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

Continous 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 comparision between RapidFuzz and FuzzyWuzzy. More detailed benchmarks for the string metrics can be found in the documentation. For this simple comparision 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 extractOne in the following way:

for sample in samples:
  extractOne(sample, word, 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 extractOne is a lot faster than directly using it. Thats why they should be used whenever possible.

Benchmark extractOne

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. Thats 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

2.11.0

This version

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-2.10.3.tar.gz (788.2 kB view details)

Uploaded Source

Built Distributions

rapidfuzz-2.10.3-pp39-pypy39_pp73-win_amd64.whl (855.5 kB view details)

Uploaded PyPy Windows x86-64

rapidfuzz-2.10.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

rapidfuzz-2.10.3-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

rapidfuzz-2.10.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.3-pp39-pypy39_pp73-macosx_10_9_x86_64.whl (1.2 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

rapidfuzz-2.10.3-pp38-pypy38_pp73-win_amd64.whl (857.7 kB view details)

Uploaded PyPy Windows x86-64

rapidfuzz-2.10.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

rapidfuzz-2.10.3-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

rapidfuzz-2.10.3-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl (1.2 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

rapidfuzz-2.10.3-pp37-pypy37_pp73-win_amd64.whl (857.7 kB view details)

Uploaded PyPy Windows x86-64

rapidfuzz-2.10.3-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

rapidfuzz-2.10.3-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

rapidfuzz-2.10.3-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.3-pp37-pypy37_pp73-macosx_10_9_x86_64.whl (1.2 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

rapidfuzz-2.10.3-cp311-cp311-win_amd64.whl (920.6 kB view details)

Uploaded CPython 3.11 Windows x86-64

rapidfuzz-2.10.3-cp311-cp311-win32.whl (819.7 kB view details)

Uploaded CPython 3.11 Windows x86

rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ x86-64

rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ s390x

rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_ppc64le.whl (2.1 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ ppc64le

rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ i686

rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_aarch64.whl (1.9 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ ARM64

rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ s390x

rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ i686

rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.3-cp311-cp311-macosx_11_0_arm64.whl (1.0 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

rapidfuzz-2.10.3-cp311-cp311-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

rapidfuzz-2.10.3-cp311-cp311-macosx_10_9_universal2.whl (2.3 MB view details)

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

rapidfuzz-2.10.3-cp310-cp310-win_amd64.whl (917.5 kB view details)

Uploaded CPython 3.10 Windows x86-64

rapidfuzz-2.10.3-cp310-cp310-win32.whl (816.8 kB view details)

Uploaded CPython 3.10 Windows x86

rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ s390x

rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_ppc64le.whl (2.1 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ ppc64le

rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ i686

rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_aarch64.whl (1.9 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ ARM64

rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ s390x

rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686

rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.3-cp310-cp310-macosx_11_0_arm64.whl (1.0 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

rapidfuzz-2.10.3-cp310-cp310-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

rapidfuzz-2.10.3-cp310-cp310-macosx_10_9_universal2.whl (2.3 MB view details)

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

rapidfuzz-2.10.3-cp39-cp39-win_amd64.whl (918.9 kB view details)

Uploaded CPython 3.9 Windows x86-64

rapidfuzz-2.10.3-cp39-cp39-win32.whl (819.1 kB view details)

Uploaded CPython 3.9 Windows x86

rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ s390x

rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_ppc64le.whl (2.1 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ ppc64le

rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ i686

rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_aarch64.whl (1.9 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ ARM64

rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ s390x

rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686

rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.3-cp39-cp39-macosx_11_0_arm64.whl (1.0 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

rapidfuzz-2.10.3-cp39-cp39-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

rapidfuzz-2.10.3-cp39-cp39-macosx_10_9_universal2.whl (2.3 MB view details)

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

rapidfuzz-2.10.3-cp38-cp38-win_amd64.whl (919.4 kB view details)

Uploaded CPython 3.8 Windows x86-64

rapidfuzz-2.10.3-cp38-cp38-win32.whl (818.1 kB view details)

Uploaded CPython 3.8 Windows x86

rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ s390x

rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_ppc64le.whl (2.1 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ ppc64le

rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ i686

rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_aarch64.whl (1.9 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ ARM64

rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.7 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ s390x

rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686

rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.3-cp38-cp38-macosx_11_0_arm64.whl (1.0 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

rapidfuzz-2.10.3-cp38-cp38-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

rapidfuzz-2.10.3-cp38-cp38-macosx_10_9_universal2.whl (2.3 MB view details)

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

rapidfuzz-2.10.3-cp37-cp37m-win_amd64.whl (915.2 kB view details)

Uploaded CPython 3.7m Windows x86-64

rapidfuzz-2.10.3-cp37-cp37m-win32.whl (816.3 kB view details)

Uploaded CPython 3.7m Windows x86

rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_x86_64.whl (2.1 MB view details)

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

rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ s390x

rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_ppc64le.whl (2.1 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ ppc64le

rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ i686

rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_aarch64.whl (1.9 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ ARM64

rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.7 MB view details)

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

rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ s390x

rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ i686

rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.3-cp37-cp37m-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

rapidfuzz-2.10.3-cp36-cp36m-win_amd64.whl (910.7 kB view details)

Uploaded CPython 3.6m Windows x86-64

rapidfuzz-2.10.3-cp36-cp36m-win32.whl (810.8 kB view details)

Uploaded CPython 3.6m Windows x86

rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_x86_64.whl (2.1 MB view details)

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

rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ s390x

rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_ppc64le.whl (2.1 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ ppc64le

rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ i686

rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_aarch64.whl (1.9 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ ARM64

rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.7 MB view details)

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

rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ s390x

rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ i686

rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.3-cp36-cp36m-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file rapidfuzz-2.10.3.tar.gz.

File metadata

  • Download URL: rapidfuzz-2.10.3.tar.gz
  • Upload date:
  • Size: 788.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for rapidfuzz-2.10.3.tar.gz
Algorithm Hash digest
SHA256 a8f03b316e38f88c97415a3e261c4fa998e2e5448a2ff6da7bffb9f4304afeb1
MD5 6022434b2c3cdc1405d8385875aad8cb
BLAKE2b-256 e42a453bf834ce355313cfc2522a499c5b49e9390bda3f70fffbbf19c154b69f

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 02613a9f1ce85106aa6c11d45f1fc510a888c0d4ba258cbb144db61ce0d5f5c5
MD5 5c12b7b2c34771ad00e083809806f9eb
BLAKE2b-256 8b9b26a1991f40b3cb1426939fbbf77af1684d5a3203e55f217e08a2296e1d93

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a1f11768d97f15d18759d3b2249d2437c951e6db7ec63c5fd1b834eb97adce4f
MD5 2cb49463a822cb6a48cb0cf2ab00705a
BLAKE2b-256 ce0fc7899cca521482f053d14d7949420e2d4767e95cd2846bdc5087fd79fdce

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 17be5f758e70146fefeda1cbf95ec0d3a6a1dee6bfe369f942c23fabcbba4ada
MD5 678874fc80a75178796ec0041248e8e1
BLAKE2b-256 cdb958121e19d0fbaa0d287b952392a5bad7fe182a85944f0d745aaf5bd67bce

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 2a346fa42d5a461228be02d179c76bd9c8cb4e940d2f3b1638c2e543785277a1
MD5 cd39f6552270927c7cb5d082a68092dc
BLAKE2b-256 d7952ab6d17b2fb30c6e0ece19be64299771bc3305c5664926a0f3505091256d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp39-pypy39_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 a7fa3157038463ff2917a05d509272a9bfe04bf0113975cca2ce1c0a1bf2d5c5
MD5 7dc3771790b701dd77303856d21e8afe
BLAKE2b-256 6fcd836fe54379ef392921ef9bea3f33d76e8a6ebb6c533d9e49edb9cf3f364e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 14a59ae2374720a2b855a6f46c0dfc2baf535694f4aa37185fcd3146bc7af237
MD5 7f6e4f1c73f7bf0824dc93a9f2b383a5
BLAKE2b-256 6440b76fdc85da66a56599ad5ae0008c2fcde7ff552c3e51da4942826270e8c1

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e00ab5933637867f7f292d5a5068d1cde4d87afe32156c00d1363b15b5a4888e
MD5 2df04a58c455b2d0ff8a8a3d05e7e857
BLAKE2b-256 2ce4b3ae32cb2790b43e6081e945e120109bec5bce42d13605c234d0e6f62211

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 873cbe8fc3a283c4996858192ba7ad64321254accc6b06e464c4023e0c1c6470
MD5 8c9913cd9b99dc6c54a12d4090c1102e
BLAKE2b-256 faef13ccedc307404a425b71408a688ed6368c114f5db16ee941300167d84e46

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 56bf09f803c628b76a0b3d054ddf61bcf819c580349db867279b086531dc0000
MD5 e18a06eba5055f08ab6a4fc12acb323e
BLAKE2b-256 6c6cae7f7854d7ca88988489810d825797337b128d7512b3b343fac5a47c5442

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0e0b0257e0ba8b541c9f56fae075d426913617e5a194bf5d03f20a4e5e598625
MD5 2666a3283110d3a06dd7a8cfb03651cc
BLAKE2b-256 b51c373e064487f8940e1a7ca8986dc1139f8b7ca7c2e34a706e75de53482c3c

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp37-pypy37_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp37-pypy37_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 b08c1b8c6e861896df551a8537172dbbbe3d39be61c7e98b244500ae4deb7b3d
MD5 eee1a693b9a211a732269e233e77cfe9
BLAKE2b-256 3a0e32acdbeb268a65c1660a810847a2b9d765529cc13803112fd518b767475e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a306011de712e98a40fbf05dd7c9b5719974fef547ed57335303046b5e9436b0
MD5 61a0b1ca134275b5072c967c5252109c
BLAKE2b-256 2ab8980d3dccd2419cf7c8b5d85ffc46c2b8a3912e741ce47f1dec3d840ca469

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 deb4ce8229149ff57052c1f3ca95493fa6ad673ab7ccf1ff33ec1c9ebf41be15
MD5 58e52b82b7897450b24333781b672af2
BLAKE2b-256 b90a6a65b4cf23060a136a43682a7e8ce9ded089d5fc66f7e9aa2391d2e776d6

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 f969501316642c5c376c89e3605f7f8cc1c4a3ffdae6dc92b0b0602531acc8c1
MD5 6bd9050c897c4645678948908306e74e
BLAKE2b-256 9771d73cbabeef875b904fd487762ad3d8f79d1f30593b0874892a58286b2260

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-pp37-pypy37_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-pp37-pypy37_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 fc33161f599c6b1076da020a6ffbd158a777a5a52bd203ad3456923eb69fb0de
MD5 b2e8ccf9f632d33ac8f9a2697cd10064
BLAKE2b-256 7505a1b7629f129b818397a3f4ebbfe2eeaebfe3a200310f55c3916d19e73422

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 dea68224b56eb8fad01ff5e4b8aa17868720145ca6c2f9e91e7f7785e75440ce
MD5 7ee45e216ee0f5f8638fb2bb34c73427
BLAKE2b-256 6ae717c344bd35a31e01af9da4873ed875cb3fb23f701294797534a6cb7b7e58

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.10.3-cp311-cp311-win32.whl
  • Upload date:
  • Size: 819.7 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-2.10.3-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 771c80795d053d42c86ab3f963f2fc306d62174b2f0ebf2b8082cc001fd52c60
MD5 8667d7703d2bf698849e5d5f719b11ba
BLAKE2b-256 2596c0b6eb35e82cb977c9a67ad223892f32a8dd9409408caac0059e97491f77

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 8d1c3a0ae90bcf214cad3a9599eef7c8bd97b6aa7a5c4c0b67744966c8a5d8cf
MD5 e2ec33792c237e922a16ed65eb44951a
BLAKE2b-256 4417b0e50cda4ab9019e01835136affd26cc70835624ed82f2cfdadbd8a01776

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 63b08eab748e288a9b65216573f5661b1b5bfbe67c3289801f3132adb9f3e8a9
MD5 053b657ec1eef4c7a2089b5a985c5177
BLAKE2b-256 272f9e1ae4c49fcfd38547bb3604baf0911663074295f43a46c1d5b046b9660b

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 085dd87949ed498734ab3db1e156596d0c63c5475d59ff2bb75991147638dc94
MD5 d612764e7b098ebc0f75c56574dd2f76
BLAKE2b-256 160f710747e773ac4a6be9db804a1a43a003f4dc46b488b6ad1b4a47976c9571

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 d343a0012fe4b32a7ab3030bd6f2b91f818b26918c9dc3e232b28e62119fe72a
MD5 cf9aacf6d3f50ac52cc1b9e91b02762e
BLAKE2b-256 961b0323b7d7843db462618e76d800e4bb31ae5a1fc9bc6cda479ead06aa7558

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 efcd1a97839d21902e509ad6c56cfa9bdd40a536e56503cae9ae7ce19a9281de
MD5 805d059fff93fb291d64b4618997b5ae
BLAKE2b-256 9f936383e457dd70797fcca644e74ae9a8d4f4c0e50636ce3f0186aa9b71f4b1

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 bddbeabf14efd2c05fb7792ef824f08e109db8ce2390c9296da27314b91273a7
MD5 c646a834610140d45a6f28f6e058e205
BLAKE2b-256 56b3f59a43b136c28450cce1a6a9cdd2c90b3dec2fca87d638545c587682a488

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 ddce2bf4429da944e7e45547eae4abcbcb8018b90cf8c93e08320a02f5f62381
MD5 93064daddbd80fcec689b7c3f7031c12
BLAKE2b-256 767371d6ce7d2702db20981db067f347254e972d1f83b0e2de0a3ecc01b136f3

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 7215888c39b7cfddb8323860549d9eb41af4d78155feea4b088bf1a4e775efe0
MD5 42851932d26aab265c938ee18ac8b667
BLAKE2b-256 53cd44ab26ccfdb7ecb1ad201b4e0ba610bc0ad10e36e56e6d3246f48a2c7ad7

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 770679e582ba3d93039f7c3e9cf02634efb1fd229d25545c4a38e1acc38d3d42
MD5 4006066ae9fb56319f9e9a57e7f98c74
BLAKE2b-256 c6f1469496722da0389166c3e72ed333b12e6f1d31a594df0cd239c8cc188532

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 f09f236bf187f59094d4a84fb795d5b1786feb9d6147a01f2fa05e627af0e86b
MD5 fd59ed1215a62de0eb4ddd02d8763529
BLAKE2b-256 69ca0b89e71441fe828c70da30c722460deb1292735a7f896e0ec7f6f5035f23

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 f0c462c947aacee1067e9fd1803ed88a2aa4fa61d8d1e91a5c2631b9400227c8
MD5 33698600609e483dd8bd868c5ad036d6
BLAKE2b-256 9e58a5dd838a65b498ab5fa3a1f93c3c397917d3135d6f9ca6d4859ac1cb9c72

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 c5a18a80bc8bc9d2609438c5615ff606fa931a29ba7c149042d2bcb604267cf4
MD5 fb8aff91f369b61f67831f8032615036
BLAKE2b-256 5a66f45386bb2b4efdd3359ad3ebd1edd4681344f370bc400e6062405bede6b6

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp311-cp311-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp311-cp311-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 2974007b34a025b795da749e3e95bc589a64bae779c4b667528a19b91d3649ee
MD5 3ad6e5d5e71b401cbc65948fc0bc8767
BLAKE2b-256 798bf5c2a36fbc54808f403d783346b216ff0b4736adfca76096ad791970027c

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 87fa733659bbc75272d2cfcb48c93d4d67f6edf453c38496c789b72b1cbd865d
MD5 bda6d6d392645f83ad68ca1287498c8b
BLAKE2b-256 e9d4afb5059ce45eaa77b4cdbd1d8c5c2b61f9c8522918ccc4e50b757b7d79bc

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.10.3-cp310-cp310-win32.whl
  • Upload date:
  • Size: 816.8 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-2.10.3-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 17938138685b0b4c08a5cf03fd5145b69651f9458165005d8e5604f7dfdb64f8
MD5 9583d42d57df85e808b0cc0f3d2bbaab
BLAKE2b-256 ecf8b68eaf612a3e0e9958f0b81ec144cb41b72749acc9573e1885ae3da14a5a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 da9aaac84982c28f4fcd36b4112f03b4983c9eb78f6693f46eb0c74758e1a221
MD5 e6f159d4a81b4d7b3fd4360c97e189c2
BLAKE2b-256 2f7548ae880136ec7d1101acd0ff6d91a84740173cd5b614e149b456c01675b1

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 e05efbf8a0f2edc7e80b35b99e142fe16b75e643d6f8ac8c8f30be58a8f14a24
MD5 d63a13e0844bd94fd5f4cac182294011
BLAKE2b-256 7fa8c77dbe503fd65a97aa5533c2bcbdcd6311e2c55ba05828151942a431ec00

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 919fdfdbef94a0b77ed18df736a9aff5db5b1ae546796d8937a9d775b66d28f5
MD5 d447e9d34c7676173a2f844e040d9762
BLAKE2b-256 d45e44a9a282a8194569b5accc1e776abb9c6046c5b92f12746a074df2e286f3

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 b2ba9a7ec61188013073cae0ad1ad52688572419ae25795ed6748007f32aecfd
MD5 6ad428a70b18bf198c760881b0eb7d1d
BLAKE2b-256 f2ee49db06beb226e4674472c4244e60e1780aaa1d60d174ea6171d04d612138

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 c5e15d60fbc6f543473e931b1cb91a7a54922d58d84b2cc8ad077e28384c11da
MD5 d518c4e329d2c0edc257a3f51f660112
BLAKE2b-256 6e6ec074457dc58eeb298ce764d11e6f4dd4dfbff77a0ecfca12cff28a8f401a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4317d20dc3c8b129f734f21541aacea4fa57d98b9c3270f6c37c202871f33d88
MD5 1b43f166b42ddc72127f9063fe587c1f
BLAKE2b-256 f7768269c1f3b12ef242be620a0ee31153c4172c3574f04eefd74684de578e21

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 c0f8ea4f95d286833cf9c6240f7063eb2547ea1c3e9d70982406e09fddb8a8e6
MD5 0d6f76038d69b288bf97abc7cfb340bc
BLAKE2b-256 c2c5228100f242e8946c9d0d1b84241a5fa1433aa8d8c7d618cf762adce8357b

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 010b779f1520f31df6fc06d2a2ed6cd3a21da2bbdc61f14771bfb39f5642c261
MD5 daf64c5b159104cc37d4235f43fc61d7
BLAKE2b-256 4c8c606979c2d142974b7a89da19a49d30c8ee538849d365be3bbf8c68a31e76

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 19004d4fc733c22d8c1f2441a7ad656bf389105b7f6a399288ae947c9bc8a88c
MD5 16ca9761b0fe602802e04e78a20902d6
BLAKE2b-256 18215fa72037c47e01234e4ebd5e9ce07cb36bac702325feacdad09c7c033443

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 ec442ba4e3dee067e62d36a727e33e65bc2cfbdd49f5d6b61cb1ffede4c0704c
MD5 5944fef7526b87ab83b012cc1ee044fd
BLAKE2b-256 d7c70b9eb0d12184c351dcba1859b5ea99b654b78b815f7af6a44758e5e937b7

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 412213065b4adb93e61818bb1657eb4c7e720f31a44f34f7f7028b7dea93e597
MD5 43963c4cbe552b63eb8b0abae8df0043
BLAKE2b-256 cb63f2653b0315ec8b72e74b14431a8463f0bb99de9c093d1b5fcb088cc8bc04

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 c5bfa5c0cde28a2aaff4c2b35a4756aceb795f3e75956439bdcd01f6705f6ea0
MD5 fb3ba8d506671a4e0cb084f02cfea9dc
BLAKE2b-256 c4e9d5e57d1b5ba924b5611e2e6b4328c6fa83903b5bc35d3ddbdba7f968e91d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 cacd0fb710ad7521a9bc274c95575ab909d2ed0c7c50321f31c7bd9ba120727a
MD5 1cff93f5e37cb3c1e5dba8770be68663
BLAKE2b-256 301e045d3b513c9a7b4b280e1400ab21ee43bad21afd6b6d0727cc32396642cf

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: rapidfuzz-2.10.3-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 918.9 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 41e40700c636e1231f79e74816f7a0a97efb39e313ba98841cff316c501bfceb
MD5 6e5119d176dc2461179117e7caeff778
BLAKE2b-256 e3a2e559c6b66e8adb45a446843b8dee8dedda77039fc6b615386c2607cea158

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.10.3-cp39-cp39-win32.whl
  • Upload date:
  • Size: 819.1 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-2.10.3-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 ae5cdb1c7e8873e4226b6e63637082a01bd6ac9159759570a6367bd2c68907d5
MD5 6c3c64ddef24180b173d57403139304f
BLAKE2b-256 f3b7b6030896f3c656c7986c69b58ac5953b927f311928c69c8734c5d0795716

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 531859f8d64a962666afd55cb587a48c8622398767bbb67c8877a4e2eacaac6c
MD5 da1f9c2aafabdb82a4aad4ce6c59a82d
BLAKE2b-256 64c5f043d7ba5aae30ee21ebd7ba85adc93a16312b5c6094a566061b280886d1

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 afa5163ca6abea1c2c2e9b61ee83b52f70975e2a7562555506eb5fdbde2bf2fa
MD5 16985f1edd05a49f13a2321fc1716188
BLAKE2b-256 b7b1440ef301abdad51336b81bd805955cdec2943470b23678cc0ce7133d147b

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 b9181fd7b452ebac39af2429f2e10938d24cb8478709d3fb5d149341d0a1589d
MD5 7f369e68603809a13751f476935b1397
BLAKE2b-256 9f0ba7977217786d6e13c26c5bca0c050025fe0d18d32649617f4b0e4c593551

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 8c48e6ecedc5460e6df927a1768df0e504c4c9fb1a34fb3c800be739400b0619
MD5 f5a877c0751ec7d88964f9a96c370ecd
BLAKE2b-256 a1937911fc4cc6452add2553823b63cbcaec1cd4fe1e89ea4d0a241bfb62ac78

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 753983d27cfb176c1bc1d42bd61fa1e2908ca5ae8a73ba09cf4d0ebda4f1163a
MD5 9da82d41ab36bf022d52b4f3778a8077
BLAKE2b-256 cd54e1e3c84d5dfa8b94fb730b765bfb716ad03ccf913560fd6c124f6de0da93

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e26aae7b0ce7bbd3fc5741eaf9793447e52855c1ffeb3d41df7c0f4f7756f091
MD5 00c279247c662ab88ef6bdeb9bd0cbbf
BLAKE2b-256 f7a5e9abb171d91983b85971118106d7058eea15eb80d24feec62162abeae9c8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 943a9b17adc50ea2f1c0a31c8a59a0c77fcb948deef6bbf20218ce42f1ce5a45
MD5 5d7e129e7d55c91c521c1d925067db9c
BLAKE2b-256 eac2bd4d3be8765699683ed1b38d1ec349c13b66e1a6486d733df06b7924007f

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 8a5467855761224e1a704ef4dc2d97cabd8035c862fbc9356068f64ce24f4dc5
MD5 1a93e82da9815aefcd46828eae9161d3
BLAKE2b-256 1918b22bf0183ad9fe277927542d394250bdfc3999a0fb83599b8f085cf3dc5d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 8c1aa0148878a5207db940746ecf2b491349bbee6733435919fc260b56e2d5ff
MD5 c4376a3c4162a2903d00d7048d4846a8
BLAKE2b-256 01c4aaeae606109464e22470e798a094b47d76c8760d68d59dfa379d2b6ce2c6

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 6a9df22d23a4258ba6795ed78829a3123544d0cefdd4d49ef04e1b5e63bd5d61
MD5 405e330d9ce81946432c96213850e463
BLAKE2b-256 60e7dec41056420bff027fe526ed891716024ba05827be1aae1bedb27e32f140

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e4688445bd49c8b05372e1bfa8e4e7b5f1b8bcc895725ac0d15c2c079f88c69a
MD5 65409b9bd3e1087550c055dace4ec787
BLAKE2b-256 07d2769c8aec381c3227fb7b340ea9b000c901c67d00d649ffd746834a1e0a9a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 3998379295a12aaf7cfa82f2c28124e031ca9841895f90ea88589bbe7f7931a9
MD5 a7e87b5ab335acc92b8caf158a999174
BLAKE2b-256 d112879499242b73362b610d1c9307a8a19b8bbef17b2841945288dbd589d6b5

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 e5baca7bd17106f9260155c05aba756a2cb0a2fc5bb8136a385f675c6a2909da
MD5 59b81d0b9ed432bc443fa7a7709813ef
BLAKE2b-256 3afd930a51c3df423cf11b4ea9e53b2cf78406b368bec7fc70cc33d27306d903

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: rapidfuzz-2.10.3-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 919.4 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.14

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 ca293f19b4a5b4a64215759f3c3a2b5d612582def37f27b9c6adb3e094433adc
MD5 4a672b24225c4391d50144f42c1ee844
BLAKE2b-256 0bc07968b240acff3cd3013cf123b17d30dbd0d8688eb81adbe4750419b34150

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.10.3-cp38-cp38-win32.whl
  • Upload date:
  • Size: 818.1 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-2.10.3-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 750272d47cd80d5689e7158f749e014480cad6bd812c69aeedf86db71dd582b5
MD5 fc7161d4d5ec019e3a92eed14bd28f05
BLAKE2b-256 96dbcd5dd63ee7e8f9d15809639ef3df7f8d9d885a03a8dada2fae85cf43174e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 8b282248300d78e47b987e7dd469f1f7de4e82810c73a8ce13ddcb3234068f46
MD5 1b714bb088e3b636fac4f08fd23e0d09
BLAKE2b-256 277faf3ac7d8cab93c89e744a8bef72d541949c49484168572ee450ccf859183

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 71d69bc9a129cfdb27f4fbec3a73a69acdafdb4fb0a72cfe0d8925c621d14e8e
MD5 1e87055e32d17e4268875b29aebad2dd
BLAKE2b-256 1ab9f14a184d7da0f124fa1d3f4e0885be391473d37d51e817e368ac41d0e13e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 6aeae21cfca1c767b897335be5abb25913393fd6c43c9cc4a23caa722e2f4f7c
MD5 f1e47c663ed8abdca27be56ce418e885
BLAKE2b-256 57b86f46475c7459cc06590318a329645ea1867a329a446273ed0a6c1753a0a1

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 5407e655bad797c9ffda2ac2dbb4946b731501a4394ad2ca0baa57ec25615643
MD5 18c0ed152c6b83667b15769e81413866
BLAKE2b-256 d14e08c463b2e2a252c4f76e6b7fc4d9b193adc41eecaf72827178bb0ffa2dcc

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 2cbea82d4111394612342202e3114ee7dabcc5af293cbfe6001001c58ac8424f
MD5 ce6782d3a5b2ae8da22251218bca3492
BLAKE2b-256 102a3a4b40e65d6e5e360ba399352ec6ab99d1f09601fe41741a306a60702712

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 78fd6fb5c6c870efd173ebb0d8b09b707e3a67acbbd2abbfaf1c035df30383e2
MD5 cb1c7a7ab592e65592de52b3497f9e85
BLAKE2b-256 e53fe4db1edd538e879da255af952d5e597c1360a63f2294d820ad86e0f0dc98

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 ffb423dafd3a35d78b4cac2f75a346eac4ef2a6d1d9a2544151985bd47e475dd
MD5 3c36d18d6da99c9ff753958a9e1abd02
BLAKE2b-256 0fe0369a5a733c66bb9a76b350db33e948d94fd93336e66a93438cb09303095f

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 489e6df1b0775934f8d83080b486d221a308bbedcbe1f227e791451a57b71fc3
MD5 1c6a49c4caaaedc3c54fb8f60d9ba4e9
BLAKE2b-256 fc2826a9e15bfe0fc7ef16ea7892a2e9d29bd5d9747b4a66857805c508e485a8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 bb772af7c7d1886d724d13404aec88a0d8552e1c6cf1a121677cf78152d82ba4
MD5 ee0f9aca3e11ca0ec54b92820046183d
BLAKE2b-256 4d55e600631af335a3c793180922f7556be5ed622c9730ff7a21c407cf249fe3

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 eab48daa4780a106e32edef1fcb5df25472372cdec7e6147c53df4bbff5ccb5d
MD5 5255b67ce4479ed9da253ba08999f8e8
BLAKE2b-256 2693456da318d18de6b125dad8e842d75be09939eeee5eed7e3ea5f4697ccc8e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 ca24d68896c7a2634fc0cfe272516bccb2f7926e1493368feb1ae06f9382de75
MD5 e524d33b483f5ef9ba5bd772b2de3d3e
BLAKE2b-256 bcf6bb7c6814d7b43376980bf6c5e54a0b8d8a5bac0179f91c8e81252eb4386b

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 57e383ceaa9a1cdc5da4b6ad5a26ccf4a1cc5fee459cba29b8425360260bfa66
MD5 1a4461fdaaea03400096e3a93e92771a
BLAKE2b-256 63e3533e182f9483989bd3bbe3644b003b9b03559d38d773524eef48f0546954

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp38-cp38-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp38-cp38-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 2db937a80bb8cc72f7e943985365ff5c984a9d356df6da39cd1bd112d6275392
MD5 6efb948691f31c0c06da53d45dfc2ee5
BLAKE2b-256 ea133d5ac1e3694c99cf48b0b3225f3bbcf6dee05765faf7504955b632411fc7

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 08aefd31eacc59ad8bb952c2cb164697bbe207a45389036c35b41779a49a36ee
MD5 f18e2789f4232e801cdfee0f8c71e49f
BLAKE2b-256 64aa0477d041cda0e5e7e7a0977ce8ce4ec02cfa3e73137ae2e33a85bb6c0523

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.10.3-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 816.3 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-2.10.3-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 1bca9cd1be6caae7e0ce363023eb84455158a76395e229d2704520f5fa34f353
MD5 305e636bdbd8fc079f87523af615ac76
BLAKE2b-256 9bef18804d1e236ee7c868c787e13b2f536f83c695c96dab3a7f9c95b611f124

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 1f161c65ecdf5d1d4cb7581536a73c0d487059db9c8e1b968e9f775c59fc3ed6
MD5 b90dd0d15a6f4497a3060b1a4c13ba39
BLAKE2b-256 8b46351eb0f412513a2ea62f925be299bf2d16af0743d0f1d7f180f388fb5215

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 2eb72ff60977b858e0e85c4fe56e66bc9073162f1bd6a6d589c758e8fcf48440
MD5 b3eb2c55b4648376f4f18f6a56ec8a49
BLAKE2b-256 ca42798271762e90edb459001bc0b0dcf455f9fef3ae9f87297db91d20c32b07

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 23c181a21e0238278d6b3bfe2575f06146a503b36392d3079fe99b3edad74807
MD5 2ad58fdf251796fcc5c98dbdc703a6ed
BLAKE2b-256 549360faed5e0ed18298e4fb3ac84a0fcc9b88191cc240da785dc9415895f3c9

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 552f8d87bb79174fcf57faace8bd6d3baa349f19d792db5417bf719e5998287f
MD5 013735ee297445578fd6ae999ec826c2
BLAKE2b-256 a7af19783e60369e6ad68f9a0d546a778bacfff3fca4207d8e5dc064bc9ded03

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp37-cp37m-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 af9aa6e83305be556f48e141a24e9df690d2e0c933e9800fbe61cafd501823e0
MD5 88332dab5164e7cecb113420841c0296
BLAKE2b-256 6168f8e1a41d674bece271b7598aa251dfd11cf72a87b59e9d1fabc9d223b63a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 bfda6ca15d390190ccd1bb64c38f917604c4d6c0bf88b598977a64603d700246
MD5 4b18b4fe01f4000826c0145f7157db65
BLAKE2b-256 da181dcea9bb720c74eca208394c860efbb19519b4e3ffb4dc3af6997ef84342

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 51aa62c2b6638f80965720ed60479e6d857098de1c15282872a9186469a0c751
MD5 6118e7d9e72313fdb13126510ad2700b
BLAKE2b-256 edbcdff1355b4453ccdce4d890483752ff7ee6e0f00035cfcb5fb23356181cca

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 e06ebf156c7a20e935aba73805833b778a9a6f018eeddc12eed551e2dbefecbc
MD5 56714019cea1c568d37f1ef06f3368d4
BLAKE2b-256 97ac9bb74f51484497ec6b4e609bed5110fdc33a81c3a2ba33a7ee74f2c45faa

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 a20caa84f7ecd53810d7ce801b8fb7ef01e00815dc69b967a2046a5fbd532aac
MD5 0fa01fbd8dce213894ea8fa82e3d4189
BLAKE2b-256 88ab17675733a6401b300b53a157a0d954e30ddf11667a6db59b2a4b3bf57d9f

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 15f81096b6a28879158822c50ced0dc64308446603a54109c1754b1ab29a0690
MD5 70cd6ba511d01e3644256cac8ef2b2a0
BLAKE2b-256 cf266ee5eb2a57607209d292a994172c6eac7c79ff018f4a5c0db84309468e78

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e2db4f91e793ef09ef1dd95e1c002ec6b782457c0ea95fa7a6124d89328b92da
MD5 5bc4227cc33f45781c05818f755e1824
BLAKE2b-256 06e134ab177f4a65458b72272e81a98bb3e36a8b5e8b6f4e022c40de1c016bb0

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 59b554bc3931664ce44ec0919a7e4b34ae7d2e925acd1e57235c508369cfd635
MD5 47e9bbe7d6ce7cb2085db8996adf8281
BLAKE2b-256 682f7288eec2e12dc45348ac04ec518343f8f360c3b10bfcf1f698427b2ac447

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.10.3-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 810.8 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-2.10.3-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 d242153e6554f279d95d9d65996c69edcb5a48dad68023916daeaa078a86f10f
MD5 5699975c0d2bcca885172df4247137c9
BLAKE2b-256 c5073686c2d52468a465f123553ca972de4d886e6d5ce55d868b45ee39bc73cc

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 cbde3131bb070fc23e1d58582f9c35a0274a35bf872925a24dcd8b08586a6233
MD5 54a43ab13a31e227da9d2c3d1ee492e7
BLAKE2b-256 6b57bf6d90f4995898d5a7fc4918114089408922b24614c4bff98470022b5c33

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 4664e16b80053f4fea78ad9d96f98f30215436c2485413ca09ae804e4cf4b92d
MD5 ae79a10db08cbe1f1f7af1bb6e5e9df4
BLAKE2b-256 c5426f311362248e32832642451cda48a69f65528de6fd2f411389440732b1a8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 bf65f28fb5604cfde2a69b4f2b0830719b6352fe875aa9b59ded6a5fdc203d3c
MD5 e08923662ecdb6df36e85d854f45de7b
BLAKE2b-256 a3c9bebc6eb62e9aa1fafa0ad9eecd9e55ebbc5a26b4052655962fd83efa0c56

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 5966bf6857c9e67a56ff40c96c7eab4665ee68534b880f7e710d23bbc5f3300b
MD5 bd5a994f36cbd182a72aa7dc51f36fea
BLAKE2b-256 31dd4dceaef7a0e09b1dcbfccedc1af80e5fc28030ee3d76e24f04faebc9f388

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp36-cp36m-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 3ff2e3450e39e4241690db7d33773edb27ad708d7f6daff7c62953e190c9c6f0
MD5 467da522fac43b8ddb9aad26b2390f2d
BLAKE2b-256 02f3792f68e036cea3d3cc1fcc9de5ae108539ba46661929cb673b4c01b60008

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1060cbc3bdf7f8c3e34f15c70acb031a1a9365c5b9090ce52626b78cdd644343
MD5 30382f4d09cc713fa6d05faf2fa6e129
BLAKE2b-256 ed804c0ab3c8da2e440bfb05faf12c2743bd86d15ef9331d30637908ce2ed811

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 c6ad7be4d58d7143dad65745da7b1bdd7db848e812058d56e860d5641ff5b819
MD5 59a3c7834f4008c253b9ca5d9afcfa7d
BLAKE2b-256 8063a4ffaee5fdca608d1d9e12d615e7f47628ebca4aa2b93edbb9a8c498092c

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 6afb1a51394045809647f761ff0bf887ae484d9f6b198c75f7c2c62f85c19555
MD5 4edfd908a0a51ef87217c54cbd23c709
BLAKE2b-256 4139c5d7d10bb104fea66158a2c5c9add0d2dc7edfb4e5b7943fe2bb7d1a921f

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 006d6d9fe0b5ab75c77222b04147097aa92775e7473a0fb94ea6f63574c32fb6
MD5 f1343d27deb74ee5a95a5f698d97e89b
BLAKE2b-256 b25cbc3c3c069f2074282d6314715bdf936d861f4ff498f8d4a31401797f3696

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 d28c045973feab701537684b19e0e340697e570d84565884f92b679bf6c142ba
MD5 61686f698bc537d0fdc70d293aae9100
BLAKE2b-256 928c8b80b00e3ea5345318ea580cdf112caf500e3439ca2384fb29f672bdc6c8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.3-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.3-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 05ccc001b5e9c3d4a3632ed4dbb0c4d950b9f82dd722373c79fee8dbea04a35d
MD5 26d796abf3343aa03347880366eb415f
BLAKE2b-256 18cc25f004db960ae7f6022b3227161093e9cffe846c4b13eab72f4dc3b985a8

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