xcube’s functionality can be extended by plugins. A plugin contributes extensions to specific extension points defined by xcube. Plugins are detected and dynamically loaded, once the available extensions need to be inquired.

Installing Plugins

Plugins are installed by simply installing the plugin’s package into xcube’s Python environment.

In order to be detected by xcube, an plugin package’s name must either start with xcube_ or the plugin package’s file must specify an entry point in the group xcube_plugins. Details are provided below in section plugin_development.

Available Plugins


The xcube_sh plugin adds support for the SENTINEL Hub Cloud API. It extends xcube by a new Python API function xcube_sh.cube.open_cube to create data cubes from SENTINEL Hub on-the-fly. It also adds a new CLI command xcube sh gen to generate and write data cubes created from SENTINEL Hub into the file system.

ESA CCI Open Data Portal

The xcube_cci plugin provides support for the ESA CCI Open Data Portal.

Copernicus Climate Data Store

The xcube_cds plugin provides support for the Copernicus Climate Data Store.

Cube Generation

xcube’s GitHub organisation currently hosts a few plugins that add new input processor extensions (see below) to xcube’s data cube generation tool xcube gen. They are very specific but are a good starting point for developing your own input processors:

  • xcube_gen_bc - adds new input processors for specific Ocean Colour Earth Observation products derived from the Sentinel-3 OLCI measurements.

  • xcube_gen_rbins - adds new input processors for specific Ocean Colour Earth Observation products derived from the SEVIRI measurements.

  • xcube_gen_vito - adds new input processors for specific Ocean Colour Earth Observation products derived from the Sentinel-2 MSI measurements.

Plugin Development

Plugin Definition

An xcube plugin is a Python package that is installed in xcube’s Python environment. xcube can detect plugins either

  1. by naming convention (more simple);

  2. by entry point (more flexible).

By naming convention: Any Python package named xcube_<name> that defines a plugin initializer function named init_plugin either defined in xcube_<name>/ (preferred) or xcube_<name>/ is an xcube plugin.

By entry point: Any Python package installed using Setuptools that defines a non-empty entry point group xcube_plugins is an xcube plugin. An entry point in the xcube_plugins group has the format <name> = <fully-qualified-module-path>:<init-func-name>, and therefore specifies where plugin initializer function named <init-func-name> is found. As an example, refer to the xcube standard plugin definitions in xcube’s file.

For more information on Setuptools entry points refer to section Creating and discovering plugins in the Python Packing User Guide and Dynamic Discovery of Services and Plugins in the Setuptools documentation.

Initializer Function

xcube plugins are initialized using a dedicated function that has a single extension registry argument of type xcube.util.extension.ExtensionRegistry, that is used by plugins’s to register their extensions to xcube. By convention, this function is called init_plugin, however, when using entry points, it can have any name. As an example, here is the initializer function of the SENTINEL Hub plugin xcube_sh/

from xcube.constants import EXTENSION_POINT_CLI_COMMANDS
from xcube.util import extension

def init_plugin(ext_registry: extension.ExtensionRegistry):
    """xcube SentinelHub extensions"""

Extension Points and Extensions

When a plugin is loaded, it adds its extensions to predefined extension points defined by xcube. xcube defines the following extension points:

  • xcube.core.gen.iproc: input processor extensions

  • xcube.core.dsio: dataset I/O extensions

  • xcube.cli: Command-line interface (CLI) extensions

An extension is added to the extension registry’s add_extension method. The extension registry is passed to the plugin initializer function as its only argument.

Input Processor Extensions

Input processors are used the xcube gen CLI command and gen_cube API function. An input processor is responsible for processing individual time slices after they have been opened from their sources and before they are appended to or inserted into the data cube to be generated. New input processors are usually programmed to support the characteristics of specific xcube gen inputs, mostly specific Earth Observation data products.

By default, xcube uses a standard input processor named default that expects inputs to be individual NetCDF files that conform to the CF-convention. Every file is expected to contain a single spatial image with dimensions lat and lon and the time is expected to be given as global attributes.

If your input files do not conform with the default expectations, you can extend xcube and write your own input processor. An input processor is an implementation of the xcube.core.gen.iproc.InputProcessor or xcube.core.gen.iproc.XYInputProcessor class.

As an example take a look at the implementation of the default input processor xcube.core.gen.iproc.DefaultInputProcessor or the various input processor plugins mentioned above.

The extension point identifier is defined by the constant xcube.constants.EXTENSION_POINT_INPUT_PROCESSORS.

Dataset I/O Extensions

More coming soon…

The extension point identifier is defined by the constant xcube.constants.EXTENSION_POINT_DATASET_IOS.

CLI Extensions

CLI extensions enhance the xcube command-line tool by new sub-commands. The xcube CLI is implemented using the click library, therefore the extension components must be click commands or command groups.

The extension point identifier is defined by the constant xcube.constants.EXTENSION_POINT_CLI_COMMANDS.