Skip to main content

Python library for Apache Arrow

Project description

Python library for Apache Arrow

pypi conda-forge

This library provides a Python API for functionality provided by the Arrow C++ libraries, along with tools for Arrow integration and interoperability with pandas, NumPy, and other software in the Python ecosystem.

Installing

Across platforms, you can install a recent version of pyarrow with the conda package manager:

conda install pyarrow -c conda-forge

On Linux, macOS, and Windows, you can also install binary wheels from PyPI with pip:

pip install pyarrow

If you encounter any issues importing the pip wheels on Windows, you may need to install the Visual C++ Redistributable for Visual Studio 2015.

Development

See Python Development in the documentation subproject.

Building the documentation

See documentation build instructions in the documentation subproject.

Project details


Download files

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

Source Distribution

pyarrow-16.1.0.tar.gz (1.1 MB view details)

Uploaded Source

Built Distributions

pyarrow-16.1.0-cp312-cp312-win_amd64.whl (25.8 MB view details)

Uploaded CPython 3.12 Windows x86-64

pyarrow-16.1.0-cp312-cp312-manylinux_2_28_x86_64.whl (40.8 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.28+ x86-64

pyarrow-16.1.0-cp312-cp312-manylinux_2_28_aarch64.whl (38.1 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.28+ ARM64

pyarrow-16.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (41.0 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

pyarrow-16.1.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (38.7 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ ARM64

pyarrow-16.1.0-cp312-cp312-macosx_11_0_arm64.whl (26.0 MB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

pyarrow-16.1.0-cp312-cp312-macosx_10_15_x86_64.whl (28.4 MB view details)

Uploaded CPython 3.12 macOS 10.15+ x86-64

pyarrow-16.1.0-cp311-cp311-win_amd64.whl (25.9 MB view details)

Uploaded CPython 3.11 Windows x86-64

pyarrow-16.1.0-cp311-cp311-manylinux_2_28_x86_64.whl (40.8 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.28+ x86-64

pyarrow-16.1.0-cp311-cp311-manylinux_2_28_aarch64.whl (38.1 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.28+ ARM64

pyarrow-16.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (40.9 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

pyarrow-16.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (38.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

pyarrow-16.1.0-cp311-cp311-macosx_11_0_arm64.whl (26.0 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

pyarrow-16.1.0-cp311-cp311-macosx_10_15_x86_64.whl (28.4 MB view details)

Uploaded CPython 3.11 macOS 10.15+ x86-64

pyarrow-16.1.0-cp310-cp310-win_amd64.whl (25.9 MB view details)

Uploaded CPython 3.10 Windows x86-64

pyarrow-16.1.0-cp310-cp310-manylinux_2_28_x86_64.whl (40.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.28+ x86-64

pyarrow-16.1.0-cp310-cp310-manylinux_2_28_aarch64.whl (38.1 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.28+ ARM64

pyarrow-16.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (40.9 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pyarrow-16.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (38.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

pyarrow-16.1.0-cp310-cp310-macosx_11_0_arm64.whl (26.0 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pyarrow-16.1.0-cp310-cp310-macosx_10_15_x86_64.whl (28.3 MB view details)

Uploaded CPython 3.10 macOS 10.15+ x86-64

pyarrow-16.1.0-cp39-cp39-win_amd64.whl (25.9 MB view details)

Uploaded CPython 3.9 Windows x86-64

pyarrow-16.1.0-cp39-cp39-manylinux_2_28_x86_64.whl (40.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.28+ x86-64

pyarrow-16.1.0-cp39-cp39-manylinux_2_28_aarch64.whl (38.1 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.28+ ARM64

pyarrow-16.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (41.0 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pyarrow-16.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (38.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

pyarrow-16.1.0-cp39-cp39-macosx_11_0_arm64.whl (26.0 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pyarrow-16.1.0-cp39-cp39-macosx_10_15_x86_64.whl (28.4 MB view details)

Uploaded CPython 3.9 macOS 10.15+ x86-64

pyarrow-16.1.0-cp38-cp38-win_amd64.whl (25.9 MB view details)

Uploaded CPython 3.8 Windows x86-64

pyarrow-16.1.0-cp38-cp38-manylinux_2_28_x86_64.whl (40.9 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.28+ x86-64

pyarrow-16.1.0-cp38-cp38-manylinux_2_28_aarch64.whl (38.1 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.28+ ARM64

pyarrow-16.1.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (41.0 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

pyarrow-16.1.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (38.8 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

pyarrow-16.1.0-cp38-cp38-macosx_11_0_arm64.whl (26.0 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

pyarrow-16.1.0-cp38-cp38-macosx_10_15_x86_64.whl (28.3 MB view details)

Uploaded CPython 3.8 macOS 10.15+ x86-64

File details

Details for the file pyarrow-16.1.0.tar.gz.

File metadata

  • Download URL: pyarrow-16.1.0.tar.gz
  • Upload date:
  • Size: 1.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for pyarrow-16.1.0.tar.gz
Algorithm Hash digest
SHA256 15fbb22ea96d11f0b5768504a3f961edab25eaf4197c341720c4a387f6c60315
MD5 1a1a9df31b4ca634627bb53ea27a0278
BLAKE2b-256 1af267533f116deb6dae7a0ac04681695fe06135912253a115c5ecdc714a32d4

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: pyarrow-16.1.0-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 25.8 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for pyarrow-16.1.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 febde33305f1498f6df85e8020bca496d0e9ebf2093bab9e0f65e2b4ae2b3444
MD5 cd0192b0cb93cf3fd0bd114dd815f133
BLAKE2b-256 fa2ba0053f1304586f2976cb2c37ddb0e52cf4114220e805ebba272a1e231ccc

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 e1369af39587b794873b8a307cc6623a3b1194e69399af0efd05bb202195a5a7
MD5 84ec05d785b99b926b0e55b13d441f27
BLAKE2b-256 257b8da91f8de0b40b760dd748031973b6ac2aa3d4f85c67f45b7e58577ca22e

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp312-cp312-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp312-cp312-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 8785bb10d5d6fd5e15d718ee1d1f914fe768bf8b4d1e5e9bf253de8a26cb1628
MD5 7b4c72e6fc7293b07e7504452bca6ca6
BLAKE2b-256 f78fa51a290a855172514b8496c8a74f0e0b98e5e0582d44ae7547cf68dd033b

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0d32000693deff8dc5df444b032b5985a48592c0697cb6e3071a5d59888714e2
MD5 e9b1f5c461fdf7a3c0ffbec72f4ee137
BLAKE2b-256 084a668e7fb6bc564e5361097f1f160b2891ca40bcacfe018638e2841073ec3d

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 b04707f1979815f5e49824ce52d1dceb46e2f12909a48a6a753fe7cafbc44a0c
MD5 b606f069fe51462e24723f1590294133
BLAKE2b-256 565e3cd956aceb1c960e8ac6fdc6eea69d642aa2e6ee10e2f10ce7815dbf62a9

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 06ebccb6f8cb7357de85f60d5da50e83507954af617d7b05f48af1621d331c9a
MD5 85f73fa9a50077721c34c4b5eb88ca1b
BLAKE2b-256 9b73560ef6bf05f16305502b8e368c771e8f82d774898b37a3fb231f89c13342

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp312-cp312-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp312-cp312-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 2e51ca1d6ed7f2e9d5c3c83decf27b0d17bb207a7dea986e8dc3e24f80ff7d6f
MD5 da2f17b0bc779b08097c1dce3fb39b4d
BLAKE2b-256 84bdd5903125e38c33b74f7b3d57ffffd4ef48145208cfd8742367f12effb59c

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: pyarrow-16.1.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 25.9 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for pyarrow-16.1.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 185d121b50836379fe012753cf15c4ba9638bda9645183ab36246923875f8d1b
MD5 6e05a0060ff350bab4b41e707785a4e2
BLAKE2b-256 494d62a09116ec357ade462fac4086e0711457a87177bea25ae46b25897d6d7c

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 a33a64576fddfbec0a44112eaf844c20853647ca833e9a647bfae0582b2ff94b
MD5 88b290878fbae38535208127857e5233
BLAKE2b-256 fa1548a68b30542a0231a75c26d8661bc5c9bbc07b42c5b219e929adba814ba7

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp311-cp311-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp311-cp311-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 25233642583bf658f629eb230b9bb79d9af4d9f9229890b3c878699c82f7d11e
MD5 efc5601a1fe576f6abbc1e94d9954bfc
BLAKE2b-256 4762b446ee0971b00e7437b9c54a8409ae20413235a64c0a301d7cf97070cffa

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ddf5aace92d520d3d2a20031d8b0ec27b4395cab9f74e07cc95edf42a5cc0147
MD5 8a3a1c93f93ae926eeedace0976d8ea4
BLAKE2b-256 d2344e3c04e7398764e56ef00f8f267f8ebf565808478f5fee850cef4be670c3

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 bf9251264247ecfe93e5f5a0cd43b8ae834f1e61d1abca22da55b20c788417f6
MD5 5665410c3252af5d53d484e893da2ff7
BLAKE2b-256 7e34d5b6eb5066553533dd6eb9782d50f353f8c6451ee2e49e0ea54d0e67bc34

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 2e73cfc4a99e796727919c5541c65bb88b973377501e39b9842ea71401ca6c1c
MD5 bcf8f28de26cbc12e2964aea846364e0
BLAKE2b-256 f3944e2a579bbac1adb19e63b054b300f6f7fa04f32f212ce86c18727bdda698

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp311-cp311-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp311-cp311-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 d0ebea336b535b37eee9eee31761813086d33ed06de9ab6fc6aaa0bace7b250c
MD5 03cbb71978092eb9a8d275e5f5ff4997
BLAKE2b-256 2817a12aaddb818b7b73d17f3304afc22bce32ccb26723b507cc9c267aa809f3

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pyarrow-16.1.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 25.9 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for pyarrow-16.1.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 9cf389d444b0f41d9fe1444b70650fea31e9d52cfcb5f818b7888b91b586efff
MD5 9dde39663f6394850730d75b72b0a312
BLAKE2b-256 481623218e1e965123e70defb1c9603305ef4616e9f1bfbcd735280f36ec28d3

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 48be160782c0556156d91adbdd5a4a7e719f8d407cb46ae3bb4eaee09b3111bd
MD5 fefed0753f82810c5898ec06ce9dfef9
BLAKE2b-256 b054eb7fcfc0e1ec6a8404cadd11ac957b3ee4fd0774225cafe3ffe6287861cb

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp310-cp310-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp310-cp310-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 a8914cd176f448e09746037b0c6b3a9d7688cef451ec5735094055116857580c
MD5 30844d68281b140297ba82bb73e8aa50
BLAKE2b-256 a4533446907cced548d8beaf1be9dfa9d52b7ec38fa44f25d292d7999e6bf509

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f68f409e7b283c085f2da014f9ef81e885d90dcd733bd648cfba3ef265961848
MD5 31cbcc14bf49d9a6e005d85bb2f47090
BLAKE2b-256 918357572c088ec185582f04b607d545a4a6ef7599c0a3c1e60d397743b0d609

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 98100e0268d04e0eec47b73f20b39c45b4006f3c4233719c3848aa27a03c1aef
MD5 a5d2707209bc70d9cc9815d359a5c2d1
BLAKE2b-256 8d4b82f67b58a4e0ac4ebaa0e04d7a17b59ed4fbd63094f62893160f606350a0

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 4740cc41e2ba5d641071d0ab5e9ef9b5e6e8c7611351a5cb7c1d175eaf43674a
MD5 5e156726906936b2ca77ebfcd37e5386
BLAKE2b-256 dc5c4d5c43361ee36b8bca29a3a7afaa9d651aa8d5dc05d87ab507e6b2e4e2f8

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp310-cp310-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp310-cp310-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 17e23b9a65a70cc733d8b738baa6ad3722298fa0c81d88f63ff94bf25eaa77b9
MD5 8f832c13ca9d39b03e174e2c1a88fbaf
BLAKE2b-256 e0848a80b9ed7f595073ee920c2eafaecaeda4b8adffee8dcb88275fce4609d8

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pyarrow-16.1.0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 25.9 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for pyarrow-16.1.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 31a1851751433d89a986616015841977e0a188662fcffd1a5677453f1df2de0a
MD5 63b61962796555bae8c98f779ede1d79
BLAKE2b-256 5e1bd59f6ee8f55a233b85299d0b93fb24ac487571849f8ca93807dcd182d614

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp39-cp39-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp39-cp39-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 ba8ac20693c0bb0bf4b238751d4409e62852004a8cf031c73b0e0962b03e45e3
MD5 f0a91db36bfbf8024b70e1d420d0e1b5
BLAKE2b-256 4a0eca72b2e27d8d7a23e9866c819436ebeb518f934ac2b8b871fab373f9c859

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp39-cp39-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp39-cp39-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 3b20bd67c94b3a2ea0a749d2a5712fc845a69cb5d52e78e6449bbd295611f3aa
MD5 0bc7de20ad977c2573786aab7ce4c0a7
BLAKE2b-256 8760cc0645eb4ef73f88847e40a7f9d238bae6b7409d6c1f6a5d200d8ade1f09

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ddfe389a08ea374972bd4065d5f25d14e36b43ebc22fc75f7b951f24378bf0b5
MD5 becbb3efa237e26f173e8f1a892a6d05
BLAKE2b-256 df3e9cfa78ad9744c77e4f3c183d919de3649505e50663d3715151a094c27769

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 f07fdffe4fd5b15f5ec15c8b64584868d063bc22b86b46c9695624ca3505b7b4
MD5 8051b56742645ce8bd1f80df62325fbb
BLAKE2b-256 100fccfee8b6260888fe5e08d962af28a4b9115d5d245d4e61f8938a8b69f981

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 99f7549779b6e434467d2aa43ab2b7224dd9e41bdde486020bae198978c9e05e
MD5 dbca3a2775104cd057ceff29da1ff467
BLAKE2b-256 e312635c509b84c50cd92fa35a2dee8bc9c1f6fc042da86276ca726f24c5d87f

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 18da9b76a36a954665ccca8aa6bd9f46c1145f79c0bb8f4f244f5f8e799bca55
MD5 6c2a145ad223c8a7a6b9978a5f88e7f5
BLAKE2b-256 6b5b7b1c11872ddd2fd0ca472d0beaf2a3aa2e6cc168a933985e79498d79b71d

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pyarrow-16.1.0-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 25.9 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for pyarrow-16.1.0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 e6b6d3cd35fbb93b70ade1336022cc1147b95ec6af7d36906ca7fe432eb09710
MD5 6681dc06d96142a9ad5567455f902f14
BLAKE2b-256 1ee1068a97b80968f50ad969c11be1a12e0979b282d57afe0a13899399ccfefd

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp38-cp38-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp38-cp38-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f2c5fb249caa17b94e2b9278b36a05ce03d3180e6da0c4c3b3ce5b2788f30eed
MD5 7cf504f98996c128ea45663bdc1f09ab
BLAKE2b-256 95963fc14bb56d118a1ac2284c3066281339fd86ab83d28f493e5c8f983f7614

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp38-cp38-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp38-cp38-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 19741c4dbbbc986d38856ee7ddfdd6a00fc3b0fc2d928795b95410d38bb97d15
MD5 18338d6f32d6ad1d3e25277d5e0163a6
BLAKE2b-256 285e89746311740c0bfcfc8fe4e6cb51e5d78d3145b3d86eeba17e750adc2782

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fbef391b63f708e103df99fbaa3acf9f671d77a183a07546ba2f2c297b361e83
MD5 73334751bb5a69ba9cefccd0910a091e
BLAKE2b-256 6ee8ae66b4aa457143329e5677149afe552e3e0d1062582ef688b9cce444e7c7

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 0d07de3ee730647a600037bc1d7b7994067ed64d0eba797ac74b2bc77384f4c2
MD5 d1c6eb5ef4af6c6337e657c0aa0eb02b
BLAKE2b-256 d4bb3236773fb52dd263b22adf2e6e4637cdb965778b0c06315737468d614b80

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 0d27bf89dfc2576f6206e9cd6cf7a107c9c06dc13d53bbc25b0bd4556f19cf5f
MD5 543d9937ee8404f3f2a70e72372db1d0
BLAKE2b-256 ebf35413ac69a1c3443bc397e1adab09db69b8ddd2468e1505241aa3d10baf47

See more details on using hashes here.

File details

Details for the file pyarrow-16.1.0-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for pyarrow-16.1.0-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 b5f5705ab977947a43ac83b52ade3b881eb6e95fcc02d76f501d549a210ba77f
MD5 3f8a82e2284290ab2c377f3ac1ea3cbe
BLAKE2b-256 6362f3346d26d0c1706e19e05155c3159689095519fe67065f52b325f0a26215

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 Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page