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MIT License
Copyright (c) 2020-2024 Brendan C. Ward and pyogrio contributors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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Metadata-Version: 2.1
Name: pyogrio
Version: 0.10.0
Summary: Vectorized spatial vector file format I/O using GDAL/OGR
Author: pyogrio contributors
Author-email: "Brendan C. Ward" <bcward@astutespruce.com>
Maintainer: pyogrio contributors
License: MIT License
Copyright (c) 2020-2024 Brendan C. Ward and pyogrio contributors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Project-URL: Home, https://pyogrio.readthedocs.io/
Project-URL: Repository, https://github.com/geopandas/pyogrio
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: GIS
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: certifi
Requires-Dist: numpy
Requires-Dist: packaging
Provides-Extra: benchmark
Requires-Dist: pytest-benchmark ; extra == 'benchmark'
Provides-Extra: dev
Requires-Dist: cython ; extra == 'dev'
Provides-Extra: geopandas
Requires-Dist: geopandas ; extra == 'geopandas'
Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'
Requires-Dist: pytest-cov ; extra == 'test'
# pyogrio - Vectorized spatial vector file format I/O using GDAL/OGR
Pyogrio provides a
[GeoPandas](https://github.com/geopandas/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](https://pyogrio.readthedocs.io/en/latest/).
WARNING: Pyogrio is still at an early version and the API is subject to
substantial change. Please see [CHANGES](CHANGES.md).
## 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](https://anaconda.org/conda-forge/pyogrio)
and [PyPI](https://pypi.org/project/pyogrio/)
for Linux, MacOS, and Windows.
Please read the
[installation documentation](https://pyogrio.readthedocs.io/en/latest/install.html)
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](https://pyogrio.readthedocs.io/en/latest/supported_formats.html)
for more information.
## Getting started
Please read the [introduction](https://pyogrio.readthedocs.io/en/latest/supported_formats.html)
for more information and examples to get started using Pyogrio.
You can also check out the the [API documentation](https://pyogrio.readthedocs.io/en/latest/api.html)
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](https://github.com/Toblerity/Fiona)
- Inspired by [Fiona PR](https://github.com/Toblerity/Fiona/pull/540/files)

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