Vectorized spatial vector file format I/O using GDAL/OGR

Navigation

Verified details

These details have been verified by PyPI
Project links
GitHub Statistics
Maintainers
Avatar for bcward from gravatar.com bcward Avatar for jorisvandenbossche from gravatar.com jorisvandenbossche Avatar for martinfleis from gravatar.com martinfleis

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT License Copyright (c) 2020-2024 Brendan C. Ward and pyogrio contributors Permission is hereby ...)
  • Author: pyogrio contributors
  • Maintainer: pyogrio contributors
  • Requires: Python >=3.9
  • Provides-Extra: benchmark, dev, geopandas, test
Classifiers

Project description

pyogrio - Vectorized spatial vector file format I/O using GDAL/OGR

Pyogrio provides a GeoPandas-oriented API to OGR vector data sources, such as ESRI Shapefile, GeoPackage, and GeoJSON. Vector data sources have geometries, such as points, lines, or polygons, and associated records with potentially many columns worth of data.

Pyogrio uses a vectorized approach for reading and writing GeoDataFrames to and from OGR vector data sources in order to give you faster interoperability. It uses pre-compiled bindings for GDAL/OGR so that the performance is primarily limited by the underlying I/O speed of data source drivers in GDAL/OGR rather than multiple steps of converting to and from Python data types within Python.

We have seen >5-10x speedups reading files and >5-20x speedups writing files compared to using non-vectorized approaches (Fiona and current I/O support in GeoPandas).

You can read these data sources into GeoDataFrames, read just the non-geometry columns into Pandas DataFrames, or even read non-spatial data sources that exist alongside vector data sources, such as tables in a ESRI File Geodatabase, or antiquated DBF files.

Pyogrio also enables you to write GeoDataFrames to at least a few different OGR vector data source formats.

Read the documentation for more information: https://pyogrio.readthedocs.io.

WARNING: Pyogrio is still at an early version and the API is subject to substantial change. Please see CHANGES.

Requirements

Supports Python 3.9 - 3.13 and GDAL 3.4.x - 3.9.x.

Reading to GeoDataFrames requires geopandas>=0.12 with shapely>=2.

Additionally, installing pyarrow in combination with GDAL 3.6+ enables a further speed-up when specifying use_arrow=True.

Installation

Pyogrio is currently available on conda-forge and PyPI for Linux, MacOS, and Windows.

Please read the installation documentation for more information.

Supported vector formats

Pyogrio supports some of the most common vector data source formats (provided they are also supported by GDAL/OGR), including ESRI Shapefile, GeoPackage, GeoJSON, and FlatGeobuf.

Please see the list of supported formats for more information.

Getting started

Please read the introduction for more information and examples to get started using Pyogrio.

You can also check out the the API documentation for full details on using the API.

Credits

This project is made possible by the tremendous efforts of the GDAL, Fiona, and Geopandas communities.

  • Core I/O methods and supporting functions adapted from Fiona
  • Inspired by Fiona PR

Project details

Verified details

These details have been verified by PyPI
Project links
GitHub Statistics
Maintainers
Avatar for bcward from gravatar.com bcward Avatar for jorisvandenbossche from gravatar.com jorisvandenbossche Avatar for martinfleis from gravatar.com martinfleis

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT License Copyright (c) 2020-2024 Brendan C. Ward and pyogrio contributors Permission is hereby ...)
  • Author: pyogrio contributors
  • Maintainer: pyogrio contributors
  • Requires: Python >=3.9
  • Provides-Extra: benchmark, dev, geopandas, test
Classifiers

Release history Release notifications | RSS feed

This version

0.10.0

0.9.0

0.8.0

0.7.2

0.7.1

0.7.0

0.6.0

0.5.1

0.5.0

0.4.2

0.4.1

0.4.0

0.4.0b1 pre-release

0.4.0a1 pre-release

0.3.0

0.2.0

Download files

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

Source Distribution

pyogrio-0.10.0.tar.gz (281.9 kB view details)

Uploaded Source

Built Distributions

pyogrio-0.10.0-cp313-cp313-win_amd64.whl (16.2 MB view details)

Uploaded CPython 3.13 Windows x86-64

pyogrio-0.10.0-cp313-cp313-manylinux_2_28_x86_64.whl (24.0 MB view details)

Uploaded CPython 3.13 manylinux: glibc 2.28+ x86-64

pyogrio-0.10.0-cp313-cp313-manylinux_2_28_aarch64.whl (23.0 MB view details)

Uploaded CPython 3.13 manylinux: glibc 2.28+ ARM64

pyogrio-0.10.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (23.9 MB view details)

Uploaded CPython 3.13 manylinux: glibc 2.17+ x86-64

pyogrio-0.10.0-cp313-cp313-macosx_12_0_x86_64.whl (16.4 MB view details)

Uploaded CPython 3.13 macOS 12.0+ x86-64

pyogrio-0.10.0-cp313-cp313-macosx_12_0_arm64.whl (15.1 MB view details)

Uploaded CPython 3.13 macOS 12.0+ ARM64

pyogrio-0.10.0-cp312-cp312-win_amd64.whl (16.2 MB view details)

Uploaded CPython 3.12 Windows x86-64

pyogrio-0.10.0-cp312-cp312-manylinux_2_28_x86_64.whl (24.0 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.28+ x86-64

pyogrio-0.10.0-cp312-cp312-manylinux_2_28_aarch64.whl (23.1 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.28+ ARM64

pyogrio-0.10.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (23.9 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

pyogrio-0.10.0-cp312-cp312-macosx_12_0_x86_64.whl (16.4 MB view details)

Uploaded CPython 3.12 macOS 12.0+ x86-64

pyogrio-0.10.0-cp312-cp312-macosx_12_0_arm64.whl (15.1 MB view details)

Uploaded CPython 3.12 macOS 12.0+ ARM64

pyogrio-0.10.0-cp311-cp311-win_amd64.whl (16.2 MB view details)

Uploaded CPython 3.11 Windows x86-64

pyogrio-0.10.0-cp311-cp311-manylinux_2_28_x86_64.whl (24.1 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.28+ x86-64

pyogrio-0.10.0-cp311-cp311-manylinux_2_28_aarch64.whl (23.1 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.28+ ARM64

pyogrio-0.10.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (23.9 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

pyogrio-0.10.0-cp311-cp311-macosx_12_0_x86_64.whl (16.5 MB view details)

Uploaded CPython 3.11 macOS 12.0+ x86-64

pyogrio-0.10.0-cp311-cp311-macosx_12_0_arm64.whl (15.1 MB view details)

Uploaded CPython 3.11 macOS 12.0+ ARM64

pyogrio-0.10.0-cp310-cp310-win_amd64.whl (16.2 MB view details)

Uploaded CPython 3.10 Windows x86-64

pyogrio-0.10.0-cp310-cp310-manylinux_2_28_x86_64.whl (23.9 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.28+ x86-64

pyogrio-0.10.0-cp310-cp310-manylinux_2_28_aarch64.whl (22.9 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.28+ ARM64

pyogrio-0.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (23.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pyogrio-0.10.0-cp310-cp310-macosx_12_0_x86_64.whl (16.5 MB view details)

Uploaded CPython 3.10 macOS 12.0+ x86-64

pyogrio-0.10.0-cp310-cp310-macosx_12_0_arm64.whl (15.1 MB view details)

Uploaded CPython 3.10 macOS 12.0+ ARM64

pyogrio-0.10.0-cp39-cp39-win_amd64.whl (16.2 MB view details)

Uploaded CPython 3.9 Windows x86-64

pyogrio-0.10.0-cp39-cp39-manylinux_2_28_x86_64.whl (23.9 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.28+ x86-64

pyogrio-0.10.0-cp39-cp39-manylinux_2_28_aarch64.whl (22.9 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.28+ ARM64

pyogrio-0.10.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (23.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pyogrio-0.10.0-cp39-cp39-macosx_12_0_x86_64.whl (16.5 MB view details)

Uploaded CPython 3.9 macOS 12.0+ x86-64

pyogrio-0.10.0-cp39-cp39-macosx_12_0_arm64.whl (15.1 MB view details)

Uploaded CPython 3.9 macOS 12.0+ ARM64

File details

Details for the file pyogrio-0.10.0.tar.gz.

File metadata

  • Download URL: pyogrio-0.10.0.tar.gz
  • Upload date:
  • Size: 281.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for pyogrio-0.10.0.tar.gz
Algorithm Hash digest
SHA256 ec051cb568324de878828fae96379b71858933413e185148acb6c162851ab23c
MD5 27e6ec45f9a65ccf177e0d7ad1ced45d
BLAKE2b-256 a58f5a784595524a79c269f2b1c880f4fdb152867df700c97005dda51997da02

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: pyogrio-0.10.0-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 16.2 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for pyogrio-0.10.0-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 02e54bcfb305af75f829044b0045f74de31b77c2d6546f7aaf96822066147848
MD5 9e84c3d12d5190baabb0ab315c792887
BLAKE2b-256 275d0deb16d228362a097ee3258d0a887c9c0add4b9678bb4847b08a241e124d

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 7c02b207ea8cf09c501ea3e95d29152781a00d3c32267286bc36fa457c332205
MD5 6590fcd53110685e0448b3b54a87b6f3
BLAKE2b-256 d73ec35f2d8dad95b24e568c468f09ff60fb61945065465e0ec7868400596566

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp313-cp313-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp313-cp313-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 cea0187fcc2d574e52af8cfab041fa0a7ad71d5ef6b94b49a3f3d2a04534a27e
MD5 d89717364057226eef773ad0c7487f7c
BLAKE2b-256 25acca483bec408b59c54f7129b0244cc9de21d8461aefe89ece7bd74ad33807

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 28cb139f8a5d0365ede602230104b407ae52bb6b55173c8d5a35424d28c4a2c5
MD5 38ef7200c1f717e4716df3609852f16b
BLAKE2b-256 9677f199230ba86fe88b1f57e71428c169ed982de68a32d6082cd7c12d0f5d55

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp313-cp313-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp313-cp313-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 fec45e1963b7058e5a1aa98598aed07c0858512c833d6aad2c672c3ec98bbf04
MD5 334d2c49cde954e935ce6e878f8277b7
BLAKE2b-256 5fbe7db0644eef9ef3382518399aaf3332827c43018112d2a74f78784fd496ec

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp313-cp313-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp313-cp313-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 c90478209537a31dcc65664a87a04c094bb0e08efe502908a6682b8cec0259bf
MD5 89a27fd56c0e96caba2e59bbfda490ef
BLAKE2b-256 144a4c8e4f5b9edbca46e0f8d6c1c0b56c0d4af0900c29f4bea22d37853c07f3

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: pyogrio-0.10.0-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 16.2 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for pyogrio-0.10.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 2a3e09839590d71ff832aa95c4f23fa00a2c63c3de82c1fbd4fb8d265792acfc
MD5 06b2c39ad9f1de1a7d0872e3575be52f
BLAKE2b-256 439734605480f06b0ad9611bf58a174eccc6f3673275f3d519cf763391892881

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 1abbcdd9876f30bebf1df8a0273f6cdeb29d03259290008275c7fddebe139f20
MD5 677f834f42cfa3a13241a15d5bae736b
BLAKE2b-256 47782b62c8a340bcb0ea56b9ddf2ef5fd3d1f101dc0e98816b9e6da87c5ac3b7

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp312-cp312-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp312-cp312-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 19f18411bdf836d24cdc08b9337eb3ec415e4ac4086ba64516b36b73a2e88622
MD5 b0ed44d7e1268a5a95d0fef036423cf1
BLAKE2b-256 bd4c79e47e40a8e54e79a45133786a0a58209534f580591c933d40c5ed314fe7

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3a4c373281d7cbf560c5b61f8f3c7442103ad7f1c7ac4ef3a84572ed7a5dd2f6
MD5 97215137fbc7765a654fcb11ae405788
BLAKE2b-256 5ebbb4250746c2c85fea5004cae93e9e25ad01516e9e94e04de780a2e78139da

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp312-cp312-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp312-cp312-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 a99102037eead8ba491bc57825c1e395ee31c9956d7bff7b4a9e4fdbff3a13c2
MD5 359e754e1847b0ab54f9e1304fdcc87d
BLAKE2b-256 b89a1ba9c707a094976f343bd0177741eaba0e842fa05ecd8ab97192db4f2ec1

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp312-cp312-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp312-cp312-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 2d6558b180e020f71ab7aa7f82d592ed3305c9f698d98f6d0a4637ec7a84c4ce
MD5 6e209239da9728bc7b3a7af4a98b1414
BLAKE2b-256 b5b53c5dfd0b50cbce6f3d4e42c0484647feb1809dbe20e225c4c6abd067e69f

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: pyogrio-0.10.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 16.2 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for pyogrio-0.10.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 d0d74e91a9c0ff2f9abe01b556ff663977193b2d6922208406172d0fc833beff
MD5 60f2084d2afbe4ff33ec45e31b7ce5dd
BLAKE2b-256 948d24f21e6a93ca418231aee3bddade7a0766c89c523832f29e08a8860f83e6

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 11e6c71d12da6b445e77d0fc0198db1bd35a77e03a0685e45338cbab9ce02add
MD5 499686ac31176d5831bff1c8532fcf99
BLAKE2b-256 ae15501aa4823c142232169d54255ab343f28c4ea9e7fa489b8433dcc873a942

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp311-cp311-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp311-cp311-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 0a47f702d29808c557d2ebea8542c23903f021eae44e16838adef2ab4281c71b
MD5 4b245500e8f526053a390efd9231e771
BLAKE2b-256 8bb22ca124343aba24b9a5dcd7c1f43da81e652849cfaf3110d3f507a80af0a1

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a2f0b75f0077ce33256aec6278c2a9c3b79bf0637ddf4f93d3ab2609f0501d96
MD5 e3958e6273b9d2797c687d62cafe7095
BLAKE2b-256 fa9a7103eee7aa3b6ec88e072ef18a05c3aae1ed96fe00009a7a5ce139b50f30

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp311-cp311-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp311-cp311-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 216d69cd77b2b4a0c9d7d449bc239f8b77f3d73f4a05d9c738a0745b236902d8
MD5 045c5e20c606ccfe09e2399852c9dbb7
BLAKE2b-256 c3e5983aa9ddf2ff784e973d6b2ec3e874065d6655a5329ca26311b0f3b9f92f

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp311-cp311-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp311-cp311-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 5b1a51431a27a1cb3e4e19558939c1423106e06e7b67d6285f4fba9c2d0a91b9
MD5 b48d79dbfa14eb252b312cd130f9b8d0
BLAKE2b-256 8d2cc761e6adeb81bd4029a137b3240e7214a8c9aaf225883356196afd6ef9d8

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pyogrio-0.10.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 16.2 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for pyogrio-0.10.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 eac90b2501656892c63bc500c12e71f3dbf7d66ddc5a7fb05cd480d25d1b7022
MD5 fd88ab007d61fb223eca63a54e1a6938
BLAKE2b-256 75cab31083da2e6c4b598b6609a98c655977189fe8982c36d98ea4789a938045

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 3539596a76eb8a9d166d6f9d3f36731a8c5bd5c43901209d89dc66b9dc00f079
MD5 4326605343b67314c2885d5e46dfd9f6
BLAKE2b-256 568b67187ae03dce5cd6f5c5a2f41c405e77059f4cf498e0817b69cec094f022

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp310-cp310-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp310-cp310-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 1fea7892f4633cab04d13563e47ec2e87dc2b5cd71b9546018d123184528c151
MD5 267e1eb39585fd78df09e60df9a7c965
BLAKE2b-256 a60735e4127a878ecdcbaaf46f0f2d068b385a454b5b0cab44ea901adc5888a0

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 14fd3b72b4e2dc59e264607b265c742b0c5ec2ea9e748b115f742381b28dd373
MD5 e06414beea93ba54cecf811e64ef6139
BLAKE2b-256 458674c37e3d4d000bdcd91b25929fe4abc5ad6d93d5f5fbc59a4c7d4f0ed982

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp310-cp310-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp310-cp310-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 44380f4d9245c776f432526e29ce4d29238aea26adad991803c4f453474f51d3
MD5 a442d0a41b05a315e5c82d005d0e2f53
BLAKE2b-256 90f8a58795a2aee415c612aac8b425681d932b8983330884207fd1915d234d36

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp310-cp310-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp310-cp310-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 046eeeae12a03a3ebc3dc5ff5a87664e4f5fc0a4fb1ea5d5c45d547fa941072b
MD5 f97e250a11a7bfc88165d296e1e70ae9
BLAKE2b-256 41eacba24d241858a72b58d8fcd0ad2276f9631fd4528b3062157637e43581eb

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pyogrio-0.10.0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 16.2 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for pyogrio-0.10.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 eea82171bfc07fc778b8dc87b0cdc9ac06c389bc56b0c0b6f34bf9e45fb78c0e
MD5 31633341d7e90eb31cd7882afb133a94
BLAKE2b-256 f814aff4499cc544a02343043a16322b51dcc0ca947d21a96b7aacb1dd1b8e3a

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp39-cp39-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp39-cp39-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 22d57495e835fe51b88da43dfbda606c07e1f6c3b849af0c3cfc18e17467641c
MD5 2a1235da724c3928c719e8b03ebed9ea
BLAKE2b-256 769b8974f77ded5661522023cfb7898d7851f9b1056f4bbaacc4de2812dbf7fd

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp39-cp39-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp39-cp39-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 6166ae81462c257ed8e151c404e316642703813cf771c95ef8e11dcdf2581e47
MD5 b4c2cea9a989373714891782678b6f17
BLAKE2b-256 1d9f3bb9a15fbe5f66907f957310b0f6d7191dfbfd9d9b31a361053d8d763bd5

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 82f7bd6a87bd2e9484bcb4c87ab94eee4c2f573ad148707431c8b341d7f13d99
MD5 765491f21efa96bb110f62c99c65a200
BLAKE2b-256 207a56ef1f49388244b5d9e4f22db58745fd329f441f87af71fce0bbd6ddd894

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp39-cp39-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp39-cp39-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 32d349600561459791a43f528a92f3e9343a59bdc9bc30b1be9376f0b80cbf16
MD5 e3cf49089ad244de6e637cabe20a4d56
BLAKE2b-256 071d1bc2162a7d1cef13edcf645e562d047742dad68c4e933b757d4cf2837b00

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.10.0-cp39-cp39-macosx_12_0_arm64.whl.

File metadata

File hashes

Hashes for pyogrio-0.10.0-cp39-cp39-macosx_12_0_arm64.whl
Algorithm Hash digest
SHA256 ea96a1338ed7991735b955d3f84ad5f71b3bc070b6a7a42449941aedecc71768
MD5 6af94811760cfbcf6b903bde3524616a
BLAKE2b-256 ecfeea995a55289a4c378a29130435a400d577bd151a518a5238fd5bc21fe09f

See more details on using hashes here.

Provenance

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