

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 2d876dba9a11fcf60dcf1562c5a84ef559db14c2ceb41e1ad2d93cd1dc085889
MD5 0d15445196e1d2af150e14932e69ce84
BLAKE2b-256 7310ba6328b6dd542e90a95796ab672c1757bf17736fa703fce57c6654f9c4b4

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 1a4a7832737f87583f3863dc62e6f56dd4a9fefc5f04a7bdcb4c433a0f36bb1b
MD5 6d6872ef8f3a6958b1bdb92879b29ed1
BLAKE2b-256 6fdd273186a30879569e648351e89f3a7ad8bfbaf422d79422a88d111a1ca436

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 97b043fe8185ec53bb3ff0e59deb89425c0fc6ece6e118939963aab473505801
MD5 62c10329b0cfb26a6ec29d15edce3812
BLAKE2b-256 96502575ed599005822a56ecf58569e8aabdd7bb4d57046087c24c5ff0277b43

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 fdfdb3685b631d8efbb6d6d3d86eb631be2b408d9adafcadc11e63e3f9c96dec
MD5 311153db560a688e2740c15ce02ad202
BLAKE2b-256 5d47309addcb9e8d818a8456956ffa9f4db57be11187515b64d24ca0d500e3a4

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp311-cp311-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp311-cp311-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 bff7d3127ebc5cd908f3a72f6517f31f5247b84666137556a8fcc5177c560939
MD5 7c046f18ec37720b05bf62f77dfc2b9b
BLAKE2b-256 288839df1cf00dd4d56d4d8afae4404da9a9505d19db3d96d5e882f77b1ef9d1

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-win_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-win_arm64.whl
Algorithm Hash digest
SHA256 1dd2542e5103fb8ca46500a979ae14d1609dcba11d2f9fe01e99eec03420e193
MD5 45a28a6a5b83adc45ef232a21fd674b2
BLAKE2b-256 55e14a7978846e8da910a4cd5f20bbe3c3af8e4ec5f7968dfb026840e6120eb6

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 6541ffb70097885f7302cd73e2efd77be99841103023c2f9408551f27f45f7a5
MD5 f1905d264739869ce33b0313813d22aa
BLAKE2b-256 de8f404add97fef8c94bb41d6d1be08c5f8430f48d280fd3cee979cceab94c46

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-win32.whl.

File metadata

  • Download URL: rapidfuzz-3.5.2-cp310-cp310-win32.whl
  • Upload date:
  • Size: 2.1 MB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.6

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 2cf9f2ed4a97b388cffd48d534452a564c2491f68f4fd5bc140306f774ceb63a
MD5 8c214e95be7d57557a395744ad3b7543
BLAKE2b-256 1cb32ea6c9049814ac9200f0be362e494854e22b04d93421ee156a6242b8f89e

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 c1d33a622572d384f4c90b5f7a139328246ab5600141e90032b521c2127bd605
MD5 0ca7a23cfdb119170519e83d10ba837f
BLAKE2b-256 8867797ee50d4b52944c857b22af39e9d202a77d3d915767d5394eb3759969e6

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 affb8fe36157c2dc8a7bc45b6a1875eb03e2c49167a1d52789144bdcb7ab3b8c
MD5 7937bbd6670c91db71764171e8e6284c
BLAKE2b-256 6337950e6bd5ce18341a93ec114f1076e63177b0532fd5d7e93a5330bda8abd0

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 b4e9ded8e80530bd7205a7a2b01802f934a4695ca9e9fbe1ce9644f5e0697864
MD5 2a50247145f55b8aa29383ecd192c441
BLAKE2b-256 0aa0b7641250c7776d207ae59e83d7d549adee10fd4286e0eac8bd77dd35a671

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 12424a06ad9bd0cbf5f7cea1015e78d924a0034a0e75a5a7b39c0703dcd94095
MD5 ca2f24402df6a23c7f6b4fa32c5260ee
BLAKE2b-256 e78b1faf79fdb4103ddf6d84c8540fbca77b649ecde6cad244883f2d02f50f27

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 852b3f93c15fce58b8dc668bd54123713bfdbbb0796ba905ea5df99cfd083132
MD5 52a82cab5882628efe727339c42730d9
BLAKE2b-256 6c82338f9494c7dffaf8d089b24d2293b1769f3534673debbebb1f37b8eefc7b

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 8658c1045766e87e0038323aa38b4a9f49b7f366563271f973c8890a98aa24b5
MD5 071ccad2601e9ec4a37fb1d573f9b76f
BLAKE2b-256 586955f7a10f5760d8539081718f1a87172cd5b0ea21f6c1232c40a6b7cf9470

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 84be69ea65f64fa01e5c4976be9826a5aa949f037508887add42da07420d65d6
MD5 b541a0ce140ddb38cb35f8526afeccd1
BLAKE2b-256 9fc210e62fe5ed9efb6b02d4ae9efc994fe10cba1356b277eb59c1f43d7f7109

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 5afc1fcf1830f9bb87d3b490ba03691081b9948a794ea851befd2643069a30c1
MD5 3270f762584d0671cd467776d674c420
BLAKE2b-256 25f3938bb145bb97012796ca0ec93a3f110ec0f8878a9baa13da06089612b432

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 8f2df3968738a38d2a0058b5e721753f5d3d602346a1027b0dde31b0476418f3
MD5 a36cf9de16dda0b98889cdde9c8eb543
BLAKE2b-256 c7ea440f62956cdf8e765d2f755b2cd38e65be627744cdf0d434a14800030359

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 d05146497672f869baf41147d5ec1222788c70e5b8b0cfcd6e95597c75b5b96b
MD5 fdcd1cc5f22e6f71e67b41f84bad3740
BLAKE2b-256 788498f8ea6f1e6d214b13e2b0c6ebe7f272e2473474cc398e3cdd10d8176f11

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e0f448b0eacbcc416feb634e1232a48d1cbde5e60f269c84e4fb0912f7bbb001
MD5 c55c140f7939e41b2ea535a32d0dae98
BLAKE2b-256 d044279a4b8ac631f65a5168651ed1bdef20a996a50a693464fca5410a8239c2

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 22877c027c492b7dc7e3387a576a33ed5aad891104aa90da2e0844c83c5493ef
MD5 f7313dd3fa1eed050da688e0903fbc11
BLAKE2b-256 13dd5f0859ee48595167cb8ee8b4464e5298dbaf67bd012ee19f5a3274921819

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 1a047d6e58833919d742bbc0dfa66d1de4f79e8562ee195007d3eae96635df39
MD5 f27be3aad32efb4d6a89a7cdb108deae
BLAKE2b-256 4e3546e359dd232ac91ff100d0ef780694d2a6f88ce46c809520431070f8962d

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-win_arm64.whl.

File metadata

  • Download URL: rapidfuzz-3.5.2-cp39-cp39-win_arm64.whl
  • Upload date:
  • Size: 861.8 kB
  • Tags: CPython 3.9, Windows ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.6

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-win_arm64.whl
Algorithm Hash digest
SHA256 c5075ce7b9286624cafcf36720ef1cfb2946d75430b87cb4d1f006e82cd71244
MD5 ac58fdfbab410072123d66fbb5a0107a
BLAKE2b-256 22030e51c25f542a2c8f55ec470ff864dc6ca3edc221fbba5496831fda187ab1

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: rapidfuzz-3.5.2-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 1.7 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.6

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 58ee34350f8c292dd24a050186c0e18301d80da904ef572cf5fda7be6a954929
MD5 c3ea932c3e0823666fc2d13d29452019
BLAKE2b-256 b2bd0f08f481c840103f6c996d038ebf57ea4e904d5ace7369f46d0a6ac4e809

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-win32.whl.

File metadata

  • Download URL: rapidfuzz-3.5.2-cp39-cp39-win32.whl
  • Upload date:
  • Size: 2.1 MB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.6

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 97f811ca7709c6ee8c0b55830f63b3d87086f4abbcbb189b4067e1cd7014db7b
MD5 265e0a1b3b4f9d2375caec3558c8176a
BLAKE2b-256 702c22832cbb4a35d96261a6ea563d490f4ca5b132dff77972889328464f1501

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 1d5a686ea258931aaa38019204bdc670bbe14b389a230b1363d84d6cf4b9dc38
MD5 e2f7c9b0c877c968c8d3936697a26f22
BLAKE2b-256 fb36a81e21eca9072385c634ea9c48e36f9f9063d8b31964e46c508fda07533a

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 b581107ec0c610cdea48b25f52030770be390db4a9a73ca58b8d70fa8a5ec32e
MD5 814c65eca68c64b532c7ca9106de8f29
BLAKE2b-256 d97eb10c2860dc140f10ff9e592234a954659e04c0a6b4d5f4b7c7b2ffa58188

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 54f0061028723c026020f5bb20649c22bc8a0d9f5363c283bdc5901d4d3bff01
MD5 05f12103df676779f00a81ea59b4b0ab
BLAKE2b-256 95c7afd114169e2deec5789f6e5614fcac60037f9ed0efe37841e7cf64ea2afc

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 908ff2de9c442b379143d1da3c886c63119d4eba22986806e2533cee603fe64b
MD5 cf78dd19fea8e8a90b7ab023e5bec6ad
BLAKE2b-256 5737c12e6dfe27849c50c7ed38e799c9589a27d40ec5f18f47f981f286b1ed91

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 de89585268ed8ee44e80126814cae63ff6b00d08416481f31b784570ef07ec59
MD5 c1c341a55bc28a0fa762ef0e0f95c927
BLAKE2b-256 297879ab99f33c91e0caecf5416af53d05eeea13fc46091e4b8eb00b726d58c9

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ada0d8d57e0f556ef38c24fee71bfe8d0db29c678bff2acd1819fc1b74f331c2
MD5 e6e88996277ce109c08c19a5f5b21deb
BLAKE2b-256 b45678028f9aace3a58894afc276477169c4e3e79c16d0abbac2a24c09399b24

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 00be97f9219355945c46f37ac9fa447046e6f7930f7c901e5d881120d1695458
MD5 3a0308e067fecf236a42e1fcb2803827
BLAKE2b-256 4e95fbba9347da22d4dc98a3e6f37750424e024c6ac605754deaee5f925fd20a

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 c29958265e4c2b937269e804b8a160c027ee1c2627d6152655008a8b8083630e
MD5 c266c38163374f508955f1403498c020
BLAKE2b-256 0169abd61c896f43300db1fd2b45e7bc91a5622b797ebdd463deb5b088df7f92

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 b2e8b369f23f00678f6e673572209a5d3b0832f4991888e3df97af7b8b9decf3
MD5 7272a1f8be5bf067de10f865e59887cc
BLAKE2b-256 2770dffc9612ad34ca7fb61cecd98bbe296696e05d7548577483f395ac401729

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 e5fd627e604ddc02db2ddb9ddc4a91dd92b7a6d6378fcf30bb37b49229072b89
MD5 efc35c131fdd9900d41d1e4e5b89b983
BLAKE2b-256 b9a51b9a45faa95eda11f2527c248f7c3d7676db498b1f5c7c580e6f888aced8

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 2bacce6bbc0362f0789253424269cc742b1f45e982430387db3abe1d0496e371
MD5 6185242742370cfda8f96a3cf94b21c9
BLAKE2b-256 e03c1915a51a67ee15cc07a6a0f2576e8dcbc3b130d0018129bd7597d0086692

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 75d8a52bf8d1aa2ac968ae4b21b83b94fc7e5ea3dfbab34811fc60f32df505b2
MD5 4467548ba91bf039e6d4ee0aaa4775d4
BLAKE2b-256 851738d7933d8440f2335b506c0e003457d3894cc1ba61f1cdbb0b196f846d64

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 089a7e96e5032821af5964d8457fcb38877cc321cdd06ad7c5d6e3d852264cb9
MD5 8810ebe216b0f83812db19bbe87bdbb9
BLAKE2b-256 7ec47d0312904c80b2414a7a3b953bd08ef9cc04cc80077dcd89889b86278740

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: rapidfuzz-3.5.2-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 1.7 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.6

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 e3f2be79d4114d01f383096dbee51b57df141cb8b209c19d0cf65f23a24e75ba
MD5 084b461fb8224e488503b7ccd0f53a42
BLAKE2b-256 5903a8366004c805f16dc1dc4f91db6c14580341f99e73095281b55617931875

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-win32.whl.

File metadata

  • Download URL: rapidfuzz-3.5.2-cp38-cp38-win32.whl
  • Upload date:
  • Size: 2.1 MB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.6

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 2da3a24c2f7dfca7f26ba04966b848e3bbeb93e54d899908ff88dfe3e1def9dc
MD5 64a731a995a568bc010444fe9dde20fb
BLAKE2b-256 cbfae9adde445fa9b1a63b45b8a76a1938f972faf131dc57f36355ad774adcdf

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 6b2ad5516f7068c7d9cbcda8ac5906c589e99bc427df2e1050282ee2d8bc2d58
MD5 0f6d7f487f4c9475f1820d0dabb18fe0
BLAKE2b-256 d3c6c45895763836d6cb838e9f89e467e7fffb99a9842f06a791134af6f400d9

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 0fef4705459842ef8f79746d6f6a0b5d2b6a61a145d7d8bbe10b2e756ea337c8
MD5 103601c95f12afe62d32a5df8d71ca63
BLAKE2b-256 158673a1030002e12571cfd7a830f97baffdb95af55b7646846f21072ddaef1c

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 40139552961018216b8cd88f6df4ecbbe984f907a62a5c823ccd907132c29a14
MD5 d56c263819b6bcd70445e01c3b38ffcb
BLAKE2b-256 f71000a0452796bd46a4460c49382ea20350435d36ea27d1ba74c2fe6fb2c150

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 b685abb8b6d97989f6c69556d7934e0e533aa8822f50b9517ff2da06a1d29f23
MD5 9d247270b481998299595d5b36d2c57e
BLAKE2b-256 6d2c0001198986db088ebd0b53ae51bcf1676a168567316257e6eb6d7813aab8

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 db45028eae2fda7a24759c69ebeb2a7fbcc1a326606556448ed43ee480237a3c
MD5 a31e08168e41dec081f7354ef02032ab
BLAKE2b-256 30ec332137241629ec2c235ea5880060018b2cda91caab6a7aa3e9da6ae893b3

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1962d5ccf8602589dbf8e85246a0ee2b4050d82fade1568fb76f8a4419257704
MD5 b6e55651883497518262860b8ba11715
BLAKE2b-256 feefb44d8c1c6aa68c43bfca39c2cb1ef029b31b61d4acd90a3532f6aea47333

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 7cdf92116e9dfe40da17f921cdbfa0039dde9eb158914fa5f01b1e67a20b19cb
MD5 5bab7479157926898e4368923473f1b2
BLAKE2b-256 75ed067bbe5044b95979ab9e2492cae27d6082402b9c575e061579f3a6aa4975

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 73e14617a520c0f1bc15eb78c215383477e5ca70922ecaff1d29c63c060e04ca
MD5 9abe6773e672027954f439c37ce26f08
BLAKE2b-256 8c208932f362ad6538c02d572d7f2b6d8537709a95a78a59619d2d011e0508c1

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 abafeb82f85a651a9d6d642a33dc021606bc459c33e250925b25d6b9e7105a2e
MD5 7e4baec2f05f423698495b0ed2fd4e4e
BLAKE2b-256 9d889c03ef6fb5076d022729ffc78eeb4c69991aa18276143d6891daab83ea6d

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 54576669c1502b751b534bd76a4aeaaf838ed88b30af5d5c1b7d0a3ca5d4f7b5
MD5 9a06ef646ac92cdf657bc1083810d716
BLAKE2b-256 d1d7c0b954f363f8a0a57de1006f379211847eebe5f8dc2eae09aa7b1445512b

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 467a4d730ae3bade87dba6bd769e837ab97e176968ce20591fe8f7bf819115b1
MD5 23920ccde07564f8de068a05e0565e9e
BLAKE2b-256 127dc9eff8d3e01bb751b2344bf9abf0c97ad48232d7655dd7a3a9054780eb51

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 dd6384780c2a16097d47588844cd677316a90e0f41ef96ff485b62d58de79dcf
MD5 de147b74553580aa56c986fed9315989
BLAKE2b-256 6331b636dffb3cdb70c88a53cf791a72348539b55ae7c2f7bbad67f6ad7469e8

See more details on using hashes here.

File details

Details for the file rapidfuzz-3.5.2-cp38-cp38-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-3.5.2-cp38-cp38-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 df8fae2515a1e4936affccac3e7d506dd904de5ff82bc0b1433b4574a51b9bfb
MD5 038a883391b94daa5d1c56e669aeec4d
BLAKE2b-256 e24d18f218bbf1bc214eeb1d3f6ab5bacc335e691c79b80fff5716ea3d825348

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page