xcube gen


Generate xcube dataset.

$ xcube gen --help
Usage: xcube gen [OPTIONS] [INPUT]...

  Generate xcube dataset. Data cubes may be created in one go or
  successively for all given inputs. Each input is expected to provide a
  single time slice which may be appended, inserted or which may replace an
  existing time slice in the output dataset. The input paths may be one or
  more input files or a pattern that may contain wildcards '?', '*', and
  '**'. The input paths can also be passed as lines of a text file. To do
  so, provide exactly one input file with ".txt" extension which contains
  the actual input paths to be used.

  -P, --proc INPUT-PROCESSOR      Input processor name. The available input
                                  processor names and additional information
                                  about input processors can be accessed by
                                  calling xcube gen --info . Defaults to
                                  "default", an input processor that can deal
                                  with simple datasets whose variables have
                                  dimensions ("lat", "lon") and conform with
                                  the CF conventions.
  -c, --config CONFIG             xcube dataset configuration file in YAML
                                  format. More than one config input file is
                                  allowed.When passing several config files,
                                  they are merged considering the order passed
                                  via command line.
  -o, --output OUTPUT             Output path. Defaults to 'out.zarr'
  -f, --format FORMAT             Output format. Information about output
                                  formats can be accessed by calling xcube gen
                                  --info. If omitted, the format will be
                                  guessed from the given output path.
  -S, --size SIZE                 Output size in pixels using format
  -R, --region REGION             Output region using format "<lon-min>,<lat-
  --variables, --vars VARIABLES   Variables to be included in output. Comma-
                                  separated list of names which may contain
                                  wildcard characters "*" and "?".
  --resampling [Average|Bilinear|Cubic|CubicSpline|Lanczos|Max|Median|Min|Mode|Nearest|Q1|Q3]
                                  Fallback spatial resampling algorithm to be
                                  used for all variables. Defaults to
                                  'Nearest'. The choices for the resampling
                                  algorithm are: ['Average', 'Bilinear',
                                  'Cubic', 'CubicSpline', 'Lanczos', 'Max',
                                  'Median', 'Min', 'Mode', 'Nearest', 'Q1',
  -a, --append                    Deprecated. The command will now always
                                  create, insert, replace, or append input
  --prof                          Collect profiling information and dump
                                  results after processing.
  --no_sort                       The input file list will not be sorted
                                  before creating the xcube dataset. If
                                  --no_sort parameter is passed, the order of
                                  the input list will be kept. This parameter
                                  should be used for better performance,
                                  provided that the input file list is in
                                  correct order (continuous time).
  -I, --info                      Displays additional information about format
                                  options or about input processors.
  --dry_run                       Just read and process inputs, but don't
                                  produce any outputs.
  --help                          Show this message and exit.

Below is the ouput of a xcube gen --info call showing five input processors installed via plugins.

$ xcube gen --info
input processors to be used with option --proc:
  default                           Single-scene NetCDF/CF inputs in xcube standard format
  rbins-seviri-highroc-scene-l2     RBINS SEVIRI HIGHROC single-scene Level-2 NetCDF inputs
  rbins-seviri-highroc-daily-l2     RBINS SEVIRI HIGHROC daily Level-2 NetCDF inputs
  snap-olci-highroc-l2              SNAP Sentinel-3 OLCI HIGHROC Level-2 NetCDF inputs
  snap-olci-cyanoalert-l2           SNAP Sentinel-3 OLCI CyanoAlert Level-2 NetCDF inputs
  vito-s2plus-l2                    VITO Sentinel-2 Plus Level 2 NetCDF inputs

For more input processors use existing "xcube-gen-..." plugins from the github organisation DCS4COP or write own plugin.

output formats to be used with option --format:
  csv                     (*.csv)       CSV file format
  mem                     (*.mem)       In-memory dataset I/O
  netcdf4                 (*.nc)        NetCDF-4 file format
  zarr                    (*.zarr)      Zarr file format (http://zarr.readthedocs.io)

Configuration File

Configuration files passed to xcube gen via the -c, --config option use YAML format. Multiple configuration files may be given. In this case all configurations are merged into a single one. Parameter values will be overwritten by subsequent configurations if they are scalars. If they are objects / mappings, their values will be deeply merged.

The following parameters can be used in the configuration files:


The name of an input processor. See -P, --proc option above.


The default value is 'default', xcube’s default input processor. It can ingest and process inputs that

  • use an EPSG:4326 (or compatible) grid;

  • have 1-D lon and lat coordinate variables using WGS84 coordinates and decimal degrees;

  • have a decodable 1-D time coordinate or define the one of the following global attribute pairs time_coverage_start and time_coverage_end, time_start and time_end or time_stop;

  • provide data variables with the dimensions time, lat, lon, in this order.

  • conform to the `CF Conventions`_.

output_size[int, int]

The spatial dimension sizes of the output dataset given as number of grid cells in longitude and latitude direction (width and height).

output_region[float, float, float, float]

The spatial extent of output datasets given as a bounding box [lat-min, lat-min, lon-max, lat-max] using decimal degrees.


The definition of variables that will be included in the output dataset. Each variable definition may be just a name or a mapping from a name to variable attributes. If it is just a name it must be the name of an existing variable either in the INPUT or in processed_variables. If the variable definition is a mapping, some of the attributes affect the way how variables are processed. All but the name attributes become variable metadata in the output.


The new name of the variable in the output.


An expression used to mask this variable, see Expressions. The expression identifies all valid pixels in each INPUT.


The resampling method used. See --resampling option above.


By default, all variables in INPUT will occur in output.


The definition of variables that will be produced or processed after reading each INPUT. The main purpose is to generate intermediate variables that can be referred to in the expression in other variable definitions in processed_variables and valid_pixel_expression in variable definitions in output_variables. The following attributes are recognised:


An expression used to produce this variable, see Expressions.


The name of a supported output format. May be one of 'zarr', 'netcdf4', 'mem'.




A mapping that defines parameters that are passed to output writer denoted by output_writer_name. Through the output_writer_params a packing of the variables may be defined. If not specified the default does not apply any packing which results in:

_FillValue:  nan
dtype:       dtype('float32')

and for coordinate variables

dtype:       dtype('int64')

The user may specify a different packing variables, which might be useful for reducing the storage size of the datacubes. Currently it is only implemented for zarr format. This may be done by passing the parameters for packing as the following:


      scale_factor: 0.07324442274239326
      add_offset: -300.0
      dtype: 'uint16'
      _FillValue: 0.65535

Furthermore the compressor may be defined as well by, if not specified the default compressor (cname=’lz4’, clevel=5, shuffle=SHUFFLE, blocksize=0) is used.


    cname: 'zstd'
    clevel: 1
    shuffle: 2

General metadata that will be present in the output dataset as global attributes. You can put any common CF attributes here.

Any attributes that are mappings will be “flattened” by concatenating the attribute names using the underscrore character. For example,:

  name:  "Brockmann Consult GmbH"
  url:   "https://www.brockmann-consult.de"

will create the two entries:

publisher_name:  "Brockmann Consult GmbH"
publisher_url:   "https://www.brockmann-consult.de"


Expressions are plain text values of the expression and valid_pixel_expression attributes of the variable definitions in the processed_variables and output_variables parameters. The expression syntax is that of standard Python. xcube gen uses expressions to produce new variables listed in processed_variables and to mask variables by the valid_pixel_expression.

An expression may refer any variables in the INPUT datasets and any variables defined by the processed_variables parameter. Expressions may make use of most of the standard Python operators and may apply all numpy ufuncs to referred variables. Also most of the xarray.DataArray API may be used on variables within an expression.

In order to utilise flagged variables, the syntax variable_name.flag_name can be used in expressions. According to the CF Conventions, flagged variables are variables whose metadata include the attributes flag_meanings and flag_values and/or flag_masks. The flag_meanings attribute enumerates the allowed values for flag_name. The flag attributes must be present in the variables of each INPUT.


An example that uses a configuration file only:

$ xcube gen --config ./config.yml /data/eo-data/SST/2018/**/*.nc

An example that uses the default input processor and passes all other configuration via command-line options:

$ xcube gen -S 2000,1000 -R 0,50,5,52.5 --vars conc_chl,conc_tsm,kd489,c2rcc_flags,quality_flags -o hiroc-cube.zarr /data/eo-data/SST/2018/**/*.nc

Some input processors have been developed for specific EO data sources used within the DCS4COP project. They may serve as examples how to develop input processor plug-ins:

Python API

The related Python API function is xcube.core.gen.gen.gen_cube().