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 >=3.6
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 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

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.

Scorers

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

Simple Ratio

> fuzz.ratio("this is a test", "this is a test!")
96.55171966552734

Partial Ratio

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

Token Sort Ratio

> fuzz.ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear")
90.90908813476562
> fuzz.token_sort_ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear")
100.0

Token Set Ratio

> fuzz.token_sort_ratio("fuzzy was a bear", "fuzzy fuzzy was a bear")
83.8709716796875
> fuzz.token_set_ratio("fuzzy was a bear", "fuzzy fuzzy was a bear")
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', 100, 1), ('New York Giants', 78.57142639160156, 2)]
> process.extractOne("cowboys", choices, scorer=fuzz.WRatio)
("Dallas Cowboys", 90, 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 >=3.6
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

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

This version

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-2.11.0.tar.gz (812.7 kB view details)

Uploaded Source

Built Distributions

rapidfuzz-2.11.0-pp39-pypy39_pp73-win_amd64.whl (930.3 kB view details)

Uploaded PyPy Windows x86-64

rapidfuzz-2.11.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

rapidfuzz-2.11.0-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

rapidfuzz-2.11.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

rapidfuzz-2.11.0-pp39-pypy39_pp73-macosx_10_9_x86_64.whl (1.7 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

rapidfuzz-2.11.0-pp38-pypy38_pp73-win_amd64.whl (930.7 kB view details)

Uploaded PyPy Windows x86-64

rapidfuzz-2.11.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

rapidfuzz-2.11.0-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

rapidfuzz-2.11.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

rapidfuzz-2.11.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl (1.7 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

rapidfuzz-2.11.0-pp37-pypy37_pp73-win_amd64.whl (930.7 kB view details)

Uploaded PyPy Windows x86-64

rapidfuzz-2.11.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

rapidfuzz-2.11.0-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

rapidfuzz-2.11.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

rapidfuzz-2.11.0-pp37-pypy37_pp73-macosx_10_9_x86_64.whl (1.7 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

rapidfuzz-2.11.0-cp311-cp311-win_amd64.whl (993.1 kB view details)

Uploaded CPython 3.11 Windows x86-64

rapidfuzz-2.11.0-cp311-cp311-win32.whl (898.6 kB view details)

Uploaded CPython 3.11 Windows x86

rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_x86_64.whl (2.4 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ x86-64

rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_s390x.whl (2.0 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ s390x

rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_ppc64le.whl (2.0 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ ppc64le

rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_i686.whl (2.4 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ i686

rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_aarch64.whl (1.7 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ ARM64

rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ s390x

rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ i686

rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

rapidfuzz-2.11.0-cp311-cp311-macosx_11_0_arm64.whl (1.1 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

rapidfuzz-2.11.0-cp311-cp311-macosx_10_9_x86_64.whl (1.8 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

rapidfuzz-2.11.0-cp311-cp311-macosx_10_9_universal2.whl (2.4 MB view details)

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

rapidfuzz-2.11.0-cp310-cp310-win_amd64.whl (991.6 kB view details)

Uploaded CPython 3.10 Windows x86-64

rapidfuzz-2.11.0-cp310-cp310-win32.whl (896.0 kB view details)

Uploaded CPython 3.10 Windows x86

rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_x86_64.whl (2.4 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_s390x.whl (2.0 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ s390x

rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_ppc64le.whl (1.9 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ ppc64le

rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_i686.whl (2.4 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ i686

rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_aarch64.whl (1.7 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ ARM64

rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ s390x

rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686

rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

rapidfuzz-2.11.0-cp310-cp310-macosx_11_0_arm64.whl (1.0 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

rapidfuzz-2.11.0-cp310-cp310-macosx_10_9_x86_64.whl (1.8 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

rapidfuzz-2.11.0-cp310-cp310-macosx_10_9_universal2.whl (2.4 MB view details)

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

rapidfuzz-2.11.0-cp39-cp39-win_amd64.whl (993.0 kB view details)

Uploaded CPython 3.9 Windows x86-64

rapidfuzz-2.11.0-cp39-cp39-win32.whl (898.1 kB view details)

Uploaded CPython 3.9 Windows x86

rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_x86_64.whl (2.4 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_s390x.whl (2.0 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ s390x

rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_ppc64le.whl (1.9 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ ppc64le

rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_i686.whl (2.4 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ i686

rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_aarch64.whl (1.7 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ ARM64

rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ s390x

rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686

rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

rapidfuzz-2.11.0-cp39-cp39-macosx_11_0_arm64.whl (1.1 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

rapidfuzz-2.11.0-cp39-cp39-macosx_10_9_x86_64.whl (1.8 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

rapidfuzz-2.11.0-cp39-cp39-macosx_10_9_universal2.whl (2.4 MB view details)

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

rapidfuzz-2.11.0-cp38-cp38-win_amd64.whl (994.3 kB view details)

Uploaded CPython 3.8 Windows x86-64

rapidfuzz-2.11.0-cp38-cp38-win32.whl (899.3 kB view details)

Uploaded CPython 3.8 Windows x86

rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_x86_64.whl (2.4 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_s390x.whl (2.0 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ s390x

rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_ppc64le.whl (1.9 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ ppc64le

rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_i686.whl (2.4 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ i686

rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_aarch64.whl (1.7 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ ARM64

rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ s390x

rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686

rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

rapidfuzz-2.11.0-cp38-cp38-macosx_11_0_arm64.whl (1.1 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

rapidfuzz-2.11.0-cp38-cp38-macosx_10_9_x86_64.whl (1.8 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

rapidfuzz-2.11.0-cp38-cp38-macosx_10_9_universal2.whl (2.4 MB view details)

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

rapidfuzz-2.11.0-cp37-cp37m-win_amd64.whl (987.3 kB view details)

Uploaded CPython 3.7m Windows x86-64

rapidfuzz-2.11.0-cp37-cp37m-win32.whl (894.9 kB view details)

Uploaded CPython 3.7m Windows x86

rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ x86-64

rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_s390x.whl (2.0 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ s390x

rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_ppc64le.whl (1.9 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ ppc64le

rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_i686.whl (2.4 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ i686

rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_aarch64.whl (1.7 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ ARM64

rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ s390x

rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ i686

rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

rapidfuzz-2.11.0-cp37-cp37m-macosx_10_9_x86_64.whl (1.8 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

rapidfuzz-2.11.0-cp36-cp36m-win_amd64.whl (980.9 kB view details)

Uploaded CPython 3.6m Windows x86-64

rapidfuzz-2.11.0-cp36-cp36m-win32.whl (888.5 kB view details)

Uploaded CPython 3.6m Windows x86

rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ x86-64

rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_s390x.whl (2.0 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ s390x

rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_ppc64le.whl (1.9 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ ppc64le

rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_i686.whl (2.4 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ i686

rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_aarch64.whl (1.7 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ ARM64

rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ x86-64

rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ s390x

rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ i686

rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ARM64

rapidfuzz-2.11.0-cp36-cp36m-macosx_10_9_x86_64.whl (1.8 MB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file rapidfuzz-2.11.0.tar.gz.

File metadata

  • Download URL: rapidfuzz-2.11.0.tar.gz
  • Upload date:
  • Size: 812.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for rapidfuzz-2.11.0.tar.gz
Algorithm Hash digest
SHA256 03af4a644c7785d2a12d43fdc58076415452426c2ba92b9141768e5df4baf95f
MD5 945b3cbf933b269529e273ea1508e30d
BLAKE2b-256 d5f00dbbabd6c6044c55227fc7a25190ed177d7255f0bfce29a652c4a18b8e48

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 a66b699f9c048d3c319b024a9d0c67eb166327ac2e516b10bf7ef97ec83b8b1b
MD5 00286bcb9a79593d8c0c17abf7135e8d
BLAKE2b-256 0d94d1ceae67ec8f683e4a4ec673fa2b9719b273a5d459b25890a74632da9661

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 baac0a4d5f416e73be0110c87ac6f3c95da6b4e8811b3ed745b3fe40261947d6
MD5 78eeab2ce27fcce43566555428f84074
BLAKE2b-256 a74334bcb8f8f4a7746382b5def7a4f2c1174decd8b47e33d34ab08ac2afedc8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 0f7be4f18e860ada62a97bcf9ae4f8bc2d71368449aa0f1edfe1b8ff485b3b6a
MD5 a23a8b7d6ebd6583b204038e4a312c00
BLAKE2b-256 99a8f5980ef1b788f99c85d904071a59c3441f72e2dc05830a7fca7bc3ad0479

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 392314ae4dad88244d6e12345980d880f20e4693d819d1ea9218f887de7648de
MD5 af52a52826ee5720e9366815c07aa805
BLAKE2b-256 7a6392be6c6910c3287147ebc65945a33ffc9a383846813eb88fcf37b7ef56bf

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp39-pypy39_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 c94cf387b6859b4ca8e1fa36f375fe59b8a2476d05e76fb5df081560ef67ad92
MD5 97c0a2c74b797a3310e406266c9e4c1a
BLAKE2b-256 c46bbc1a1cd0760eeab4462809a74e54c07b74161c26e7be5efcfd421eb5679a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 d95849df62c67ad0fc162ab8e42eb95aab690df175c987bb20bf66734333cbf0
MD5 3e7a860e4506d3a41d0ac787c2848418
BLAKE2b-256 a9f1a96ea403bc480b777c5f9ba063f0511891ab67c521c856d4e7c2f2793e4d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ea1b52ec9250c3e4a5db2fda027102a828c33ed45f12e396157b0d7282344f45
MD5 f53023edbd14d360db1a3699741e7c5b
BLAKE2b-256 168c95382be304844e7a5fc2fd08e66fc1e9ca6c27adec477362b0b77ad57fea

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 464e4621cf6f2aa69a0af8d4b81cdbe37ca265ccb15ae25ba265f9ab2ac14055
MD5 4851773bf1b05e8d30d7632e95c2ad44
BLAKE2b-256 d8732926c8dd95b76fbc8f2b4b45ba9c909301c08194eace897c239fb2f4c661

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 7174d028c85db4e1f722c418935814e76c2f3fbf26d6f786a9e3d0d643ffea70
MD5 1807ea38b090674285042cd697a6d709
BLAKE2b-256 f11ca7580a1d667b4867d5b645f05730e40a9699d0d0919f87b73656a27c6909

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ab4af3ffdf52c9076ef4805e0fd547e733b5e8090a555de9e82049749f5b5013
MD5 9cc4d056c5a248cfebc1521a2c9a3ffd
BLAKE2b-256 a0d62e7f383f3aadd185846a797ce7ff242458dc0b8cc4de6d37a98d815feb5b

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp37-pypy37_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp37-pypy37_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 c726271647dae2fe379b78af0c4ca34b8b056ef816443f12c28a2984a4ca8b10
MD5 5ffe60eba5bd553b4202de75300b0b55
BLAKE2b-256 80cde80795911a8f4ffd1064ea1547f9c54a203401a5c3b48f1152e9588d9494

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2bda7239d62da0944e385f6755f195982922a3a233e5cfb6fa407a2b1340fc08
MD5 e8827f47ab3735d497aa4888595cbda1
BLAKE2b-256 4d3951f265ab6a525700bd8c6fe7f21b1184e2f3f2db48766d18c993ecc3959e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 f7758eef4a9a458b4c9cefe1a5890fa06ba27c81d5ad98f5040dffdea5542806
MD5 c5d6f841ce89cac1ce69d770eab732d0
BLAKE2b-256 51f647ae0f161250c4559451b8df321fa1c60b5dc32258c93494278b6a474964

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 663cd07f1a68c01ce2aedca936b743407073b1938c33fb9f01432bf1dd645118
MD5 e5446c295ca4be501eca374e2c4a6f58
BLAKE2b-256 0aa41dca3b9e0fda34a4006c11dea4ed386698ccf517774154879cb17d69a9df

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-pp37-pypy37_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-pp37-pypy37_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 d4e60f35c18f9edea9e6cfb60f793c1991e813c9bac3cf40c22339d22a6efffa
MD5 2f7153c32eaaf5f07263704bd2d7637b
BLAKE2b-256 2e2a00f28fcce1a8200737acca238f469c2285a286c19c36e2e889fb25ee1ba0

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 3462e59481c12e454fe41fe995d243cbb262d49010666e908849d9f255483789
MD5 b21cadd7f0de9162e13b1d1450744103
BLAKE2b-256 582d80aa988df4017aa1081cb659303e92d92554f929d29aa8c902abfaf9a75a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.11.0-cp311-cp311-win32.whl
  • Upload date:
  • Size: 898.6 kB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 e17b25c1ff2be2125391bf5af422fa8acea12d04bc2f4f5b833f1d3f17ea6a82
MD5 6d00e0a4f29e1c8a2eea7409b4538613
BLAKE2b-256 5bdce256933a0cf0879df334112fa99551f1c3d125d77a14738b5a2f7d5178fb

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 5d68d48fd5a1b1265575f5c189fb34ea3a8abe9328af220015bf43fb23dcfba2
MD5 3e4b981b9b0a31e56b7c1e7c122bac45
BLAKE2b-256 f74f7a59baa756d275c8223af3aaa60d29f6f39b5f531d8b5dbc38d529888fe7

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 e74e89779e76fd3344817fac15a0e7086a8dca14cbefeea00d07f77ff0a251bc
MD5 912dcd482ec2752f14bedc89fb7ca650
BLAKE2b-256 3ff52bde77de980bbcd100887d9a67fb2c6adb4c7c958838eaed5b425be21949

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 4655434ebfd3580eccdd1ce288334307ee1685f070d2270b2fc43326c488e177
MD5 562142c51270c06c659b23575fdd5fd5
BLAKE2b-256 0637993681e8cd54a6382bfa657b26b7b34dc678f8620aa9c17185bde29a542b

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 730ab53a172c06172b92be7f2d74bb6f3aa5d5aa09638eb52856ed1e8715a06c
MD5 2e1d581a294134d39bae581d56fa2836
BLAKE2b-256 67a64908978626ec040f2d7a6a8f8bb5d11f0c69d5fb4d79a542c89ed034d2b1

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 5cfbb4d12945d425818a46d6ed26a559f8ada3126b5e08d68fbf2960e1c6c6c8
MD5 2f5c56b8e6ed1a0be5b6b4207cb08d05
BLAKE2b-256 4e872fa183cdd98a8783576dda4554bff1336161b4d1a0e5c151e21239763ff7

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 05acd12a54c2266e214709e42cb37b1f92bcbde753058172427ac584a72f4ea0
MD5 ea0f62be9f01b3954006b1403f6c3de6
BLAKE2b-256 927f556d30dae15a19396d78c71b84b16a7340a15b1972f7fa956ab4ed7abf07

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 9eda2793e0956f6931f304a84c2343c62dfa8f42448aea18012c521c18ee4e1f
MD5 d874db5fdcc593a768f36cedbb487b8f
BLAKE2b-256 578eb87c6d9afbd2bbca66f863b623a08d43f21c2ccfbac19c71d537d7100354

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 b819bd94b01b25b47c67c53a48b7909c055f749420e1d1046d4fd9ba514b91c0
MD5 75e9b2db7be7354c119a65ccd085686d
BLAKE2b-256 def36815503568136dc6630185fb93b2037e6bf1e77095e7e6bd89c2c4f6917e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 4a40015662076e7db9241ff360d901cf3821fba2aa6f36c21c74ecf7ff6e30fc
MD5 15b50026df0f31615c2ee5467c28983e
BLAKE2b-256 bd4c1b65a388af6424e20ea11bc53d4a0b01ea8bf8ac6bdb0fb38b363266db59

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 cb48a57cbf50c8216920448628a724642a75b56f8f2d0557fda3cd52a43a3322
MD5 21084ae7b2658f1473296565b7b93f38
BLAKE2b-256 7634c85bba79532378909dc097533b2bf899c5d39c9d90edb2b7bfb8dd4f64e6

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 08bee7aecd315d21edaad315b9f7d30942562820352649d2d796cbbb4eeba041
MD5 17b467fe7852c2fb3f02066d01411b82
BLAKE2b-256 43cebe7ad9aaf7c61242d71c2b6047bb23b85abe829edb72b39a94432f58a794

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 6cc6717b00c4ced50c53f6f7813abc676ad18ae8f2e970c4d2ac113ea8a7c984
MD5 45a13fe5da1de59fb4a6a3ad3e54fb0d
BLAKE2b-256 d833246e26f605235fc204e54598fc85e23aea85b027dcfbd9d1a501d919a8ac

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp311-cp311-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp311-cp311-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 fe71fd1167cd0411e90b5244c9d78f784dcf390f63f6ee44a2acece56bceb8fa
MD5 598d9d524cf5f10fc30836f5edd4fbe7
BLAKE2b-256 63185285a36942f2a9d6cc8992f6d365aeafec62d932ea99617cffac2f547929

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 bcbad256627864759bff6ce76e8b9ccde03ba7aef3e7e5e8be02c914e2e3d8a0
MD5 2b70b76689aaf52bf405b0c7e57b2757
BLAKE2b-256 3088ce02ab64798acb966f74ef34526257ef99eae3fb03ff2cb104673670e284

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.11.0-cp310-cp310-win32.whl
  • Upload date:
  • Size: 896.0 kB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 a08619daf876009912dd39c41f096c0eeefdd19195c38b464ea56e2863a983ad
MD5 deb5acdecaf3547217d2875ee58b0c67
BLAKE2b-256 edc32046b0342aa341b50decc546abcd669aea512589d6f5542a51f8e238211a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 6113fa742ae784e455e3b0c7ac4609fc9cf83ef2d9c1c780cadcacceb1434d9b
MD5 9b57a7dea7b0e2f7de2b6fb05d0fbe4b
BLAKE2b-256 e4b6b5b4162d079970eac64297c18d9abb20592ce90056b22a53a22cf9ee8c5d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 957baeb7d069b6ab754acb9a61e72d87a470d7f7aaf0c8a7fbb792279cf72ce6
MD5 22792b41cb4ccdb4f0552bd6f405a841
BLAKE2b-256 829c2aa78eca3e108b5ff3f85ec10477c4de146646fbef7b68263f30ad5b28be

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 b710fbe85f79141263d1ace623c3828d2538288d053e9894a8217625c6c15d90
MD5 be2d2fa70a46ddce8faf0b4ade380d8a
BLAKE2b-256 a6a491c406418f726cf1ba5dc5d45aae5b565465d5024a033f0863bc84368e75

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 133c0bdc6d3e8ce5888607b0b15436d1a6f08456eb4dce0344aa5577e965c512
MD5 e2d8178c58ec1ca9eada01137a2d7b4f
BLAKE2b-256 f932a1b571964d4d89d8c911dc4539a98b61f2a263121ff68de466792e73cf04

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 6569551762ba99a5acdcec3f83dbf17a2121acd263d16d0d96f80401f09f2dd6
MD5 cdd2e9c213ed0efe430fd366e8f3bc92
BLAKE2b-256 0d1df40ddf7f63fefcca7c6be3fdc822e1b1ed1faf685e018379bee4181a8b8a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 647861aa2b01ab3fd95b0a2db38bca2699fc17c6906fccd4e6df2c2d21ea67b4
MD5 35f43543ee8bbd55d0c90b117b5173b9
BLAKE2b-256 c2dcc593110d2bea6dc7f011943b0f52520b04e27a278e2df702b0e84ddc11c8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 1e5a3a7c4605ec557908e8b59cffee29ae3beabf6920bc1af595a8feee4c6408
MD5 037f255c9d17a4a3953c82b84fd222df
BLAKE2b-256 ee565549e3c7aa83f73c9a8c2d93f86a21c94a7e62fddeeb5238e45b3a885b13

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 6c8b35cb80fb6f1f11a50f3b5f1cf19b12ab2cf53e3063205de5d861e96c7be9
MD5 93147c33b610d4fb09d1b93abc69ce9f
BLAKE2b-256 d516a687bda012ed6de8d727c2c33c5d465b7fd5a8dcf8df2c701938bb5342d3

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 562f00b787996fdcb8a68479db05815a632fadf169753511318cd4d3f5f4381f
MD5 a929b8b5e6caaba7fd87cf6f2cc9faec
BLAKE2b-256 05869ed092036b51f023de2e30d8aab1a60b9d618abc8008b78a2b4f1b497b2a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c4c1aa56304198312fba5d6a192d050ccb806e081e0306e0745cb8bbabac7648
MD5 2a155ec1a585a93ca77e2a246164d9ca
BLAKE2b-256 616f7467030807c48ff05d135d7a0dc04511f91ae5e6b17b3462f61f6a6537bc

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 aa90177af9d158afdeaf0db11493d9194a78b60db93b6cb0d543e6d87e76422e
MD5 6ef8f6adfc8b2b5cd995e11bcf2fe01f
BLAKE2b-256 5b757dc489c7119fd2cea2e13d0bd12ab23beb9725e0ccae83476229ab251358

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 f8d6471a2bd865c245daf97f0d226d8e7a7919780285e946df8e558818e470b5
MD5 8538bb240a47545979767da72da383e6
BLAKE2b-256 78d94d287a91250cd2142a39ed3e9b06f34ab7af5f204bdc3a5e48daa886c0ae

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 0b0451c4ea999d100f7df17b3f262efebfdb63fd0f05a0a9a15035988690be0c
MD5 a7d542fc60794ac7a4521f41b8d98dd1
BLAKE2b-256 19a7d4558e529ac647be6afc8ed1bcc37680b262761c0c24d5516554ac66135a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 1b8b5911a8820aba203656068599db7f6d1e74a50a0cea9970de0ab3f9294d30
MD5 06ef4dfb0de1fae28bade4d1740409ff
BLAKE2b-256 79185d0b15c7aeb022899af8a408ab55e5ea59d22b3dd34aa58deca841ad930d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.11.0-cp39-cp39-win32.whl
  • Upload date:
  • Size: 898.1 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 f2f73a8a55211e200f9712d4bf22147d5290d35d5775b9d5c6b56e52f31c66ff
MD5 06f941cb42dda0a5d6b0ee32176acef8
BLAKE2b-256 b1f68fedca03df8e48e6e84db4f9ff3fb93bbde1040eecb98819607cbea8ab4b

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 e2cae99cd7f8b8fd18c7b570c0603d527046d3c85a863679638408ca33536f88
MD5 59aafe4c4716322f1a797c078295db76
BLAKE2b-256 5e9a212f374d76ca8a15d49bfd9a7e05aca97453c239de3ef128aa33acff5ded

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 4b4a6fce18f20bcee0763e1cd59d15a01dbdb4fd975c4e512b320dbb97d6bc8a
MD5 a38b04f2c799573e1a3a3be93dd36652
BLAKE2b-256 30640858b669b28d9f13876547e0ecc1b6c606639308efa547f94fc13416d62e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 ab9041f4877bb7829c95c65e3b108322b73dbbd19277b892867c6b6f9430155f
MD5 b9507cd6df3348c313f1fce4679c13bc
BLAKE2b-256 d8c73877bc3f4ca9e99400a2e231e18ccb1cbc2155f20895ed744965d2e84592

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 eaf75ac91376d53e8e5977f49e094748bd061ee8a85981a557233369d60a103a
MD5 4838b105b2a43bfb5d79e8df9dec0fab
BLAKE2b-256 ae6edb96926cf2cf10441907f460c1c2f9d807a56954b549d8a91ae29963b032

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 3b598f4b02c523acace1bee5c0eee8b0614f1af85ec9206fd4e5effc467e397d
MD5 d982c4aef66abb13cc2bf2019d5b0cea
BLAKE2b-256 3f4fba0b6043f357f021b0c583b0a8b50aaaaf14a08553160db544c9f4de815a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 5adc8f1ee3ec46b3ce3cd46d64425f6520ecadc044d45515531bd36a6b606a32
MD5 5db80e2214e5293ececabd7c141196c1
BLAKE2b-256 810bf4d5b5dc3313016650f187d92b664ca4dad31a6d09bfe81e7b648142c744

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 61c025b90f0bd2b5fc542292bc793943bd93866f3c9753cce681ac009c5cccf1
MD5 af0d6a992bff4d89699afd8f57bee9b5
BLAKE2b-256 32911c9de8bfb5e5ef0172d32987b9f3f44785b2075b0e4bc4a8049f0d66992b

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 4829f449dab3ab31eeb65f2a3580ab3af4893c8af6fa639d500f5ab16698e847
MD5 5bdf38dfdd8139b704f29d38ce9f4c8e
BLAKE2b-256 fcc51aad37ede6e1f48c5e731e15f2acbd0f8e6bf14ce3568cc5e806cb4f84a1

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 b90762667bc711a8ae40e9ff965eeffdd847012b87cc68e0a3dc55a1a51e183f
MD5 8398f9d50cd7110c59a6afc0401343f8
BLAKE2b-256 6e97e8560428ba9c540b7baf525f644683fe08c7c0b1aeaf4cbaa8ac77dfd731

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 288f326256a2f6513ea2ceb75f1fa327c899a4b39bad755771cb79e551e0cd9b
MD5 cdc0a1f7e3be4011741e62b79af66202
BLAKE2b-256 6660648cc38db2b3ec5eda34bcc1551b2bf6d90a368f6df89f7ae027fc929a15

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 805d189ebfbcd86120269247912bc97da346526072e289bead27fa135dda8ce9
MD5 d63a93b032873ed538285b100213c2a8
BLAKE2b-256 94f500a7f318866c905a52c3b654af330ae0960bacde0a239f176408317d6fe1

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e62836584751852d6c42e84d8c3ee7e2e30fa2cd7ee23455b3e756a724e96fde
MD5 537cada52956daab3e78eeb4c689619a
BLAKE2b-256 7ef924ccd2d984e67e936324ffa2cea30ecb507c1f803fc283e255c24ebb5e55

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 870ba2fa3158fbf1a96593cca2d8f72ea0315916b0105b13e8b0aede125184ab
MD5 d58c73953d29b23f922318bc554e5490
BLAKE2b-256 d37480c9a1e21b7cc9d26b7dfd60ed57426c4c7a3441cca8a2174cb7305aef3b

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 e11489c134dcdf77e466cbce25a38cd3e7224e3d9c379c4040f99da55e6f09a7
MD5 a70eb938965941932c8bcb19693207b2
BLAKE2b-256 1aca18ac90f45b17a5489d9a4cd139de49779ed73245dfcbe254e58b88cfa17a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.11.0-cp38-cp38-win32.whl
  • Upload date:
  • Size: 899.3 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 cf2738ff805537d162bb33b25a43c5e333ff119efa347ab6e02fbdc6fa740613
MD5 7e925067dd163cd6982b0d6a8868824e
BLAKE2b-256 04e3bc4d4807c0033cc518545670508897e56741ebd38bb0bb9b31151d67dbf5

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 ee19c17ea22c97d81dffd5497a7252b2a32795d88f06ce3ed5f56499f2eb17e3
MD5 b63c46ab9651da9507afd0d3ebd0b5fd
BLAKE2b-256 c3c916d192c63f01683b1d8e7350666008a7f3bdbae9e7cc0e93120395679607

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 1c49461b885b58c311dc4336b16d463c152159aa73f347f048c2ec39e0c151eb
MD5 c969e38e923689662f76d742909da9f2
BLAKE2b-256 476aced6e57c045dbdf331a70b3931bf353199d9733edfeef74a6accb21282bd

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 03d6c8f069835755769d9f0b761f10c23f80b8834deb1fdaf8a2ab5236e458ea
MD5 16a9492885543c391f3561ad2d1466aa
BLAKE2b-256 868ea6f4d6f092ada36970ff97c097a257c0c5036ee2d9900467124aa227ef07

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 994464b7e76bae97dcdb9d1b56cc3c3ea8be9a5e21d445f1ea37444b9fa363a4
MD5 111fc5d9c6961f8ad7fa652e3ee72be7
BLAKE2b-256 fdc4533d0bae6fc1bdd27c3051de85766299b6e5d50cb834373af2a63fd9ee78

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 df966768ed4a7d7a07e80763edad91690383f86d9c51b9fb9dfa720d7ff0b5c9
MD5 ec2eece75a7d28b1df5bc8aa6ca1c409
BLAKE2b-256 9f775993937622a521a5e37ac05c7a4cdb0ca121af018495db90a593968526fe

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b62d72c5728e7f61c3e381e72130817ae1520cb60699a4e1a577d55bb8c8a691
MD5 945ef7b1b282189b5a32b4bac547f271
BLAKE2b-256 3ca460a8c76a34291a3cd7895bdd6d4f80fdbd39b374bbc4cab3607c0b993e87

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 9bfe7821d1840396ea00399c4a8ea8a3440b5dde358d43192e0b2a6c2fd4a986
MD5 02cc6530de5b70d9087d6236b10235e2
BLAKE2b-256 e0b75dc8f01a1e417ded4bb3258ce649d8c7d9aafc2fb5e86f9eb9021f62a299

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 62fa2600d34283d9e4e806c4380a01d10250fcfbca140c03b1721a2995873fb5
MD5 ef88db93b626fdadfefbbaa1f9396a27
BLAKE2b-256 5e6253bfaddcfcabb971ce2bccace8c2c9a62af389ec3b93f994409da8a871fc

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 40738992548755cb50d3d148acdb736fb9c9a69f8836139281b726e72e922577
MD5 487134895f8510250586878b9675eec5
BLAKE2b-256 c222a1b243304273ee0eb282f3317dc40685ee305c8663fad5032ff91e4a508c

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 b5d2a0b4407cc1fffb36901c0f228e90980fc3cc7f75df76ab392ebe0e4b78b0
MD5 f2d0a4fdd54143a4851ddbab0a5f68ec
BLAKE2b-256 9ee00717ccbb405907293142de2918e9fb910e81c04db2583838e0f7eb4f46fe

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 28138c1685ff776e30329659aca2ba8343c85ef3c8ac3be234b10a6c970f7a1c
MD5 2f1653bbf440fcb439db973893f0061a
BLAKE2b-256 cf2bac11d57b213fda7c99dddee4817add87ea2937ab681ccfc869481ae41ea6

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 c8462c98ad359841199e985f524eaaebe1aacde096419f1b8e83560fc19ac50e
MD5 6c98dd7b2f72ca9a4aa92b5d0310f704
BLAKE2b-256 5d7368ebb3aa6c112e19a134d992ebb6e2314a7e8cf2e95e93c1a452d5166e07

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp38-cp38-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp38-cp38-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 188fd2488142e7b43a821c693fb4d17fb62fdb365b6357d765764bf14ce85734
MD5 a19a42e9ada3cbbf8181e8f1d5d58880
BLAKE2b-256 7911faed48c9bf0f17256dea3af895e570038c0f6ce44b118d4882bd46ca7cd1

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 be36643302b77d24bedd825f882e9639c07ba16639b2e3ffc2a089771d601993
MD5 c900a1295b680896d332e47b0eaaadeb
BLAKE2b-256 f9d5c918ef91a2a9e13595c7e46210a7e76433614048094767be04f259d605a9

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.11.0-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 894.9 kB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 02ae2b1481f2973d4bdb2be10201a81e4e9e2351a3cc384e4c53a3ef0864feb9
MD5 1c98bf065d21bbd7b4ae75ebf636838a
BLAKE2b-256 c869be8a8eff7413bf6f5704bf53650e874846410b64727069eff460b5c1b944

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 f9ae9703ee613f3e514d60d917398a82dcfb7367e103ef34ba66f703fc31895e
MD5 55c137d6bf04f43d770a767b70ac8daf
BLAKE2b-256 045ddbf332cd5104146eecb3815d583b29289682c6b6fd0478d55d6807b92b53

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 2af272a0ab739d34cd3d1ba5b2a6dfa66d77460a0f11a1d5fa912d404b313385
MD5 4a6bc4fe9f27c94befe17476e25cd3b1
BLAKE2b-256 feb4ea2694d5f1ab6e0385675baef0acb1586b72448743b5ef9f2303e4da61b2

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 a1802f8917267a5674654e75cbc58cb24bbde14e914371195a674eb653ae2ce7
MD5 324079285a4ba611e075e5e7e198068e
BLAKE2b-256 4ee5b2341c16677d37e352ee2517a7dc79259f2eab850446f82dd1768807b7bd

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 d62b1c4d2680e7be78bfcf43b0a28918be68a14c40fa68b459ea6322af5b4340
MD5 9b9ce1eb7821f9f5b7cc0255fb0559f8
BLAKE2b-256 a3424a88b02f9229097586877dfcea426e7a0b9c1f5a02b997763d587422798a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 f39f575ce07be19f1c942e8cc82775353984e3311304f1fb420fd7463af249ab
MD5 80267c18111b9a922b514ddd513fc3ce
BLAKE2b-256 9147c3c9e200caa2443a741d4fe5aa01d5fe85b32d683b90f633fea901da40e8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a0b8938f068298aa471253f13210833b8a76e25cfb8e03ef75faa43c09b516c7
MD5 319ca9a1b9222ce6f288f154e851770e
BLAKE2b-256 b3052af6b0349cad89cf9db8d0bfc7e9f3d6068d686eb05192d0ad5852047d60

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 93c1189812cb729d239b80d5128dabadc0cf5c8a9aa7e86ba15eed6ff16ea957
MD5 a43790d339c7dc8a0ba9e15892962418
BLAKE2b-256 c82d9e75f8fce4719a33059123292fbe10ee1c6d9569d71f4d833d85dbaee1f4

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 8ccac93bfc06654ab8027dafb6299ae4818a2c9109e57d6916ce35ff1a30b925
MD5 e3a46d9b31e4bb0b6bbeac197e997b9c
BLAKE2b-256 44570c7c498dab166330f2420f24a4857f81e6e39a69cf824389bfa8b3c4386e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 5d12d79cee30e7f94cc1c1fc2d31d38a667e76a9eb5a6a87cd29c5d9297d6c78
MD5 39f9151defeed144c087c28127b1ffb5
BLAKE2b-256 a87421649e13dc674cec72ad642d38fe36ed564384cdcb7768014c1c52539ca3

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c58e036a38e17f453e74de512e5f252e5f8d8e1671cf7d8bceee3f3a350ca16e
MD5 20525bb7e0a3f6a5812ef4a5d44e08b1
BLAKE2b-256 4eff8b82eaec8dcb5bda5f1942cd8e63f6366a6476b582bde5e19c8ea61de96d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 961518f6b9041bcdedfd6144ae613077391d43169e7bbd7e758337a7fff7ef92
MD5 02e709751276143adbd31332fcf59ea8
BLAKE2b-256 78125b7cdb4eaa0aea5018f8050a22204cdadc0118cf98aed93a3805edbb5d6b

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 3036886dacba83276824cd1d14079e75bc1ac55ff5dedd0136a617597cf554f3
MD5 8170dd737592be6554bad11ca5ea72a5
BLAKE2b-256 9eb697b11eb44a580d2343ae46d49119642db63be86afb1006d13ba96cab0a4e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.11.0-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 888.5 kB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 0a17034402189b4acb33dd939da92f0b25d4b59db651717ecf33c114b4d6c788
MD5 4d94a6c2a5ff937eab360fce8151e4ad
BLAKE2b-256 dfef69ae4adac268637a5e558e39eaafcf0b8e710469a122de7e14387198b195

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 d20820f5a3159425667cd735d50669042cd0d6baebc4abff8f88db96ace8f8c8
MD5 20aca67cf8ff321bfe1dfefbd21c7475
BLAKE2b-256 84e78811c5182fd9e4abccf0bd1f737aaac4b3e86ba668ba900194eb24a6da3c

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 31fc667d013c5a4a1cafc69e33e5adb72d3f936d410aa465b48e360443abec11
MD5 58a9927e8e1504222b2d8c6f048f595d
BLAKE2b-256 72ad250c439b7bae4afadd9f7cb8e3ef5cebde8cf9be875cea49a8e1b51a547d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 2bf4646174094ae7346520aefead0920f1eabcf8d1d408757da707eef0825446
MD5 ff123a87dad1b61a958722b6311b1a3b
BLAKE2b-256 c73494a685587067442d05d81fcf8cacde5b6a258cd8623c738aa3e381478c32

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 7641bf47f3c3e93221a75726c525a6031de9abeafd55424873ec1edf744c76b7
MD5 1a0368f67deea0d4ee20b7bcb96373aa
BLAKE2b-256 f5b4ca9d4fb5df9313d6454c8a7029200b6b8315d6541516aea7a89ff0869d82

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 aa8a972275bb5cd8148d1222d853a16d80fb4b85db938d32d1bd7dfcb041d19c
MD5 0e1c16c06d2e41ba93aaaa053dbc3a27
BLAKE2b-256 26cfd9e1d7055f8661d233702e964a26056860775e093b3cd9053edfd40182d8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6c1beae2fb39e631b646b1286273f6153a2c99756137b55a3f1cc9b026b26fa3
MD5 ca4a3f5b43e0755a8a1749586f25bc32
BLAKE2b-256 3b702625089395e9736bf6765559d46d0d14b6608c7183b0b6542fbfcff34064

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 506bda42f036f5a7bdd10aa6ec8eae603128436a6d15d564ceb85b2bbe6d0507
MD5 3b74786c66a9403d12f3c7017fa983c1
BLAKE2b-256 8f1727f354b5912dbe5106dde30cd2665d7094c98734862cc37fd9bdef208a5d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 5ec144a0e8b3d8a8b3f61cd138af9a836fb9e3dcf424a41cf5eab33f267ded9b
MD5 d2045cbc573ce4439567b8799a55e33c
BLAKE2b-256 95f044848009128d47149d7b366972cf10cac38426d5ae219f58204ab5b2e313

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 ce95e0451ce28632324e1c2c48c85973dad3a8170dab0c03a1a3595b28a66938
MD5 c28bafcf50e7f6e3014072ac1470ba5c
BLAKE2b-256 61258953e862f59b20eea57e4ed196ab5fdfd9a396e96ed240956115890fc641

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 62ed4d74a1e01a22936dc32a6a2d37f938f23efdef1cd9a81f4aa0091eb5694d
MD5 61614b08cfd61e152d54942244a9a0f3
BLAKE2b-256 d391d9742b15bea160a47424bba7a22f9591184a973df1de4d37fedcffc0c9e3

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.11.0-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.11.0-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 df44060516b9f33dc0206835f8828dfe977ff68fa4515ce876e0a1ec8b381e05
MD5 020414608ee256cf4fdfde1fa31a22fe
BLAKE2b-256 b4ba674f01fa78c7e23dc36963e614f10e8780bb45a952ab3cd4360e77b2d152

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