Metadata-Version: 2.1
Name: GDAL
Version: 3.2.2
Summary: GDAL: Geospatial Data Abstraction Library
Home-page: http://www.gdal.org
Author: Frank Warmerdam
Author-email: warmerdam@pobox.com
Maintainer: Howard Butler
Maintainer-email: hobu.inc@gmail.com
License: MIT
Description: 
Provides-Extra: numpy
Requires-Dist: numpy (>1.19.0) ; extra == 'numpy'

        GDAL/OGR in Python

        ==================

        

        This Python package and extensions are a number of tools for programming and

        manipulating the GDAL_ Geospatial Data Abstraction Library.  Actually, it is

        two libraries -- GDAL for manipulating geospatial raster data and OGR for

        manipulating geospatial vector data -- but we'll refer to the entire package

        as the GDAL library for the purposes of this document.

        

        The GDAL project (primarily Even Rouault) maintains SWIG generated Python

        bindings for GDAL and 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 `GDAL API Tutorial`_ includes Python examples.

        

        Dependencies

        ------------

        

         * libgdal (3.2.2 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

        ------------

        

        Unix

        ~~~~~~~~~~~~~

        

        The GDAL Python bindings support both distutils and setuptools, with a

        preference for using setuptools.  If setuptools can be imported, setup will

        use that to build an egg by default.  If setuptools cannot be imported, a

        simple distutils root install of the GDAL package (and no dependency

        chaining for numpy) will be made.

        

        easy_install

        ~~~~~~~~~~~~

        

        GDAL can be installed from the Python CheeseShop::

        

          $ sudo easy_install GDAL

        

        It may be necessary to have libgdal and its development headers installed

        if easy_install is expected to do a source build because no egg is available

        for your specified platform and Python version.

        

        setup.py

        ~~~~~~~~~

        

        Most of setup.py's important variables are controlled with the setup.cfg

        file.  In setup.cfg, you can modify pointers to include files and libraries.

        The most important option that will likely need to be modified is the

        gdal_config parameter.  If you installed GDAL from a package, the location

        of this program is likely /usr/bin/gdal-config, but it may be in another place

        depending on how your packager arranged things.

        

        After modifying the location of gdal-config, you can build and install

        with the setup script::

        

          $ python setup.py build

          $ python setup.py install

        

        If you have setuptools installed, you can also generate an egg::

        

          $ python setup.py bdist_egg

        

        Building as part of the GDAL library source tree

        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

        

        You can also have the GDAL Python bindings built as part of a source

        build by specifying --with-python as part of your configure line::

        

          $ ./configure --with-python

        

        Use the typical make and make install commands to complete the installation::

        

          $ make

          $ make install

        

        A note about setuptools

        .......................

        

        ./configure attempts to detect if you have setuptools installed in the tree

        of the Python binary it was given (or detected on the execution path), and it

        will use an egg build by default in that instance.  If you have a need to

        use a distutils-only install, you will have to edit setup.py to ensure that

        the HAVE_SETUPTOOLS variable is ultimately set to False and proceed with a

        typical 'python setup.py install' command.

        

        Windows

        ~~~~~~~~~~~~

        

        You will need the following items to complete an install of the GDAL Python

        bindings on Windows:

        

        * `GDAL Windows Binaries`_ Download the package that best matches your environment.

        

        As explained in the README_EXE.txt file, after unzipping the GDAL binaries you

        will need to modify your system path and variables. If you're not sure how to

        do this, read the `Microsoft Knowledge Base doc`_

        

        1. Add the installation directory bin folder to your system PATH, remember

           to put a semicolon in front of it before you add to the existing path.

        

           ::

        

             C:\gdalwin32-1.7\bin

        

        2. Create a new user or system variable with the data folder from

           your installation.

        

           ::

        

             Name : GDAL_DATA

             Path : C:\gdalwin32-1.7\data

        

        Skip down to the `Usage`_ section to test your install. Note, a reboot

        may be required.

        

        SWIG

        ----

        

        The GDAL Python package is built using SWIG_. The earliest version of SWIG_

        that is supported to generate the wrapper code is 1.3.40.  It is possible

        that usable bindings will build with a version earlier than 1.3.40, but no

        development efforts are targeted at versions below it.  You should not have

        to run SWIG in your development tree to generate the binding code, as it

        is usually included with the source.  However, if you do need to regenerate,

        you can do so with the following make command from within the ./swig/python

        directory::

        

          $ make generate

        

        To ensure that all of the bindings are regenerated, you can clean the

        bindings code out before the generate command by issuing::

        

          $ make veryclean

        

        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

        

        Additionally, there are five compatibility modules that are included but

        provide notices to state that they are deprecated and will be going away.

        If you are using GDAL 1.7 bindings, you should update your imports to utilize

        the usage above, but the following will work until at least GDAL 2.1. ::

        

          >>> import gdal

          >>> import ogr

          >>> import osr

          >>> import gdalnumeric

          >>> import gdalconst

        

        If you have previous code that imported the global module and still need to

        support the old import, a simple try...except import can silence the

        deprecation warning and keep things named essentially the same as before::

        

          >>> try:

          ...     from osgeo import gdal

          ... except ImportError:

          ...     import gdal

        

        Docstrings

        ~~~~~~~~~~

        

        Currently, only the OGR module has docstrings which are generated from the

        C/C++ API doxygen materials.  Some of the arguments and types might not

        match up exactly with what you are seeing from Python, but they should be

        enough to get you going.  Docstrings for GDAL and OSR are planned for a future

        release.

        

        Numpy/Numeric

        -------------

        

        One advanced feature of the GDAL Python bindings not found in the other

        language bindings (C#, Perl) 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.

        

        These facilities have evolved somewhat over time. In the past the package was

        known as "Numeric" and imported using "import Numeric". A new generation is

        imported using "import numpy". Currently the old generation bindings only

        support the older Numeric package, and the new generation bindings only

        support the new generation numpy package. They are mostly compatible, and

        by importing gdalnumeric (or osgeo.gdal_array) you will get whichever is

        appropriate to the current bindings type.

        

        Examples

        ~~~~~~~~

        

        One example of GDAL/numpy integration is found in the `val_repl.py`_ script.

        

        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 API Tutorial: https://gdal.org/tutorials/

        .. _GDAL Windows Binaries: http://gisinternals.com/sdk/

        .. _Microsoft Knowledge Base doc: http://support.microsoft.com/kb/310519

        .. _Python Cheeseshop: http://pypi.python.org/pypi/GDAL/

        .. _val_repl.py: http://trac.osgeo.org/gdal/browser/trunk/gdal/swig/python/samples/val_repl.py

        .. _GDAL: http://www.gdal.org

        .. _SWIG: http://www.swig.org

        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: C
Classifier: Programming Language :: C++
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Description-Content-Type: text/x-rst
Provides-Extra: numpy
