GDAL/OGR in Python
==================
This Python package and extensions are a number of tools for programming and
manipulating the GDAL_ Geospatial Data Abstraction Library.
The GDAL project maintains SWIG generated Python
bindings for GDAL/OGR. Generally speaking the classes and methods mostly
match those of the GDAL and OGR C++ classes. There is no Python specific
reference documentation, but the https://gdal.org/api/python_bindings.html#tutorials includes Python examples.
Dependencies
------------
* libgdal (3.9.0 or greater) and header files (gdal-devel)
* numpy (1.0.0 or greater) and header files (numpy-devel) (not explicitly
required, but many examples and utilities will not work without it)
Installation
------------
Conda
~~~~~
GDAL can be quite complex to build and install, particularly on Windows and MacOS.
Pre built binaries are provided for the conda system:
https://docs.conda.io/en/latest/
By the conda-forge project:
https://conda-forge.org/
Once you have Anaconda or Miniconda installed, you should be able to install GDAL with:
``conda install -c conda-forge gdal``
pip
~~~
Due to the complex nature of GDAL and its components, different bindings may require additional packages and installation steps.
GDAL can be installed from the `Python Package Index <https://pypi.org/project/GDAL>`__:
::
pip install gdal
In order to enable numpy-based raster support, libgdal and its development headers must be installed as well as the Python packages numpy, setuptools, and wheel.
To install the Python dependencies and build numpy-based raster support:
::
pip install numpy>1.0.0 wheel setuptools>=67
pip install gdal[numpy]=="$(gdal-config --version).*"
Users can verify that numpy-based raster support has been installed with:
::
python3 -c 'from osgeo import gdal_array'
If this command raises an ImportError, numpy-based raster support has not been properly installed:
::
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/usr/local/lib/python3.12/dist-packages/osgeo/gdal_array.py", line 10, in <module>
from . import _gdal_array
ImportError: cannot import name '_gdal_array' from 'osgeo' (/usr/local/lib/python3.12/dist-packages/osgeo/__init__.py)
This is most often due to pip reusing a cached GDAL installation.
Verify that the necessary dependencies have been installed and then run the following to force a clean build:
::
pip install --no-cache --force-reinstall gdal[numpy]=="$(gdal-config --version).*"
Potential issues with GDAL >= 3.9, Python >= 3.9 and NumPy 2.0
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The pyproject.toml file of GDAL 3.9 requires numpy >= 2.0.0rc1 (for Python >= 3.9)
at build time to be able to build bindings that are compatible of both NumPy 1
and NumPy 2.
If for some reason the numpy >= 2.0.0rc1 build dependency can not be installed,
it is possible to manually install the build requirements, and invoke ``pip install``
with the ``--no-build-isolation`` flag.
::
pip install numpy==<required_version> wheel setuptools>=67
pip install gdal[numpy]=="$(gdal-config --version).*" --no-build-isolation
Building as part of the GDAL library source tree
------------------------------------------------
Python bindings are generated by default when building GDAL from source.
For more detail, see `Python bindings options <https://gdal.org/development/building_from_source.html#building-python-bindings>`__
The GDAL Python package is built using `SWIG <https://www.swig.org>`__. The currently supported version
is SWIG >= 4
Usage
-----
Imports
~~~~~~~
There are five major modules that are included with the GDAL_ Python bindings.::
>>> from osgeo import gdal
>>> from osgeo import ogr
>>> from osgeo import osr
>>> from osgeo import gdal_array
>>> from osgeo import gdalconst
API
~~~
API documentation is available at https://gdal.org/api/python/osgeo.html
Numpy
-----
One advanced feature of the GDAL Python bindings not found in the other
language bindings is integration with the Python numerical array
facilities. The gdal.Dataset.ReadAsArray() method can be used to read raster
data as numerical arrays, ready to use with the Python numerical array
capabilities.
Tutorials
---------
See https://gdal.org/api/python_bindings.html#tutorials
Gotchas
-------
Although GDAL's and OGR's Python bindings provide a fairly "Pythonic" wrapper around the underlying C++ code, there are several ways in which the Python bindings differ from typical Python libraries.
These differences can catch Python programmers by surprise and lead to unexpected results. These differences result from the complexity of developing a large, long-lived library while continuing to maintain
backward compatibility. They are being addressed over time, but until they are all gone, please review this list of https://gdal.org/api/python_gotchas.html
Examples
--------
* An assortment of other samples are available in the `Python github samples directory <https://github.com/OSGeo/gdal/tree/master/swig/python/gdal-utils/osgeo_utils/samples>`__
with some description in the https://gdal.org/api/python_bindings.html#examples.
* Several `GDAL utilities <https://github.com/OSGeo/gdal/tree/master/swig/python/gdal-utils/osgeo_utils/>`__
are implemented in Python and can be useful examples.
* The majority of GDAL regression tests are written in Python. They are available at
`https://github.com/OSGeo/gdal/tree/master/autotest <https://github.com/OSGeo/gdal/tree/master/autotest>`__
One example of GDAL/numpy integration is found in the `val_repl.py <https://github.com/OSGeo/gdal/tree/master/swig/python/gdal-utils/osgeo_utils/samples/val_repl.py>`__ script.
.. note::
**Performance Notes**
ReadAsArray expects to make an entire copy of a raster band or dataset
unless the data are explicitly subsetted as part of the function call. For
large data, this approach is expected to be prohibitively memory intensive.
.. _GDAL: https://gdal.org
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"description": "\nGDAL/OGR in Python\n==================\n\nThis Python package and extensions are a number of tools for programming and\nmanipulating the GDAL_ Geospatial Data Abstraction Library.\n\nThe GDAL project maintains SWIG generated Python\nbindings for GDAL/OGR. Generally speaking the classes and methods mostly\nmatch those of the GDAL and OGR C++ classes. There is no Python specific\nreference documentation, but the https://gdal.org/api/python_bindings.html#tutorials includes Python examples.\n\nDependencies\n------------\n\n * libgdal (3.9.0 or greater) and header files (gdal-devel)\n * numpy (1.0.0 or greater) and header files (numpy-devel) (not explicitly\n required, but many examples and utilities will not work without it)\n\nInstallation\n------------\n\nConda\n~~~~~\n\nGDAL can be quite complex to build and install, particularly on Windows and MacOS.\nPre built binaries are provided for the conda system:\n\nhttps://docs.conda.io/en/latest/\n\nBy the conda-forge project:\n\nhttps://conda-forge.org/\n\nOnce you have Anaconda or Miniconda installed, you should be able to install GDAL with:\n\n``conda install -c conda-forge gdal``\n\n\npip\n~~~\n\nDue to the complex nature of GDAL and its components, different bindings may require additional packages and installation steps.\nGDAL can be installed from the `Python Package Index <https://pypi.org/project/GDAL>`__:\n\n::\n\n pip install gdal\n\n\nIn order to enable numpy-based raster support, libgdal and its development headers must be installed as well as the Python packages numpy, setuptools, and wheel.\nTo install the Python dependencies and build numpy-based raster support:\n\n\n::\n\n pip install numpy>1.0.0 wheel setuptools>=67\n pip install gdal[numpy]==\"$(gdal-config --version).*\"\n\n\nUsers can verify that numpy-based raster support has been installed with:\n\n::\n\n python3 -c 'from osgeo import gdal_array'\n\n\nIf this command raises an ImportError, numpy-based raster support has not been properly installed:\n\n::\n\n Traceback (most recent call last):\n File \"<string>\", line 1, in <module>\n File \"/usr/local/lib/python3.12/dist-packages/osgeo/gdal_array.py\", line 10, in <module>\n from . import _gdal_array\n ImportError: cannot import name '_gdal_array' from 'osgeo' (/usr/local/lib/python3.12/dist-packages/osgeo/__init__.py)\n\n\nThis is most often due to pip reusing a cached GDAL installation.\nVerify that the necessary dependencies have been installed and then run the following to force a clean build:\n\n::\n pip install --no-cache --force-reinstall gdal[numpy]==\"$(gdal-config --version).*\"\n\n\nPotential issues with GDAL >= 3.9, Python >= 3.9 and NumPy 2.0\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThe pyproject.toml file of GDAL 3.9 requires numpy >= 2.0.0rc1 (for Python >= 3.9)\nat build time to be able to build bindings that are compatible of both NumPy 1\nand NumPy 2.\nIf for some reason the numpy >= 2.0.0rc1 build dependency can not be installed,\nit is possible to manually install the build requirements, and invoke ``pip install``\nwith the ``--no-build-isolation`` flag.\n\n::\n\n pip install numpy==<required_version> wheel setuptools>=67\n pip install gdal[numpy]==\"$(gdal-config --version).*\" --no-build-isolation\n\n\nBuilding as part of the GDAL library source tree\n------------------------------------------------\n\nPython bindings are generated by default when building GDAL from source.\nFor more detail, see `Python bindings options <https://gdal.org/development/building_from_source.html#building-python-bindings>`__\n\nThe GDAL Python package is built using `SWIG <https://www.swig.org>`__. The currently supported version\nis SWIG >= 4\n\nUsage\n-----\n\nImports\n~~~~~~~\n\nThere are five major modules that are included with the GDAL_ Python bindings.::\n\n >>> from osgeo import gdal\n >>> from osgeo import ogr\n >>> from osgeo import osr\n >>> from osgeo import gdal_array\n >>> from osgeo import gdalconst\n\nAPI\n~~~\n\nAPI documentation is available at https://gdal.org/api/python/osgeo.html\n\nNumpy\n-----\n\nOne advanced feature of the GDAL Python bindings not found in the other\nlanguage bindings is integration with the Python numerical array\nfacilities. 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They are being addressed over time, but until they are all gone, please review this list of https://gdal.org/api/python_gotchas.html\n\nExamples\n--------\n\n* An assortment of other samples are available in the `Python github samples directory <https://github.com/OSGeo/gdal/tree/master/swig/python/gdal-utils/osgeo_utils/samples>`__\n with some description in the https://gdal.org/api/python_bindings.html#examples.\n* Several `GDAL utilities <https://github.com/OSGeo/gdal/tree/master/swig/python/gdal-utils/osgeo_utils/>`__\n are implemented in Python and can be useful examples.\n* The majority of GDAL regression tests are written in Python. They are available at\n `https://github.com/OSGeo/gdal/tree/master/autotest <https://github.com/OSGeo/gdal/tree/master/autotest>`__\n\nOne example of GDAL/numpy integration is found in the `val_repl.py <https://github.com/OSGeo/gdal/tree/master/swig/python/gdal-utils/osgeo_utils/samples/val_repl.py>`__ script.\n\n.. note::\n **Performance Notes**\n\n ReadAsArray expects to make an entire copy of a raster band or dataset\n unless the data are explicitly subsetted as part of the function call. For\n large data, this approach is expected to be prohibitively memory intensive.\n\n\n.. _GDAL: https://gdal.org\n",
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