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It also provides access to the classic Porter stemming algorithm for English: although this has been superseded by an improved algorithm, the original algorithm may be of interest to information retrieval researchers wishing to reproduce results of earlier experiments.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

2.2.0.3

This version

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-2.2.0.2.tar.gz (441.1 kB view details)

Uploaded Source

Built Distributions

PyStemmer-2.2.0.2-pp310-pypy310_pp73-win_amd64.whl (180.3 kB view details)

Uploaded PyPy Windows x86-64

PyStemmer-2.2.0.2-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-2.2.0.2-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-2.2.0.2-pp310-pypy310_pp73-macosx_11_0_arm64.whl (173.9 kB view details)

Uploaded PyPy macOS 11.0+ ARM64

PyStemmer-2.2.0.2-pp310-pypy310_pp73-macosx_10_15_x86_64.whl (170.3 kB view details)

Uploaded PyPy macOS 10.15+ x86-64

PyStemmer-2.2.0.2-pp39-pypy39_pp73-win_amd64.whl (180.2 kB view details)

Uploaded PyPy Windows x86-64

PyStemmer-2.2.0.2-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-2.2.0.2-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-2.2.0.2-pp39-pypy39_pp73-macosx_11_0_arm64.whl (173.8 kB view details)

Uploaded PyPy macOS 11.0+ ARM64

PyStemmer-2.2.0.2-pp39-pypy39_pp73-macosx_10_15_x86_64.whl (170.1 kB view details)

Uploaded PyPy macOS 10.15+ x86-64

PyStemmer-2.2.0.2-pp38-pypy38_pp73-win_amd64.whl (179.8 kB view details)

Uploaded PyPy Windows x86-64

PyStemmer-2.2.0.2-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-2.2.0.2-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-2.2.0.2-pp38-pypy38_pp73-macosx_11_0_arm64.whl (173.4 kB view details)

Uploaded PyPy macOS 11.0+ ARM64

PyStemmer-2.2.0.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl (169.5 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

PyStemmer-2.2.0.2-pp37-pypy37_pp73-win_amd64.whl (179.8 kB view details)

Uploaded PyPy Windows x86-64

PyStemmer-2.2.0.2-pp37-pypy37_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-2.2.0.2-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-2.2.0.2-pp37-pypy37_pp73-macosx_10_9_x86_64.whl (169.4 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

PyStemmer-2.2.0.2-cp313-cp313-win_amd64.whl (185.3 kB view details)

Uploaded CPython 3.13 Windows x86-64

PyStemmer-2.2.0.2-cp313-cp313-win32.whl (141.3 kB view details)

Uploaded CPython 3.13 Windows x86

PyStemmer-2.2.0.2-cp313-cp313-musllinux_1_2_x86_64.whl (677.5 kB view details)

Uploaded CPython 3.13 musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.2-cp313-cp313-musllinux_1_2_i686.whl (643.3 kB view details)

Uploaded CPython 3.13 musllinux: musl 1.2+ i686

PyStemmer-2.2.0.2-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-2.2.0.2-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-2.2.0.2-cp313-cp313-macosx_11_0_arm64.whl (220.0 kB view details)

Uploaded CPython 3.13 macOS 11.0+ ARM64

PyStemmer-2.2.0.2-cp313-cp313-macosx_10_13_x86_64.whl (214.4 kB view details)

Uploaded CPython 3.13 macOS 10.13+ x86-64

PyStemmer-2.2.0.2-cp312-cp312-win_amd64.whl (185.4 kB view details)

Uploaded CPython 3.12 Windows x86-64

PyStemmer-2.2.0.2-cp312-cp312-win32.whl (141.4 kB view details)

Uploaded CPython 3.12 Windows x86

PyStemmer-2.2.0.2-cp312-cp312-musllinux_1_2_x86_64.whl (683.0 kB view details)

Uploaded CPython 3.12 musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.2-cp312-cp312-musllinux_1_2_i686.whl (649.2 kB view details)

Uploaded CPython 3.12 musllinux: musl 1.2+ i686

PyStemmer-2.2.0.2-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-2.2.0.2-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-2.2.0.2-cp312-cp312-macosx_11_0_arm64.whl (220.4 kB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

PyStemmer-2.2.0.2-cp312-cp312-macosx_10_13_x86_64.whl (214.9 kB view details)

Uploaded CPython 3.12 macOS 10.13+ x86-64

PyStemmer-2.2.0.2-cp311-cp311-win_amd64.whl (184.8 kB view details)

Uploaded CPython 3.11 Windows x86-64

PyStemmer-2.2.0.2-cp311-cp311-win32.whl (140.9 kB view details)

Uploaded CPython 3.11 Windows x86

PyStemmer-2.2.0.2-cp311-cp311-musllinux_1_2_x86_64.whl (673.2 kB view details)

Uploaded CPython 3.11 musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.2-cp311-cp311-musllinux_1_2_i686.whl (639.7 kB view details)

Uploaded CPython 3.11 musllinux: musl 1.2+ i686

PyStemmer-2.2.0.2-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-2.2.0.2-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-2.2.0.2-cp311-cp311-macosx_11_0_arm64.whl (220.1 kB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

PyStemmer-2.2.0.2-cp311-cp311-macosx_10_9_x86_64.whl (214.2 kB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

PyStemmer-2.2.0.2-cp310-cp310-win_amd64.whl (184.9 kB view details)

Uploaded CPython 3.10 Windows x86-64

PyStemmer-2.2.0.2-cp310-cp310-win32.whl (141.2 kB view details)

Uploaded CPython 3.10 Windows x86

PyStemmer-2.2.0.2-cp310-cp310-musllinux_1_2_x86_64.whl (656.7 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.2-cp310-cp310-musllinux_1_2_i686.whl (626.9 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.2+ i686

PyStemmer-2.2.0.2-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-2.2.0.2-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-2.2.0.2-cp310-cp310-macosx_11_0_arm64.whl (220.1 kB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

PyStemmer-2.2.0.2-cp310-cp310-macosx_10_9_x86_64.whl (214.2 kB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

PyStemmer-2.2.0.2-cp39-cp39-win_amd64.whl (185.1 kB view details)

Uploaded CPython 3.9 Windows x86-64

PyStemmer-2.2.0.2-cp39-cp39-win32.whl (141.3 kB view details)

Uploaded CPython 3.9 Windows x86

PyStemmer-2.2.0.2-cp39-cp39-musllinux_1_2_x86_64.whl (656.2 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.2-cp39-cp39-musllinux_1_2_i686.whl (625.3 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.2+ i686

PyStemmer-2.2.0.2-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-2.2.0.2-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-2.2.0.2-cp39-cp39-macosx_11_0_arm64.whl (220.4 kB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

PyStemmer-2.2.0.2-cp39-cp39-macosx_10_9_x86_64.whl (214.4 kB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

PyStemmer-2.2.0.2-cp38-cp38-win_amd64.whl (185.3 kB view details)

Uploaded CPython 3.8 Windows x86-64

PyStemmer-2.2.0.2-cp38-cp38-win32.whl (141.4 kB view details)

Uploaded CPython 3.8 Windows x86

PyStemmer-2.2.0.2-cp38-cp38-musllinux_1_2_x86_64.whl (651.0 kB view details)

Uploaded CPython 3.8 musllinux: musl 1.2+ x86-64

PyStemmer-2.2.0.2-cp38-cp38-musllinux_1_2_i686.whl (619.3 kB view details)

Uploaded CPython 3.8 musllinux: musl 1.2+ i686

PyStemmer-2.2.0.2-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-2.2.0.2-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-2.2.0.2-cp38-cp38-macosx_11_0_arm64.whl (220.6 kB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

PyStemmer-2.2.0.2-cp38-cp38-macosx_10_9_x86_64.whl (214.7 kB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

PyStemmer-2.2.0.2-cp37-cp37m-win_amd64.whl (185.3 kB view details)

Uploaded CPython 3.7m Windows x86-64

PyStemmer-2.2.0.2-cp37-cp37m-win32.whl (141.3 kB view details)

Uploaded CPython 3.7m Windows x86

PyStemmer-2.2.0.2-cp37-cp37m-musllinux_1_2_x86_64.whl (635.6 kB view details)

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

PyStemmer-2.2.0.2-cp37-cp37m-musllinux_1_2_i686.whl (602.5 kB view details)

Uploaded CPython 3.7m musllinux: musl 1.2+ i686

PyStemmer-2.2.0.2-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (629.3 kB view details)

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

PyStemmer-2.2.0.2-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-2.2.0.2-cp37-cp37m-macosx_10_9_x86_64.whl (214.9 kB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

PyStemmer-2.2.0.2-cp36-cp36m-win_amd64.whl (194.8 kB view details)

Uploaded CPython 3.6m Windows x86-64

PyStemmer-2.2.0.2-cp36-cp36m-win32.whl (151.5 kB view details)

Uploaded CPython 3.6m Windows x86

PyStemmer-2.2.0.2-cp36-cp36m-musllinux_1_2_x86_64.whl (622.5 kB view details)

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

PyStemmer-2.2.0.2-cp36-cp36m-musllinux_1_2_i686.whl (589.8 kB view details)

Uploaded CPython 3.6m musllinux: musl 1.2+ i686

PyStemmer-2.2.0.2-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (618.3 kB view details)

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

PyStemmer-2.2.0.2-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (585.7 kB view details)

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

PyStemmer-2.2.0.2-cp36-cp36m-macosx_10_9_x86_64.whl (212.8 kB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file pystemmer-2.2.0.2.tar.gz.

File metadata

  • Download URL: pystemmer-2.2.0.2.tar.gz
  • Upload date:
  • Size: 441.1 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-2.2.0.2.tar.gz
Algorithm Hash digest
SHA256 959be98ef3a72f37697288864e93789dc817fffda959499e426964b11e618a3e
MD5 f5f0484b63d82c4537ccb93f5eede909
BLAKE2b-256 f55f4403b30bae5937d251150f72305ac584954a807f1b0fffd809351c00755c

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp310-pypy310_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp310-pypy310_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 19a6a536f9e0544058e5bbcecf63ec34454a20238e6e9c667640b1e2bd148f2d
MD5 715b342e33652a65ac1862138e1680c6
BLAKE2b-256 0f4ad7557ba5d99608075c386d82a48e65539f4f2de940782b7e51624a16780b

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-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-2.2.0.2-pp310-pypy310_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b56a54c7bebe7e355dff3590a7477fef9b5c7de2877ba2150f559e782e61aa25
MD5 184d3ed6c287ac2fc66160af306d145b
BLAKE2b-256 7f3560f2764b059892896777b2193ebefb8baf66a6b8ab4d99cee6061ca1a259

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 64363c93c3acb323cbbac6366916ea6858a27d8855365410c18250a26627d59a
MD5 e4b919ffffbc7f74e2155bc4d63d1933
BLAKE2b-256 e37ed8617b6c99a7bb1d6bd47a1dd7f69d3843f4fb0d128a378e5de8967ece66

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp310-pypy310_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp310-pypy310_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 33687eddec679456fd9455ce70896a9459035e6689a640fd439f5e1ebf571a40
MD5 497c022bef78ec14b1b74a57ba774ff1
BLAKE2b-256 68d1a720751e984500f98c14c0f1dac96f6e389c1ad24fb9ec5637810567ede5

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp310-pypy310_pp73-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp310-pypy310_pp73-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 91b4928e82b9cf0483553c6e59707b06515680bed8bc23819ec59dcd8b0d94aa
MD5 7a056adcba562f5a72f860fbf4218cc2
BLAKE2b-256 a827f870d0402d378f2c616da88269005e89759cf545af42a487889010e1a49f

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 f257dfb7a6f8f616e52eb0b0dc5e8838b5a5d4841a2bae6caeff41759682975c
MD5 9315564ba2cdd0ff515dba71e65fe188
BLAKE2b-256 d637a889a4869c263f6c819a6c8df7c19500f2b6286433676f893d082ba519b5

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-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-2.2.0.2-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 75fc0ee5e9fabc3a030e01d2a51a4ee232876b8806bea7c96c2689d7503056ab
MD5 3a3eeb5e60aebba6257f7b570dfc7805
BLAKE2b-256 0e33f88f97a106792e7ef24e8cfd8c5510463c704aa5647844516ecf54e49e8e

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 39f1950b59372aff7c19bd7ce1aaf2816c4a85d073b33fdc91e16cc3492d52b3
MD5 9f31b6e506180c476e72aed6b21981d3
BLAKE2b-256 b70fef0e9f46de419aa23934789338f38e190182fbfbaeaccd531ab93e7357d2

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp39-pypy39_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp39-pypy39_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 5d7b209915c35be3850f087b389cec99cb6bab5e1f40918c5cb3af638078ef25
MD5 9cb644c284a2d450e0104144fe67d3b9
BLAKE2b-256 df027bc1ab922a19e89eec7d88a6f54e71e9dbd6c82db6c76d05ef0f9bf72412

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp39-pypy39_pp73-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp39-pypy39_pp73-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 24615aab75b3b93e02347d71141507ade1215a2ddeceffe016d2664b9bf0eb21
MD5 ea056a220fb6e4b9668aaabc3b14742c
BLAKE2b-256 7399058f049256dc4c6221ded3d8c6ad99b2016d1db787036687615b3c81ea14

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 975a0eb4ec8fa2450cb1c63e0e3e5e38cbb4b3b2c456500124d8435eec59efb0
MD5 f8f7ea7f6086d8f0e94c5fb1c3c4759d
BLAKE2b-256 b757415b6b1a5c96c86e45a9d97f05afdea874d1e0ef7f22e394cc3e6f73f6e1

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-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-2.2.0.2-pp38-pypy38_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 7d2d6cb9938152c47625c2ac57043957b886b493315dc7c9b75427b694a50d57
MD5 9f5a0180deab71689961747a31196d13
BLAKE2b-256 2e71a2e05584f63d6aafbfdd36b14a16eb8db463482a5d69d91482c336bd509c

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 4c4d90749a1d0ea8bb036f411abef38d2ff75b2aef5323a2c2524b24f9eab624
MD5 bd87cbb496c461f6d3971147f1d64c03
BLAKE2b-256 96896151fdf9d04807cbf67b18bdb59d039d63953089a98e2c2618b01d102caa

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp38-pypy38_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp38-pypy38_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 724c057c3b62e7324832f3c1ee09f82558e0cf60e9267ebffac48415441577bf
MD5 ad9f436e0dc12233788ffc66d92bd850
BLAKE2b-256 b0f3ae4b9a2e5b54032c87513a7e1d46ecb64ed5beb39cad1da502165a65c913

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 cb78419c857ff89e50dc849eca4b3daa6848dbcaa689591e42a9ee9501791cb4
MD5 32cb8d441ffe220a054fdac588e24552
BLAKE2b-256 69138ac88cd625362e2ba1e1311a13ef7cafe1ea675e1b1b7bab1584555abe97

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp37-pypy37_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp37-pypy37_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 7efd2cacf6c7be166d72cba0386b873b6d56bda503b7663102ec84285865d85f
MD5 bcf01a7b4e954d046c81a5cb84a680ac
BLAKE2b-256 c7a6505756dbd3f8d33e2ef0e796289e419b23ccc629a11d33070f4e00fa5593

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-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-2.2.0.2-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ad28dd6a324a84886ede01d4f1d714a148f6dbb6985fcb85f1186a0563e939e4
MD5 825b05be0fc35ce0c675cec2a4661f9f
BLAKE2b-256 e98941293787136aec110ca90c8541a57698828dfe4a638064b72bb2b3f2b015

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 90fd719d4d2ddbd726a39c8c346862be3111bd4171c1c8b21135add2b58b83ee
MD5 62a67d19a7d293dad62aae073759db95
BLAKE2b-256 9670a0370afd176b73020b8c0171c5fc3dd2d091008eb2fe5520683a6b9102f2

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-pp37-pypy37_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-pp37-pypy37_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 aff39dfb805113924c012c2c14f5f6498dbaff0ff3039f1f118ccb8d90aa736c
MD5 e3fa0503584990ae21712b4dc31c7fc7
BLAKE2b-256 aab3659bb19fc49a81e189f4d4571dae570946cace725d6e619c3a6dbe811441

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 3106ccf14edb6fb12c3f6c1e4b8e87a9447300180c0c4257cdbe6f03d7c69e59
MD5 88201ae2304b4aa3cc3de02794d70275
BLAKE2b-256 d2c10c609d769edca64bc470af1a3ea138f96a547e8695934cdc9c58413f3e54

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp313-cp313-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp313-cp313-win32.whl
Algorithm Hash digest
SHA256 075b42d3da832cfee2ef525dd18475d30d2aaaffc4c257885f4916fa3fde771b
MD5 41b64e5a01627754698913e20f466544
BLAKE2b-256 0dd8bad00cc9fea08cf29607d1d7197f9aef24513b9a7413869efc70b45f2497

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp313-cp313-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp313-cp313-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 56fc83dbaba382bec688163943b986d0e801c733f7b02b6609a39dbfe84c5c3e
MD5 209c7c76e4e57aebf0add802171a91c1
BLAKE2b-256 038451c180ea01fe1b00a3d7253ac9f9444eeb2ceb76e6a3589e47e05e54db22

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp313-cp313-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp313-cp313-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 be00c8458f0d036c823898cc39f4f732589485b84bb9c4c4de80060fd6597569
MD5 3691fa3d4d2ccf47375d97be5232fb3a
BLAKE2b-256 3fdb898b94dcf0d48a1278a33d6e474781f370f3c35c15305eb4db0ecd92e1ab

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-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-2.2.0.2-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a3e5fa667d2516227aa9186a2045b97ead6f440dbcf364020cb0ed2eabcd5726
MD5 78912553118cd2c7e72a02927205420a
BLAKE2b-256 3d33a9ea771c4d969ef38646ed463f0b5f0f7c6207602de7caeae557bd12d320

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 d909617ef5dcbf95eb927dc596f9a3b56d757f723e5598817383cb6c2a015f66
MD5 7226b27cf9afdf349787190bab0749b6
BLAKE2b-256 c92bd947c4f09ffd792d6ba843667fd98f849850e6949edca7baa7ae2b93ba45

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 bc1393d0e9252ab3acc54b8db18e3ccfd8e4209c7df177fa17453e0f202fa088
MD5 f50519fb16a9010060ba0532f2d6a06d
BLAKE2b-256 b52a642e8e8ae773a6301fbb54c5498386a5dfff6f33e0c52e0934824f698a08

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp313-cp313-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp313-cp313-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 94ef17fe7f62b32bf6089ea4f62d82e0a00b0e8c56262b5d1e7b1d95d7e7dec7
MD5 a7b0114a142f9fa64ce96bfdff5fcf8c
BLAKE2b-256 9bc8e1b77a2f90a4e40378a8e2310edd53643f268d5c39ab873140b5c2568ef3

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 c85f9b7ed991319bf20cf6facab6a521a8c06983282dbf9b44f67720350c0cd8
MD5 54aecacf5ee225469b6b1130ceff67ea
BLAKE2b-256 7e9e9b9d2e160359db9f7d06c7becd08285b9f6f41082b76906f858ff37e17d4

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp312-cp312-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp312-cp312-win32.whl
Algorithm Hash digest
SHA256 ca78038ae99a8569bc9563a994c028610e6310944bf0b7c524e85d268d8e51d4
MD5 4daa283a3ae5b0f2ed5a6c1bb4a773ed
BLAKE2b-256 c931f414b138de80c14f69c2cd51c89e817acc9d39223a985ebc89de67b269a2

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp312-cp312-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp312-cp312-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 aa3775132a1223821cf04940c96262f9ee983d2dbb9e6fccb78e177d4593610c
MD5 df01e3dc5f27a89abfca7ff14f6d6c18
BLAKE2b-256 81a29f367b8d80c8a015e620393fe9bd6efe73bed9a05a1d5b1feceb94659f1c

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp312-cp312-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp312-cp312-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 0fc3216397963bf329da915fc05f27b015e80f8508c4148b6e87e33d80933835
MD5 61dfbd5eb6d667b239e13327503199cb
BLAKE2b-256 6cec429d779594eafbfb357b0fb12aeac5fcf8bf9945a3ee963ead190117c8d1

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-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-2.2.0.2-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4f5b18ada59db96b9b26180c9271ed18b8385b6ffdf96c621b9727dbdaf2f9b1
MD5 072cf9d64bc2d9cd84f4dddd318d9145
BLAKE2b-256 122c9cb57cfb8e45bc2b1ffeeca3a7a081405ad57295821e62dacae1d3af8bce

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 89b09aaaf25e609406bbfa541e5057090f31ed7533f337f1a163a4fe80fc6de7
MD5 b612f0705799d62247315a936377f8f8
BLAKE2b-256 01f977d6f86ce7ffaaac06959c812adb8dd9adeb6de0f592fa60e5b7532bb401

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7fa70e2b02a574a724dfc0180a445fc29ee7cca081246186d0fa3d8906ce3bff
MD5 f184772d707846087fdf77eb6e733f42
BLAKE2b-256 459b1595fd769c8626184bf5d915ab534ea92543ee7cb008fe4b51d62638282e

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp312-cp312-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp312-cp312-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 8530bdd59491ab24d038e63b385ecd3309dca4c39dc75c6e4178e0429adac62e
MD5 bb56c21b68cf6ac1179e8fff74ff4590
BLAKE2b-256 ec711f143254031457bcfdc4431f51aea0ee6be73b2fa6f3754efc64db0e6f1c

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 00e5650741a872ee4eeecc1e871642226bba6e705b7685436e14d676166b6e7a
MD5 99fba3a333b8b93f2e991fef19203a91
BLAKE2b-256 d7bbff7bfe90aefb156a77e79f85e21ef691be0108d52824c2c71bc4b97de5aa

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp311-cp311-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 2f87ac249dd5107c7db8b90d85ab04a883f647d10a02c8e419b08ca6ec56e156
MD5 880a1df7d01da48ebba383f38c96a8dd
BLAKE2b-256 9dc2d388b291a84696cf29ebc4a0a30d207c15834ddfaff88d9a6eb5ea9820a0

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp311-cp311-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp311-cp311-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 bfec5fe64a761a60650440f9040734aa691e5d1269c66bfbb87cd65483d31a77
MD5 61073283b093db4fc943fd12cd24bb70
BLAKE2b-256 f1d931f74e436e873300af2f3e404263df1b9ae52ed673ecfe025c085bc8fa46

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp311-cp311-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp311-cp311-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 2d08b676298ab534c43f98e542b62ac334b092a4b4d89e182d759cca3755e69f
MD5 36b3c46b0b1df8cbaa12f4d8f26e39c4
BLAKE2b-256 5bb73d8a1032dd56b86aca45d7dc7f6a89e1198c400c63b825e13460dcb23102

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-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-2.2.0.2-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1dce1f198814196b3e3ada3514f1e4cca2ba765f2c8434ec2d3c788aa12489ce
MD5 e932510b49e421a3340795bcb52e2937
BLAKE2b-256 c1c35bc2d0757ebf78ed77ccfe8a5495e63ce2b986ccc9bc0ad070479f823811

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 17795ba270ee0ea238a6c56cd00e428d91f1aa03ad8816491b8b0bfc6a8c7551
MD5 5a06272cb9b9cc49dbf184f402f3ad94
BLAKE2b-256 1a57df7f0c86b95c0687e5b2110dd437d7c3dc4e132d2fd636d368b9b293818d

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 6ee7da37cd96b999fd0fc8c7deb5348ea44768d9d37b6cacff1b169538e2dfb0
MD5 6ca0957f9f1d3a455ff6e250fb5869a2
BLAKE2b-256 bce81c5180fbf23cf772e0f5d295e8ec63fd350c6810547baab73fae774ce66e

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 a7b4e0cdf2a08bdae2993990bb82b7b9ed6ad1ef130e4ef44a38f2dd89b7cb7c
MD5 a0b1db25b66f596ba5cea6de4b88babe
BLAKE2b-256 ac4296b595ab431835b239033b66b114ad6bcde53bf4a86fa78325bf180a894c

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 7a0caee80eb3a7ab199d9a6dae4b672f07ba8599c1e002f66ef6d42023fe69de
MD5 6fdd39d52a19e149db16a4bfb3f9179a
BLAKE2b-256 41f6f885f98c492198579a51bbcc1535310250e431ab47a8a875d209abfbc7bd

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp310-cp310-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 e31368662fa9d05c48ef2cb0782ba251f4f0422a784ce84b93385dd4415dcdda
MD5 3a9534b5a26ebbed61328edccea83ce4
BLAKE2b-256 618bf0f560fcc8f49afa8d794996739fa873b86d92370d734832a14b182e9f83

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp310-cp310-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp310-cp310-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 c321cf0b55552d9e78c7acc9461426d7ceb3fbdb8bbbfd6676aa57f5aea463dc
MD5 78d9a17c729894fd6986725db16be45c
BLAKE2b-256 a5cabacc888128f88b0ea16ffd74660ff66f1d81570d8a669818b438c4ac6026

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp310-cp310-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp310-cp310-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 6c7c714447be6edcb0d81c3722d887b3d361f8f74136a34c09ae46aa7f8bd07e
MD5 94c35c557e2c5d74bf85b5912855548f
BLAKE2b-256 a057915dbb373d1f53e0763f185968aaa6a1179b7a42f2eebac26a8afd9a864d

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-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-2.2.0.2-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 dd1f5349d9ebe847f3468acdc4631aa0a86b5059a3d959b57990635ccfd268a4
MD5 1f05a10c3390cb9549c6831bcabdc4fd
BLAKE2b-256 791792fb6d784320156ade9e29d382e7f50e98764d464c64795e8a47041f73fc

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 8da6ef723d188fadd52aabea9bcaef8a3620044b2fdeddf52c89a01c8aa624e8
MD5 87176b3d77ce01f068b6c9bb57366e27
BLAKE2b-256 4840b7778007fdb945669f402a40e89af77513f340af72af2555753c518a8430

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 6475595e04995760035f663306144808cee002547e91d20f7920cf789cede4c2
MD5 ed8db3b0eed817a2400c57d16e8aa5c2
BLAKE2b-256 f873f77d0623897eb3a52d7f118d1b2dc1f3e1fe754101d668864c897985d84a

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0b99c29401b0954ab537cc79453586a5e89f1465089383420c2c36e0dda8e5a8
MD5 bdddce1306062c6b8f8552863a50910f
BLAKE2b-256 767dc05f4dbe584aa55d754da633daa8fccf755090400806617912b259898fc7

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 c111fb56c0af1e67d68168eb39d7cf0bbe8ca1f37e40cda1866d9a55b0c05044
MD5 b2fc4abac91295205106af05df6f6681
BLAKE2b-256 fb93c854caf88f448e0d20688997cd0a34129f586e7c65ada9bf751499f61235

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp39-cp39-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 8d5a1bd1796f637008ffdb31b7ac21328fe46624e2cf863aaa2de1803f6e5267
MD5 2da8463c36f52c7bfdc584b4b3b7b467
BLAKE2b-256 2f076ce015580e47f12fd6ecb53f713d980493be83c988391ecfee3851b99c99

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp39-cp39-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp39-cp39-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 3d585d3dd377317c48324cc785db8b0f90aa86f2219d14b21084ed98c663d8bf
MD5 12310c85047b8d3e0c039c4648c8dde4
BLAKE2b-256 f4d25c50af95d5fc608988dadeb498efd7977ab7c9b914651117c146642ec15b

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp39-cp39-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp39-cp39-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 ac4c77b346e3aac641b79e203cc89e4822226a701e931803481f518256c5ed05
MD5 bf407b3ac4823178600794d37dd92bc7
BLAKE2b-256 e8c1d6da133049b91352196065a9a4cdd9f70683200617e61ac0509cb8611fa6

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-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-2.2.0.2-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ee2afe628ad6c369d41b1ca6735e3b1122af23f46d41fddbde30910cbc8b4c96
MD5 0761008f7ee1f13c3ba490efe3d199dd
BLAKE2b-256 678e2044f8276d766bfc8e0692c403e8323c5de64da19353afa1e8b0bf64c718

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 bf54a700485d9a1b35d4d2744722cc81f1880468bb075ba15cf72cd88d087a4b
MD5 6b3bf96895dc96ade4bc1a8b6dc6052f
BLAKE2b-256 8e8ffa0907a17f2914a6c80ccb2da2045391e1f4ac387db13591cecc1258203f

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 124438d5749fbe49e9286d0850851bb08d94d635bc26b05125c43f6c761bd629
MD5 97785c09ba3639426572c550e201d869
BLAKE2b-256 68c9aaa843fde5d1e4f098ce0ebf0f2ed0b747159e3c0f4bb7b235f49e184ed8

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 b274138bf49d7947ec362098c3eb15abdca4fcd92ef38bee863dbd5f1761934b
MD5 770f5defeb20ac7aaed5fd1a45a714fc
BLAKE2b-256 c7bbc74f64c651dd208c4a4c9054e8e2465ffc955b4584ad66c65dce6f952c61

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 3fcc7195b97a371f66b75b5bcbaaaa5f40c89fabbc05e81d3b6bd6e754e428e8
MD5 97ff64951ad17a27cf03c250280a706d
BLAKE2b-256 2196c85df659a6117b105cfc2887bb90c962ed5ad71ed8471de58373059f9c9d

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp38-cp38-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 dae8dbb674b11900661ae25ef960d525729e742fb0e068368aa60733ced59400
MD5 3d717eb83d889bffb11c507db6f7d999
BLAKE2b-256 592aa767645696f37f4f52ffdea07a835adb3493ab9e1dbb1780c96c1962a635

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp38-cp38-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp38-cp38-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 394fa4b603379f1728aeefbc9ea5790bc717edad14d70abbe278d8c8e8b577a1
MD5 1fc690bf5bd189e342e2302c04c8e77b
BLAKE2b-256 bcc306daeb7e63f6db65df372f4089e9421f789fe509f695e1acea05e148e3c6

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp38-cp38-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp38-cp38-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 5e617ed4056d66b037b342b07eb61ecb0a5a97a3dd352451e6282dc4f7015d3c
MD5 e6c2116ed86b3650d2c481e92b3c6ebb
BLAKE2b-256 4a66247d18c26bf60ed1123e65c93c6c99d5ead8d0dfdd69f15346a5bdd6bfcd

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-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-2.2.0.2-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 965c8d91b2f2a74ae178073c8ef156e4aa78c6c2e7b7663155bca8ae4957cdce
MD5 54e313ea65471bf8f783a2ee0e512e89
BLAKE2b-256 1641c9a445c223f4f852c1acb58b59d192ab24f9ad3a4d4df4bdc0f13838524d

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 a39b758049ad64d760ec72c2bacfbbf3db9588cbd59e79b367030b98b485cd6e
MD5 49e5617224f556de0abe9acd4a514342
BLAKE2b-256 0aafca40d59127c40541f4a92a9df14c204f59253aba1e0daf605c02401d534a

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 2e2cfefffbcebb52853905887bb64a1f39cd9df2312db12cbce901ba3066e05e
MD5 72daa5cf0ab3b0472c9cd4d67e534240
BLAKE2b-256 d5f551a69b7b0806e3dd472f7fbcb7927fc6d5c6d243e8a9773d5cc68184a5fc

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 a976e9c86b46b2e008720a41e3e472b9e42e68cd51ba1199ba5d1c1a3f4ef93b
MD5 4458c97ac4f13a13c58cd0aebe79e73d
BLAKE2b-256 71a05b1921724991eed38a098c2ee1e7199a4c7dc8be846cbb57eb8ea9309a2b

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 e8c353624912de86094c1a477706a3bdfc905a71c8882bd85f9eb7d283431871
MD5 4df3b0241c532e2617841134162ff5bc
BLAKE2b-256 206a8f9b4876a729eab3de6d12029759e50f0a2ce46968fad197e0b5b960656a

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp37-cp37m-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-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-2.2.0.2-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 d802f06106f71267d4dcb86785615f14169f07903944d1a8ea9f10b25c4c3c56
MD5 26155a2cd07c9135de8a05fbb9b78a21
BLAKE2b-256 3f91270a7823f0f4316a5d5632edebf50d71ed10925a6294ee44c8c35ff9d56d

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp37-cp37m-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp37-cp37m-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 b408cd0b0ca413b3a9b198f73ac11067587e73b4c0a792185c7b5d78f733246c
MD5 507d977674fd11d298d0159e4762275a
BLAKE2b-256 012f33748f51b2e67574d507ed16cdb44d69f1188c4044b558948b107d49a4eb

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp37-cp37m-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp37-cp37m-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 08c37661acb48dae99d9bd74a1d4ca863a492a2b09c56276cf782207bd1c0d83
MD5 91a7e1c32747068b3b100e6d003c136c
BLAKE2b-256 2478a58bc7a13d3d95cec9532ad0ec907a0a9b0b008e39a1d50251b35052f04c

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-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-2.2.0.2-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 7f1f70fe798f71ce5ebfbf8de858ee08370b6b73b90a27f37fc6d8c43be657fd
MD5 eeed7cbaa43e2d5ec48c4a4e87ed4b76
BLAKE2b-256 c03fa0f1b5265fd091a345c7a96b3ca04e2bb4707b3fce8660a6184eb36a8a84

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 c51ac8c302fe0aa022588d48244880d0e747a12d07553d1c7894d768a3f39380
MD5 61ea74861720cdc6ef1ef79923bfa02a
BLAKE2b-256 9d69551b2380a1cc35741500aad214a33c94fd471ef68b9c56b9308cc36bab61

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e8c20d751a9ac31ffa044aba2feec9a84bb3b8d320f63ffc7b7bb18ae7f7fbb8
MD5 d285ace915d686548c767a327ac7ca1c
BLAKE2b-256 d95e11d5f984201f4b63a2ea71b0a8707a36a66868e3cd410ff00325f7ae44bb

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 194.8 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-2.2.0.2-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 f3be39f729c7420a03811f6f8d8ea134dde1b30b95446ec82e344c3ba1737c38
MD5 8a9679d36b944bf07efee5f6d1be4080
BLAKE2b-256 c4241e4383157f46f2fb688bd6d9669455abb0ee20b577f1ef8bd3d6a2def35a

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp36-cp36m-win32.whl.

File metadata

  • Download URL: PyStemmer-2.2.0.2-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 151.5 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-2.2.0.2-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 120c5b6d3e4e4d236125a750f62f829e6a8bb4c80abe6a35f89069663796b725
MD5 22c382f653e722cd6b6f1e9a37104f35
BLAKE2b-256 af92cbc1494c7cafe7fb6645c6f14ea118bd57624993be26320fdc46c91555c3

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp36-cp36m-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp36-cp36m-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 835cdcfa3c59823a560133f0ca043d09ee73eda235dffea9441741a1e5c9f234
MD5 5503d9cf3cafb6639001a8588af41f45
BLAKE2b-256 8740600ae3e727495d6614377356556cd194e467a5625ba68b3aee7e03d37626

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp36-cp36m-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp36-cp36m-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 fb037afe82ea91ca533287294e762d4e10283a2f37aaa9943dbcd3dfe933ce5e
MD5 c57d95d7dc1eb10700d1474be3febfed
BLAKE2b-256 2d8cc6ffe5cc9fb75e4a08fceea37638b3523c61259c2f67bba3570966d65dea

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-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-2.2.0.2-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 98e8f9d54e228c19ed415b17627725e971f02d5b93d65a7187f9abedcc8e685b
MD5 0bef0d4e6ea2afa6b19089654d0b1331
BLAKE2b-256 3bab96fbb2584739cbd76aebcbd6b893cb9c5f2a593dfac8598f949309d986ba

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 426f808e2e666fbc6552f4b5a3a1df6e738d54629822f3ce3535516064c44c1a
MD5 950feb0bbd3157b490f331e261823981
BLAKE2b-256 3c8b9c7f12e0eeadf4c0b20d11cef941ef85714130201f6f14f5718efd298bad

See more details on using hashes here.

File details

Details for the file PyStemmer-2.2.0.2-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyStemmer-2.2.0.2-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 8550eafada1a42b312175e23152f2c586012ab6bcc17e55a64aadfff8546eafe
MD5 256c63f05f0c2eefeaf1beeed5746ee5
BLAKE2b-256 a261a41919f101ff4efd00565e86cb13a25c21fc38ef3e6d85cf923342764b9d

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