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

2.10.3

This version

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-2.10.2.tar.gz (788.2 kB view details)

Uploaded Source

Built Distributions

rapidfuzz-2.10.2-pp39-pypy39_pp73-win_amd64.whl (855.5 kB view details)

Uploaded PyPy Windows x86-64

rapidfuzz-2.10.2-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-2.10.2-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

rapidfuzz-2.10.2-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl (1.2 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

rapidfuzz-2.10.2-pp38-pypy38_pp73-win_amd64.whl (857.8 kB view details)

Uploaded PyPy Windows x86-64

rapidfuzz-2.10.2-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-2.10.2-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

rapidfuzz-2.10.2-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl (1.2 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

rapidfuzz-2.10.2-pp37-pypy37_pp73-win_amd64.whl (857.7 kB view details)

Uploaded PyPy Windows x86-64

rapidfuzz-2.10.2-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-2.10.2-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

rapidfuzz-2.10.2-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.4 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.2-pp37-pypy37_pp73-macosx_10_9_x86_64.whl (1.2 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

rapidfuzz-2.10.2-cp311-cp311-win_amd64.whl (920.6 kB view details)

Uploaded CPython 3.11 Windows x86-64

rapidfuzz-2.10.2-cp311-cp311-win32.whl (819.7 kB view details)

Uploaded CPython 3.11 Windows x86

rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ x86-64

rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ s390x

rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_ppc64le.whl (2.1 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ ppc64le

rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ i686

rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_aarch64.whl (1.9 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ ARM64

rapidfuzz-2.10.2-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-2.10.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ s390x

rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ i686

rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.2-cp311-cp311-macosx_11_0_arm64.whl (1.0 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

rapidfuzz-2.10.2-cp311-cp311-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

rapidfuzz-2.10.2-cp311-cp311-macosx_10_9_universal2.whl (2.3 MB view details)

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

rapidfuzz-2.10.2-cp310-cp310-win_amd64.whl (917.5 kB view details)

Uploaded CPython 3.10 Windows x86-64

rapidfuzz-2.10.2-cp310-cp310-win32.whl (816.9 kB view details)

Uploaded CPython 3.10 Windows x86

rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ s390x

rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_ppc64le.whl (2.1 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ ppc64le

rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ i686

rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_aarch64.whl (1.9 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ ARM64

rapidfuzz-2.10.2-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-2.10.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ s390x

rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686

rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.2-cp310-cp310-macosx_11_0_arm64.whl (1.0 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

rapidfuzz-2.10.2-cp310-cp310-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

rapidfuzz-2.10.2-cp310-cp310-macosx_10_9_universal2.whl (2.3 MB view details)

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

rapidfuzz-2.10.2-cp39-cp39-win_amd64.whl (918.9 kB view details)

Uploaded CPython 3.9 Windows x86-64

rapidfuzz-2.10.2-cp39-cp39-win32.whl (819.1 kB view details)

Uploaded CPython 3.9 Windows x86

rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ s390x

rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_ppc64le.whl (2.1 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ ppc64le

rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ i686

rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_aarch64.whl (1.9 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ ARM64

rapidfuzz-2.10.2-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-2.10.2-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ s390x

rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686

rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.2-cp39-cp39-macosx_11_0_arm64.whl (1.0 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

rapidfuzz-2.10.2-cp39-cp39-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

rapidfuzz-2.10.2-cp39-cp39-macosx_10_9_universal2.whl (2.3 MB view details)

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

rapidfuzz-2.10.2-cp38-cp38-win_amd64.whl (919.4 kB view details)

Uploaded CPython 3.8 Windows x86-64

rapidfuzz-2.10.2-cp38-cp38-win32.whl (818.1 kB view details)

Uploaded CPython 3.8 Windows x86

rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ s390x

rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_ppc64le.whl (2.1 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ ppc64le

rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ i686

rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_aarch64.whl (1.9 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ ARM64

rapidfuzz-2.10.2-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-2.10.2-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ s390x

rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686

rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.2-cp38-cp38-macosx_11_0_arm64.whl (1.0 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

rapidfuzz-2.10.2-cp38-cp38-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

rapidfuzz-2.10.2-cp38-cp38-macosx_10_9_universal2.whl (2.3 MB view details)

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

rapidfuzz-2.10.2-cp37-cp37m-win_amd64.whl (915.2 kB view details)

Uploaded CPython 3.7m Windows x86-64

rapidfuzz-2.10.2-cp37-cp37m-win32.whl (816.3 kB view details)

Uploaded CPython 3.7m Windows x86

rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_x86_64.whl (2.1 MB view details)

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

rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ s390x

rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_ppc64le.whl (2.1 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ ppc64le

rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ i686

rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_aarch64.whl (1.9 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ ARM64

rapidfuzz-2.10.2-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-2.10.2-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ s390x

rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ i686

rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.2-cp37-cp37m-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

rapidfuzz-2.10.2-cp36-cp36m-win_amd64.whl (910.7 kB view details)

Uploaded CPython 3.6m Windows x86-64

rapidfuzz-2.10.2-cp36-cp36m-win32.whl (810.8 kB view details)

Uploaded CPython 3.6m Windows x86

rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_x86_64.whl (2.1 MB view details)

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

rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_s390x.whl (2.1 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ s390x

rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_ppc64le.whl (2.1 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ ppc64le

rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ i686

rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_aarch64.whl (1.9 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ ARM64

rapidfuzz-2.10.2-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-2.10.2-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.7 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ s390x

rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.8 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ppc64le

rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ i686

rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.5 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ARM64

rapidfuzz-2.10.2-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-2.10.2.tar.gz.

File metadata

  • Download URL: rapidfuzz-2.10.2.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-2.10.2.tar.gz
Algorithm Hash digest
SHA256 26a80cfe249a3100f94737c0207626b0b6f3ac4e77077248599f6dbe7860a9d0
MD5 2b45cf55658f07b020b1e75b3a15c2a3
BLAKE2b-256 ee920c0366b108f658dd29fdf7e9ae73874e9b0c36a9d7c72e7690d075132a3d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 669808bcac656759c011861cf2e5cea61895c7fad57a23f7e020023b7e4ceed6
MD5 9e28e0b1328789d1d82005ab58ac313a
BLAKE2b-256 9e22ecccc3782f0f437e385b1a6ba2a66e0fe415baa717c836f96fefd2419313

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4a4e0ab3655a8aa696b041955356a38105843726858b18668ce23eff87715a64
MD5 f7a82ac77da88cfef02433a8419cb197
BLAKE2b-256 8f8bf9acb23f202d4a76160e8e9bebfdd056f3adc948e4c6836425a0bd49823d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 454e0c6b50bcc65e9f549b149cd6e4cb906af7f327992900ed98e6734cf4e370
MD5 5d87f8c944195543e85a8a740c270ed2
BLAKE2b-256 0e3c68ac60cf90c8d3d726e762cbff542d806dd8c481ed193920011940aef8bc

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 866a5d95ed945345a37d560ec1bc6ecca670cf6349dda9f4775d3f8d41088c9c
MD5 29f4917955552d0a7b3a7a5306ec51ad
BLAKE2b-256 44bc701cb8e469827d93967d2a414a01972453f4b3255c032bfa0ab5df179b57

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 3e534fd1b7424165c40380216117e689a74a9c25448be51914338b7088c26048
MD5 800da6fe92a5a2ec358c4c4d1f27a313
BLAKE2b-256 0ea04e566357e7da96e9013cd9c5b4d1b743cbeb6cb26f0328904c3bd81b1726

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 c8ff3803b3daa4351ecbb9ee5e9eaa1d2f2f00e739a50c338de075bb04aff8c5
MD5 6f5e4e7c94bd789785a4665b2cfb09ad
BLAKE2b-256 6a7df6432df91b009da1257693254c8ea6733b6726fc362244f12a38133fba0e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0c3c2055f835c58ac73e621e649ed43a0b4047c3bed6973c65ee704e4fb4880d
MD5 218164fa0a310e601569201c90b1e288
BLAKE2b-256 3813d50effc64ee25f5b9d5308b88e97278ecd345b33719a68d82f3cfcc6025e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 d048dfc22133036d5156cec0532b4dcc859555451f6df4e9f081872aab4bf96e
MD5 9548153559f01634270ca5bb3a977fb5
BLAKE2b-256 bcd5ffee8d3f37106f8b8654509cceac147e9218d5d6d3935bf1a4215457f27f

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 2da90762b6ef7b182b86cc2a6d225b38aa3d882fc16ebd1a4e7a3ac24828bd41
MD5 1eaa4e195c87ca0b8d21bb4c65841c4f
BLAKE2b-256 9f8b4a4b0046ce58ca7d7071cb7dc51c42620062b61bf9efadbca57feb16512c

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 3314db75f3634e4b557c4775d460e834531610050b5ddb9750f7235b8ff49875
MD5 23daa6e9e2d208638be67938f85c3741
BLAKE2b-256 de0b560194ccd1b258084caebf5a872604119f10f5424a0800977b5fb24e5994

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp37-pypy37_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp37-pypy37_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 9b0d572d817782c794c392e5a3d1e0741372e5f17d6476f43c09176b02542a15
MD5 ead68bb6dcb010bc6e6ecd0cfb4d763a
BLAKE2b-256 3770333c8e1c00d55b07437cd3b4fce4c419de51131510a26080e78fe6ab927d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e31b61c03daa6b9d2a8cf840dc64bda930b7bc8c636eec69bb5f825f2bcbf11f
MD5 c76118ddb99847c7309fccd6c2368a42
BLAKE2b-256 c9d665dd13f23bf0eacb82c59e9139b832f147226844982ac0fc57df91a6ff4e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 5c7a16bd803d12fdcf508379f8271986ca321e44db958674dd0f2b9cdba0136a
MD5 2a7c51ff24746d89a179884b237a0033
BLAKE2b-256 d90fa8f3c90c968957b665ed284695b5d0bda53c0db3ed64bfa89d11231c72a1

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 57a3c4e2f6dd92a099b563e079e528b039eadd5086389596f5b3db92d88110cb
MD5 a9a75c8b216eb657df17502c909ef100
BLAKE2b-256 e8aeaed5573f84df7471b15a188d62079c30e98db4b927a983119d14aea9013f

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-pp37-pypy37_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-pp37-pypy37_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 f7777f8f58dcbe228378be285b96da5dff78ac47a243fd3a51ae8cbfd343e469
MD5 f7126497ef9297eb17a838dd3f489735
BLAKE2b-256 9b63630f782100fd2fa27cc6b4ef9a92887350615d9ca34f547de86ed5ca0791

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 d7e5f8d4f449a75e374e0a99c8e5bc5ce12074050326f5c92087386eb343bd2e
MD5 b2b81fb84d119be19c9e91c1d2ffaa0f
BLAKE2b-256 e7f6543e9191eb1bacf9b08d23336ca96a8abb003a1e3207a73ddc751863a198

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.10.2-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-2.10.2-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 d1444145017adbcdad6607dba6644e2006e1d76d2ebbff0b3128a6cadce52350
MD5 5d4260cf87803995743acfcee52e9857
BLAKE2b-256 5710c7724a273a9112ca533a6b7537b6157a5f76b1430917059d98d5a03997ae

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 7bb2f0cdcdfa4753a020ade11550abab270ddfa6b57c71cff69b18c658054679
MD5 db73f5c75edbdb3e051af100f5429866
BLAKE2b-256 6439b4990f7a5aa0324572e1fe48f19025f40851ba3a632d824d0bdf27717908

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 3be968fa4df10c36c3bfb837e74abba1ab1bf6e495f838127bc935d0a156c05a
MD5 5920cb55a8c5df08a46cf1547ce96c1d
BLAKE2b-256 6d59cf2f9c527510a8a879c14fd7f031b973fdc58cb5d5b6d0bb5b7488b240ee

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 ecdcd84e8b59c8fcc8b34088f5b3d39ed72db7c7cb63bead93d67bd3e71af96b
MD5 8cddad6376cc49c4c18212353fafaf56
BLAKE2b-256 f41e1f90e70eea06e5685afb22237e22ff707debee30eb7d97ba2bc86bad2c8d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 d3162b6f62d216689cd099e17ef0dd40914d048ae34d2cb8d94a2038b3327759
MD5 8235facefd8d4deec58bf975124c5686
BLAKE2b-256 ae05af39bc6840f9d7c5fa5840725f7bcae2869aee21759fa85500c6d8bc9b88

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 69e629f2af5adecbc5c6ed1a706ce7c73c00ff9b8ed1e1c16f4ce62f34d5daef
MD5 306279e7dc5d6ce8598a08f4b28f036e
BLAKE2b-256 f38ea580e2fa8fa88a07b07491d889095122fcfb7973494ac8a394a58b381578

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 03e383fb0f7528cbdbdec457821c17608503f44d181d3be097123089a76672dd
MD5 ce7a3a061863e7ea645796e79d8b27fa
BLAKE2b-256 308e2bb0c3423b25d1565923fd066b774f49ea2f847a7a06c425208e17b01448

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 2db80fa00e3c5e3bb7b3964c97d3cfaf28e31086205a8ebd802e3cb5b0aa5a82
MD5 b610178e012f4c4092284281c980f7d4
BLAKE2b-256 7f878ed59d344ac7262085712322e4080d85f2890588f51b3a301cfee64224cd

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 2d2845c0ca8562cf3f0442ea8ea47ff809ca3070a88375547c2661975b987df4
MD5 a8973e00eae986ae4d540ab1185caf04
BLAKE2b-256 d8e7282235319e99fa6635ef2803f38a876ec8eba9feaf4b7aacdf1c3463a037

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 254da78cc451bade8a13c339ce8c0497b8d11a026bcf115648ca1bc0fb93452c
MD5 ca0146126e6705777b169bea87599614
BLAKE2b-256 e387c642176d0c59c5106363448c0ebd2580ed5784234c2e0e6db90cb80b524d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 42f2277377e4ece4e6d5ce3706496c91c0198d601639559936139a75476d88f6
MD5 13a5f549f4b7803f31955a2215638fbe
BLAKE2b-256 dabf0404c876682d7a8878d611306c1bf316dbee3ab1989186932f271f9db02c

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 bfc5b924f886b095eb09f7c3d8ae54caefb12d36f07664a38f563f4f6534b0ef
MD5 a289547f35d7199690a7401f30b264e2
BLAKE2b-256 0eb575439836aea76d9d85f67096da36d47f3117e1b6b99020f5080afb905c43

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 acc5ced3f1b2268d47ada404e7db89cef6a084ab3f11efdcc3ed19ca99b281fb
MD5 2a589285c957355533c7926c81314b86
BLAKE2b-256 2c64f7056e7d48fde3e0c0ace3ce6d5318b0ad39519610e4d5fdb49fe6cc97fd

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp311-cp311-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp311-cp311-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 2ceba10342b141273dca5d9ad005e4a0ed8397bb76fb6136f9c6e3a2bc19fcc5
MD5 7d5e719012c3e31c13eb4ea25f390dc9
BLAKE2b-256 5165a72d48f5ccd67ed48f0fcc4ce4b490c72ee8ad87e95315f477b12e5ab1e0

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 cbe7f2eacbbe49dd8853b8d3c1ec823deb4fa575aea8136d202dee8a411e2026
MD5 5018db3f3fe7d04aa1d4a498b175807a
BLAKE2b-256 354fd6d092e7f6253d93ba6d2448ccf3f09cb0c3f19949890dd6a54ccd7551cc

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.10.2-cp310-cp310-win32.whl
  • Upload date:
  • Size: 816.9 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-2.10.2-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 d48411624c7a976ba8a657f04a7722fc3e0782398f57b9919221ecac279811ee
MD5 d58f5448de1744c1ddd2bc82cdc3a9af
BLAKE2b-256 fd382282c6fbc87e271e27a75331ac2c0b90b5f371a2929e376a2b056739c099

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 75a699e8f9b04980139617cd4be4c58ff06f49947e3e3237648b05b2727e40ce
MD5 0e516629f7a12687e9df00afe0a4559d
BLAKE2b-256 13a064365fc3c638498b9db4d388be257a48ac7c0f26d96b14fb9dc15c3ac53c

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 882bb4030400ae2ea0357273360d3c20150781b950e9b1df15dce3d776bbd100
MD5 0afe13d1d49e255ad4dafc40096e6fc6
BLAKE2b-256 420eaadb926b01a21d9e2be2dc3b95e33f89ab7e9f0aa7b34c3eb963381d6461

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 decb14fb5d52b454c702376a80faa7b36c0575356090669121a692789f55db1e
MD5 1339196fe7935af11e74e0f613a5fc76
BLAKE2b-256 37dade8e351d22729032e2d84a431599d669453c914f614f25190e2ed4f0b523

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 35494d7b8dcd77704c28468b4b4f895d78f76ae28e1de3bfe5bf8957c6e8bd92
MD5 755fc763b7bd545ab2ec45a5aee77fae
BLAKE2b-256 9595c7fa7ff15fd11a8afdcc982c61cf6a33e02427c96eaf2aa39e36af104667

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 362b2b0c19c22b4e70c92a3c05828350d1bd3a011bf1c62375e2a31890dcb1bc
MD5 11fc7ca15da8203f2cbb12eae112cceb
BLAKE2b-256 07ffd89d243d53318efc5881d3a1dbca9209c3a301d2e4135cf7d5dffb77a2aa

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ada91d41f9064a79e21536871ec648db3c80ebc91e889f8f5e5aa3b69e4ebe40
MD5 d81d0ebb9da5fc9931213082c08e1e79
BLAKE2b-256 004ceec901d271b9e2d2c8acfeaa090e99e8a5754d883d96d29f5454063269e6

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 0284e5c4122e009f1217c008d98f201ca59f6ea31cbbdbe53345d25f60101ab8
MD5 f5db318a44d035ca990b972929f7af31
BLAKE2b-256 c7d4e535d6ac7e3f91913ee77b5c6bec49387f7b0e7ff751d076bb9213f9f5df

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 1f601754b6fefe335162d77b2fd112c6a60efb378fa0d64c74ff716112c3b748
MD5 0ece59cd87ef98d7d8a12eab577a66c8
BLAKE2b-256 cae81dd3021c2c0d2b8edf5aa37b5d3dfeaf0880cc1d4cb7845cf8da715e8692

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 71ec4151b8e46d3e51a92aa3a65ebda8a58ab6ad28493fe701da3b1137276e72
MD5 a04fcc62914e5edead186aa868549330
BLAKE2b-256 a904f28577d4bbe12e4eb26216c491630d5b71849c4364de2e86530c61114d28

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 fd45c3d943ed0fd90ec5569bc0297e5f44fbafed0791dfdfdfc342d779a95671
MD5 b1ce846ff9168dd5c090fee5543b49cf
BLAKE2b-256 83cde9a2802965418fc4cd5e5c8e74c233886ba58f54bc3c51c009288a4eb19a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 553300dbdbcc29262326c910337988b7ca89dc880e1ab804ca826218a15a6a6c
MD5 d30b5380d49675268d28e772a3a1e947
BLAKE2b-256 c6a60707e7968b2882eee45927e741cf0006e10dd7053eb291be896ec35b2a63

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 3451111affbdf5ee06dee92bebca71ba5b642f38ae843860eb9c38233c0b71e8
MD5 c67a96c1e90ed4642e37f498a1b872ad
BLAKE2b-256 aa5e771852e380c3ff3d4b0ae3a288cd9e8063a833b05807e79be3c3a9e2d71f

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 b867f0b75751e898ed4dc411c379bdf9bac0bc45d913eaa08482793e7a2ec2a9
MD5 070e2fc5753ca7a5230cb4a447297c77
BLAKE2b-256 4fb80e54dcb3b2f74451fb1b78b8fb81f4632117b8f000d1f2e93815774cc51d

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: rapidfuzz-2.10.2-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-2.10.2-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 b63746d773ed7374b46b3a60fd7b4d51936c21ded6749013cb9fc212bce3bdfc
MD5 d01360781b831f9bd6504c2c9b6d1c94
BLAKE2b-256 823db053b6f50922dc2b30887fdde49dab5b377ea17b3fdd70f629395684ae72

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.10.2-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-2.10.2-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 3506222bff145beebe4e0062ac52f3c51259a4d05f37a8abb9012cc752b034cc
MD5 ac828e9352601699a88856e5ffcf64f3
BLAKE2b-256 2016b865f6760ca81e285a36caa71bffe4fd2bf00d8611ffa1b0bb80038f61e8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 ef5857b30e4f49ac165ba7c57ed377451a2dadadb9fc772e10c574c435c8e634
MD5 679fe89ccee24dcab1eeb90e8fc1104f
BLAKE2b-256 846350f0f82706d6b895ab8292f6b3e5359da4917e119314357a1c31c793519c

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 c3e4e9384bbd1e8e2dd62149bc547720f26483df5fbaf272f995200ca4603975
MD5 1b22c3932f2ee066268e9c428486fa6b
BLAKE2b-256 1980b078c3d7bfdb3a9a2e51424d0d9884211d6b3a148cb0e8bcb0017ea5fd4c

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 86c0703064fa7ba127a881985de8dc8462b461dbe9aff365782fed51c11ae20a
MD5 0f91f8ae5680d8c738b179555893f647
BLAKE2b-256 23e65e31d10bb4bc1aa7675aab4b12261cff0b8b847734099edb2567d2e19495

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 2d783c753763437c4cc7c36b433ca458bc5aae69da76f3c0e8890b8cb6ac79d3
MD5 ed9da587604c7f2ff29176d377f4b484
BLAKE2b-256 b967176701693da018843ba204c6409d922cb9e5c486e474e7f8d15419aaf187

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 39007c02478452cba66f6117876d0823487a16fed0ad6d25136f5ad9d2bacafd
MD5 16de7f97e3a31220198f310a9c606995
BLAKE2b-256 548a2e49ad6bde518a0caa22bd7e4a63c89bd3050b28b1ecced0ce12fa1bbf03

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c395984b607835eac0c97d68aa03778dc075bf5cb02d6dc12495368514794a9a
MD5 ee02e5f1d9ddccbb45b7dfc50671d043
BLAKE2b-256 a76b9d731839e87226f95f1b44c6c80ffb8eed709f97acd3f73fa81c5ab63657

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 e49b8b2e76b602e6bb001709505381b95dc233372676d90a675ab94d1f086013
MD5 b382cecd232e50d2152a4fd1a4647873
BLAKE2b-256 443f52c6a02ab6b67bc05c879ee0ea5fce7b341f82b4e1302e58eff6692f2913

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 f7cc19629576d390ff656df13fe93f7443bbdc819455aad2177946cbe84140cf
MD5 eb6791a605b48ddb3f68046ecfe0d676
BLAKE2b-256 9623435a263fe1c91f00d9b31be12d4376b84f5425c762342fa2246c6c3831d2

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 d985e0149f2b2cdf4debc22d3ea742916ad2ed3e218fd45b4cd2061c95bf99dd
MD5 85b3593157fe7891ae9de2e154212697
BLAKE2b-256 ddedc9690ccac567644e5c5c9b209670fe986e5c2abebfd55b37e6fcf2f176c4

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 066c75b50cb1b3ce5edf35ed1bd7b650ad0378933246e45793d6c8f2b718c637
MD5 9b42e6ad41eebbdcf3b771f8a5daff0c
BLAKE2b-256 7a1f7c7b8a05e3a1970b28420e987803f4c12c09a6d7e7fa7c9b6c3ddd5e3d86

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 9b4ffa2bca2338c5fbdb241b50e761dd7bfcfaa3377168e32111b95292aad3b3
MD5 ce90269d344f58b4622ef1d8ced161a1
BLAKE2b-256 4467b2a4ac47afe5fd3a0b1f35a782702815978757b012d34662049e9df99fdd

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 a582e59e90a025e4e38013b17a434fa37b5eae8992925bd1c64c901827a7d124
MD5 0f4aae06f7fb74b0f8e81ba2aec8158f
BLAKE2b-256 86705e933bf72e05d19868a628a2371c0c0ea250f67b54366b0cbd07e68a44e8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 17343390c6623232ed8bf63659a89c3b4195edf6b90a1eaf7a46995f2ce8f1e3
MD5 e745d3a3f65a3ae748da8dada419a105
BLAKE2b-256 b81e2f484f15e839634c52c82ca51eec7e63a498b891b696c643b297259b6349

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: rapidfuzz-2.10.2-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-2.10.2-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 269c992257e4bf59dacab15b7ab5968cfafa6cde96b5d89776b03771a404c9e9
MD5 6658343c32b4e92f04ab5919da7447f5
BLAKE2b-256 568ce1ff094c7986422b8dee5172352f3109062dca77941207485461c7962a80

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.10.2-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-2.10.2-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 23b421b58c0982a15851ae142be2746fac606654359f3826c632fd504a51b0f5
MD5 202d630b50dad8e2e6c7dae06b37c128
BLAKE2b-256 efa7378302d2ecc4633d6939a9da0e08083d75818a65f72f3099b943f1709089

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 a3f1d9e4570115fbec9544f5c703ddf29daa92c2303f7113307d229726df7feb
MD5 dd722b4219ca9b3e379c32d5cdadd21d
BLAKE2b-256 0591bfc966e7d9745c26ddaa1fa6b95364448627066da435efbdca27245a54b8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 8b77b687f594ba7d82866adb24a40a92fd21eb330fb694ba580b2bff6161b049
MD5 91ebb8c703bfb0c22b42077df9496f23
BLAKE2b-256 70e7fccd9886df51c14297152573e1aa5a1ea75533981d86c653792c7e80c0f8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 537876a7d9895d21c22b76041cea791a299aa7a009335b9c42cf3ea4b0332ebc
MD5 0a91f555f50ca0aba869b1d8594d0cc2
BLAKE2b-256 dca7d567b140e2f258e2bf0c6488bce8f47e98c9cd7958c05d70927eb3ca818f

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 3b2056568b63aeadf57e628d38c9d7db72d01fd22b4524559a719382e18259bf
MD5 f898b95e91deb18ed51dd236d8d608fa
BLAKE2b-256 7a0644b175e730eb8728f7ccd7d680d5e91f65dd61fa02efc7a3c6a1a18e3a7e

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 9b57b05cf61c0112fb1b67d7a8d7470cee97a9c87745be2938e34f739374ae95
MD5 054cbf213c03dcf756dfe2e86236ddf4
BLAKE2b-256 e1459bfe292568f4ec84b6c69dba873625d54db7839eb9019a41fffeb545e534

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3c04633c70e3bb9342c009dbd644f5888912a894042fa651e3bfbf53fa2a523b
MD5 c573954dd8dcc18bece106f250d84cb1
BLAKE2b-256 b156413f228afe484b5a05c76d0531370d18b0924dea82125b05ae8ddfddbf22

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 de162a764b7958fcef59f5a17dc3b4a531c17b978735f83d0d4cb56c9a6734a1
MD5 5a7fdcd0adbd9f7f6808d5d7dcead1d5
BLAKE2b-256 3b844e0ee28a2b5d7ad443c6a2957027a228c0d9089997c2d00fcc0f8c7818bc

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 f81120f7a502ec3623ed0ba63be1d03e0cdb7f931310d48389756bd7e5d38ce7
MD5 944eb311a26c934a3d73de8067c618ba
BLAKE2b-256 942fa57563b476fa4f6b0dea6ac75704343e68b17bab93805247ef2c9eb7420c

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 5c180ba789b842943223b0e4d62546c8f95427316384d1839b70ef7a308961d3
MD5 bfaf38836ce270426e9a5ed5b6a9f3d1
BLAKE2b-256 a2a0d8846e1d917b727383cdd68ac41207c55f4c7f9833c15395acba0bd620a9

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 2693a81790fcddd203495ff49c7bb2e0d6c237a2de251caed2e863acf26c5d62
MD5 3b7f9dbebd35fdb07231e83604c1881f
BLAKE2b-256 0d6299313add6cc24536fee24456786a64674f163cb24745c237a5617ff57aeb

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 42e953165c2e56f5601b47685ff20ec69ca2e90d7072406358d1a7031b1d3e4e
MD5 993b6cde0bac37ebcac5ad27d65092e4
BLAKE2b-256 59069068fa3467f7b54bf2e3163cc360514282a1f0ab7c9fae05ed90c322aa31

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ea52eaef7d7b218206bcc9f35053981451369b9ccd10a0b270d27c88593571a5
MD5 8f2a0630ba7eb1fedb08e598d0b70a79
BLAKE2b-256 7c071cc60ff87ea28e1745e940f872cb1bda52f71e87e774ba684e52256c9fb1

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp38-cp38-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp38-cp38-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 b64c6c5e55519effe85d5231c04b2e5a6a54bcca9cbc0b1f3b930a8f73615d8e
MD5 98ee8998d541911616bc7600ae591048
BLAKE2b-256 003c09ee30b5da572b7a999a273917348e9605d819ada3dab53f425f1ef14e19

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 68e8e86b8a9a5b200a53a9a574240cb6edf5a393c7f82e94127e589021da95f4
MD5 7eebda09badfddf58f813423bad27ee9
BLAKE2b-256 9dfc0192de4bf4276747541e078f5a7bf30967d77c11a01d814e8e155407e252

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.10.2-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-2.10.2-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 a99664b37d3fd8b82cd80e62ea416921326a78acec12b2d8a3bed0105a2b94e4
MD5 f4539428677e17bef3e3431b15cc7eff
BLAKE2b-256 6475dd0b8119249bc7675b4b95a8727ed11a35d3460f30dfa8596bff66d993fd

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 87f6f157cfece06ca394d8bb49388e042a2abed926cf2123e7f5863ca5ee45a1
MD5 210e0b516c41efe6bf8ab740389b13fe
BLAKE2b-256 c73d2c4ac4db4ec1181aa29e8aaae5a25930e7871e0622a0ac57172453bb2ca4

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 e9cd17d3be0efc4de37c71513e6d2dcdcdfd618c26a62d04f49f9fbd0fc3f70c
MD5 6fc8535fee1018b488a796a1c9c5c454
BLAKE2b-256 c6be3bbfb7c6514226beb5dd9ccdf3666ecefa3c0be4f3c60bf6e2777537b18a

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 878540c4dc26a20b84932d9bfb81a54f1218b5f21fb44cdf075edf15915ce3d6
MD5 63be21b83baa2234b65c7fced8ed25e3
BLAKE2b-256 6756633aa2300791a84d474fc0558b6940916d53a64f18c740175fb1b5c5c84f

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 582381a0251a7b5df8701b07a77198019b507ab5195b2fad3e7da65b4026a954
MD5 38064399bf9acce2b04b6ca97053184b
BLAKE2b-256 e4807c0679a2e407a3f57c798d9d5a426472cf5cb40797ceb75e42a9ff382b36

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp37-cp37m-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 b04a7815031531b9b6657c8aa160cdeb4f97d47eaf7e673e4b7c81effb200d64
MD5 105eb011051d3d3060418b4bbbc13476
BLAKE2b-256 275359a510e4b0f2ea7f9178c0ff4d6f73f70a82852c6603b1806b59f2d06bec

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9bc9913a456069c76970ca31780b0aa0bec355f57a20013214b8a2528ff7cb07
MD5 387c24b78af973509de65f37c537b608
BLAKE2b-256 77150c6d9eab4a7db973522c1d3ff0591c4b78477e0cc72fc114ca84bc936fff

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 11e4a3fc374dfd76526eedc66b26431bc1f0810a2c2035bc8d7a6ef0aebe5bbe
MD5 b457de768a468d8cdd4bd83efb85a51c
BLAKE2b-256 2d770b3b33ca1912118b5d016196b0ba59a73de5d82011d40fd6d6b2e36cc04c

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 67ada4dcbb0cdd636505797f1fdf4047f88dac55ae1868d7424480977cf76321
MD5 e4578f517553017e5329b205db06d631
BLAKE2b-256 381c828e9eb8fb040112c9751805f31bdd825d7a7973706dc10c96468a14e6ef

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 6b599fc8b83080f359afbd08d440f48fcad8f3b569e3c2de988ec45f9bd97b64
MD5 a00708fcb2aa2a8349b579d086be0a6a
BLAKE2b-256 b5e73c6e9d4c7e419c7522aadd0b22cb0439c9d5786378fcaa593e889e31c6d2

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 7a043c60afa1f04bafefad4f41a1e7cf9e87246e0252ddb651330397412a924b
MD5 3b1668f3bb6a15eb5d51de68897858c8
BLAKE2b-256 7fee9325942ff35525507999ee4027388351a15114efc5d329a70b80c7b197aa

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 2c7a7d4aad3281d60922fc085122b7530e734183de6d5079a76c012e70c11311
MD5 c507c1e3c33ae6cf5cdf58a92f31a26b
BLAKE2b-256 c8e5c363119869a0ff3b0fefc6bfb1d5fd1c9080219406154a2fe20e29609abe

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 89cb358e29bb9361fe2e714195937e5e4a843a2f3b2ebeab804c1ec2f88aab0d
MD5 78255ffdb1ef2a71bf688080f4d1b507
BLAKE2b-256 3c8fb150173ecf6624e409a84449bab9c6854d72a93b77bdca4dbc0e61a72df7

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-win32.whl.

File metadata

  • Download URL: rapidfuzz-2.10.2-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-2.10.2-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 1197d0fbcbf7f536159b3a0b7cb3fce88e253fb381fc974223daa9d2eb7ecebe
MD5 e045d2f8221ba51ba5758c6fd7595c9d
BLAKE2b-256 3cd58e95bf6d61d4f0bd49043fc80b734250e54daf1136129b358cb59091a955

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 ee73d74a1dda83a3c4f045dbf5a5d7169d07c982359ac98428570be4fd807e96
MD5 801eb8988c864bad7c204160fcfc285c
BLAKE2b-256 c91b61d8b554cb944ed99846d2dbda2499a636a3eea9f5d72b35f40a69faa911

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_s390x.whl
Algorithm Hash digest
SHA256 3ad0d8b49fa341106fce6a8edaea288eba0de8b952d00a3ec6dfe67b10a4a993
MD5 87b68c83a8d4ea0b41ab9059073f92b3
BLAKE2b-256 60750cc8df2343d67685211e7cffb2b77c905de9a213abd2127f12f54ed7e8c0

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_ppc64le.whl
Algorithm Hash digest
SHA256 218aaaa85ec3a6b0fd43eb45b29958f9fc62dc912f200da08fae74a69c7e04ca
MD5 1a6565751af58c9811cf842db1ab078a
BLAKE2b-256 fed0706438becb47babf2300e766552cb9176051b9d0c5634bf33e8a0b818757

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 43dd54c4f6eef741387700bc7e3a2ded3873c81704c66aa458e6147b6005ccf1
MD5 0c71636af6a0fe85b4187c97af8ec070
BLAKE2b-256 c8450bc1a9f1dd96b73018cf8bcdde0b26fc4c84d58fd45a66c040841d37e135

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp36-cp36m-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 48be65a68e54ac987a7d1ce4e3c1ffa1ac1dcf8b6d18e3390876294334f5ea01
MD5 df2cef78722fb460fa2b9058e5cd53df
BLAKE2b-256 5c12844dae07e377a1e06e971847b34d6be7b0898956c656cde9a2165ed767b3

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3e7d465d8bdfe5b4c80d7f5d4a30f90fc51e1de06d57ff05f4594a6dab819e4e
MD5 7aab6064f55b7c68c6121e7e63754e3e
BLAKE2b-256 63c5c2b5ae0aa3a442123c35ba9c64c4276c282373b7761db9e89cee0a9118de

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 e322db1cfdc1efe269ad6e85e02bbaaea52bb3b52433420b302d39701cc222f7
MD5 26fabdedae8ef370d8f5229981000968
BLAKE2b-256 d648f8011cb82e395f5bc59a8884785e62316e9cfb3c484665de4804e9ef8f91

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 b8df0f8dfa9b0a9b3eeffadff8c468219a2e6f1794dd8a722260825f78c233ed
MD5 60f180b69e2618a4573f1533df9d28d0
BLAKE2b-256 8ab624090b473b14ea7aab26a834f6a1eb9d25075baee7854908c5442412c9f8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 a3e50b213ad85ec51fe8a0752d4d66808a44de44548b9f24028b449f68d3ff73
MD5 a2fc78d218998aabbaf124ab4bd1f76c
BLAKE2b-256 b9d42ce988a766b64976bff1abb86064fc9ef3d9d885b5b2f3d7ea24e2aebbe8

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c8da4f23998eb265bf4a6773a9efcae1e3f5e994c2478406e8fdb353c87ad3ec
MD5 140c83b85786e3dd2df9f90ab10acc52
BLAKE2b-256 9011bae1da636b9025f5d55a0033a86439b2b432d818470a815348989dd6e212

See more details on using hashes here.

File details

Details for the file rapidfuzz-2.10.2-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidfuzz-2.10.2-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 6a74967e9ff9d19318df3416e830ac0168803b01818f0529a4da8b78ab19560c
MD5 2057689187c59de760c1fef238d3698b
BLAKE2b-256 08d72a46ca098148b896ecb0a20b008b446fbbd7e5cd7067f9571ec188dddac6

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