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

Navigation

Verified details

These details have been verified by PyPI
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

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 3.8 - 3.11 and GDAL 3.1.x - 3.6.x.

Reading to GeoDataFrames requires geopandas>=0.8 with pygeos or 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
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

Release history Release notifications | RSS feed

0.10.0

0.9.0

0.8.0

0.7.2

0.7.1

0.7.0

0.6.0

0.5.1

This version

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-0.5.0.tar.gz (316.7 kB view details)

Uploaded Source

Built Distributions

pyogrio-0.5.0-cp311-cp311-win_amd64.whl (14.0 MB view details)

Uploaded CPython 3.11 Windows x86-64

pyogrio-0.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (21.0 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

pyogrio-0.5.0-cp311-cp311-macosx_11_0_arm64.whl (13.6 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

pyogrio-0.5.0-cp311-cp311-macosx_10_9_x86_64.whl (14.9 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

pyogrio-0.5.0-cp310-cp310-win_amd64.whl (14.0 MB view details)

Uploaded CPython 3.10 Windows x86-64

pyogrio-0.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (21.0 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pyogrio-0.5.0-cp310-cp310-macosx_11_0_arm64.whl (13.6 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pyogrio-0.5.0-cp310-cp310-macosx_10_9_x86_64.whl (14.9 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

pyogrio-0.5.0-cp39-cp39-win_amd64.whl (14.0 MB view details)

Uploaded CPython 3.9 Windows x86-64

pyogrio-0.5.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (21.0 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pyogrio-0.5.0-cp39-cp39-macosx_11_0_arm64.whl (13.6 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pyogrio-0.5.0-cp39-cp39-macosx_10_9_x86_64.whl (14.9 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

pyogrio-0.5.0-cp38-cp38-win_amd64.whl (14.0 MB view details)

Uploaded CPython 3.8 Windows x86-64

pyogrio-0.5.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (21.0 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

pyogrio-0.5.0-cp38-cp38-macosx_11_0_arm64.whl (13.6 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

pyogrio-0.5.0-cp38-cp38-macosx_10_9_x86_64.whl (14.9 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

File details

Details for the file pyogrio-0.5.0.tar.gz.

File metadata

  • Download URL: pyogrio-0.5.0.tar.gz
  • Upload date:
  • Size: 316.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyogrio-0.5.0.tar.gz
Algorithm Hash digest
SHA256 a2a8ac97d48c653f747e45d3c802d669d3ce17d67a28f7efeab0ed61605041b9
MD5 cc07ea14fbff4838a44928b6f2bc3e5b
BLAKE2b-256 bef9edbe5b945794be882bd149db50f0e0b1e8df32a6e150c2ecfbdf7aa09ae4

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: pyogrio-0.5.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 14.0 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyogrio-0.5.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 006e536f51dad7ccce24ab5732afeed189c71b114dc880d3df2abd39c477504d
MD5 9df5f71cf57a9397d6542cccf4f27e21
BLAKE2b-256 eeaf5fc985caa69c7184f8e011ae68e958a591dbadbb1b556adc98698e5bde05

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2ec3f21bae7d33994b955ab00d20aba8162fd898bd162dd78bf5309a26e72e57
MD5 a6d349492c1a488935df03115e6f12e8
BLAKE2b-256 440cb4b5110e5ca645c664c6992bfccfb73ab62f35dedf43c1664cd949b6022e

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyogrio-0.5.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 224739fab2f199daf2e62cc2a4ffdc3308af4b5380179ff7523546e8cadff5db
MD5 c18af8d99748cc3cd387120fa5fa1a4a
BLAKE2b-256 69d44d92557ecd705f1c2f54c1023772b80a2dcba6340c8ddefb7d6ee720a86a

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.5.0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 b4d424477082280d4930a64d4cfa1e3d48974a368e30f87f8846f88d12b1d57c
MD5 f9faf8c068e844cc1f5fe4a35f892f66
BLAKE2b-256 b97103994955069c248ad451271a12bae23ba2cc6be2bd1b9c186a283ecad691

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pyogrio-0.5.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 14.0 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyogrio-0.5.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 89b125e6915eeb9544d2673c06a786a5ac85f9ad26c7b8e4aa266b86b80c71cf
MD5 4255497c448fa9b486a9856b0c33ef59
BLAKE2b-256 1a1e4d86a646851a9f220dc983baa2a231e09a2f8a673fa7934b916043b522c1

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 43919ad84aa17f7c3da98133746211ae76465f8c8a6887404cf0faa4c843f94c
MD5 7f5fff43560b395d0866e3b521d609a3
BLAKE2b-256 5ceb84b4bc5ee75427b68b5ca41b9e0b956bc2ee9099768bcaa76be77d147ca1

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyogrio-0.5.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1fb7ade67e28ab654bac611c99a61f43f9bf380837a79792f2b243c45a874418
MD5 b05396e48b2ad77c36c17ef9da40c036
BLAKE2b-256 5a544d1af6bbd89eeed2677c4be55a5aefb035de02eb267c2cd32e6ef73cf317

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.5.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 28a951ff78c13561f0fd246c226b64411b3c3b3c9a73f48bdaee5441407e1221
MD5 f34804c0d74d67c176eeeceeedaa83b3
BLAKE2b-256 863d6e4aceeb4ceb18371e06dc169634272d39fd46489fce31ee26f3bfc75487

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pyogrio-0.5.0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 14.0 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyogrio-0.5.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 bdf86f2cca412fadfa7e8bf91079d52fe0269075f8a7dff15684ee99f195c437
MD5 e9923b3c3252a920e6c6bae61f060fc6
BLAKE2b-256 24333cf661c1099b45783d03725edee7cb5e3ac600e1aca7153131cb46e72ead

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.5.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 40952008e1f10bf5f3ba328c9c3d02c486941ad6b5f2c33c4f424a36ec92064d
MD5 e486ff3ccacce69482ac957c87259837
BLAKE2b-256 09d00f654b09789f6d085158d86629a94326f4829ea6a46edabb4b2b3aa5852b

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyogrio-0.5.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a8c9fd2a170137ff5277ad6c6e196c80b9ad55f2c780a0ec18843393fff84875
MD5 78ec1d1755042b4e94481a59a5d32840
BLAKE2b-256 4d9205a8c965f7b5c3425482c31bcf047ae701836d3de87468a865757b4bb17d

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.5.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 463dcaf19c312200d0f6693a703bd6ad9c35286700e918415496f4b2b234aa9d
MD5 ba7caaa0474464ffb6437a9791ebfcc7
BLAKE2b-256 e743fd47526943a62ba7516024507bafb78799fb0852953c4f13dcd0e71a38b8

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pyogrio-0.5.0-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 14.0 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyogrio-0.5.0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 5688be6bfe6931dd7f6f93d64d4e2777a8f46cecdcd19b20f3aa694d9c8f4cc4
MD5 09f67d11c0797961a7ba31774370274c
BLAKE2b-256 df6ca21e1362703f2e02de0744b164462a7e7c8e4dfc9dd39e7d40997a74d71e

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.5.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 01c48dc4bc5a8b8ebb121ce8e83114e406912394af2cc7d7596640fbd156f0bd
MD5 71cb235ab78cec2e86056dea24373cf3
BLAKE2b-256 56dd126064d695681b5e1f7b7934b29f4ece7c5f8c4fd565d155a2a3102c8101

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyogrio-0.5.0-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 3b5436664b76f67596ca3fad4808e4a20375f83fc3a0dc4fb403791a80b46cba
MD5 4be53e6e8fd8d62d94954053ed2abd7d
BLAKE2b-256 8c628093e5e73c371a962a4d0fd1cc1fb6282852dc418d1ec7a85f20b17082ab

See more details on using hashes here.

Provenance

File details

Details for the file pyogrio-0.5.0-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyogrio-0.5.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0ccc5493076c23b539174b88749f9a1cf904ba71772ffb0e671631b6e3650f12
MD5 31d18c35054a618aa391cf162f9a0c8b
BLAKE2b-256 f9c01b30353a88de448e608bd9c02f84e3ee90c70c1c7bd293f4287dc9347e48

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