Snowball stemming algorithms, for information retrieval

Navigation

Verified details

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

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: BSD License, MIT License (MIT, BSD)
  • Author: Richard Boulton
  • Maintainer: Richard Boulton
  • Tags python, information retrieval, language processing, morphological analysis, stemming algorithms, stemmers
Classifiers

Project description

Stemming algorithms

PyStemmer provides access to efficient algorithms for calculating a “stemmed” form of a word. This is a form with most of the common morphological endings removed; hopefully representing a common linguistic base form. This is most useful in building search engines and information retrieval software; for example, a search with stemming enabled should be able to find a document containing “cycling” given the query “cycles”.

PyStemmer provides algorithms for several (mainly European) languages, by wrapping the libstemmer library from the Snowball project in a Python module.

It also provides access to the classic Porter stemming algorithm for English: although this has been superseded by an improved algorithm, the original algorithm may be of interest to information retrieval researchers wishing to reproduce results of earlier experiments.

Project details

Verified details

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

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: BSD License, MIT License (MIT, BSD)
  • Author: Richard Boulton
  • Maintainer: Richard Boulton
  • Tags python, information retrieval, language processing, morphological analysis, stemming algorithms, stemmers
Classifiers

Release history Release notifications | RSS feed

This version

2.2.0.3

2.2.0.2

2.2.0.1

2.2.0

2.0.1

2.0.0.1

2.0.0

1.3.0

1.2.0

1.1.0

1.0.1

1.0

Download files

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

Source Distribution

pystemmer-2.2.0.3.tar.gz (303.9 kB view details)

Uploaded Source

Built Distributions

PyStemmer-2.2.0.3-pp310-pypy310_pp73-win_amd64.whl (180.3 kB view details)

Uploaded PyPy Windows x86-64

PyStemmer-2.2.0.3-pp310-pypy310_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (225.1 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

PyStemmer-2.2.0.3-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (218.3 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

PyStemmer-2.2.0.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl (173.9 kB view details)

Uploaded PyPy macOS 11.0+ ARM64

PyStemmer-2.2.0.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl (170.3 kB view details)

Uploaded PyPy macOS 10.15+ x86-64

PyStemmer-2.2.0.3-pp39-pypy39_pp73-win_amd64.whl (180.2 kB view details)

Uploaded PyPy Windows x86-64

PyStemmer-2.2.0.3-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (225.0 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

PyStemmer-2.2.0.3-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (218.2 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

PyStemmer-2.2.0.3-pp39-pypy39_pp73-macosx_11_0_arm64.whl (173.8 kB view details)

Uploaded PyPy macOS 11.0+ ARM64

PyStemmer-2.2.0.3-pp39-pypy39_pp73-macosx_10_15_x86_64.whl (170.1 kB view details)

Uploaded PyPy macOS 10.15+ x86-64

PyStemmer-2.2.0.3-pp38-pypy38_pp73-win_amd64.whl (179.8 kB view details)

Uploaded PyPy Windows x86-64

PyStemmer-2.2.0.3-pp38-pypy38_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (224.7 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

PyStemmer-2.2.0.3-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (217.7 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

PyStemmer-2.2.0.3-pp38-pypy38_pp73-macosx_11_0_arm64.whl (173.4 kB view details)

Uploaded PyPy macOS 11.0+ ARM64

PyStemmer-2.2.0.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl (169.5 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

PyStemmer-2.2.0.3-pp37-pypy37_pp73-win_amd64.whl (179.8 kB view details)

Uploaded PyPy Windows x86-64

PyStemmer-2.2.0.3-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (224.6 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

PyStemmer-2.2.0.3-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (218.1 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

PyStemmer-2.2.0.3-pp37-pypy37_pp73-macosx_10_9_x86_64.whl (169.4 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

PyStemmer-2.2.0.3-cp313-cp313-win_amd64.whl (185.3 kB view details)

Uploaded CPython 3.13 Windows x86-64

PyStemmer-2.2.0.3-cp313-cp313-win32.whl (141.3 kB view details)

Uploaded CPython 3.13 Windows x86

PyStemmer-2.2.0.3-cp313-cp313-musllinux_1_2_x86_64.whl (677.5 kB view details)

Uploaded CPython 3.13 musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.3-cp313-cp313-musllinux_1_2_i686.whl (643.3 kB view details)

Uploaded CPython 3.13 musllinux: musl 1.2+ i686

PyStemmer-2.2.0.3-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (678.4 kB view details)

Uploaded CPython 3.13 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

PyStemmer-2.2.0.3-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (638.2 kB view details)

Uploaded CPython 3.13 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

PyStemmer-2.2.0.3-cp313-cp313-macosx_11_0_arm64.whl (220.0 kB view details)

Uploaded CPython 3.13 macOS 11.0+ ARM64

PyStemmer-2.2.0.3-cp313-cp313-macosx_10_13_x86_64.whl (214.4 kB view details)

Uploaded CPython 3.13 macOS 10.13+ x86-64

PyStemmer-2.2.0.3-cp312-cp312-win_amd64.whl (185.4 kB view details)

Uploaded CPython 3.12 Windows x86-64

PyStemmer-2.2.0.3-cp312-cp312-win32.whl (141.4 kB view details)

Uploaded CPython 3.12 Windows x86

PyStemmer-2.2.0.3-cp312-cp312-musllinux_1_2_x86_64.whl (683.0 kB view details)

Uploaded CPython 3.12 musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.3-cp312-cp312-musllinux_1_2_i686.whl (649.2 kB view details)

Uploaded CPython 3.12 musllinux: musl 1.2+ i686

PyStemmer-2.2.0.3-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (683.3 kB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

PyStemmer-2.2.0.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (644.1 kB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

PyStemmer-2.2.0.3-cp312-cp312-macosx_11_0_arm64.whl (220.4 kB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

PyStemmer-2.2.0.3-cp312-cp312-macosx_10_13_x86_64.whl (214.9 kB view details)

Uploaded CPython 3.12 macOS 10.13+ x86-64

PyStemmer-2.2.0.3-cp311-cp311-win_amd64.whl (184.8 kB view details)

Uploaded CPython 3.11 Windows x86-64

PyStemmer-2.2.0.3-cp311-cp311-win32.whl (140.9 kB view details)

Uploaded CPython 3.11 Windows x86

PyStemmer-2.2.0.3-cp311-cp311-musllinux_1_2_x86_64.whl (673.2 kB view details)

Uploaded CPython 3.11 musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.3-cp311-cp311-musllinux_1_2_i686.whl (639.7 kB view details)

Uploaded CPython 3.11 musllinux: musl 1.2+ i686

PyStemmer-2.2.0.3-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (669.3 kB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

PyStemmer-2.2.0.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (630.9 kB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

PyStemmer-2.2.0.3-cp311-cp311-macosx_11_0_arm64.whl (220.1 kB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

PyStemmer-2.2.0.3-cp311-cp311-macosx_10_9_x86_64.whl (214.2 kB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

PyStemmer-2.2.0.3-cp310-cp310-win_amd64.whl (184.9 kB view details)

Uploaded CPython 3.10 Windows x86-64

PyStemmer-2.2.0.3-cp310-cp310-win32.whl (141.2 kB view details)

Uploaded CPython 3.10 Windows x86

PyStemmer-2.2.0.3-cp310-cp310-musllinux_1_2_x86_64.whl (656.7 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.3-cp310-cp310-musllinux_1_2_i686.whl (626.9 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.2+ i686

PyStemmer-2.2.0.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (646.7 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

PyStemmer-2.2.0.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (612.1 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

PyStemmer-2.2.0.3-cp310-cp310-macosx_11_0_arm64.whl (220.1 kB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

PyStemmer-2.2.0.3-cp310-cp310-macosx_10_9_x86_64.whl (214.2 kB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

PyStemmer-2.2.0.3-cp39-cp39-win_amd64.whl (185.1 kB view details)

Uploaded CPython 3.9 Windows x86-64

PyStemmer-2.2.0.3-cp39-cp39-win32.whl (141.3 kB view details)

Uploaded CPython 3.9 Windows x86

PyStemmer-2.2.0.3-cp39-cp39-musllinux_1_2_x86_64.whl (656.2 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.3-cp39-cp39-musllinux_1_2_i686.whl (625.3 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.2+ i686

PyStemmer-2.2.0.3-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (646.6 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

PyStemmer-2.2.0.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (612.3 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

PyStemmer-2.2.0.3-cp39-cp39-macosx_11_0_arm64.whl (220.4 kB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

PyStemmer-2.2.0.3-cp39-cp39-macosx_10_9_x86_64.whl (214.4 kB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

PyStemmer-2.2.0.3-cp38-cp38-win_amd64.whl (185.3 kB view details)

Uploaded CPython 3.8 Windows x86-64

PyStemmer-2.2.0.3-cp38-cp38-win32.whl (141.4 kB view details)

Uploaded CPython 3.8 Windows x86

PyStemmer-2.2.0.3-cp38-cp38-musllinux_1_2_x86_64.whl (651.0 kB view details)

Uploaded CPython 3.8 musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.3-cp38-cp38-musllinux_1_2_i686.whl (619.3 kB view details)

Uploaded CPython 3.8 musllinux: musl 1.2+ i686

PyStemmer-2.2.0.3-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (642.3 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

PyStemmer-2.2.0.3-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (608.6 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

PyStemmer-2.2.0.3-cp38-cp38-macosx_11_0_arm64.whl (220.6 kB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

PyStemmer-2.2.0.3-cp38-cp38-macosx_10_9_x86_64.whl (214.7 kB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

PyStemmer-2.2.0.3-cp37-cp37m-win_amd64.whl (185.3 kB view details)

Uploaded CPython 3.7m Windows x86-64

PyStemmer-2.2.0.3-cp37-cp37m-win32.whl (141.3 kB view details)

Uploaded CPython 3.7m Windows x86

PyStemmer-2.2.0.3-cp37-cp37m-musllinux_1_2_x86_64.whl (635.6 kB view details)

Uploaded CPython 3.7m musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.3-cp37-cp37m-musllinux_1_2_i686.whl (602.5 kB view details)

Uploaded CPython 3.7m musllinux: musl 1.2+ i686

PyStemmer-2.2.0.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (629.2 kB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

PyStemmer-2.2.0.3-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (594.9 kB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

PyStemmer-2.2.0.3-cp37-cp37m-macosx_10_9_x86_64.whl (214.9 kB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

PyStemmer-2.2.0.3-cp36-cp36m-win_amd64.whl (195.3 kB view details)

Uploaded CPython 3.6m Windows x86-64

PyStemmer-2.2.0.3-cp36-cp36m-win32.whl (151.0 kB view details)

Uploaded CPython 3.6m Windows x86

PyStemmer-2.2.0.3-cp36-cp36m-musllinux_1_2_x86_64.whl (623.0 kB view details)

Uploaded CPython 3.6m musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.3-cp36-cp36m-musllinux_1_2_i686.whl (590.8 kB view details)

Uploaded CPython 3.6m musllinux: musl 1.2+ i686

PyStemmer-2.2.0.3-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (618.1 kB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

PyStemmer-2.2.0.3-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (581.8 kB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

PyStemmer-2.2.0.3-cp36-cp36m-macosx_10_9_x86_64.whl (213.0 kB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file pystemmer-2.2.0.3.tar.gz.

File metadata

  • Download URL: pystemmer-2.2.0.3.tar.gz
  • Upload date:
  • Size: 303.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for pystemmer-2.2.0.3.tar.gz
Algorithm Hash digest
SHA256 9ac74c8d0f3358dbb050f64cddbb8d55021d831d92305d7c20780ea8d6c0020e
MD5 ba07aa8cd65b875013a625dca31a28b1
BLAKE2b-256 26120378ba4391a4674067ae9db0e025ec998f6ca74caddd22fbdc59dc19aafb

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp310-pypy310_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp310-pypy310_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 7f0d5f36922ea94599f79f86383972e91cdeab28918f8e1535cd589d2b5fb345
MD5 7bc658a30923906bc8a6fd095877f677
BLAKE2b-256 65ac3822a77de25f035b77130bfd30dcf57871c8818795918c3806b9b4e152ca

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp310-pypy310_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp310-pypy310_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f8c307f1d5084e6074bc1826df9453887e589e92bab63851991b444f68a08b7e
MD5 468486d845df80e375fcdd093d12ebed
BLAKE2b-256 5011e9a0e32573391d335560e9caf05011d15c8b7d368f318d3a4516275c8938

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 4abcb516040d7a561eb95c60125f9f5636080c154f46d365b14cd33197ac74fd
MD5 82687457a61cf7f8eed05c5453d608f1
BLAKE2b-256 f437a4a4b8d9db835fbf55dd532c357286b58c7418188a38233f067ef0197ad0

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 41a31d8ad810063e2cc675d93d0951dbfbb6ede278e111f15d74b7d781612364
MD5 8e79a2a3aba7d7bf89931ebdc81e340f
BLAKE2b-256 2131eb832a4296814acd8c403eb555ada436700d93ab526c824e2f1d69dced15

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 ff3feeac41968fd8b50e9d6b8a03a5f15b27e765a0826f06dc32155f8f22909c
MD5 ec71a523190e2d604f0f90a494834f4e
BLAKE2b-256 0e69cbc7f00bda703f5b60a665a68e2d9df6c077c59da2bea52f35b1a496c549

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 825b81d3340671583cae72ff0918ad898718aa0e37662c6b4d63e63e8f5f98d9
MD5 95102b7dcf63b68ff936245298724637
BLAKE2b-256 7b3d17d504f7e4fff198edc2e5941df5f0d20a1d7eba33db2d094408205822bf

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e92f8bdd2b7ddf84cafdda6eb613e1c536b62d6a412d633a202d7d5e41155b89
MD5 6e7602a63f48d5b3de940f74bbdcd4ed
BLAKE2b-256 b5b5f4a93188e862c795dd2a1d905b2fb69ecca8f7e64c968e4a3b5e7ae75163

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 e051104462150ce801e8fb4ca3aee23e4a9a2ba31c21a8a95b231ee776a12a56
MD5 78b2e15a5a5201617063eb6fdd5dcbba
BLAKE2b-256 5d4456c88eac931925262021127ed105657700a90832c622c7a3c4ed0386129a

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp39-pypy39_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp39-pypy39_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 5b4229166a04b6c0dab7e2234e4203ba4a4993805367524cd79d7e7bdd15b7af
MD5 0e5ac649aaae250d0a597c13017888ba
BLAKE2b-256 3032bbbb69aa39b128f8e89e4a863832208f0234bc63e8d571963210ca80df41

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp39-pypy39_pp73-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp39-pypy39_pp73-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 84c141725402033472b64b4d40deb828de040b6890399de2fbe9b9b16f939cc4
MD5 bc5ebcab680cfc596e616f02e0dfa891
BLAKE2b-256 2b8e3b53036674b7b1274bb1e8966de22693a72c19d99f28a9af1b970857054a

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 09d236633ba63ab312e8d763a23803dcef4d2192c3cc3760f14bb749393413c6
MD5 e1ec5f2a32df24dba6ab9a292a4531a0
BLAKE2b-256 10c87824fbbc3f83129ee06a08193ec7772197444e22d0bcec358a08b0d186d9

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp38-pypy38_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp38-pypy38_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d648b669bf761a61d42b82497d397a84039e22f3a20a601b718ec7db7bfe0feb
MD5 e1047fcc911fb28d985cd1622791f883
BLAKE2b-256 eb1399b0f7dd2fd7d0b4a07f4189da1bfee0c0eeab1fd9331b75668f4f1f98df

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 e88eeeb5b221b4647f7471a683b7cc9e270bd11e5b8e83c983dc62fd72b9f5c3
MD5 d26fafe9ebd69869d48e49ab2cb4d076
BLAKE2b-256 d8796df79eb5b31b01ccd73b6a394e50890058c8af77f2799252bfa25e8b8062

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp38-pypy38_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp38-pypy38_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a79a06f642ffd9c9f8fc8cfe84c6e278965d5d250598f27f86af774bcc78fdf7
MD5 b0341514fe97cffc8c61ec4f26c3533a
BLAKE2b-256 415bcf0912155f74db4ea09797ae4b00b9ff6a8e397f13f2fc99c438e576bf12

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 a278907d4cf9bd65888fe45f264765b579791af5ed32dd943761b26213b78bcd
MD5 b5dfba5a6d5ed753aa2a5f4fa772b14d
BLAKE2b-256 509bf1febe21d8a601530f6524b4f69d9dc9b936698b48985389fcfb6fa5f4d2

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp37-pypy37_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp37-pypy37_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 0f17dc30e656710ca866ca4f8a4af6bb1e46e4da349b89a59a9ebc2825b93852
MD5 42e0e4c8543e79a008145a2ee05e34c6
BLAKE2b-256 b5300309e57214ae77b1f2b438be6d47594728c7c90f951bc9c1cc70ef9ce635

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6974514fe5c6909599e7122937ddb73fd8313da7ee68ce2e601c5c28b3c4e2f5
MD5 902d24d08107c896292955b3f6d43608
BLAKE2b-256 92346de69b879f6b54afd3a01159a100d5e3e47984899b958dd2aee8bb589f6f

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 b573b678f8d34a1349eceb4ea047bbfae8fa6b1b7c77ffbe36ea3ab9b86a5391
MD5 1cee187021db559f01472415f6cc75ba
BLAKE2b-256 6077dc85ed11ade9336e0b0ba69a8195e71abc7c5232d24f666d991e4abb237f

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-pp37-pypy37_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-pp37-pypy37_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 6f9b01764d7bacfb2655d305259de27a023624df2c5ba6acbf2b25ed0f4f2271
MD5 9879fcb52e04be2f96e7c533329cac85
BLAKE2b-256 1b04fa7b5fb36a65584e6376d948ba2772b3a690e0f76bf2fe032aa26d3185dc

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 185.3 kB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 4e192613a1e02b0cebcbb9f8a708001bdf7ec842972b42008f3b0b006a8c53b6
MD5 4b9a2188a98fbec4f9e50cc71f3efd57
BLAKE2b-256 716587b637539c73bf5b1074eba87389616949e073d91f6c670a4d91e16504de

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp313-cp313-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp313-cp313-win32.whl
  • Upload date:
  • Size: 141.3 kB
  • Tags: CPython 3.13, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp313-cp313-win32.whl
Algorithm Hash digest
SHA256 91ab47d071383b5c558542bf54facf116f3fd1516c177ef10843f41e528d8873
MD5 24e868e4a18b465c14375188d5cd22fb
BLAKE2b-256 11793f429bd0c97fe95d62aee32216dfbe3db9a59c3a8a3ff185bb1927e45658

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp313-cp313-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp313-cp313-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 4acd71d4359399e41543198caf150e7f398a8d52e371a0c89ba63a90ec3e0909
MD5 b0bf5f1bbb336832e84cf54c88ccb965
BLAKE2b-256 0a0e7fad0a408def5738ce1deffc6242bd8086f76fae1f7a5a4c36e31ab528d0

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp313-cp313-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp313-cp313-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 f44e27fbdeffd46b513ed80d5dab0c7e0e09fb1cd85e8dbf8041b6e4a2d55bee
MD5 64428f936059b6d914d7fdf7d2bac26a
BLAKE2b-256 90bdcd603a89316769c4ae3a4d2271c9c9707b26939517bbe2f780c4f171ade3

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f3d229a8451e5e909c3f41e19c2f1c9a531d3281954a8cbc06163a458adcc465
MD5 2d9cbeedf93cc1ccad543d25849a9048
BLAKE2b-256 c6e7d22c50ac8e76c2878cc1056010d0db26b7e5a7936262320c62a6dcdfdbc9

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 cf26cc1071685597b54b78dd2f62080c58f9be1cb9b4f9c92f94d5c0b5e5e65d
MD5 827f186f38293ed67535938b377c44e3
BLAKE2b-256 5c52cb3ad58e8ce701c97a38f7828d899cfd12f0b7b06c49a4d67a17298641eb

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d3fe53911811ec554b13a2c3b0ceb1a23c6fbed3d510ea0d8544a4e0b861e4d6
MD5 cebc576dc47687613cc78e5ea73d649b
BLAKE2b-256 addb93f0fd99c99cfdfb68a6d671324ceb3e9c0cf2040f47d917a42e615faf03

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp313-cp313-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp313-cp313-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 806530b6a1542efd6453fc5f5b5aa348d52c337d0eb1dfc54a5ff6a8733d7ccc
MD5 265cdb55ff288bd74041fc7fdcbb427b
BLAKE2b-256 c0ebb39bef7c8ec2ad9e198b956104741c1e7a94f0003875ef0a5a32ae20443f

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 185.4 kB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 320c1da333f5f8571e2b313c9fa6c0a7a79d8a00a2ad0bf29932d931d236d7e8
MD5 ef46207eb325b773eb080a9783810d61
BLAKE2b-256 0f73861a71009f20331cd22aff1c37b9c39ef3af4d57d6816df79d51b3fca533

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp312-cp312-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp312-cp312-win32.whl
  • Upload date:
  • Size: 141.4 kB
  • Tags: CPython 3.12, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp312-cp312-win32.whl
Algorithm Hash digest
SHA256 186c2e90ea2c3d0fab21f10f17b48fb7d716cba5f49b68f7f0fe539db4ff0499
MD5 45d91211db517364faab9db8313f7d93
BLAKE2b-256 9a95f04305ab6fc6312b4727b725ab983342237c7bb95d21d98bd768146dd9e8

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp312-cp312-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp312-cp312-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 5634f38a781b9a893550c23380af080ca5291d19c2bcb1753a34022d1d0de7cb
MD5 7a476e3abab26423d3e4c9e052b6253a
BLAKE2b-256 7f133d57038439293d93e40af89b48bc06c714f8cd8c5d22a9e6d0870f49ea1c

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp312-cp312-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp312-cp312-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 264f09d5f70b09c845a6f0d0d4973de674056fd50452cb9383ffae8fc0967f1d
MD5 c565bda25e8f02790de9290a0f33c05b
BLAKE2b-256 3b4b8b077958eb760ac647d2362f8bd1ae99097fa351edc6333fde0dee51f912

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ec763ee2994402c534bf898ff318edd158c32071c3ffbdcd7ae7b7c884250471
MD5 9eb518b93301dc400001aa9eb49c910c
BLAKE2b-256 a69fe95eeccf29ad1e1dbf4a14b76e2fa5b6698ba06f10634b097b32258839b0

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 2d42b41082553fa23a4ce191860fd7caffdeaf8507e84db630a97ed154bd2320
MD5 9a91ab43af36402feab2193b211b46f0
BLAKE2b-256 f768eb9f06b2f04f408ed748d6e71fb2f5ae92deba0eea07b6e374268d53cb49

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a6adf0b86b6be85f0cf80b2b255b2b0179782b4a3f39c0a6c5b3dd07af5f95eb
MD5 567b1cf454a3a4b62a96d685133a7f75
BLAKE2b-256 e5dcb30dd228af740b1ffe18e4cfb48c22aa8481ce1e79405cac31086fb849bd

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp312-cp312-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp312-cp312-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 c30c44241065beb9432273874f199fc109473338d9f2c921a3387fd534fd94a7
MD5 171ef566c3ce3dd5cc49d923124789ff
BLAKE2b-256 817ce09c0ac1aa4571ded5f46c14aed5d4828b61392611ed1c59a8faf1cae98a

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 184.8 kB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 258af638eb68273f130c9878de2bb4a427fe99e86900b9b9b09c1cd7a185c189
MD5 49541c9d04fe5e19ed2b28f30a87edb4
BLAKE2b-256 e8d46ee439fe4ece1ebe40d13b7ef6f6bcd42a9775d725032db40b226be66bf8

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp311-cp311-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp311-cp311-win32.whl
  • Upload date:
  • Size: 140.9 kB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 e9bbaa5aa38a2f82bb1eaa6b97396e58c3a7f87e46607f52c7fda53927616eda
MD5 4c4d0d6aa7c001030c6589edea82cf15
BLAKE2b-256 c401e4ae834f93cffda555907b7d8e4678113d94d2874ba39e7cbbfe14ad9373

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp311-cp311-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp311-cp311-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 b199cbab2ce93ee1dd76da4d0523af5af4446d775b7bcb75dfdfcd2a8226404e
MD5 7de37af2dc5317f94929e7552d6669b2
BLAKE2b-256 d6ad10571e4e79bd9b9101bf33d274b7ad2b09c4d5ddc241cdac451ea889cdc0

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp311-cp311-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp311-cp311-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 af925366939839e4bf11f426388201195c305a3edcdd9097e8775fbd083ff309
MD5 fdb69614f9474d7c7793738ed5f32641
BLAKE2b-256 b002cbd096d8ba891384ba9f3e684ff3cfd52b7f7131581b7f5e4b35d66b7289

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f74f6e0bb2034880bf4688ab5b95f97bb90952086682a93f080b260b454f933e
MD5 e44923512499be8f93661e46065e5b74
BLAKE2b-256 b29b91b46ea4d920014181b2d7256086a68ae1374f40bfeebee13497674511c4

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 3932f794e84bf29bdf4952d018b00c290fd06b055648f8e8fb9132e6684c4472
MD5 c3949e5c4a04c8f5d6afd5a863e523a0
BLAKE2b-256 a58dc5101e915ea17f0ae8faefe7370c997315947d488bc1c8087dc5dee0bf43

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 ee100ba27a07d2fc3bd29cdd619cdff51735ed059002574c550697d1d160b7c9
MD5 4f1f756c1e0a57e1e8041836cf0985f1
BLAKE2b-256 59b2591ff043474cc1d2e2a86d4460b310b6bcc6d4fa91cc59ef4ffb887e64e4

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0c76ac603ff774fe3137340083315f34d6afbcd4ebebab99c1564c00c1c318ee
MD5 c9afa1dda1f6235cbb3097affada3f5b
BLAKE2b-256 03bf664bf08622e54aea83006f168ee3655a50dcebc7df66e023557bb1333d00

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 184.9 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 4556b2718bb22052f39a50f3166c4ee0e140c58ee06bbab31d57d765159d2f00
MD5 fb106271335e07bbcead5b2bb3f5ab01
BLAKE2b-256 aa9451643ed8adb4a558c784fbbb9df2877a103cd34a55d2c2863030badab54d

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp310-cp310-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp310-cp310-win32.whl
  • Upload date:
  • Size: 141.2 kB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 85e583ec705b1b1c0503bc9cdbca027d3446cbc7cf7de3d29f1e0ab58999e5fe
MD5 e1258d9803cbfd823a3a55ae7e46fcd2
BLAKE2b-256 6acd224127bdf035803cfeddf83029d4398ee122289f11f5c2252832885de1c0

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp310-cp310-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp310-cp310-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 aa0f70f84c69b7a6a38ddbea51a29f855c42120e8069ea4c450021a2c7dc42d8
MD5 62960373e2da4ea1d812f121ccb5dde0
BLAKE2b-256 70f23275207f690d1eeea8e0e4900f5311e9e48497b39946e5519b8b4aa068d3

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp310-cp310-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp310-cp310-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 7024cdbcf4bbc2a5e1c277e11a10cb2b7481b7f99946cdcfa7271d5e9799399a
MD5 04dcec30216d6907a7fffe943de41bbc
BLAKE2b-256 9976b09792a8141fb03f27f61c75333c84793298287f0d978a755deeb96029c3

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 be904f4d0d522de98ff9f0a348d8748c2f95926523b7b04ee75b50967289782d
MD5 c2dd0be372615984bd50282ba59ee7d4
BLAKE2b-256 9e532fd493c6d61d8cd42a3b3f8268ddae6658f3c8bad0adf205f218606f236d

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 584ead989545a60919e4015371dd2f69ff0ca985e76618d41930f77b9e248286
MD5 cdbb7af60ed71b2c5868c05631a3530d
BLAKE2b-256 b0f5d3fd6aab0d6a3c400f9a1bff1ec091ec29a34d76ef3b69b8472801b6d979

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 31c9d3c808647d4c569737b32b40ed23c67133d2b89033ebc8b5756cadf6f1c1
MD5 104a63aa871429c61253778ad8dd1e23
BLAKE2b-256 f727b3950b55542ec9c59bae8484d0a3dcb88cba9f2268222f60f5538c8a853f

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 2935aa78a89b04899de4a8b8b6339806e0d5cd93811de52e98829b5762cf913c
MD5 718f7df1d32e14aa0dc4f88815caf577
BLAKE2b-256 c1c66929a114ca2b41464cd7643b5c7b12be2ef0bf43f65c3bba02bff3ddf163

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 185.1 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 dad2cdbd1acf81e838db79ed7dc65574069a9a2ebef7c9650a47d2a4bdcb542d
MD5 41b16d40d3d085b67f168b32b9c9ca06
BLAKE2b-256 e6bcef073dc777eff835fee2e8d8df123189af9ef121bbabf9320d536b044d06

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp39-cp39-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp39-cp39-win32.whl
  • Upload date:
  • Size: 141.3 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 31eeabc246768efa25b36110acd7486768e72f0d4a21509119dd2c89a12b4a4f
MD5 b96189e0839ee8a07be83f496b74b2f9
BLAKE2b-256 c2cd7f71987c0b97f1188c7370e7d849debdb6e50a13aee74d24615b2caa37e2

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp39-cp39-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp39-cp39-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 f072dc2445ecac86a8e85540d5c2b8da0b0d21533c4ecd5e1ed1cde435530d66
MD5 520ec3cd5700e900c8578c00f6df502e
BLAKE2b-256 f633d840ecd792ef24482f44e1a8ade7511b707d60fc46ddc99d47dc5e4ba4bc

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp39-cp39-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp39-cp39-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 fe861224607410ea36c363ae0c77fd8a34efcf94663f1f9422fcf8e55869aeb8
MD5 b80927f39e2a7eb565f6f07daf1823a6
BLAKE2b-256 4089ac8958fd07887208c72077080d7554aa06099dd305dda56251520cf99265

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 66aa082011dbce0d58632f4b01a427116e0377d80c0aed991e331dfe2b55577d
MD5 00833d79685b44a9b8c235dd29c30a7e
BLAKE2b-256 65e57a48005351c501c5f6193f8a337094fe3e141eacabfd18e280648bdb400c

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 8bbdd506b5b242f830f34d6ad842adeb8e45f4675ac7548dc7f541fdbdd1748d
MD5 36c736a0afdfd2f848006d29e1d33a6e
BLAKE2b-256 09b3b7338e665e24bc609c1d2c9fab75b5a333195e426ba390b567159868bb2b

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 bc1b867d17859d68ffe00b0511eeb3a1904cef794c77f5c30f165075d9f487d5
MD5 815de9b515dba28f82a8859087aef6e9
BLAKE2b-256 8a4247ae5dda9d02d219e44689baf1b80b101b0fb1f00596b766f6ae34f238ef

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 931b0327eb52f87621444576ca11e6d45ba44edfecc591ff77d8ed4dfaa7293f
MD5 7fb2d953eb88ea522a998ac051e8391b
BLAKE2b-256 a7ca75e88ada459c5985fc0bc5956b81251e7038eb4b7a705fdbb2154ddd251e

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 185.3 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 ef50a927740ad366fad147a387a0976b50f35fa62da3dd8c6791a00353b258cc
MD5 56d3c0f1bebae19c485de08bcec840e3
BLAKE2b-256 9abf1f6da6c07d8df5c672a946bbf31f15695b062c0d0d8fd05ce654a7793ac7

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp38-cp38-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp38-cp38-win32.whl
  • Upload date:
  • Size: 141.4 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 1ea84ed2411b6671363e51cfb31af64370a48627a64e465c5dc1ae9545529fd8
MD5 52d4f2084f3379c9a6055c1f4eed96a0
BLAKE2b-256 56ad0f3a703e7264949856d3c2aa7b855d111b7dc50f9a010722887328c9345a

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp38-cp38-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp38-cp38-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 783e5451eb8bb48f24c60f749c7912fd32439330c61738acf4fc91c1ef610066
MD5 f05fa50838cb22c5456ce7bc74eef11d
BLAKE2b-256 6f997b282410e36344f730ac1f880e9935c7cb9db8e88d1297ebff5d7f2f4893

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp38-cp38-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp38-cp38-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 61e239b8b48713270bb6b03f211c170e84d5a33a49ec735552e2f30001082a12
MD5 d6e0c476d1033198f8b638fc57cf5f7c
BLAKE2b-256 16993f2a64f0526f6058a68268d52d2c4d73be6772e08f0aa615a2d05dd9755a

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b820bd316351de434ddc331fb3f861e5f2c6bcd8f495636be5cc6e2d4b2147aa
MD5 62aec36b814e9f48271dbb87a1936251
BLAKE2b-256 563cc2950bbbe4a961977c6301197643a0ca97079ed145c4622d242c8c912244

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 5c57e1cb57f3d535de1ff2a6be9b9525557d252ed290b708b79bc35d9f058319
MD5 e894208c732f5a07b25274e421b1a564
BLAKE2b-256 b8dc75828079d95b534336b359984af37845e91167d0edd52a2c9553963903ba

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 dfcd54f6e8c01ed63693f6ada399f59fe78c777d26f9e7d0b22ec03afbe19b98
MD5 ebf4c0e851d4f02f1cd83a0485d6d377
BLAKE2b-256 4e8e97eb4680cb6ecb52c04fdd2b5af30d7c1cea1a7e18f1767596b25313b85f

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 77fbe1c9c382dbed42aabf61c481e68559f9fd4281ada051f0dc49317e08d38f
MD5 62062ed45a4b570804a70a174ed0c256
BLAKE2b-256 6defeb27ab07cd8ae26eadcecb43dcb3fe90af7d23fe0f6a1169343cb86a34cd

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 185.3 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 73dbd546a3122677aeebc8f0e645d4b95ea548c98784fd06157080222690080b
MD5 68212b013e038d722a5ba845e4f0088b
BLAKE2b-256 db268feeaf00dd6151c07574cf2cadc3d6d005ccf5b0eebda530b007b8e01948

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp37-cp37m-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 141.3 kB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 62fb36213acbafe4d2f6a358b187b516c39daf0491a41377b915810f2a1cd959
MD5 3337f7f6d0bac04fa71f9b7512233c3d
BLAKE2b-256 c3922ec8842069648674a6c463c67efb7d7ecd1e666254caa369d9421377d1ec

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp37-cp37m-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp37-cp37m-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 1483ffdc48d7065bdae99abcb3075b892b0508295f2a5627d2eeeceae56c7ec2
MD5 d131675aa74f97d3054457c18b562ba5
BLAKE2b-256 511103075d2bb66c1d0cceef4f1059dbdbf0fdd4a0a2cf138a812f1bd3a4a6eb

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp37-cp37m-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp37-cp37m-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 edac115a129ee11c8bd47822d898199568e3ef90118c03f154d1d4c48bfb49df
MD5 025c0fa7e36b2cc61fe281f6ee811b1f
BLAKE2b-256 aa49f748855c9290a44b16ee1d4f31d6a94676d95d5aa326cd52619e2d140b5a

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ef83887dee6a636e8c89bba24dfe04d695a808ffb41280e4ca64985135a0892d
MD5 45861b6f4a03e6afa154d511ec97e9d7
BLAKE2b-256 a2c6c58be2b88c92977facd55d3b4332a727354894c12f3f0e8fc9d56f780a88

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 9491400aa99f1172e53c9619fde67f7419f0256e48d3d660b8c6e5d637e4701a
MD5 4062c503fe1787755f40dfdcae82d380
BLAKE2b-256 eeb8b83cb30b039f00afae928068ef05460dca5b8eb9ba658074c02d083f5e47

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 71f75c04b8a90499b4a54d50baa2ec647504853613ec486e1f1d922c11dfb6b6
MD5 7f25cfd2a8672a5ee9fdf204312c22da
BLAKE2b-256 5b3a5bfa4d2ab3ae89d395b51cfc7cd65381756867578b7411134be5f3e63584

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 195.3 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 15e12442d393aa8d4e2ed8a2e513f46f8d340981cab3173351d0a36919888658
MD5 9d39aff2a26b187e58bd86f4b8c89730
BLAKE2b-256 35d79ef513e65e57a18cc911c2d12fc00f980e9477ceeec3025dc0dd06ddc1d8

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp36-cp36m-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.3-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 151.0 kB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.1.dev0+g94f810c.d20240510 CPython/3.12.7

File hashes

Hashes for PyStemmer-2.2.0.3-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 70f4d62d60483f8463ee759b6754a0482fd902652f87d37511ffffc579a2b276
MD5 85d32e33cd2a5ceb8772962507b10b23
BLAKE2b-256 c0db1532f9256a7efd713fe184aafa7c917c47e885eff47a713d9cb3c4ba1747

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp36-cp36m-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp36-cp36m-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 fa584c6890c18ec379bf597bc71fed902d900827c63f615d45ad24b2cc4cad9a
MD5 b8138c891d912572dda1c1fbbadd253c
BLAKE2b-256 16fabffa51f363997a3d6570a4df128eee0cbdf55d10036100296238e6369c0c

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp36-cp36m-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp36-cp36m-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 033a3d2a78d8ff03520da9d7a419599e91455f875b9bac51245ec4b24ea5de9c
MD5 6044edd68499efa10d406384d5005b49
BLAKE2b-256 49fab41ed4e2343661d47722662d0e612cd03812b5ac19e21fae5708a877001d

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 591230dce77c49ab61a923409cfd271e1a1db41e58081dd1125511d6a7cb0239
MD5 d905bc5c208b92e2aedf463c02f6bd66
BLAKE2b-256 0f53f7f1325b541a48bb996ccc043979db4de63c866ea075ff60e973dc7a2c9c

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 b428a233f0f86ef99147d803478f4050a3dc770a760c1cefdadaf080e0900155
MD5 64c365c47a71b02d863500823f4d50a7
BLAKE2b-256 d82e76af70c2be4b80833c2769d80a5aa2a5e4a786818571eba044da3ec4e5a7

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.3-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.3-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 5abfc79e82bbec2242f766876f7a2afa3b7bd124b73016650319e95bcb6449d6
MD5 04ffdc0e22710bbf052b1f14fc045ca6
BLAKE2b-256 3d14277798a957e1a5964210c76765c009f1e7745f4c7a5fc11893dbb1491438

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