How to use "gdal" CLI algorithms from Python

Principles

"gdal" CLI algorithms are available as osgeo.gdal.Algorithm instances.

A convenient way to access an algorithm and run it is to use the osgeo.gdal.Run() function.

Run(*alg, arguments={}, progress=None, **kwargs)

Run a GDAL algorithm and return it.

Parameters:

• alg (str, list[str], tuple[str], Algorithm) -- Path to the algorithm or algorithm instance itself. For example "raster info", or ["raster", "info"] or "raster", "info".

• arguments (dict) -- Input arguments of the algorithm. For example {"format": "json", "input": "byte.tif"}

• progress (callable) -- Progress function whose arguments are a progress ratio, a string and a user data

• kwargs -- Instead of using the arguments parameter, it is possible to pass algorithm arguments directly as named parameters of gdal.Run(). If the named argument has dash characters in it, the corresponding parameter must replace them with an underscore character. For example dst_crs as a a parameter of gdal.Run(), instead of dst-crs which is the name to use on the command line.

Return type:

a osgeo.gdal.Algorithm instance

If you do not need to access output value(s) of the algorithm, you can call Run directly: gdal.Run(["raster", "convert"], input="in.tif", output="out.tif")

The name of algorithm arguments are the long names as documented in the documentation page of each algorithm. They can also be obtained with osgeo.gdal.Algorithm.GetArgNames().

>>> gdal.Algorithm("raster", "convert").GetArgNames()
['help', 'help-doc', 'version', 'json-usage', 'drivers', 'config', 'progress', 'output-format', 'open-option', 'input-format', 'input', 'output', 'creation-option', 'overwrite', 'append']

For a command such as gdal raster info that returns a JSON output, you can get the return value of osgeo.gdal.Run() and call the osgeo.gdal.Algorithm.Output() method.

alg = gdal.Run("raster", "info", input="byte.tif")
info_as_dict = alg.Output()

If the return value is a dataset, osgeo.gdal.Run() can be used within a context manager, in which case osgeo.gdal.Algorithm.Finalize() will be called at the exit of the context manager.

with gdal.Run("raster reproject", input=src_ds, output_format="MEM",
              dst_crs="EPSG:4326") as alg:
    values = alg.Output().ReadAsArray()

Raster commands examples

Example 1: Getting information on a raster dataset as JSON

from osgeo import gdal

gdal.UseExceptions()
alg = gdal.Run("raster", "info", input="byte.tif")
info_as_dict = alg.Output()

Example 2: Converting a georeferenced netCDF file to cloud-optimized GeoTIFF

from osgeo import gdal

gdal.UseExceptions()
gdal.Run("raster", "convert", input="in.tif", output="out.tif",
         output_format="COG", overwrite=True)

or

from osgeo import gdal

gdal.UseExceptions()
gdal.Run(["raster", "convert"], {"input": "in.tif", "output": "out.tif", "output-format": "COG", "overwrite": True})

Example 3: Reprojecting a GeoTIFF file to a Deflate-compressed tiled GeoTIFF file

from osgeo import gdal

gdal.UseExceptions()
gdal.Run("raster", "reproject", input="in.tif", output="out.tif",
          dst_crs="EPSG:4326",
          creation_options={ "TILED": "YES", "COMPRESS": "DEFLATE"})

Example 4: Reprojecting a (possibly in-memory) dataset to a in-memory dataset

from osgeo import gdal

gdal.UseExceptions()
with gdal.Run("raster", "reproject", input=src_ds, output_format="MEM",
              dst_crs="EPSG:4326") as alg:
    values = alg.Output().ReadAsArray()

Vector commands examples

Example 5: Getting information on a vector dataset as JSON

from osgeo import gdal

gdal.UseExceptions()
alg = gdal.Run("vector", "info", input="poly.gpkg")
info_as_dict = alg.Output()

Example 6: Converting a shapefile to a GeoPackage

from osgeo import gdal

gdal.UseExceptions()
gdal.Run("vector", "convert", input="in.shp", output="out.gpkg", overwrite=True)